In the present paper, we introduce (p, q)-extension of Apostol type Frobenius-Euler polynomials and numbers and investigate some basic identities and properties for these polynomials and numbers, including addition theorems, difference equations, derivative properties, recurrence relations and so on. Then, we provide integral representations, explicit formulas and relations for these polynomials and numbers. Moreover, we discover (p, q)-extensions of Carlitz's result [L. Carlitz, Mat. Mag., 32 (1959), 247–260] and Srivastava and Pintér addition theorems in [H. M. Srivastava, A. Pinter, Appl. Math. Lett., 17 (2004), 375–380].

In this paper we provide an ``expository overview" of classic epidemic projection models. Starting with the simple case of an epidemic that grows exponentially we then investigate ``compartmental" models. These assume that the growth of an infected population is limited endogenously by the size of the underlying pool of susceptibles. We then describe a new family of so-called "Exo-r" statistical models, which hinge on an exogenously driven growth rate of the infected population. This family, which can be used to model both infections and deaths, captures parsimoniously both the depletion of susceptibles and the effect of interventions such as lockdowns and ``social distancing". The model is used to fit numbers of Covid-19 infections in China. It is also used to model and project deaths in the United States. Results are used to inform a discussion on i) the challenges at hand and ii) the extent to which epidemic projection models may be useful despite being wrong.

COVID-19 represents an unprecedented threat to global public health and economies. Assays are urgently needed for rapid detection and diagnosis of SARS-CoV-2-infected patients in order to inform treatment and quarantine strategies. Establishing globally accepted easy-to-access diagnostic tests is extremely important to understanding the epidemiology of the present pandemic. While nucleic acid-based tests are considered to be more sensitive with respect to serological tests, but the present gold standard RT-PCR-based assays possess limitations such as low sample throughput, requirement for sophisticated reagents and instrumentation. To overcome these shortcomings, recent efforts of incorporating LAMP-based isothermal detection, and minimizing the number of reagents required are on rise. Novel CRISPR- and other nuclease-based techniques, when merge with isothermal and allied technologies, promises to provide sensitive and rapid detection of SARS-CoV-2 nucleic acids. Here we discuss and present compilation of state-of-the-art CRISPR based detection techniques for use in COVID diagnosis and epidemiology.

Background: Shortly after the detection of the COVID virus in January 2020 the US Government introduced and enforced a series of restrictions to protect the elderly from a “deadly virus” and the “pandemic of the century”. Persons who disagreed were silenced and punished. Objective: In the 15^th month of COVID epidemic (April 2021), we have access to sufficient statistical data and methods to better understand the nature, origin of the COVID pandemic. It is now possible to reliably evaluate the effectiveness of the restrictions and the human factors / driving forces behind this drastic limitations of our natural freedom in this country. Methods: Publicly available epidemiological and population parameters were collected and analyzed using the ‘political score’ and ‘restriction ranking’ of 50 states and evaluated by simple and usual statistical methods, mainly correlation analyses. The Political Score of the States (D/R) is the ratio of the number of citizens who self-identified as democrats (D) or republicans (R). The political scores of the 50 states altogether defined a wide, continuous scale, the political scale, that could be used to measure (and statistically evaluate) the effect of politics of a state on the numerical parameters of that state, including population and epidemiologic parameters. The COVID Restriction Score of the States were created to rank the states from 1-50, there 1 is the lowest number of restrictions and 50 is the highest number of restrictions applied by the States. It was based on 13 different key metrics. ResultsThis study revealed, that 1) restrictions reduced the number of viral infections, but 2) they totally failed to reduce the number of supposedly COVID related deaths, expressed as mortality, 3) they increased (SIC!) the lethality of coronavirus. The grade of restrictions were/are strongly associated to the 4) left/right political ratio of the States, there States with more democrat citizens practiced more restrictions. It was found that race, religion and Medicare/healthcare spending have significant influence on politic as well as on the grade of restriction orders. Factors moving States toward the political left and harder COVID restrictions have 5) larger ‘non-white’ population, 6) larger number of ‘non-protestant’ believers, 7) larger Jewish population, and 8) more generous Medicare/healthcare spending. It was not possible to see any influence of the size of the 9) senior (65+) population [i.e. those who are allegedly the most vulnerable and are mostly in need of protective restrictions] neither on the States politic nor on the restrictions. Conclusions: The degree of restrictions enforced by different states ware not primarily determined by biological or epidemiological factors (like number of elderly, say 65+ in the state) but by social, political influences instead. Political (a), religious (b) ethnic (c) and economic (d) forces represented the decisive forces on the state’s restrictive orders and not the convincing evidence of the potentially harmful effects of the COVID infection and the well-founded adequacy of the defense against it.

Background: Short after the detection of the COVID virus in January 2020 the US Government introduced and enforced a series of restrictions to protect the elderly from a “deadly virus” and the “pandemic of the century”. Persons who disagreed were silenced and punished. Objective: In the 15^th month of COVID epidemic (April 2021), we have access to sufficient statistical data and methods to better understand the nature, origin of the COVID pandemic. It is now possible to reliably evaluate the effectiveness of the restrictions and the human factors / driving forces behind this drastic limitations of our natural freedom in this country. Methods: Publicly available epidemiological and population parameters were collected and analyzed using the ‘political score’ and ‘restriction ranking’ of 50 states and evaluated by simple and usual statistical methods, mainly correlation analyses. Results: This study revealed, that 1) restrictions reduced the number of viral infections, but 2) they totally failed to reduce the number of supposedly COVID related deaths, 3) they increased (SIC!) the mortality of coronavirus. The grade of restrictions were/are strongly associated to the 4) left/right political ratio of the States, there States with more democrat citizens practiced more restrictions. It was found that race, religion and Medicare spending have significant influence on politic as well as on the grade of restriction orders. Factors moving States toward the political left and harder COVID restrictions have 5) larger ‘non-white’ population, 6) larger number of ‘non-protestant’ believers, 7) larger Jewish population, and 8) more generous Medicare spending. It was not possible to see any influence of the size of the 9) senior (65+) population [i.e. those who are allegedly the most vulnerable and are mostly in need of protective restrictions] neither on the States politic nor on the restrictions Conclusions: The conclusion is that COVID restrictions are primarily politically motivated, they are ineffective to reduce COVID related mortality and they provide no extra health benefit for the so called “vulnerable” minority (elderly).

Background: The COVID-19 pandemic has exacerbated existing healthcare disparities among American Indian/Alaska Native (AI/AN) populations, rooted in historical traumas and systemic marginalization. Methods: This study conducted at a single Indian Health Service (IHS) clinic in central Michigan examines the effectiveness of educational interventions in enhancing COVID-19 knowledge and attitudes among AI/AN populations. Utilizing a pre/post prospective study design, participants received either a video or infographic educational intervention, followed by a survey assessing COVID-19 knowledge and attitudes. Results: The results indicate significant improvements in knowledge and attitudes post-intervention, with both modalities proving effective. However, specific factors such as gender, political affiliation, and place of residence influenced COVID-19 attitudes and knowledge, emphasizing the importance of tailored interventions. Conclusions: Despite limitations, this study highlights the critical role of educational interventions in addressing vaccine hesitancy and promoting health equity within AI/AN communities. Moving forward, comprehensive strategies involving increased Indian Health Service funding, culturally relevant interventions, and policy advocacy are crucial in mitigating healthcare disparities and promoting health equity within AI/AN communities.

Background: The exacerbation of psychosocial problems among children and adolescents during the coronavirus disease 2019 (COVID-19) pandemic necessitates an assessment of the long-term mental health impact of pandemic interventions. Focusing on both pandemic-related factors and demographic variables, such as gender and daily habits, an analysis was conducted to under-stand how these elements continue to affect young populations in the post-pandemic era. Methods: In April 2023, a comprehensive online survey was administered to families in South Tyrol, Italy, with children aged 7–19 years, to ensure age and gender representation. The survey included par-ent ratings and adolescent (11–19 years) self-reports using standardized instruments to measure the symptoms of mental health problems (Strengths and Difficulties Questionnaire, SDQ), anxiety (Screen for Child Anxiety Related Emotional Disorders, SCARED), and depression (Patient Health Questionnaire-2, PHQ-2). Statistical analyses included descriptive statistics, chi-square tests, and unadjusted odds ratios (ORs). Results: Of the 4,525 valid responses, 1,831 were self-reported by adolescents. Notable gender differences in mental health outcomes were identified, along with significant demographic predictors, such as age, single parenthood, parental mental health problems, and immigrant background. Negative effects were associated with reduced family climate and increased screen time, whereas physical activity showed beneficial effects. Proxy reports overestimated adolescents' mental health problems, whereas self-report tended to underestimate them. Conclusions: Persistent mental health problems and gender disparities high-light the need for a public health approach. This should include accessible support services, resili-ence building, targeted support for vulnerable families and gender-specific interventions.

The World Health Organization declared the coronavirus disease 2019 (COVID-19) pandemic in 2020, following which a global genetic vaccination program has been rapidly implemented as a fundamental solution. However, it has been reported worldwide that the modified mRNAs encoding spike proteins and lipid nanoparticles, which are used as drug delivery systems, not only cause thrombosis and cardiovascular disorders post vaccination, but might also cause diverse diseases involving all organs and systems, including the nervous system. Furthermore, the toxicity and pathogenicity of spike proteins may necessitate defining these proteins as nonbiological infective material. Based on these reports and the abundant evidence that has come to light in the past few years, this paper aims to draw the attention of medical professionals to the various risks associated with transfusion using blood products derived from long COVID patients or from genetic vaccine recipients, and to make proposals regarding specific inspection items, testing methods, regulations, etc. This paper provides insights to address the post-vaccination syndrome and its consequences following such genetic vaccination programs.

Irrational belief is a product of complex personality traits and Machiavellianism Intelligence. The present study is conducted to trace the significance of predictive nature of personality characteristics and Machiavellianism Intelligence (Mach Intelligence) on irrational beliefs among chronically ill older people. The research method is cross-sectional with correlational design, purposive sampling with a total of 200 chronically ill older people aged between 40–60 years with disease type such as Systemic lupus erythematosus, Complicated Diabetes, Glomerulonephritis and Chronic Heart Failure. The analysis revealed that personality characteristics and irrational belief subscales such as worrying, rigidity, problem avoidance and Mach Intelligence are significantly positively correlated; however, Emotional irresponsibility has significant negative correlation with personality characteristics and Mach Intelligence. Gender differences revealed that males are high on all the subscales of personality characteristics, irrational beliefs (except emotional irresponsibility) and Mach Intelligence as com-pared to female chronically ill older people. Predictive analysis also revealed that overall personality characteristics explained a total of 67% variance in irrational beliefs. Moreover, Mach Intelligence predicts irrational beliefs. Future health related recommendations should be planned accordingly.

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a rare but severe adverse event that was first observed during the global vaccination campaign against SARS-CoV-2 infection, specifically in those receiving adenoviral vector-based vaccines for Coronavirus disease 2019 (COVID-19). VITT develops 4 to 42 days post-vaccination and is characterized by the development of platelet-activating anti-platelet factor 4 (PF4) antibodies, leading to thrombocytopenia and thrombosis at unusual sites. The rise in awareness and subsequent prompt recognition of VITT was paramount in reducing mortality. Moreover, as vaccination campaigns around the world continue, a better understanding of VITT not only has important clinical implications but is also crucial for future vaccine development. In this review, we summarize the clinical features, pathophysiology, and incidence rates of VITT as well as highlight other anti-PF4 antibody-mediated disorders of growing clinical significance.

We study here what can be learned from our experience with COVID-19 vaccination for an initially naïve population, that can inform planning for vaccination against the next novel, highly transmissible pathogen. We focus on the first two pandemic years (wild strain through Delta), because after the Omicron wave in early 2022, few people were still SARS-CoV-2-naïve. Almost all were vaccinated, infected, or often both. We review the evidence on COVID-19 vaccine effectiveness (VE), waning effectiveness over time, and what we should expect about VE and waning from a future pathogen. As a basis for our analysis, we conducted a PRISMA-compliant review of all studies on PubMed through August 15, 2022 reporting VE against four endpoints: any infection, symptomatic infection, hospitalization, and death, for the four principal vaccines used in developed Western countries (BNT162b2, mRNA1273, Ad26.CoV2.S, and ChAdOx1-S). The mRNA vaccines (BNT162b2, mRNA1273) had high initial VE against all endpoints but protection waned after approximately six months, with BNT162b2 declining faster than mRNA1273. Both mRNA vaccines initially outperformed the viral vector vaccines. A third “booster” dose, roughly six months after the primary doses, substantially reduced symptomatic infection, severe disease, and mortality, and in hindsight should be seen as part of the normal vaccination schedule.

Healthcare workers' stress, burnout, and job dissatisfaction were exacerbated by the Covid-19 pandemic, whose mid-term negative effects are still present. The aim of this study was to investigate in healthcare workers the effect of the dimensions of burnout (Psychophysical exhaustion, Relational deterioration, and Professional inefficacy) on Career satisfaction. These relationships were evaluated by considering the direct and mediated effects of Disillusion. For these purposes, the Link Burnout Questionnaire (LBQ) and the Career Satisfaction Scale (Occupational Stress Indicator - OSI) were administered to 295 healthcare professionals working at three Italian public hospitals in Cagliari, Italy. The analyses were conducted using the Partial Least Square Structural Equation Model (PLS-SEM) method. Findings highlight that healthcare workers were in a condition of work distress, high risk of burnout, and career dissatisfaction. Also recognized was the direct negative effect of burnout dimensions on career satisfaction. Finally, the mediated negative effect of Disillusion in the relationship between burnout and career satisfaction was identified. This study emphasizes the relevance of the dimension of Disillusion, and its “bright side” Fulfilment, in healthcare workers, specifically referring to the disregarded relationship between burnout and career satisfaction.

The main objective of this article was to evaluate the repercussions of the crises resulting from the COVID-19 pandemic and the war in Ukraine on changes in the European Union's reliance on energy raw material imports, particularly from Russia. Furthermore, several specific objectives were outlined: to ascertain the EU's energy balance and any alterations therein, to identify changes in the concentration of energy raw material imports among EU countries during the crises, to determine the level and fluctuations in energy raw material import dependence within the EU and individual member states throughout the crises, and lastly, to assess changes in the concentration of energy raw material imports from Russia in EU countries during the crises. The research encompassed all 27 EU Member States as of 31st December 2022, and the examination period spanned from 2010 to 2022. The information sources included relevant literature on the subject and data sourced from Eurostat. In conducting the analysis and presenting the data, several methodologies were employed, including descriptive, tabular, and graphical techniques. Additionally, quantitative measures such as the Gini structure concentration coefficient and concentration analysis through the Lorenz curve were utilized. During the COVID-19 pandemic, the EU experienced a slight reduction in dependence on energy raw material imports. However, this reduction was short-lived and mainly attributed to the decrease in energy demand caused by the pandemic. Conversely, the war in Ukraine had a substantial impact, leading to a notable surge in energy raw material imports as a result of stockpiling efforts and the need to safeguard against further disruptions in the energy market. Notably, the EU's reliance on energy imports from Russia was already considerable. Following the outbreak of the conflict in Ukraine, imports of oil, petroleum products, and solid fossil fuels experienced significant decline due to imposed sanctions. Nonetheless, restrictions on natural gas imports were comparatively less severe.

People must have particular personality traits and social resources, also known as health literacy, in order to access, comprehend, and use information to make decisions about their health. Patients' ability to engage in complex disease management and self-care is strongly related to their level of health literacy. It can help us stay healthy by preventing illness and effectively managing existing illnesses. People with low health literacy (LHL) may find it difficult to manage their condition and prevent illness, which may lead to increased use of healthcare services. Furthermore, LHL is associated with increased hospitalizations, increased use of emergency care, decreased use of preventative services, and a worsened ability to understand labels and health messages, a worsened state of health, higher mortality, and more expensive medical care.

COVID-19 and long COVID-19 vulnerabilities may be caused indirectly by albumin binding deficiency (ABD) which can be corrected by the correct administration of human serum albumin (HSA). The liver is the primary site of nutrient regulation and fluid volume maintenance, control of both is by changes to albumin concentration. In healthy subjects the HSA lymphatic nutrient pump (HSALNP) ensures continual pumping of nutrients from the liver are appropriately distributed to organs. Nutrients are delivered to cells according to the availability of binding to HSA. The HSALNP therefore maintains the correct nutrients and colloidal pressure balance in all tissues independently. In unhealthy tissues, following COVID-19 infection, the passage of HSA/nutrients through the interstitial spaces and lymph will be impeded. Fluid therapy into the periphery leads to dilution of essential nutrients attached to the protein-carriers such as albumin. The levels of albumin being charged by the liver with nutrients is critical in maintaining immune stability by maintaining nutrient support and colloidal pressure of cellular structures. The site of HSA binding by the liver is of great importance and direct infusion of albumin into the Hepatic Portal Vein is the most appropriate method of maintaining colloid pressure and cellular nutrient levels.

The review of previous works shows this study is the first attempt to analyse the lockdown effect using Natural Language Processing Techniques, particularly sentiment analysis methods applied at large scale. On the other hand, it is also the first of its kind to analyse the impact of COVID 19 on the university community jointly on staff and students and with a multi-country perspective. The main overall findings of this work show that the most often related words were family, anxiety, house and life. On another front, it has also been shown that staff have a slightly less negative perception of the consequences of COVID in their daily life. We have used artificial intelligence models like swivel embedding and the Multilayer Perceptron, as classification algorithms. The performance reached in terms of accuracy metric are 88.8% and 88.5%, for student and staff respectively. The main conclusion of our study is that higher education institutions and policymakers around the world may benefit from these findings while formulating policy recommendations and strategies to support students during this and any future pandemics.

G-protein-coupled receptors (GPCR) belong to a large family of molecules eliciting different responses to a variety of signaling molecules. These receptors participate in various physiologic pathways such as metabolism, growth, immune responses, inflammation, vision, taste, olfaction, neurotransmission and even and pathologic responses including chronic inflammatory and vascular diseases. Receptors contributing to the biological responses of renin-angiotensin system (RAS) are members of GPCR family. COVID-19-induced inflammatory cascade has been attributed to acute ACE2 downregulation and imbalance of proinflammatory ACE/AngII/AT1R and anti-inflammatory ACE2/angiotensin (1-7)/Mas axes in favor of the former. Some of the receptors contributing to activities of proteins in RAS including AT1R, AT2R and Mas receptors are members of GPCR family. It is notable that these receptors induce their effects both through G protein and β-arrestin pathway; the former exerts temporary and the latter more sustained effects. In addition to the imbalance of GPCR responses contributing to RAS activities, it has been suggested that SARS-CoV2 pathogenesis might be attributed to the activation of GPCRs or modulating G-proteins involved in adenosine-CFTR regulation system and epithelial Na channel function.This article includes a minireview about the physiological functions of GPCRs and their contribution to COVID-19.

Background: The epidemiological situation generated by COVID-19 has cast into sharp relief the delicate balance between public health priorities and the economy, with businesses obliged to toe a line between employee health and continued production. In an effort to detect as many cases as possible, isolate contacts, cut transmission chains and limit the spread of the virus in the workplace, mass testing strategies have been implemented in both public health and industrial contexts to minimize the risk of disruption in activity. Objective: To evaluate the economic impact of mass workplace testing strategy as carried out by a large automotive company in Catalonia in terms of health and healthcare resource savings. Methodology: Analysis of health costs and impacts based on the estimation of mortality and morbidity avoided because of screening and the resulting savings in healthcare costs. Results: The economic impact of the mass workplace testing strategies (using both PCR and RAT tests) was approximately €10.44 per test performed or €5,575.49 per positive detected. 38% of this figure corresponds to savings derived from better use of health resources (hospital beds, ICU beds and follow-up of infected cases), while the remaining 62% corresponds to improved health rates due to avoided morbidity and mortality. In scenarios with higher positivity rates and a greater impact of the infection on health and the use of health resources, these results could be up to ten times higher (€130.24 per test performed or €69,565.59 per positive detected). Conclusion: In the context of COVID-19, preventive actions carried out by the private sector to safeguard industrial production also have concomitant public benefits in the form of savings in healthcare costs. Thus, governmental bodies need to recognize the value of implementing such strategies in private settings and facilitate them through, for example, subsidies.

Research on the chemical mechanism and reciprocal behavior of the coronavirus relate to living organisms, engaging in the give and take of electrochemical mediators, is a very important, controversial and vital issue. What we should accept is the chemical identity of this scenario, and not preferably a characteristic of a biological system. This chemical reaction should be familiar, referring to the theory of chemical pathways involved in DNA/proteins in the body against aggressive guests (such as viruses). From the point of view of a chemist, this simple reaction is nothing more than an oxidation-reduction reaction (redox-stress signaling) which conducted and carried out by coronavirus in a biointerface medium. Thereby, oxidizing as well as reducing reagents should be very constructive, promoting development in such chemical process. We understand redox reactions as switchable thiol/disulfide exchanges (formation and cleavage of inherent disulfide bonds), then, we can hugely profit from redox-responsive nano-surfaces equipped with multiple new ionic and covalent interactions. This game-changing idea can substantiate by surface modified-nanoparticles to play powerful roles in synthesis of nano oxidizers as well as reducing agents in nanomedicine. Chemists and pharmacists must then explore new thoughts and present modern experiences/approaches of preparation nanoparticles and nanocomposites to create novel vaccines as well as coronavirus drugs. In this regard, this experience can also be so helpful for HIV/AIDS, which is caused by viruses.

We present a model of infection dynamics that might explain slower approaching the herd immunity during the covid-19 epidemy in Sweden than it was predicted by a variety of other models; see graphs Fig. \ref{GROWTH2}. The new model takes into account the hierarchic structure of social clusters in the human society. We apply the well developed theory of random walk on the energy landscapes represented mathematically with ultrametric spaces. This theory was created for applications to spin glasses and protein dynamics. To move from one social cluster (valley) to another, the virus should cross a social barrier between them. The magnitude of a barrier depends on the number of social hierarchy's levels composing this barrier. As the most appropriate for the recent situation in Sweden, we consider linearly increasing (with respect to hierarchy's levels) barriers. This structure of barriers matches with a rather soft regulations imposed in Sweden in March 2020. In this model, the infection spreads rather easily inside a social cluster (say working collective), but jumps to other clusters are constrained by social barriers. This model's feature matches with the real situation during the covid-19 epidemy, with its cluster spreading structure. Clusters need not be determined solely geographically, they are based on a number of hierarchically ordered social coordinates. The model differs crucially from the standard models of spread of disease, such as the SIR-model. Our model describes such a specialty of spread of covid-19 virus as the presence of ``super-infectors'' who by performing a kind of random walk on a hierarchic landscape of social clusters spreads infection. In future, this model will be completed by adding the SIR-type counterpart. But, the latter is not a specialty of covid-19 spreading.

COVID-19 has affected 212 countries around the world, killing nearly 300,000 and infecting more than 4.4 million by May 14, 2020. Bangladesh, a South Asian low-middle-income economy, has experienced a demographic and epidemiological transition with rapid urbanization and a gradual increase in life expectancy. It is the seventh most populous country in the world and population of the country is expected to be nearly double by 2050. The increasing burden of communicable diseases in Bangladesh can be attributable to rapid urbanization and nearly 50% of all slum dwellers of the country live in Dhaka division. In 2017, National Rapid Response Team of IEDCR investigated 26 incidents of disease outbreak. The joint survey of the Power and Participation Research Centre and BRAC Institute of Governance and Development reveals that per capita daily income of urban slum and rural poor drops by 80% due to present countrywide shutdown enforced by the government to halt the spread of Covid-19. 40%-50% of these population took loans to meet the daily expenses. However, the country has just 127,000 hospital beds, 91,000 of them in government-run hospitals. Researchers say, the country’s economy is economy is losing BDT 33 billion every day from its service and agriculture sectors during the nationwide shutdown.

Soil water balance (SWB) in woody crops is sometimes difficult to estimate with one-dimensional models because these crops do not completely cover the soil and usually have a deep root system, particularly when cropped under rainfed conditions in a Mediterranean climate. In this study, the actual crop evapotranspiration (ETc act) is estimated with the soil water balance model SIMDualKc which uses the dual-Kc approach (relating the fraction of soil cover with the crop coefficients) to improve the estimation of the water requirements of a rainfed vineyard, using data from a deep soil profile. The actual basal crop coefficient (Kcb act) obtained using the SIMDualKc model was compared with the Kcb act estimated using the A&P approach, which is a simplified approach based on measurements of the fraction of ground cover and crop height. Spectral vegetation indices derived from Landsat-5 satellite data were used to determine the fraction of ground cover (fc VI) and thus, the density coefficient (Kd). The SIMDualKc model was calibrated using soil water content (SWC) measurements down to a depth of 1.85 meters, which significantly improved the conditions for using a SWB estimation model. The test of the model was performed using a different SWC dataset. A good agreement between simulated and field measured SWC was observed for both data sets along the crop season, with RMSE<12.0 mm, NRMSE <13%. The calibrated Kcb values were 0.15, 0.60 and 0.52 for the initial, mid-season, and end season, respectively. The ratio between actual (ETc act) and crop evapotranspiration (ETc) was quite low between veraison and maturity (mid-season), corresponding to 36%, indicating that the rainfall was not sufficient to satisfy the vineyards water requirements. Spectral vegetation indices used to compute fc VI were unable to fully track the plants’ conditions when water stress. However, ingestion of data from remote sensing showed promising results that could be used to support decisions making in irrigation scheduling. Further studies on the use of the A&P approach using remote sensing data are required.

Photovoltaic materials convert light into electrical voltages. So far, most research in the field are focused on how to refine/improve the existing or standard photovoltaic cells to yield more efficient electricity, to reduce weight, to make more flexible shape, or to minimize costs under standard and uniform sunlight illuminations. In this project, we explore and demonstrate a hypothesis that non-uniform light illumination photovoltages can also be generated due to photo doping induced mobile charge carrier density gradient between light and dark areas in either p-type or n-type photo doping semiconductors. The term non-uniform light illumination was coined to refer to subjecting our photo sensing thin film devices to areas of high and low intensities of light illumination simultaneously, with an intention of creating a charge density gradient and therefore a voltage. Specifically, a polymeric composite thin film composed of P3HT (p-type photo doping semiconductor) and PCBM (photo doping electron acceptor and trap) at varying p-doping levels were studied. We observed that the fabricated photovoltaic cells with about 80% PCBM doped P3HT thin film devices exhibited 0.5-1.2 volts photovoltages under non-uniform light illuminations.

Background. ADHD is a neurodevelopmental disorder that is accompanied by executive deficits. Objectives. To obtain evidence of the usefulness of the BRIEF-P and to analyse the possible ceiling and floor effect of its scores in the assessment of executive function in preschoolers with signs compatible with a possible diagnosis of ADHD. Methods. Seven articles were selected from 2538 potentially eligible articles from different databases. We included studies assessing samples of individuals with symptoms compatible with ADHD, with age range 2-6 years, published in English or Spanish, during the period 2012-2022. References published in: Science Direct, NCBI (PubMed), ProQuest Education Journals in the last decade. Risk of bias was assessed using the QUADAS-2 questionnaire. The main variables were: age and executive functioning. Conclusions. Executive deficits in early-life individuals with ADHD-compatible symptoms are more extensive than deficits in working memory. BRIEF-P is an instrument that facilitates obtaining a sensitive and discriminative executive profile. It should be used in combination with other neuropsychological performance tests, finding a floor effect in tests associated with warm executive functions and a ceiling effect in cold executive functions. This requires using a variety of tests to assess executive performance in preschoolers with symptoms compatible with ADHD and designing intervention proposals in line with them...

Neuroinflammation is considered to be a significant component in a range of neuropathologies. Unfortunately, whilst its role is well recognized, the options for therapeutic intervention are limited. As such, there is a need to identify novel targets in order to increase treatment options. Given its role as both a neurotransmitter and an immune modulator, substance P and its NK1 receptor have been widely studied as a potential therapeutic target. There is evidence that NK1 receptor antagonists may exert beneficial effects in a range of conditions, including traumatic brain injury and stroke. Blocking the NK1 receptor has been shown to reduce blood-brain barrier dysfunction, reduce cerebral oedema, and reduce the levels of pro-inflammatory cytokines. These actions are associated with improved survival and functional outcomes. The NK1 receptor has also been shown to be involved in the inflammatory reaction to CNS infection, and hence antagonist may have some benefit in reducing infection-driven inflammation. However, the NK1 receptor may also play a role in the host immune response to infection, and so here, the potential beneficial and detrimental effects need to be carefully balanced. As such, the purpose of this review is to provide a summary of the involvement of substance P in acute inflammation, particularly in the context of traumatic brain injury and stroke.

Films prepared from poly(3-hydroxybutyrate-co-4-hydroxybutyrate) copolymers produced by Aneurinibacillus sp. H1 using an automatic film applicator were homogeneous and had a defined thickness, which allowed a detailed study of physicochemical properties. Their properties were compared with a poly (3-hydroxybutyrate) homopolymer film prepared by the same procedure, which proved to be significantly more crystalline by DSC and XRD. Structural differences between samples had a major impact on their properties. With increasing 4-hydroxybutyrate content, the ductility and release rate of the model hydrophilic active ingredient increased significantly. Other observed properties, such as the release of the hydrophobic active substance, the contact angle with water and ethylene glycol, or the surface morphology and roughness, were also affected by the composition. The identified properties predetermine these copolymers for wide use in areas such as biomedicine or smart biodegradable packaging for food or cosmetics. The big advantage is the possibility of fine-tuning properties simply by changing the fermentation conditions.

It is unclear how important it is to reduce fluoroquinolone consumption in the general population to prevent the spread of fluoroquinolone resistance in Neisseria gonorrhoeae (bystander selection). Methods We assessed bystander selection by using Spearman’s correlation to assess if the country-level prevalence of fluoroquinolone resistance in N. gonorrhoeae was correlated with the prevalence of fluoroquinolone resistance in four other gram-negative species - Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa. Results Fluoroquinolone resistance in N. gonorrhoeae was positively associated with homologous resistance in all 4 species - A. baumanii. (ρ=0.61, P=0.0003, E. coli (ρ=0.67, P<0.0001), K. pneumoniae (ρ=0.52, P=0.0004) and P. aeruginosa (ρ=0.40, P=0.0206). Positive associations were also found between the national prevalence of fluoroquinolone resistance and fluoroquinolone consumption in the general population in the preceding year for 4 of the 5 species. Conclusions Gonococcal fluoroquinolone resistance can be productively viewed as being part of a syndemic of fluoroquinolone resistance. Strengthening antimicrobial stewardship programs may help retard the spread of fluoroquinolone resistance in N. gonorrhoeae.

Dendrobium okinawense is an endangered epiphytic orchid, and there has been no scientific report so far on its propagation. Protocorm is mass of cell, and protocorm-like bodies (PLBs) look alike protocorm produced by vegetative explants in vitro. Regeneration of PLBs is the most efficient technique for the orchids micro-propagation. We used different light emitting diodes (LEDs) for the efficient PLB organogenesis of D. okinawense. PLBs regenartion under green and red LED surpassed respectively 81.1% and 71.6% in numbers, and respectively 80.8% and 57.8% in fresh weight over white fluorescent light. We manipulated the culture media by different concentrations of PCIB and HMI. PLBs organogenesis promoted by low concentration, it increased respectively 35.9% and 19.3% over control by 0.01 mg/L PCIB and 0.01 ml/L HMI in numbers. Green LED and PCIB independently produced mostly similar numbers of new PLBs. Interestingly, culture media with 0.01 mg/L of PCIB further increased 8.5% of the numbers of PLBs under green LED, whereas the culture media with 0.01 mg/L HMI reduced the number of PLBs under green LED. PLBs culture under green LED with very low concentrations of PCIB manipulated culture media can significantly increase their organogenesis of D. okinawense.

The circuitry of the summarized "floating" differential stages (FDS) based on complementary field-effect transistors with a control p-n junction (CJFET), intended for use in low-noise analog microcircuits, for example, operational amplifiers. The results of modeling the flow characteristics of one of the CJFET FDSs in the LTSpice XVII environment at low temperatures (down to -197 ⁰С) and exposure to a neutron flux in the range of 1e13 ÷ 1e15 n / cm² are presented.

The article introduces a new solution approach to grid-connected single-stage three-phase PV inverter whereby a dc-link voltage can successfully achieve the desired performance. As a single-stage, the variable output of perturb and observe maximum power point tracking (P&O based-MPPT) is fully utilized as dc-link voltage reference in inverter control scheme. As a result, it is challenging for the dc-link voltage to preserve energy balance by tracking its variable dc-link voltage reference under unpredictable environmental changes. To overcome this challenge, an adaptive reference proportional-integral (ARPI) controller, self-tuning, is designed and implemented to compel the dc-link voltage tracking its voltage reference to be equal as closely as possible; hence, the capability of the dc-link under abnormal events substantially guarantees the best energy balance and transient performance enhancement. To verify the validity of the method, simulation results for multiple events scenarios on 250 KW single-stage grid-connected PV systems show the effectiveness of the ARPI controller compared with PI controller.

Background and objective: The impairments and duration of PASC (Post-acute sequelae of COVID-19) symptoms in mental health have up to date not been comprehensively examined. Our objective is to provide longitudinal data on the mental health of Post-COVID patients and to identify risk and protective factors associated with a severe or prolonged course. Methods: Mental health of 265 Post-COVID patients of the outpatient Post-COVID centre of the University-Hospital Erlangen was assessed 17.1 (T0) and 22.5 months after infection (T1). An online survey with validated questionnaires for Post-COVID symptoms (Post-COVID-Syndrome-Score), depression (Patient-Health-Questionnaire 9), somatic symptoms (Patient-Health-Questionnaire 15), anxiety (Generalized-Anxiety-Disorder 7), fatigue (Fatigue-Severity-Scale) and Post-Exertional Malaise (PEM) (DePaul Post-Exertional-Malaise Screening) was conducted in the home environment. Results: 80% of patients experienced severe PASC at follow up. Clinically relevant symptoms of depression, persistent somatic symptoms, anxiety, and fatigue were reported by 55.8%, 72.5%, 18.9% and 89.4% respectively. Depressive, anxiety and somatic symptom severity decreased significantly over time; fatigue and PEM remained on an unchanged high level. Risk factor for higher depression scores was older age; prior psychiatric illness treated with psychotherapy was associated with more severe depressive, somatic, anxiety and PASC symptoms. PEM symptoms were significantly associated with longer duration between acute infection and initial presentation in the Post-COVID centre. Conclusion: Our findings align with previous research, claiming severe mental health symptoms in PASC syndrome, lasting for months after infection. In-depth assessment of risk and protective factors for mental health implications of PASC is needed for planning health services and disease prevention.

Quorum Sensing (QS) and Machine Learning (ML) hybrid systems represent a groundbreaking innovation in synthetic biology, offering unprecedented control and adaptability in microbial gene regulation and metabolic processes. QS, a microbial communication mechanism, is crucial for coordinating gene expression in response to population density, impacting behaviors such as biofilm formation, virulence, and resource optimization. However, traditional QS systems are constrained by their reliance on static, pre-programmed feedback loops, limiting their flexibility in dynamic, complex environments. This review highlights how integrating advanced ML algorithms—such as reinforcement learning and deep learning—into QS systems can overcome these limitations by enabling real-time data processing, predictive modeling, and dynamic feedback control. Through these innovations, QS-ML systems can autonomously adjust gene expression and metabolic outputs, making them more efficient and scalable in applications ranging from pathogen control to precision medicine and industrial biomanufacturing. Key case studies illustrate the successful deployment of QS-ML systems to combat antimicrobial resistance, optimize bio-production, and enhance therapeutic precision in cancer and immune modulation. Despite the clear advantages, challenges remain in data integration, system robustness, and regulatory oversight. Addressing these hurdles through interdisciplinary collaboration and developing scalable, multi-omics data platforms will be critical for advancing QS-ML systems from experimental settings to real-world applications. This review underscores the transformative potential of QS-ML systems in revolutionizing synthetic biology, with profound implications for personalized medicine, sustainable biomanufacturing, and environmental health.Quorum Sensing (QS) and Machine Learning (ML) hybrid systems represent a groundbreaking innovation in synthetic biology, offering unprecedented control and adaptability in microbial gene regulation and metabolic processes. QS, a microbial communication mechanism, is crucial for coordinating gene expression in response to population density, impacting behaviors such as biofilm formation, virulence, and resource optimization. However, traditional QS systems are constrained by their reliance on static, pre-programmed feedback loops, limiting their flexibility in dynamic, complex environments. This review highlights how integrating advanced ML algorithms—such as reinforcement learning and deep learning—into QS systems can overcome these limitations by enabling real-time data processing, predictive modeling, and dynamic feedback control. Through these innovations, QS-ML systems can autonomously adjust gene expression and metabolic outputs, making them more efficient and scalable in applications ranging from pathogen control to precision medicine and industrial biomanufacturing. Key case studies illustrate the successful deployment of QS-ML systems to combat antimicrobial resistance, optimize bio-production, and enhance therapeutic precision in cancer and immune modulation. Despite the clear advantages, challenges remain in data integration, system robustness, and regulatory oversight. Addressing these hurdles through interdisciplinary collaboration and developing scalable, multi-omics data platforms will be critical for advancing QS-ML systems from experimental settings to real-world applications. This review underscores the transformative potential of QS-ML systems in revolutionizing synthetic biology, with profound implications for personalized medicine, sustainable biomanufacturing, and environmental health.

Since severe acute respiratory syndrome coronavirus (SARS-CoV)-2 emerged in December 2019, significant research has been conducted around the world to understand the virus- and vaccine-generated immune response, and to identify the drivers of severe coronavirus disease 19 (COVID-19). Although viral tropism is largely limited to the respiratory tract, SARS-CoV-2 infection can lead to severe COVID-19 disease, which is characterized by multiorgan failure and permanent cognitive disorders. The combined effects of virus-mediated inhibition of host antiviral mechanisms and the recognition of pathogen-associated molecules by pattern recognition receptors (PRRs) are the main drivers in the pathogenesis of severe disease. The innate immune system constitutes the first line of defense against SARS-CoV-2 by limiting the entry of the virus into the host cell, suppressing viral replication, detecting virus-infected cells, and accelerating the formation of the adaptive immune response. The adaptive immune system is composed of two basic cells, B and T cells, which serve different but complementary functions in viral infections. Although the critical role of adaptive immunity in clearing SARS-CoV-2 infection is well known, its function in the development of virus-induced immunopathogenesis remains poorly understood. The basic characteristic of the humoral immune response is the creation of specific antibodies to each foreign antigen encountered. Antibodies that sense pathogens are classified as neutralizing antibodies (nAbs) and non-neutralizing antibodies (non-nAbs) based on their capacity to neutralize pathogens and inhibit membrane fusion. While nAbs exert their activities by blocking ACE2-dependent viral entry into host cells and neutralizing pathogens, the functions of non-nAbs are often undetectable. The level of anti-SARS-CoV-2 antibodies in serum and mucosal tissues varies with the stage and severity of the COVID-19 infection. Although current COVID-19 vaccines elicit robust antibody responses, this effect decreases over time, due to the weakening of immunity and the emergence of novel variants that evade the antibody response, such as Delta and Omicron. SARS-CoV-2 may evade host innate immune surveillance by minimizing host recognition and interfering with cellular immune signaling. In this review article, the central role of host immune responses in the pathogenesis of COVID-19 and the effectiveness of COVID-19 vaccines, as well as the immune evasion strategies of SARS-CoV-2 are discussed in detail in the light of novel knowledge.

Abstract: Thermostability of vaccines, particularly enveloped viral vectored vaccines, remains a challenge for their delivery wherever needed. Freeze-drying of viral vectored vaccines is a prom-ising approach but remains challenging due to the water removal process from the outer and in-ner parts of the virus. In the case of enveloped viruses, freeze-drying induces increased stresses on the envelope, which often leads to inactivation of the virus. In this study, we design a method to freeze-dry a recombinant Vesicular Stomatitis Virus (VSV) expressing the SARS-CoV-2 spike glycoprotein. Since the envelope of VSV is composed of 50% lipid and 50% protein, the formula-tion study focused on both the protein and lipid portions of the vector. Formulations were pre-pared primarily using sucrose, trehalose, and sorbitol as cryoprotectants; mannitol as a lyopro-tectant; and histidine as a buffer. Initially, the infectivity of rVSV-SARS-CoV-2 and cake stability were investigated at different final moisture contents. High recovery of the infectious viral titer ( 0.5 to 1 log loss) was found at 3-6% moisture content with no deterioration of the freeze-dried cakes. To further minimize infectious viral titer loss, the composition and concentration of the ex-cipients were studied. An increase from 5 to 10% of both cryoprotectants and lyoprotectant, to-gether with the addition of 0.5% gelatin, resulted in the improved recovery of infectious virus titer and stable cake formation. Moreover, the secondary drying temperature of the freeze-drying pro-cess showed a significant impact on the infectivity of rVSV-SARS-CoV-2. The infectivity of the vector declined drastically when the temperature was raised above 20°C. Throughout a long-term stability study, formulations containing 10% sugar (sucrose/trehalose), 10% mannitol, 0.5% gelatin, and 10 mM of histidine showed satisfactory stability for six months at 2-8°C. The development of this freeze-drying process and the optimized formulation minimizes the need for a costly cold chain distribution system.

Various vaccines have been developed in response to the SARS-CoV-2 pandemic, and the safety of vaccines has become an important issue. COVID-19 vaccines-related central nervous system inflammatory demyelinating diseases (CNS IDDs) have been reported recently. We present one case of AstraZeneca vaccine-related myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease and literature review another 78 patients published from January 2020 to October 2022. Patients were divided into three vaccine groups (viral vector, mRNA and inactivated vaccines) for further analyses. Among 79 patients with COVID-19 vaccines-related CNS IDDs, 49 (62%) cases received viral vector vaccines, 20 (25.3%) received mRNA vaccines and 10 (12.7%) received inactivated vaccines. Twenty-seven cases (34.2%) were confirmed with autoantibodies, including 15 patients (19%) with anti-MOG, 11 (13.9%) with anti-aquaporin 4 (AQP4), and one (1.3%) with both antibodies. Significantly, more males developed CNS IDDs post viral vector vaccines compared to mRNA and inactivated vaccines. Patients receiving mRNA vaccines were older than other groups. Furthermore, mRNA and inactivated vaccines correlated more with anti-AQP4 antibodies, while viral vector vaccines showed higher MOG positivity. The research suggests potential associations between COVID-19 vaccines-related CNS IDDs and gender, age, and autoantibodies, contingent on vaccine types. Protein sequence analysis implies similarities between the S protein and AQP4/MOG. Further studies may elucidate the mechanisms of CNS IDDs, aiding vaccine selection for specific groups.

Background: Antiphospholipid antibodies (aPL) are a laboratory criterion for the classification of antiphospholipid syndrome (APS), and are known to cause clinical symptoms: vascular thrombosis or obstetric complications. It is suggested that aPL may be associated with thromboembolism in severe COVID-19 cases. Aim: to combine clinical data with aPL findings at 4 time points (admission, worsening, discharge, 3-month follow-up) in patients hospitalized with COVID-19 pneumonia. Methods: current and past history of thrombosis and obstetric complications; aPL determined at 4 time points: anticardiolipin (aCL), anti-β2-glycoprotein I (anti- β2GPI) and antiphosphatidylserine/prothrombin (aPS/PT) of the IgM, IgG or IgA isotypes. Results: 111 patients with COVID-19 pneumonia were enrolled. During hospitalization, 7 patients died, 3 of them due to pulmonary artery thromboembolism (none was aPL positive). Only one of the five who developed pulmonary artery thrombosis was aPL positive. Of 9/101 patients with a history of thrombosis, 5 had arterial thrombosis and none was aPL positive at admission and follow-up; 4 had venous thrombosis and one was aPL positive at all time points (newly diagnosed APS). Of these 9/101 patients, 55.6% were transiently aPL positive at discharge only, compared to 26.1% without history of thrombosis (p=0.05). Conclusions: aPL were not associated with fatal outcomes and vascular thrombosis; aPL were transiently positive in more than half of patients with a history of thrombosis.

Several vaccines against COVID -19 have been developed and licenced to enhance the immune response against SARS-CoV-2. Similarly, infection with SARS-CoV-2 before vaccination has been shown to provide significant protection against severe infection and hospitalisation. The aim of this study was to investigate the effect of three doses of Sinopharm vaccine and SARS-CoV-2 infection on the specific immune response in 103 volunteers, measuring neutralizing antibodies, anti-S1 IgG, anti-RBD IgM, anti-N IgM, anti-N IgG antibodies and interferon γ. Our results showed that the presence of cardiovascular diseases increased the level of anti-N-IgG antibodies, while endocrinological diseases decreased the level of neutralizing antibodies and anti-N-IgG antibodies, suggesting that these diseases alter the effect of vaccine immunity. In addition, there was a significant decrease in anti-S1 IgG levels 6 months and in anti-N IgG levels 18 months post-infection, while neutralizing antibody and interferon γ levels were constant at 3, 6 and 18 months post-infection. Therefore, our results confirm the importance of hybrid immunity as the strongest and most durable compared to exclusively natural or vaccine-induced immunity. Significant positive correlations were found between humoral and cellular immunity markers: neutralizing antibodies, anti-S1 IgG, anti-N IgG and interferon γ, indicating a unique coordinated response specific to COVID-19.

Background:Although highly strict social distancing and viral spread protection guidelines are in force, the reported numbers of COVID-19 cases across the world are still increasing. This indicates that we are still unable to completely understand the transmission routes of SARS-CoV-2. One of the possible routes that can play a significant role is the fecal-oral transmission since SARS-CoV-2 can replicate in the intestines as demonstrated by isolation of infectious virus from fecal samples of COVID-19 cases. Scope and approach:In this review, we compare the characteristics of SARS-CoV-2 with the distinctive characteristics of enteric foodborne viruses. We also discuss and respond to the arguments given in some reports that downplay the importance of foodborne transmission route of SARS-CoV-2. Key findings and conclusions:Enteric viruses such as human noroviruses (HuNoVs) and hepatitis A virus (HAV) are known to transmit through foods such as fresh produce and berries, leading to frequent multistate foodborne disease outbreaks all over the world. SARS-CoV-2 was found to share four distinctive characteristics of foodborne viruses that allow them to transmit through foods. This similarity in characteristics, recent report of detecting SARS-CoV-2 particles from frozen food packages in China, and recent suspected foodborne COVID-19 case in New Zealand, indicate that foodborne transmission of SARS-CoV-2 is more evident than previously thought possible. To support or deny this route of transmission, urgent research needs to be undertaken to answer two primary questions and many secondary ones as described in this review.

Reciprocal Personal/Public Protection (RPPP) featured with source control is introduced, Mask Discriminating Mouth and Nose (MDMN) is employed to serve the purpose, which includes polymer based mouth cover with optional nose cover. The new knowledge that mouth is a primary, active and dominant source of the virus has been well established, which is the base of MDMN. Source classification and related source control tools are discussed, mouth cover is recommended as the tool prioritized to use. Liquid droplets is identified as a hard issue related to mask, liquid droplets, mask fitting, comfort and facial recognition constitute real challenges of mask in addition to efficiency, All of these have been addressed with MDMN. Comparisons between MDMN and masks/face covering are taken on four aspects: efficiency and efficacy, tolerance and comfort, cost and waste, and civil rights and public interest. Mouth cover is recommended to replace the face covering and act as both a personal tool and a public utensil, mouth cover with nose cover can provide better protection than N95 etc. RPPP with MDMN, could be an alternative for lockdown, a parallel strategy to vaccine, and a collectively living way during the pandemic era. MDMN, featured with high efficiency protection, high degree comfort, easy wearing, tight-fitting, easy facial recognition & communication, reusability, cost-effective, environment friendly and scale manufacturing more readily and widely etc., is a simple and sustainable solution, which is essential for ordinary people to keep wearing it properly for protection.

In Kenya, millions of children have limited access to nurturing care. With the COVID-19 pandemic, it is anticipated that vulnerable children will bear the biggest brunt of the direct and indirect impacts of the pandemic. This review aimed to deepen understanding of the effects of COVID-19 on nurturing care from conception to four years of age, a period where the care of children is often delivered through caregivers or other informal platforms. The review has drawn upon the empirical evidence from previous pandemics and epidemics, and anecdotal and emerging evidence from the ongoing COVID-19 crisis. Multifactorial impacts fall into five key domains: direct health; health and nutrition systems, economic, social and child protection, and child development and early learning. The review proposes program and policy strategies to guide the re-orientation of nurturing care, prevent the detrimental effects associated with deteriorating nurturing care environments, and support the optimal development of the youngest and most vulnerable children. These include the provision of cash transfers and essential supplies for vulnerable households, and strengthening of community-based platforms for nurturing care. Further research on COVID-19 and the ability of children’s ecology to provide nurturing care is needed, as is further testing of new ideas.

To predict how the COVID-19 pandemic progresses, we developed a systematic method for predicting disease outcomes. In the method, we evaluate how personal disease outcomes are mainly affected by viral concentration and exposure time and four defense mechanisms: human innate immunity/host response, acquired immune response, inflammation resolution and micro circulation, and the available space in the thorax cage. By considering how pandemic measures affect viral exposure and those mechanisms, we found many pandemic measures are misused or abused to deliver long-term adverse impacts. We noted that lifestyles have been changed as a result of movement restriction measures. By using the method, we found that altered lifestyles are predicted to raise infection rate, disability and death risks in the future. We show that a person can use personal, environmental, emotional factors to reduce infection rate and death risk. To prove the validity of this finding, we extensively examined medical research models, holistic and reductionist models, epidemiological models, disease risk factors, etc, and found that population methods are unfit for studying holistic health, statistical population does not exist in most clinical trials, mathematical models were misused for studying disease properties for a population, mathematical equations for modeling personal diseases are beyond human ability to solve, statistical models are misused, population-derived treatments are inherently dangerous to patients, vaccines have limited benefits due to unique lung structure and rapid RNA mutation, and immune system damage is caused by fast viral replication rate. We found that altering biological properties to improve the defense mechanisms could prevent a super majority of deaths and prevent the virus from reaching a point to damage the immune system. For vulnerable persons, such measure is a viable strategy for surviving from the pandemic. As a whole, holistic personalized medicine is more powerful than population-based reductionist treatment by one to several orders of magnitudes. We urge people do their parts to force the medical establishment to abandon population treatment models that are responsible for failure of medicine and dissemination of misleading and factually wrong information on the effectiveness of medical treatments.

The spread of the infection caused by the new coronavirus SARS-CoV-2 (COVID-19) became pandemic on March 11, 2020. From the time of the first cases (in November 2019, Wuhan, China), to date, a large number of COVID-19 observations have been accumulated in different age groups of patients both in China and abroad. Published scientific data allows us to conclude that children suffer from COVID-19 much less often than adults and tolerate the disease in a milder form, often appear to be asymptomatic. There is currently no final answer why children are less susceptible to this virus; however, scientists are increasingly inclined to consider a complex effect of the immune response and components of the renin-angiotensin system (RAS), which according to recent studies affects not only the cardiovascular system, but is also responsible for the activation of inflammatory reactions. A hypothesis of genetic predisposition to the development of severe forms of COVID-19 has recently been made. We conducted a search for publications in the databases and showed current scientific ideas about COVID-19 pathogenesis and factors influencing the disease development in childhood. Childhood immunity may have several protective features against SARS-CoV-2: immaturity of particular elements of the innate immune response, constitutional lymphocytosis with a shift towards anti-inflammatory Th2-response, as well as "trained" immunity. The influence of renin-angiotensin system reactions in this review is shown from two perspectives: expression of ACE2 receptors and polymorphisms of certain genes of this system. It was established that ACE2 transmembrane protein is not only the entry point for the virus but also plays a regulatory role, turning the pro-inflammatory vasoconstrictor angiotensin II into anti-inflammatory angiotensin (1-7), which has vasodilating properties. Higher ACE2 content in children compared with adults helps maintain balance in the renin-angiotensin system and prevents the development of complications. It was also shown that the presence of certain genetic polymorphisms (AGTR1, AGTR2, ACE2, ACE) could determine the imbalance inside the RAS, leading to more pronounced reactions of alveolocytes, vascular endothelium and smooth muscle fibers in response to SARS-CoV-2 infection due to a shift towards vasoconstrictor, proliferative and profibrotic mechanisms.

The world is in the grips of the COVID-19 pandemic. Public health measures that can reduce the risk of infection and death in addition to quarantines are desperately needed. This article reviews the roles of vitamin D in reducing risk of respiratory tract infections, knowledge about the epidemiology of influenza and COVID-19, and how vitamin D supplementation might be a useful measure to reduce risk. Through several mechanisms, vitamin D can reduce risk of infections. Those mechanisms include inducing cathelicidins and defensins that can lower viral replication rates and reducing concentrations of pro-inflammatory cytokines that produce the inflammation that injures the lining of the lungs, leading to pneumonia, as well as increase concentrations of anti-inflammatory cytokines. Several observational studies and clinical trials reported that vitamin D supplementation reduced risk of influenza, whereas others did not. Evidence supporting the role of vitamin D in reducing risk of COVID-19 includes that the outbreak occurred in winter, a time when 25-hydroxyvitamin D [25(OH)D] concentrations are lowest; that the number of cases in the Southern Hemisphere near the end of summer are low; that vitamin D deficiency has been found to contribute to acute respiratory distress syndrome, and that case-fatality rates increase with age and with chronic disease comorbidity, both of which are associated with lower 25(OH)D concentration. To reduce risk of infection, it is recommended that people at risk of influenza and/or COVID-19 consider taking 10,000 IU/d of vitamin D₃ for a few weeks to rapidly raise 25(OH)D concentrations, followed by 5000 IU/d. The goal should be to raise 25(OH)D concentrations above 40–60 ng/ml (100–150 nmol/l). For treatment of people who become infected with COVID-19, higher vitamin D₃ doses might be useful. Randomized controlled trials and large population studies should be conducted to evaluate these recommendations.

The Impact of Event Scale-Revised (IES-R) is the most popular measure of post-traumatic stress disorder (PTSD), which has been recently validated in Arabic. This instrumental study aimed to determine optimal cutoff scores of the IES-R and its subscales in Arab samples of psychiatric patients (N = 168, 70.8% females) and healthy adults (N = 992, 62.7% females) from Saudi Arabia during the COVID-19 pandemic as an ongoing collective traumatic event. Based on a cutoff score of 14 of the Depression Anxiety Stress Scale 8-items (DASS-8), receiver operator curve (ROC) analysis revealed two optimal points of 39.5 and 30.5 for the IES-R in the samples (area under the curve (AUC) = 0.86 &amp; 0.91, p values = 0.001, 95% CI: 0.80-0.92 &amp; 0.87 to 0.94, sensitivity = 0.85 &amp; 0.87, specificity = 0.73 &amp; 0.83, Youden index = 0.58 &amp; 0.70, respectively). Different cutoffs were detected for the six subscales of the IES-R, with numbing and avoidance expressing the lowest predictivity for distress. Meanwhile, hyperarousal followed by the irritability expressed stronger predictive capacity for distress than all subscales in both samples. In path analysis, pandemic-related irritability resulted from direct and indirect effects of key PTSD symptoms (intrusion, hyperarousal, and numbing). Irritability contributed to traumatic symptoms of sleep disturbance in both samples while the opposite was not true. The findings suggest usefulness of the IES-R at a score of 30.5 for detecting adults prone to trauma related distress, with higher scores needed for screening in psychiatric patients. Various PTSD symptoms may induce dysphoric mood, which represents a considerable burden that may induce circadian misalignment and more noxious psychiatric problems/ co-morbidities (sleep disturbance) in both healthy and diseased groups.

Objective: To analyze prevalence of tuberculosis among the people who presented PIMS with complaints of fever, cough, difficulty in breathing during COVID pandemic.Study Design: Retrospective/ Cross-sectional study.Place and Duration: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad. 2020-2023. Methods: Total 17121 patients who presented PIMS during COVID pandemic with complaints of high grade fever, cough, difficulty in breathing ,were included in this study. Following the acquisition, the HRCT scans were conducted by a skilled and experienced technician and researcher, utilizing GE Healthcare equipment for HRCT Chest procedures. The scans covered the lung apices to the bases and were executed with maximal inspiration, employing a CT scanner from Toshiba Aquilion. Frequency of TB among all cases was recorded. SPSS 21.0 was used to analyze all data.Results: This study incorporated a total of 17,121 patients, comprising 9,961 (58.1%) males and 7,160 (41.8%) females. The mean age of the enrolled cases was 49.11±7.67 years, demonstrating consistency with the findings of a prior study [33]. This study also examined the prevalence of Tuberculosis in different years based on imaging findings of HRCT chest as follows: in 2020, 582 cases out of 2,450, equivalent to 23.7%; in 2021, 2,377 cases out of 9,584, equivalent to 24.8%; in 2022, 1,099 cases out of 3,913, equivalent to 28.1% and in 2023, 295 cases out of 1,174, equivalent to 25.1%. The average prevalence of TB cases from 2020 to 2023 was determined to be 4,353 cases out of 17,121, which is equal to 25.42%.Conclusion: As per the National Tuberculosis Program (NTP) in Pakistan, the prevalence rate of tuberculosis stands at 340 cases per 100,000 population, equivalent to 0.34%. However, our study reveals an exceptionally high frequency of TB cases. Specifically, the prevalence of Tuberculosis in 2020 was 23.7% (582 out of 2,450), in 2021 it was 24.8% (2,377 out of 9,584), in 2022 it surged to 28.1% (1,099 out of 3,913), and in 2023 it was 25.1% (295 out of 1,174). The average prevalence of TB cases over the period from 2020 to 2023 was calculated at 25.4% (4,353 out of 17,121). Consequently, our findings suggest the presence of a substantial tuberculosis burden in Pakistan, equating to a TB Tsunami in Pakistan.

Background: The interruption of the activity of the population-based organized colorectal cancer (CRC) screening programs due to the COVID pandemic may have affected their results in terms of detection of preneoplastic lesions and CRC. We evaluated the impact of the COVID pandemic on the delays, participation, adherence to colonoscopies, lesions detected, and CRC stage at di-agnosis in a CRC screening program. Methods: We analyzed all the invitations between January 1, 2019, and December 31, 2021. We defined the pandemic period as the period after March 12, 2020. We calculated the delay intervals (successive and all rounds), the rates of participation, adherence to colonoscopy after a positive fecal immunochemical test (FIT), and the diagnostic yield of colonoscopy, specifically CRC and colorectal neoplasia (CRC and/or adenoma), as well as CRC stage at diagnosis. Results: In the period analyzed, 976,187 invitations were sent (61.0% pandemic), 439,687 FIT were returned (62.4% pandemic) and 23,092 colonoscopies were performed (59.1% pandemic). Colon-oscopies were normal in 7,378 subjects (32.4%) and a CRC was detected in 916 subjects (4.0%). In successive rounds, the delay increased significantly seven months during the pandemic period (p<0.001). In all the invitations, the delay from the invitation to the colonoscopy increased sig-nificantly by 8 days (p<0.001). Once adjusted for the confounding variables, participation in the screening program increased significantly (OR=1.1; 95% CI=1.09-1.11), with no changes in the adherence to colonoscopy (OR=0.9; 95% CI=0.8-1.0). We found no differences in the diagnostic yield of colonoscopy in terms of CRC (OR=0.90; 95% CI=0.78-1.02) or colorectal neoplasia (OR=0.98; 95% CI=0.92-1.03) detection. Finally, we found no differences in CRC stage at diagnosis (p=0.2). Conclusions: Although the interruption of the CRC screening program due to the COVID pan-demic increased the delays, it did not reduce participation, adherence to colonoscopy, or the di-agnostic yield of colonoscopy.

This paper presents a comparative bibliometric analysis of digital transformation in small and medium enterprises, focusing on the before and after the Covid-19 pandemic. Using data from the Scopus database, the study analyzes 1,566 articles published between 2001 and 2024, focusing on pre-COVID (2001–2018) and post-COVID (2019–2024). Bibliometric tools, including VOSviewer and Biblioshiny, were employed to conduct performance analysis, scientific mapping, and co-occurrence analyses of keywords and co-authorship. The results demonstrate a substantial increase in research output post-COVID, particularly in areas such as the Internet of Things (IoT), cloud computing, and e-commerce. These technologies have become vital for the survival and competitiveness of SMEs in the post-pandemic world. However, the study also highlights significant challenges, including limited financial resources and a lack of skilled personnel, which have hindered SMEs' ability to implement digital transformation fully. Government intervention, through financial assistance and strategic support, is identified as crucial in enabling SMEs to overcome these obstacles and successfully navigate the digital era. This analysis contributes to the growing body of literature on SMEs' digitalization, offering key insights for policymakers, researchers, and businesses aiming to adapt to the evolving digital landscape in a post-pandemic economy.

Neurological involvement following COronaVIrus Disease 19 (COVID-19) is thought to have a neuroinflammatory etiology. Co-ultraPEALut (an antiinflammatory molecule) and luteolin (an antioxidant) yielded promising results as neuroinflammation antagonists. This study aimed at describing cognitive impairment in post-COVID patient treated with co-ultraPEALut. Montreal Cognitive Assessment (MoCA), Prospective-Retrospective Memory Questionnaire (PRMQ), Fatigue Severity Scale (FSS) and a subjective evaluation were administered at baseline and after 10 months. Co-ultraPEALut-treated patients were retrospectively compared with controls. 26 co-ultraPEALut-treated patients showed significant improvement in PRMQ (T0: 51.94±10.55, T1: 39.67±13.02, p

Earnings management and financial distress are two critical facets of financial management in corporations that have lately been the focus of thorough research from both scholars and practitioners. The purpose of the research is to evaluate the influence of financial distress on the earnings management of companies listed at the NSE during the pre- and post-COVID eras. Multiple linear regression was applied in this study to examine the causal association between earnings management and financial distress. To assess the effect of financial distress on earnings management, the study analyzed data from 37 listed companies during the pre-COVID and post-COVID periods. The methodology also takes into account control factors like firm size, GDP, and inflation. The pre-COVID research indicates a significant positive correlation between financial strain and earnings management. In contrast, the correlation between financial distress and earnings management is not statistically significant in the post-COVID analysis. However, research shows that firm size has a statistically significant negative influence on managing earnings. The results of this study show that smaller firms are more inclined to engage in earnings management during the post-COVID era than bigger ones.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Introduction: The COVID-19 pandemic highlighted the necessity for rapid, efficient testing at large-scale events. Developing rapid and efficient testing methods was critical, especially for events with a high risk of virus spread. The queueing theory offers a powerful tool to manage the flow of people through testing centers. This study uses the M/M/c model to examine how different floor plan configurations impact the efficiency of RADT testing centers. Aim of the study: This research applies queueing theory to optimize the Rapid Antigen Diagnostic Test (RADT) processes at mass gatherings. The study uses the M/M/c queueing model to evaluate the dynamics of RADT centers configured in U-shaped and straight-line layouts. The primary goal is to assess the feasibility of using RADTs efficiently at events and mass gathering entrances, aiming to enhance throughput and minimize wait times. Methodology: The study involved 500 healthy participants, managed by medical staff across a U-shaped and a straight floor plans. Agile management techniques were employed to enhance operational efficiency. The process stages included queue number issuance, registration, sample collection, sample mixing, and results dissemination. Results: Both floor plans enabled the completion of RADT screening in approximately 2 minutes per participant. The U-shaped layout slightly outperformed the straight-line setup in efficiency, demonstrating its effectiveness in optimizing the testing process. Conclusion: This study confirms the feasibility of implementing Rapid Antigen Diagnostic Test (RADT) processes at mass gatherings. It was found that the U-shaped floor plan configuration is particularly effective, indicating its potential suitability for future mass testing scenarios.

Introduction: In Part II of this three-part series, we expose techniques that can be used by the U.S. Centers for Disease Control and prevention (CDC) and Food and Drug Administration (FDA) to manipulate and throttle the Vaccine Adverse Event Reporting System (VAERS), a vaccine safety monitoring system open to the public. The U.S. government’s recommendation of COVID-19 vaccines during pregnancy was more a product of propaganda than of science and plagued with conflicts of interest. The extreme breach of COVID-19 vaccine pregnancy complication safety signals documented in VAERS cannot be disregarded or concealed. As a result, CDC/FDA are moving to closed, government captured platforms, including V-safe, Vaccine Safety Datalink (VSD) system, and the Biologics Effectiveness and Safety (BEST) system. Public transparency of adverse events following COVID-19 vaccination in pregnancy should be increased, not thwarted. Methods: In Part I the CDC/FDA Vaccine Adverse Event Reporting System (VAERS) database was queried from January 1, 1990, to April 26, 2024 for adverse events (AEs) involving pregnancy complications following vaccination. In Part II we investigate tactics discovered in VAERS that concealed vaccine injuries and deaths. Conflicts of interest, as well as specific communications and publications from the CDC/FDA and the New England Journal of Medicine (NEJM) are analyzed. Results: Of all VAERS AE reports, 8.47% (138,983) of COVID-19 reports had no vaccination date and thus were missing from the data presented in Part I of this series. We unconcealed data presented in Part I of this series to include VAERS case reports that were excluded when using standard queries because of an “unknown vaccination date”. The unconcealed data in the 37 AE cases reported in this study (Part II) ranged from 0 - 38% with a mean of 8.2% (standard deviation 9.7%) and the significant breaches of VAERS safety signals in Part I of this series were largely underestimated. Another method of concealing vaccine associated AEs is to exclude the specific vaccine type rendering it as an “unknown vaccine type”. “Unknown vaccine type” has logarithmically increased since the rollout of the COVID-19 vaccines in 2021, ranging from 1 to 400 cases between 1990 to 2018 to 11,461 cases in 2021. CDC/FDA granted $67 million via a Cooperative Agreement grant to Massachusetts Department of Public Health (MDPH) between July 1, 2019, to June 30, 2025. MDPH then made subawards under this grant to 21 influential public and private health and civic organizations, including NEJM’s owner, Massachusetts Medical Society (MMS). As one of the subawardees under the grant, MMS as owner of NEJM received over $426,000 in federal HHS/CDC grant money from 2019 to 2020 for “public health and medical emergency preparedness projects”. Conclusions: CDC/FDA has failed to capture and account for a significant number of AE case reports following COVID-19 in VAERS by a variety of techniques in an apparent attempt to sanitize the data. CDC’s Rochelle Walensky and NEJM’s Editor-in-Chief Eric Rubin pushed novel untested COVID-19 vaccines in pregnant women despite clear evidence from multiple sources that safety signals had been breached.

This study presents the interaction with human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a Protein-Protein-Interaction Networks analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2,753 proven interactions and 1,708 interactors, specific to ORF7b. We used these proteins as functional seeds and we got a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. Seven high ranked proteins as hub and seven as bottleneck following a hub-and-spoke network-architectural-model were found. Through this interaction model, we identified significant GO-processes (5,057 terms in 15 categories) induced in human metabolism by ORF7b. High statistical significance processes of dysregulated molecular cell mechanisms by the action of ORF7b were discovered. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems and the molecular mechanisms that supervise to programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant-Connected-Components core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b mainly acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation, transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes, within the limits of the poor knowledge that these sectors still impose.

Our goal was to determine the cellular immune response (CIR) among a random sample of the Borriana COVID-19 cohort (Spain) to identify its associated factors and their relationship with infection, reinfection and sequelae. We conducted a nested case-control study using a randomly selected sample of 225 individuals age 18 and older, including 36 individual naïve to SARS-CoV-2 infection, and 189 infected patients. We employed flow cytometry-based immunoassays for intracellular cytokine staining, utilizing Wuhan and BA.2 antigens and chemoluminescence microparticle immunoassay for detection SARS-CoV-2 antibodies. Logistic regression models were used. A total of 215 (95.6%) participants exhibited T-cell response (TCR) to at least one antigen. Positive responses of CD4+ and CD8+ T cells were 89.8% and 85.3% respectively. No difference in CIR was found for naïve and infected patients. Patients who experienced sequelae exhibited higher CIR than those without. A positive correlation was observed between TCR and Anti-Spike IgG levels. Factors positive associated with TCR included A-blood group, number of SARS-CoV-2 vaccine doses received, and Anti-N IgM; factors inversely related were the time elapsed since the last vaccine dose or infection, and B-blood group. These findings contribute valuable insights into the nuance immune landscape shaped by SARS-CoV-2 infection and vaccination.

We tested the possibility of using “adverse events count” (AEC) as a drug-risk indicator and side-effect severity indicator. Data from 3938 adverse event (AE) reports for COVID-19 vaccines (Comirnaty, Moderna, Vaxzevria, and Janssen) and 6869 AE reports for other medicines were collected from the Bulgarian Drug Agency database (01.01.2018–31.03.2022). AEC was modeled with zero-adjusted negative binomial (ZANBI) and zero-adjusted Poisson inverse Gaussian (ZAPIG) regression models, which account for zero absence and overdispersion. The models’ fit was checked with residual diagnostic plots and parametric correspondence to normality. Explanatory variables were: age, sex, sequence number (order of submission), severity of AE, and vaccine type. Average AEC was higher in severe vs. non-severe AE, and in females vs. males; it decreased with age and was lower in Comirnaty than other vaccines. Variability of AEC for COVID-19 data decreased with sequence number in severe AE and increased in non-severe AE. Full ZANBI models had greater sensitivity than parametric ZANBI or ZAPIG models. Results showed correlation between AEC and AE severity, suggesting AEC as a simple and reliable measure of drug-risk and side-effect severity for clinicians and regulators, especially for COVID-19 vaccines.

Global rapidly evolving events, e.g., COVID-19, are usually followed by countermeasures and policies. As a reaction, the public tends to express their emotions on social media platforms. Therefore, predicting emotional responses to events is critical to put a plan to avoid risky behaviors. This paper proposes a machine learning-based framework to detect public emotions based on social media posts in response to specific events. It presents a precise measurement of population-level emotions which can aid governance in monitoring public response and guide it to put in place strategies such as targeted monitoring of mental health, to react to a rise in negative emotions in response to lockdowns, or information campaigns, for instance in response to elevated rates of fear in response to vaccination programs. We evaluate our framework by extracting 15,455 tweets. We annotate and categorize the emotions into 11 categories based on Plutchik’s study of emotion and extract the features using a combination of Bag of Words and Term Frequency-Inverse Document Frequency. We filter 813 COVID-19 vaccine-related tweets and use them to demonstrate our framework’s effectiveness. Numerical evaluation of emotions prediction using Random Forest and Logistic Regression shows that our framework predicts emotions with an accuracy up to 95%.

The coronavirus 2019 (COVID-19) pandemic was caused by a positive sense single-stranded RNA (ssRNA) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, other human coronaviruses (hCoVs) exist, of which Middle East Respiratory Syndrome (MERS) and SARS-CoV (SARS) showed higher mortality rates without causing a pandemic. As of December 2022, SARS-CoV-2 has resulted in over 6.6 million deaths worldwide through an array of acute to chronic pathologies. Historical pandemics include smallpox and influenza with efficacious therapeutics utilized to reduce overall disease burden. Therefore, immune system process analysis is required to compare innate and adaptive immune system interactions. Lymphatic system organs include bone marrow and thymus using a network of nodes throughout which white blood cells traverse glycolipid membranes utilizing cytokines and chemokine gradients that affect cell development, differentiation, proliferation, and migration processes as well as genetic factors affecting cell receptor expression. Innate processes involve antigen-presenting cells and B lymphocyte cellular responses to pathogens relevant to other viral and bacterial infections but also in oncogenic diseases. Such processes utilize cluster of differentiation (CD) marker expression, major histocompatibility complexes (MHC), pleiotropic interleukins (IL) and chemokines. The adaptive immune system consists of Natural Killer (NK) and T cells. Other viruses are also contributory to cancer including human papillomavirus (cervical carcinoma ), Epstein-Barr virus (EBV) ( lymphoma), hepatitis B and C (hepatocellular carcinoma) and human T cell leukemia virus-1 (adult T-cell leukemia). Bacterial infections also increase the risk of developing cancer( e.g. H. pylori). Therefore, as the above factors can cause both morbidity and mortality along-side being transmitted within clinical and community settings, it is appropriate to now examine advances in single cell sequencing, FACS analysis and many other laboratory techniques that allow insights into discoveries of newer cell types. These developments offer improved clarity and understanding that over-lap with known autoimmune conditions that could be affected by innate B cell or T cell responses to SARS-CoV-2 infection. Thus, this review quantifies and outlines the nature of specific receptors and proteins relevant to clinical laboratories and medical research by documenting both innate and adaptive immune system cells within current coronavirus immunology case study data and other pathologies to date.

Inactivated SARS-CoV-2 vaccine (CoronaVac) is commonly used in national immunization programs. However, the immune response significantly declined within a few months. Our study assessed the immune response against SARS-CoV-2 after receiving booster shots of BNT162b2 or ChAdOx1 among health care workers who previously received CoronaVac as their primary immunization. Fifty-six participants received ChAdOx1 and forty-two participants received BNT162b2 were enrolled into this study which evaluated the immune responses including anti-SARS-CoV-2 spike total antibodies (Elecsys®), surrogated viral neutralization test (sVNT) to ancestral strain (cPass™; GenScript) and five variants of concern (Alpha, Beta, Gamma, Delta, and Omicron) (Luminex; multiplex sVNT) and the ELISpot with spike (S1 and S2) peptide pool against the ancestral SARS-CoV-2 strain. The samples were analyzed at baseline, 4, and 12 weeks after primary immunization as well as 4 and 12 weeks after receiving the booster. This study showed a significantly higher B-cell response among the BNT162b2 than the ChAdOx1 booster group, particularly against the Omicron variant, as well as a trend of good T-cell immune response in the BNT162b2 group. Moreover, the immune response rapidly declined at 12 weeks after the booster. A fourth dose or a second booster should be recommended, especially for reducing Omicron severity.

Background: Acceleration of mass vaccination strategies is the only pathway to overcome the COVID-19 pandemic. Healthcare professionals and students have a key role in shaping public opinion about vaccines. This study aimed to evaluate the attitudes of dental students globally towards COVID-19 vaccines and explore the potential drivers for students' acceptance levels; Methods: A global cross-sectional study was carried out in February 2021 using an online ques-tionnaire. The study was liaised by the scientific committee of the International Association of Dental Students (IADS), and data was collected through the national and local coordinators of IADS member organizations. The dependent variable was the willingness to take the COVID-19 vaccine, and the independent variables included demographic characteristics, COVID-19-related experi-ence, and the drivers of COVID-19 vaccine-related attitude suggested by the WHO-SAGE; Results: A total of 6639 students from 22 countries representing all world regions responded to the ques-tionnaire properly. Their mean age was 22.06 ± 2.79 (17-40) years, and the majority were females (70.5%), in clinical years (66.8%), and from upper-middle-income economies (45.7%). In general, 22.5% of dental students worldwide were hesitant, and 13.9% rejected COVID-19 vaccines. The students in low- and lower-middle-income (LLMI) economies had significantly higher levels of vaccine hesitancy compared to their peers in upper-middle- and high-income (UMHI) economies (30.4% vs 19.8%; p < 0.001); Conclusions: The global acceptance level of dental students for COVID-19 vaccines was suboptimal, and their worrisome level of vaccine hesitancy was influenced by the socioeconomic context where the dental students live and study. The media and social media, public figures, insufficient knowledge about vaccines, and mistrust of governments and the pharmaceutical industry were barriers to vaccination. The findings of this study call for further implementation of epidemiology (infectious diseases) education within undergraduate dental curricula.

Background Hokkaido is the northernmost, least populous, and coldest of the Japanese islands. It was the first prefecture to be affected by COVID-19, while Kanagawa is home to one of the most populous areas of Japan, namely the Tokyo metro area. The Japanese government responded early during the pandemic by identifying infected patients, contact tracing, and performing PCR analysis on anyone who was suspected of having been exposed to SARS-CoV-2. The government has also been publishing information about each individual who tested positive for the virus. Both Hokkaido and Kanagawa started recording COVID-19 cases in the winter of 2020 and have detailed records of thousands of patients, thus providing an invaluable resource for the transmission and behavior of the virus. Methods The current study analyzed the COVID-19 registry data from the Hokkaido and Kanagawa prefectures. The Hokkaido registry contained 1,269 cases (674 (53%) females and 595 (47%) males) recorded between February 14 and July 22, 2020. The Kanagawa registry had 3,123 cases (1,346 (43%) females and 1,777 (57%) males. The final data contained a total of 4,392 cases (2,020 (46%) females and 2,372 (54%) males). By leveraging the information on viral transmission paths available in the registry data, we performed exponential random graph model (ERGM) network analysis to examine demographic and symptomological homophilies of the SARS-CoV-2 viral transmission networks. Results We observed age, symptomatic, and asymptomatic homophilies in both prefectures. Furthermore, those patients who contracted the virus through secondary or tertiary contacts were more likely to be asymptomatic than those who contracted it from primary infection cases. The transmission networks showed that transmission occurred significantly in healthcare settings, as well as in families, although the size of the networks was small in the latter. Most of the transmissions stopped at the primary and secondary levels and no transmission beyond quaternary was observed. We also observed a higher level of asymptomatic transmission in Kanagawa than in Hokkaido. Conclusions Symptom homophilies are an important component of COVID-19 and suggest that nuanced genetic differences in the virus may affect its epithelial cell type range and can thus result in the diversity of symptoms seen in individuals infected by SARS-CoV-2. Moreover, environmental variables such as temperature and humidity may also be playing an important role in the overall pathogenesis of the virus.

The COVID-19 pandemic has resulted in a wide range of spatial interventions to slow down the spread of the virus. The spatial limitations of narrow public circulation spaces within informal settlements, which house over one billion people around the world, make it impossible for pedestrians to practice physical distancing (or social distancing). In this paper, we propose a flexible mathematical method, named the Cluster Lane Method, for turning a planar circulation network of any size or complexity into a network of unidirectional lanes, making physical distancing possible in narrow circulation spaces by limiting face-to-face interactions. New notions and theorems about oriented graphs in graph theory are introduced. The paper ends with a discussion of the potential implementation of this cost-efficient, low-tech, sustainable solution, and with the introduction of a novel unidirectional tactile paving for the visually impaired.

Thermal sterilization is generally avoided for 3-D printed components because of the relatively low deformation temperatures for common thermoplastics used for material extrusion-based additive manufacturing. 3-D printing materials required for high-temperature heat sterilizable components for COVID-19 and other applications demands 3-D printers with heated beds, hot ends that can reach higher temperatures than polytetrafluoroethylene (PTFE) hot ends and heated chambers to avoid part warping and delamination. There are several high temperature printers on the market, but their high costs make them inaccessible for full home-based distributed manufacturing required during pandemic lockdowns. To allow for all these requirements to be met for under $1,000, the Cerberus – an open source three-headed self-replicating rapid prototyper (RepRap) was designed and tested with the following capabilities: i) 200^oC-capable heated bed, ii) 500^oC-capabel hot end, iii) isolated heated chamber with 1kW space heater core and iv) mains voltage chamber and bed heating for rapid start. The Cereberus successfully prints polyetherketoneketone (PEKK) and polyetherimide (PEI, ULTEM) with tensile strengths of 77.5 and 80.5 MPa, respectively. As a case study, open source face masks were 3-D printed in PEKK and shown not to warp upon widely home-accessible oven-based sterilization.

Introduction: Due to COVID-19 pandemic, performance of many program has been declined and Tuberculosis (TB) program is not an exception. TB case detection and notification has been recognized as one of worst hit area. The objective of this study was to explore the TB notification status of India during this pandemic and explore options to mitigate the issue. Methods: A secondary data analysis was performed on open source TB notification database of India. Relevant literature review was done to find out remedies based on the different initiative taken by different states of India. Results: In 2020, total TB notification decreased in all the states in comparison to 2019. The percentage of loss in the country was 34%. Private TB notification also decreased in 2020 in all the states except in Jharkhand. The percentage of loss in private TB notification in the country was 35%. Notification started declining in the month of February 2020 and it was lowest in the month of April-2020. The trend of notification began to improve since May 2020 when the States started taking innovative initiatives like Integrated TB Covid Case Search. Conclusion: Due to the ongoing COVID-19 pandemic the notifications of TB cases declined noticeably which has a serious implication in terms of silent spread within household and community. But the picture can be improved with integrated approach for TB-COVID case finding and management.

We have collected theoretical arguments supporting the functional role of nano-metallic coatings of solar cells, which enhance their efficiency via by plasmon strengthening of absorption of sun-light photons and reduction of binding energy of photo-excitons. The quantum character of plasmonic effect related with the absorption of photons (called as optical plasmonic effect) is described in terms of Fermi golden rule for quantum transitions of semiconductor band electrons induced by plasmons from a nano-metallic coating. The plasmonic effect related with the lowering of exciton binding energy (called as electrical plasmonic effect) is also quantumly characterized with particular significance for metalized perovskite solar cells. Quantum coupling between plasmons in nanoparticles from a coating with band electrons in a semiconductor substrate significantly modifies material properties (dielectric functions) both of particles and of a semiconductor, beyond the ability of a classical electrodynamics description.

Recent algorithmic-based research in the stock market has predominantly focused on ultra-high-frequency trading and index estimation. We developed an improved algorithm to address the need for a low-frequency, real-world trading model to build on the existing high hit-ratio and low maximum drawdown. We utilized established price indicators, Stochastic and Williams %R, and introduced a volume factor to increase the model's safety to enhance the model's performance. This improved algorithm demonstrated superior returns while maintaining high hit-ratio and low maximum drawdown. Specifically, we leveraged the existing algorithm to trade using 2X and 3X signals, incorporating volume data, the 52-week average, standard deviation, and other factors. The data set comprised SPY ETF price and volume from 2010 to 2023, covering over 13 years. Our enhanced algorithmic trading model outperformed both the benchmark and previous results, achieving a hit rate of over 90%, a maximum drawdown of less than 1%, an average of 1.5 trades per year, a total return of +519.3%, and an annualized return (AnnR) of +15.1%. The analysis demonstrates that the model's simplicity, ease of application, and comprehensibility can assist investors in making informed investment decisions albeit the past performance does not guarantee future returns.

The aim of this work was to investigate a new, simple one-pot combustion synthesis technique for creating sulphur-based CuS/ZnS p-n heterojunction nanocomposite photocatalysts. The study examined the photocatalytic activity and reusability of these nanocomposites in removing rhodamine B (RhB) dye under visible light irradiation. Various methods of characterisation were employed to determine the properties of the materials, including particle morphology, crystalline phases and bandgap energy. The intrinsic reaction parameters, such as catalyst loading, pH level of the solution, and initial pollutant concentration, were varied to establish the optimal photo-degradation conditions. The results showed that a binary CuS/ZnS catalyst with a 10 gL-1 loading, at pH 5, degraded 97% of 5 ppm RhB dye after 270 minutes of visible light irradiation. Addition-ally, this composite catalyst exhibited excellent chemical stability and reusability, achieving 83% RhB dye removal after five recycling runs. Scavenger tests identified the photogenerated holes (h+) and superoxide free radicals (•O2) as the primary reactive species responsible for degradation. This study provides valuable insight into the design of highly efficient nanomaterials for removing organopollutants in wastewater, and a possible reaction mechanism is proposed.

In many practical applications, it is more convenient to characterize the quality of production processes or service operations throughout the count of nonconformities. In the context of SPC, nonconformities are usually assumed to appear according to the binomial probability model. The conventional way for monitoring nonconformities involves Shewhart-type control procedures based on both constant and time-varying sample sizes. In this article, an EWMA scheme is proposed for monitoring the fraction of nonconforming items with time-varying sample sizes. The proposed control chart is referred to as the EWMAG-B and can be easily adapted to work with a constant sample size by fixing it at a needed value. By means of simulation, it was found out that the EWMAG-B chart outperforms the conventional p control chart in Phase II while detecting changes in the process level is wanted.

The thermoelectric generator (TEG) stands out in many energy harvesters due to its simple structure, small size, etc. However, previous studies rarely probe into the influence of TEG internal resistances on extracting maximum power from TEG, and tracking efficiency is limited. By analyzing the relationship between the tracking efficiency and the TEG internal resistances, a time exponential rate perturbation and observation (P&amp;O) technology is proposed to achieve maximum power point tracking (MPPT) for a wide resistance range of TEG. Using the time exponential rate P&amp;O, the MPPT circuit observes the power change by comparing PMOS on-time and perturbs the power by adjusting NMOS on-time exponentially. The MPPT circuit is implemented in a 110nm CMOS process. The tracking efficiency keeps a high level from 98.9 to 99.5%. The applicable range of the TEG resistance is from 1 to 12Ω, which is enhanced at least 2.2 times.

The cellular stress response corresponds to the molecular changes that cell undergoes in response to various environmental stimuli. It induces drastic changes in the regulation of gene expression, at transcriptional and post-transcriptional levels. Actually, translation is strongly affected with a blockade of the classical cap-dependent mechanism, whereas alternative mechanisms are activated to support translation of specific mRNAs. One of the major mechanisms involved in stress-activated translation is the internal ribosome entry site (IRES)-driven initiation. IRESs, first discovered in viral mRNAs, are present in cellular mRNAs coding for master regulators of cell responses, whose expression must be tightly controlled. IRESs allow translation of these mRNAs in response to different stresses, including DNA damage, amino-acid starvation, hypoxia or endoplasmic reticulum stress, as well as to physiological stimuli such as cell differentiation or synapse network formation. Importantly, cellular mRNA IRESs are regulated by IRES trans-acting factor (ITAFs), exerting their action by at least nine different mechanisms. This review presents an update of the reported ITAFs regulating cellular mRNA translation and of the different mechanisms allowing them to control translation initiation in specific conditions. The impact of ITAFs on coordinated expression of mRNA families and consequences in cell physiology and diseases are also highlighted.

P-glycoprotein (P-gp), a membrane-bound transporter, can eliminate xenobiotics by transporting them out of the cells or blood-brain barrier (BBB) at the expense of ATP hydrolysis. Thus, P-gp mediated efflux plays a pivotal role in altering the absorption and disposition of a wide range of substrates. Nevertheless, the mechanism of P-gp substrate efflux is rather complex since it can take place through active transport and passive permeability in addition to multiple P-gp substrate binding sites. A nonlinear quantitative structure-activity relationship (QSAR) model was developed in this study using the novel machine learning-based hierarchical support vector regression (HSVR) scheme to explore the perplexing relationships between descriptors and efflux ratio. The predictions by HSVR were found to be in good agreement with the observed values for the molecules in the training set (n = 50, r² = 0.96, q²_CV = 0.94, RMSE = 0.10, s = 0.10) and test set (n = 13, q² = 0.80–0.87, RMSE = 0.21, s = 0.22). When subjected to a variety of statistical validations, the developed HSVR model consistently met the most stringent criteria. A mock test also asserted the predictivity of HSVR. Consequently, this HSVR model can be adopted to facilitate drug discovery and development.

During the last few years, the world witnessed one of the worst calamities affecting humankind- the COVID-19 pandemic. We also witnessed the development of vaccines at an unprecedented pace against the SARS-CoV-2, the causative agent. India, which was one of the countries most impacted by COVID-19, developed its indigenous vaccine in addition to utilizing the ones developed by other countries. Initially, the antibody level and the neutralizing antibody titer against the pathogen were considered as the correlates of immune protection from the disease. The long-term protection from the pathogen is provided by the immune memory cells viz. T and B memory cells and their ability of efficient recall responses. In this regard, global research focused mainly on the mRNA-based vaccines. The studies on immune memory response, particularly- the B cell memory response bestowed by the vaccines given to Indians is relatively obscure. In this work, we examined the level of RBD specific memory B cells in the peripheral circulation of the study participants and the ability of B cells to secrete antigen-specific antibodies among Indians vaccinated with Covaxin (BBV152), Covishield (AZD1222), Corbevax (BECOV2D) and Sputnik Light as well as unvaccinated individuals. Our study revealed that Corbevax and Sputnik Light conferred better antibody-secreting cell (ASC) responses.

The relentless challenges posed by the COVID-19 pandemic have placed immense pressure on densely populated regions, such as Hong Kong, particularly in the context of an aging population. The burgeoning demand for healthcare services has necessitated the optimization of resource al-location within healthcare systems. This research presents an innovative analytical queueing model specifically tailored to address the intricate gridlock dynamics prevalent in healthcare systems, with a focused application in the challenging landscape of COVID-19 management. Hong Kong, like numerous other regions, has experienced a demo-graphic transition leading to heightened healthcare demands. Traditional methodologies for scrutinizing gridlock issues in healthcare settings, including simulation models, often prove suboptimal within the context of sophisticated optimization frameworks. This study, however, delves into analytical queueing models, offering a more efficient and effective approach. These models have been underexplored, primarily due to the intricacies involved in modeling gridlock propagation within restricted capacity, a critical concern magnified by the COVID-19 pandemic. The novel Queueing Model introduced in this research incorporates the maintenance of queue capacities and topological aspects as exogenous parameters, rendering it exceptionally adaptable for diverse gridlock-related applications. This adaptability is especially pertinent to healthcare management during the COVID-19 crisis. The model meticulously integrates the concept of gridlock, furnishing a comprehensive comprehension of its origins and repercussions. Validation of this model involves rigorous comparison with established methodologies, exact results, and simulation data, consistently high-lighting its versatility and precision. By applying the model to healthcare management, we scrutinize the dynamics of patient flow within a Hong Kong hospital, placing specific emphasis on the critical issue of bed blockage, further exacerbated by the COVID-19 pandemic. The model's gridlock decomposition unearths the nuanced impact of bed blockage on distinct hospital units, addressing the imperative requirement for quantifying in-patient bed blockage within healthcare systems during a pandemic.

The new coronavirus SARS-CoV-2 is the cause of the COVID-19 pandemic, which has created an incomparable global health problem. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. The review begins by elucidating the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Employing homology modeling, a tertiary structure model of PLpro is constructed, laying the groundwork for subsequent investigations. To expedite the search for potential therapeutic candidates, the study harnesses computational methodologies. Molecular docking techniques are employed to explore binding sites for antiviral drugs within the catalytic region of PLpro. This computational approach not only aids in drug development but also provides crucial preliminary data before experimental research commences. The stability of drug-PLpro complexes is assessed through comprehensive all-atom molecular dynamics (MD) simulations, affording dynamic insights into drug-PLpro interactions. By evaluating binding energy estimates from MD simulations, stable drug-PLpro complexes with potential antiviral properties are identified. However, it is emphasized that experimental validation is imperative to confirm these computational findings, necessitating in vitro and in vivo tests to assess safety and efficacy. This pivotal stage bridges the computational realm with real-world clinical applications. The review emphasizes the imperative need for enhancements in the existing PLpro-targeting drugs currently on the market. Their actions are insufficient for clinical use and necessitate thorough characterization and improvement. The Supervised Molecular Dynamics (SuMD) simulation technique reveals critical information about drug unbinding pathways, shedding light on opportunities for refinement. In addition to optimizing existing drugs, the investigation of sub-structurally similar molecules emerges as a promising avenue for drug development. In conclusion, the review underscores the pivotal role of targeting SARS-CoV-2 PLpro in the ongoing battle against COVID-19. By integrating molecular dynamics simulations, structural modeling, and computational insights, a robust foundation is established for identifying promising antiviral drug candidates. The continual need for improvement in existing drugs and the exploration of novel compounds remain paramount in the global effort to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, illustrating the interdisciplinary synergy crucial to this endeavor.

Home confinement during the COVID-19 pandemic has been accompanied by dramatic changes in household food dynamics that can significantly influence health. This systematic literature review presents parental perspectives of the impact of COVID-19 lockdown on food preparation and meal routines, as well as other food-related behaviors, capturing both favorable and unfavorable changes in the family food environment (FFE). Themes and trends are identified and associations with other lifestyle factors are assessed. In overall, families enjoyed more time together around food, including planning meals, cooking, and eating together. Eating more diverse foods and balanced meals was combined with overeating and increased snacking, as parents became more permissive towards food; however, food insecurity increased among families with the lowest income. Adoption of meal planning skills and online shopping behavior emerged alongside behaviors aimed at self-sufficiency, such as bulk purchasing and stockpiling. These results are an important first step in recognizing how this pandemic may be affecting the FFE, including low-income families. Future obesity prevention and treatment initiatives, but also ongoing efforts to address food management, parental feeding practices, and food insecurity, can account for these changes moving forward.

Identifying anti-spike antibodies that exhibit strong neutralizing activity against current dominant circulating variants and antibodies that are escaped by these variants have important implications in the development of therapeutic and diagnostic solutions as well as in improving understanding of the humoral response to SARS-CoV-2 infection. We characterized seven anti-RBD monoclonal antibodies for their binding activity, pairing capability and neutralization activity to SARS-CoV-2 and three variant RBDs (UK, SA and BR P.1) via lateral flow immunoassays. The results allowed us to group these antibodies into three distinct epitope bins. Our studies showed that two antibodies had broadly potent neutralizing activity against SARS-CoV-2 and these variant RBDs and that one antibody did not neutralize the SA and BR P.1 RBDs. The antibody escaped by the SA and BR P.1 RBDs retained binding activity to SA and BR P.1 RBDs but was unable to induce neutralization. Further, we demonstrated that the lateral flow immunoassay can be a rapid and effective tool for antibody characterization, including epitope classification and antibody neutralization kinetics. From these studies, the potential contributions of the mutations (N501Y, E484K and K417N/T) contained in these variants’ RBDs on antibody pairing capability, neutralization activity and therapeutic antibody targeting strategy are discussed.

RLF-100 (Aviptadil), a synthetic form of Vasoactive Intestinal Peptide (VIP) is shown to block replication of the SARS-CoV-2 virus and has been granted Fast Track Designation by the US FDA for the treatment of Critical COVID-19 with Respiratory Failure. We describe the clinical course of the first patient treated with this investigational medication in an open label manner -- a 54 year old patient suffering antibody-mediated rejection of his double lung transplant who contracted COVID-19 with respiratory failure refractory to all currently available therapies. He received three infusions of RLF-100 under an FDA-approved emergency use IND. Within 24 hours of the third infusion, substantial improvement in oxygen saturation and radiographic improvement in characteristic COVID-19 pneumonitis was noted. He was discharged from intensive care at that point and scheduled for discharge to home at 1 week on room air. Despite an intervening hospitalization for trauma, he remains alive and free of respiratory failure at 28 days post treatment.

The urgency to develop vaccines against Covid-19 is putting pressure on the long and expensive development timelines which are normally required for development of lifesaving vaccines. There is a unique opportunity to take advantage of new technologies, smart and flexible design of clinical trials, and evolving regulatory science to speed up vaccine development against Covid-19 and transform vaccine development altogether.

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2/2019-nCoV) infection is an emerging pandemic. The virus binds to angiotensin converting enzyme 2 (ACE2) and TMPRSS2 which are abundantly expressed on various human cells including lung epithelial cells and intestinal cells and the virus can infect these cells. Currently no specific treatments or vaccines are available for this disease. A per oral live attenuated vaccine can be beneficial in SARS-Cov-2 infection because the attenuated virus initially infects the gut, stimulates the mucosa associated immune system sparing the respiratory system during the initial immune response. The live virus can also spread in the community boosting herd immunity.

Increased platelet activity is a risk factor of thrombotic events in cardiovascular patients. We studied the relationship between platelet function, platelet size and content of reticulated platelets (RP) in patients with coronary heart disease (CHD, n = 55) and acute coronary syndrome (ACS, n = 95) receiving acetylsalicylic acid + clopidogrel or ticagrelor respectively. Control group consisted of patients with risk factors for CHD, but no CHD/ACS and free of antiplatelet drugs (n = 66). Platelet function was evaluated by exposure of activated glycoprotein (GP) IIb-IIIa and P-selectin. In the control group, platelets were activated by TRAP (Thrombin Receptor Activating Peptide) 10 µM, ADP 20, 5, 2.5 µM and in CHD/ACS groups, by TRAP 10 µM, ADP 20, 5 µM (+/- epinephrine 20 µM). Platelet size was assessed by mean volume, % large forms and forward scattering. RP were stained by thiazole orange. In the control group activated GP IIb-IIIa and P-selectin correlated with platelet size and RP content after platelet activation by all agonists. Despite the decrease of platelet activity by antiplatelet drugs, most correlations (primarily for activated GP IIb-IIIa) were preserved in CHD/ACS patients. In conclusion, increased platelet size and RP content are associated with increased platelet activity and reduced efficacy of antiplatelet therapy.

To improve the understanding of soil–pile interaction of laterally loaded piles, the quasi-static test of pile group foundation in silty clay with 5 foundation piles arranged in cross shape is carried out. The direct measurement-based p–y curves at different depths showed nonlinear behavior, in which the initial stiffness and ultimate soil reaction increased as the depth increased. The loading displacement amplitude corresponding to the failure of each foundation pile in the high axial compression reinforced concrete pile group foundation is given as follows: the front-end nappe foundation pile (#3 pile) is 6mm, the middle pile is 16mm, the front-end nappe foundation pile is 20mm, and the loading displacement amplitude of side pile is 24mm. In silty clay, due to the existence of pile group effect, the edge effect has little effect on the horizontal foundation bed coefficient of foundation pile in pile group, while the influence of masking effect on the horizontal foundation bed coefficient of each foundation pile in pile group is not related to the position of pile, but only to the existence of masking effect, and the influence of different columns of masking effect on the horizontal foundation bed coefficient is the same.

Post severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, Covid-19) sequalae’s, immune and RNA based treatments are associated with the development of micro-stones and chronic kidney disease (CKD). In addition, circulating cytokines cocktail and viral envelope spike protein (SP) instigates CKD. During epigenetic regulation, Covid-19 methyltransferase (MT) methylates the DNA/RNA/Proteins/Histones and generates homocysteine (Hcy). Although cysteine promotes the growth and aggregation of calcium oxalate crystals in normal undiluted human urine. However, during elevated levels of Hcy (i.e., hyperhomocysteinemia, HHcy) due in part to the impaired transsulfuration (i.e., mitochondrial sulfur metabolism) pathways, homocysteine is the only sulfur-denoting non-protein amino acid may promote crystals. HHcy is associated with severity of Covid-19 infection and pneumonia post Covid-19. It is unclear however whether the HHcy facilitates homocysteine crystals. Although an E. coli strain degrades tricarboxylic acid (TCA, citric acid), and disrupts mitochondrial TCA cycle, to dicarboxylic acid (DCA, oxalic acid), DCA also promotes calcium oxalate crystals and may contributes to kidney stones, it is unclear whether gut-dysbiosis by Covid-19 infection contributes to kidney stones. There is robust succinylation of enzymes in TCA cycle which causes dysfunctional mitochondrial bioenergetics during Covid-19 infection. In this regards interaction between SIRT5 and mitochondrial transsulfuration during Covid-19 infection attenuates TCA cycle. Interestingly, the mitochondrial bioenergetics though sulfur metabolism participate in TCA cycle and epigenetic acetylation/succinylation, therefore, Covid-19 infection transition acute kidney injury (AKI) to CKD by defective mitochondria sulfur metabolism (transsulfuration) pathways, forming uricemia micro stones.

Understanding the motivations and decisions behind COVID-19 vaccine acceptance is crucial for designing targeted public health interventions to address vaccine hesitancy. We conducted a qualitative analysis to explore COVID-19 vaccine acceptance among diverse ethnic subgroups of Black Americans in the United States. This study investigates the responses of 79 African American, Afro-Caribbean, and African respondents over the age of 18 in Washington State and Texas between 2021-2022. Qualitative responses were analyzed by content category and ethnic subgroup. Of the 79 responses, 60 expressed favorable perceptions, 16 unfavorable, and 3 neutral. Dominant categories among participants in favor of the vaccine included personal health (26), concern for health of family/or community members (13), and desire to protect others (11). Among the 42 vaccinated African American respondents, the primary motivation was personal health (20). The 12 unvaccinated African American respondents cited fear of side-effects as the dominate motivation. Caribbean respondents cited family or elders as motivation for their decision. African respondents were nearly unanimous in taking the vaccine (13/16), citing trust in healthcare, protecting friends and family, and personal health as reasons. Community and personal relationships were critical decision-making factors in accepting the COVID-19 vaccine with African Americans having the strongest hesitancy.

Objective: To summarize the prevalence of PASC/Long COVID symptoms among the general population reported in published articles. This narrative review examined 21 PASC symptoms. Methods: A PubMed/manual search returned 114 articles on general PASC/Long COVID symptoms. Manuscripts were excluded if they were not research studies, didn’t report symptom prevalence, or used a pediatric population. Ninety-eight studies were selected for review and 59 met criteria for inclusion. Risk of bias was assessed with the Hoy critical appraisal tool. Results: After excluding studies with high risk of bias, meta-analysis of prevalence for 21 symptom categories ranged from 2.6-28.7% in studies based on surveys to 0.3%-7.1% in studies based on EHR data. Conclusions: PASC symptom studies are limited by variability in study design and representation of the general population. Further research is needed to effectively cluster symptoms in meaningful ways that enable focused treatment.

The main point in the present article was the comparison of the Technical Efficiency (TE) in four years for milk production in Ecuador by the period 2018 – 2021, before and after the pandemic, and the determination of the factors related to the TE for the last year. The information from the official public database in the country were analyzed by the nonparametric technique called DEA including a bootstrap simulation. Once different variables were selected including aspects as livestock and labor, the TE with Variable Returns to Scale (VRS) with “output” orientation was calculated by each year and province. Among the provinces, statistically significant differences were found (P<0.1) for the TE means, and most of the efficient units were found throughout the Andean zone, in each year. Between the most important findings, it was important that the TE average after the beginning of the pandemic was statistically lower than the last 3 consecutive years under study (P<0.1) with 3% approximately of decrease, and the main factors related to this were multiple including labor characteristics, the field composition, and the supplies access during the pandemic. Finally, some implications for public policy were found around the gender in agriculture activities, the social security, and the difficulties in supplies access.

There is mounting evidence that patients with severe COVID-19 disease may have symptoms that continue beyond the acute phase, extending into the early chronic phase. Often referred to as 'Long COVID'. Simultaneously, case investigations have shown that COVID-19 individuals might have a variety of neurological problems. The accurate and accessible assessment of cognitive function in patients post COVID-19 infection is thus of increasingly high importance for both public and individual health. Little is known about the influence of COVID-19 on the general cognitive levels but more importantly, at sub functions level. Therefore, we first aim to summarize current level of evidence supporting a negative impact of COVID-19 infection on cognitive functions. 27 studies have been included in the systematic review representing a total of 94,103 participants (90,317 COVID-19 patients and 3,786 healthy controls). We then performed a meta-analysis summarizing the results of 5 studies (959 participants, 513 patients) to quantify the impact of COVID-19 on cognitive functions. The overall effect, expressed in Standardized Mean Differences, is -0.56 [95%CI -0.79 ; -0.34]. To prevent disability, we finally discuss the different approaches available in rehabilitation to help these patients and to avoid long-term complication.

COVID-19 (SARS-Cov-2) is spreading around the globe in a highly contagious manner. China has shown the way to halt the progression of the disease by totally sealing Wuhan from rest of china but they could not prevent community spread resulting in more than 4000 deaths in a short period of time. India, following example of china, ordered national Lockdown early on 23 March, 2020. But it is difficult to determine the transition Here we have changed the way we look at available data to detect an early onset of the effect of Lockdown. Here a simple method is described for the first time to determine at the earliest when a change is beginning to take effect after Lockdown on the progression/regression of the spread of novel COVID-19 virus which could help to frame strategy for intervention to prevent community spread and save lives.

To mitigate the COVID-19 infection, many world governments endorsed the cessation of non-essential activities, such as the school attendance. Thereby, forcing the evolution of the teaching model to the virtual classroom. In the present work we show the application of a modified version of the adapted COVID-19 stress scales (ACSS) which also included teaching anxiety and preparedness, and resilience for academic professionals in Mexico, during the unprecedented transformation of the education system undergone in the COVID-19 quarantine. Most of the studied variables: gender, age, academic degree, household occupants, having a disease, teaching level, teaching mode, work hours, resilience, teaching anxiety and preparedness, and fear of being an asymptomatic patient (FOBAP), showed significant statistical correlation between each other (p<0.050) and to the 6 areas of the ACSS (danger, contamination, social economical, xenophobia, traumatic stress and compulsive checking). Our results further showed that the perceived stress and anxiety, fell into the category of absent to mild with only the danger section of the ACSS falling into the moderate category. Finally, resilience generated throughout the quarantine, seems to be a predictor of the adaptation the academic professional has undergone to cope with stress.

While the history of Lough Derg is extremely well-documented, there have been com-paratively fewer ethnographic reports. Given the highly elaborate Lough Derg websites and multiple postings by Lough Derg pilgrims, this researcher anticipated that Lough Derg – like many other Irish pilgrimages - would attract mostly recreational tourists. It does not. Pilgrims to Lough Derg do not see the site as primarily a tourist destination. Instead, they see Lough Derg primarily as a locus of intense religious experience. Lough Derg 3-day pilgrimages are rigorous and entail considerable self-sacrifice: fasting, sleep deprivation, cold, bare feet, prayer, no cell phones, and exposure to jagged rocks. Lough Derg’s 3-day pilgrimages closely follow patterns established centuries ago. Lough Derg is both "modern" and "timeless." It selectively incorporates ancient ritual and 21st century technology. This paper looks at the impact of the covid19 epidemic on Lough Derg pilgrimages. The site was closed to pilgrims during the 2020-2021 season and an on-line virtual pilgrimage was offered as a substitute. One unintended consequence of this virtual pilgrimage is that many pilgrims to Lough Derg now give greater prominence to what Corin Braga has categorized as fisi (ecstatic revelations) than to the physical journey itself (i e. somanodias). Post-covid pilgrims highlight the Internet: production of virtual texts and Internet vlogs. As in most pilgrimages worldwide, contemporary pilgrims to Lough Derg arrive with varied expec-tations and myriad motives. This ethnographic report examines these motives and offers a critique of James L. Smith (2016), who, like Edith and Victor Turner (1978) before him – saw Lough Derg as a symbol of Irish nationalism. Smith highlighted Lough Derg’s “moral geography” which, he argued, stems from its long history of isolation. But Post- covid Lough Derg is no longer isolated. The site has become more accessible through organized bus tours, improved public transportation, and development of a commercial tourist infrastructure.

The ongoing SARS-CoV-2 pandemic has raised concerns surrounding immunological protection against the virus, particularly for people with inborn errors of immunity (IEI). While COVID-19 vaccination induces robust antibody, memory B-cell, and T-cell responses in healthy individuals, how well vaccination protects people with IEI against infection and severe disease remains unclear – especially in the context of new viral variants and vaccine formulations – leading to anxiety, ongoing self-isolation, and repeated vaccination with limited evidence of increased efficacy. Whilst most people with IEI generate some level of cellular and/or humoral immunity to COVID-19 vaccination, the level of protection and durability of the response are unclear. Alongside vaccination, antibody-based therapeutics are aimed at limiting infection and severe disease in this cohort. Immunoglobulin replacement therapy (IgRT) provides passive immunity in antibody-deficient individuals. However, to successfully prevent SARS-CoV-2 infection, a sufficient number of neutralizing antibodies must be present in product. While antibodies against circulating variants are eventually present in IgRT products (both from natural infection and vaccination of the donors), evidence of their capacity to recognize new variants is limited. Furthermore, while antibody-based pre- and post-exposure prophylaxis can be effective, they are susceptible to decreased efficacy in the context of variant evolution. This review provides an in-depth overview of current knowledge about COVID-19 vaccine efficacy in IEIs, the efficacy of SARS-CoV-2-specific antibody products, and knowledge and technological advances required for continued protection of people with IEI.

Neutrophils are the principal trouper of innate immune system. Activated neutrophils undergo a noble cell death termed NETosis and release a mesh-like structure called neutrophil extracellular traps (NETs) as a part of their defensive strategy against microbial pathogen attack. This web-like architecture includes a DNA backbone embedded with antimicrobial proteins like myeloperoxidase (MPO), neutrophil elastase (NE), histones etc. and deploys in the entrapment and clearance of encountered pathogens. Thus NETs play an inevitable beneficial role in the host's protection. However, recent accumulated evidence shows that dysregulated and enhanced NET formation has various pathological aspects including promotion of sepsis, pulmonary, cardiovascular, hepatic, nephrological, thrombotic, autoimmune, pregnancy, cancer diseases etc. and the list is increasing gradually. In this review, we summarize NETs mediated pathophysiology of different diseases, focus on some updated potential therapeutic approaches against NETs and share our future perspectives.

(1) Background: The COVID-19 pandemic had a devastating impact on the world, causing widespread illness and death. It is essential to focus on prevention strategies to limit the spread of the disease. Despite the advent of vaccines, maintaining a vigilant approach to prevention remains paramount. While vaccines are essential, they do not guarantee absolute immunity, and their protective effect may diminish over time; (2) Methods: We reviewed effective strategies to prevent COVID-19 transmission. We focused on me-ta-analyses (MA), literature reviews (LR) and the health care context. Various prevention measures and interventions were reviewed. Both es-tablished practices and unresolved issues were considered; (3) Results: Standard precautions (SP) as the cornerstone of infection control, with hand hygiene and mask use as key components. Debate about the relative importance of droplet versus aerosol transmission led to differences in recommendations between agencies at the onset of the pandemic. We have clarified the role of personal protective equipment (PPE), including eye protection. The effectiveness of masks in pre-venting transmission is reviewed. The use of surgical masks is recommended to prevent droplet transmission, while eye protection is recommended in combination with masks. Although data show some risk reduction, the clear superiority of N95/FFP2 over surgical masks remains unproven. In terms of room occupancy, ventilation is critical in reducing the risk of transmission in poorly ventilated environments. The use of negative pressure isolation rooms (NPIRs) is being investigated. The presence of viral RNA on surfaces does not necessarily indicate infectivity, and the risk of transmission by surface contact is low if surfaces are properly maintained and hand hygiene is practised regularly. Testing for SARS-CoV-2 in asymptomatic persons in healthcare settings may help prevent transmission; (4) Conclusions: Prevention of SARS-CoV-2 transmission requires a multifaceted approach, including reducing particle emissions from infected persons by wearing masks, eliminating aerosols by ventilation, ensuring physical separation, and protecting exposed persons with masks and eye protection.

The SARS-CoV-2 virus that causes the COVID-19 disease has wreaked havoc on the world community in terms of every imaginable parameter. The research output on COVID-19 has been nothing short of phenomenal, especially in the medical and biomedical sciences, where the search for a potential vaccine is being conducted in earnest. Much of the advanced research has been distributed in the leading medical journals, including the Journal of the American Medical Association (JAMA), where the latest research is distributed on a daily basis. The purpose of this paper is to provide some perspectives on 44 interesting and highly topical research papers that have been published in JAMA, at the time of writing, within the past two weeks. The diverse topics include public health, general medicine, internal medicine, oncology, paediatrics, geriatrics, and biostatistics.

In this work, we studied light-output properties, efficiency function as well as PSD capability of p-Terphenyl scintillator. The selected solid cylindrical scintillation detector has a size of (45 x 45) mm with PSD properties. Recently presented studies of light-output functions have been meas-ured only for low neutron energies. Our motivation has been to determine more accurate the light output function for p-Terphenyl scintillator over a wider neutron energy range. The measurements have been carried out with mono-energetic neutron beams in the wide energy range from 2.5 to 19 MeV. The neutron-gamma spectrometric system, which we developed has been used for the measurement. The input analogue signal from the detector is digitized with fast 12-bits analogue to digital converter with sampling frequency of 1 GHz. Measured data from the detector are processed into gamma and neutron spectra. The light output function for protons has been determined by finding the position of the protons for given neutron energies. The more accurate light output function for p-Therphenyl scintillator has been calculated. The pulse-shape discrimination capability as well as efficiency of p-Terphenyl scintillator in comparison with NE-213 equivalent detector is lower.

Silica aerogels and their derivatives have outstanding thermal properties with exceptional values in the thermal insulation industry. However, the brittle nature restricts its large-scale commercialization. Thus, enhancing their mechanical strength without affecting their thermal insulating properties is essential. Therefore, for the first time, highly thermally stable Poly(acrylamide-Co-acrylic acid) partial sodium salt is used as a reinforcing polymer to synthesize hybrid P(AAm-CO-AAc)-silica aerogels via epoxy ring-opening polymerization in the present study. Functional groups in P(AAm-CO-AAc) partial sodium salts, such as CONH2 and COOH, acted as nucleophiles for the epoxy ring-opening reaction with (3-glycidyloxypropyl)trimethoxysilane, which resulted in a seven-fold enhancement in mechanical strength compared to that of a pristine silica aerogel while maintaining the thermal conductivity at less than 30.6 mW/mK and porosity of more than 93.68%. Moreover, the hybrid P(AAm-CO-AAc)-silica aerogel demonstrated improved thermal stability up to 343 ⁰C owing to the synergetic effect between P(AAm-CO-AAc) and the silica aerogel, corresponding to thermal stability and strong covalent bonding among them. These excellent results illustrate that this new synthetic approach for producing hybrid P(AAm-CO-AAc)-silica aerogels is useful for enhancing the mechanical strength of a pristine silica aerogel without impairing its thermal insulating property and shows potential as an industrial heat insulation material.

In this paper, a study of modeling PV cell (solar cell), PV module (solar modules) and PV array solar array) using Matlab/Simulink software is presented. This study is focused on the study to design photovoltaic cell, photovoltaic modules, photovoltaic panels and PV array (solar array) and to analyze the change in PV performance according to changes in different parameters such temperature, solar irradiation, reverse saturation current, series resistance and shunt resistance. This study shows the PV and IV characteristics curve for each model from which MPP (maximum power point) is determined. In this study, different PV and IV characteristic curves are gained for varying temperatures with specified solar irradiation conditions,s and then the MPP is tracked. The highest power output is also compared between the designed PV module and the selected PV module (MX Solar USA MX60-245)

The main goal of the present paper is to construct some families of the Carlitz’s q-Bernoulli polynomials and numbers. We firstly introduce the modified Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and investigate their some explicit properties and identities arising from the bosonic q-Volkenborn integral on ℤ_p. We then define the modified degenerate Carlitz’s q-Bernoulli polynomials and numbers with weight (α, β) and obtain some recurrence relations and other identities. Moreover, we derive some correlations with the modified Carlitz’s q-Bernoulli polynomials with weight (α, β), the modified degenerate Carlitz’s q-Bernoulli polynomials with weight (α, β), the Stirling numbers of the first kind and second kind.

This paper explores the pivotal role of personalized product recommendations in enhancing the e-commerce experience. As online shopping becomes increasingly prevalent, the demand for tailored user experiences has surged, prompting the development of sophisticated recommendation systems. This study presents a comprehensive analysis of various methodologies employed to deliver personalized suggestions, including collaborative filtering, content-based filtering, and hybrid approaches. The implementation of a user-centric recommendation engine demonstrates significant improvements in user engagement, satisfaction, and conversion rates. Furthermore, the paper discusses the importance of real-time adaptation mechanisms and user feedback loops in optimizing recommendations. By providing insights into the challenges and solutions associated with recommendation systems, this research aims to equip e-commerce businesses with the tools necessary to leverage personalization effectively, ultimately leading to enhanced customer experiences and increased sales.

Background: The Covid-19 pandemic was in reality a syndemic there the balance between a multitude of biological (Nature-made) and socio-political (men-made) factors determined individually the outcome of every single infection, on a scale of nothing-to-fatal. Blaming the virus for everything bad that happened to us after January 2020 is incorrect. Now, in ~ 2 years distance from the syndemic, it may be timely and possible to uncover the human contribution to this historical event and learn of it. Objective: To identify and use some qualitative approach to estimate the objective, statistical / epidemiological ‘value’ of the virus-selected individuals (in age-normalized groups) for the rest of the society. This non-political, non-religious approach may be the only way to understand the benefit / cost ratio of actions and emergency orders we had to survive in addition to the virus itself. Methods: Statistical data were obtained from publicly available official databases, including the relevant actuarial tables and evaluated by widely used statistical methods. The estimation of statistical/epidemiological ‘value of life’ was based, strictly and exclusively, on the real age and the statistically calculated Residual Life Expectancy (RLE, i.e. remaining years alive at a given age). The American healthcare expenses were compared to the corresponding healthcare costs/capita in other similarly well-developed west-European countries. This was the only available method to get some ideas about the magnitude of the well-established (rational) healthcare spending and compare it to the American standards. Results 1) Life expectancy uninterruptedly increased in USA since 1933, due to continuous reduction of Mortality Rate of the youngest and oldest citizens. COVID didn’t stop the population growth (+8.2 M /2020-2023). 2) The total count of Excess COVID associated Deaths (XCD) is ~ 2-times as much as the official statistic was able to explain by virus infection. It is speculated that these Complementary Covid Deaths (CCD) are probably the unexpected side-effects of the pandemic related emergency orders. 3) The worldwide ‘longevity’ trend exponentially increased the healthcare expenses, especially the care of elderly. However the USA is unique in this aspect and the healthcare costs are irrationally much higher than in any other country. 4) We can see a large economic incentive in the development of excesses under COVID syndemic. Conclusions The harm of the COVID virus - as well as the benefits of the mandatory, emergency actions during the pandemic - were grossly over-estimated. Professional, unbiased (non-religious, non-political) and independent reviews are strongly recommended.

The innate and adaptive immune systems collaborate to detect SARS-CoV-2 infection, minimize the viral spread, and kill infected cells, ultimately leading to the resolution of the infection. The adaptive immune system develops a memory of previous encounters with the virus, providing enhanced responses when rechallenged by the same pathogen. Such immunological memory is the basis of vaccine function. Here, we review the current knowledge on the immune response to SARS-CoV-2 infection and vaccination, focusing on the pivotal role of T cells in establishing protective immunity against the virus. After providing an overview of the immune response to SARS-CoV-2 infection, we describe the main features of SARS-CoV-2-specific CD4+ and CD8+ T cells, including cross-reactive T cells, generated in patients with different degrees of COVID-19 severity, and of Spike-specific CD4+ and CD8+ T cells induced by vaccines. Finally, we discuss T cell responses to SARS-CoV-2 variants and hybrid immunity and conclude by highlighting possible strategies to improve the efficacy of COVID-19 vaccination.

The current SARS-CoV-2 pandemic is still threatening humankind. Despite first successes in vaccine development and approval, no antiviral treatment is available for COVID-19 patients. The success is further tarnished by the emergence and spreading of mutation variants of SARS-CoV-2, for which some vaccines are not effective anymore. This highlights the urgent need for antiviral therapies even more. This article describes how the Genome-Scale Metabolic Model (GEM) of the host-virus interaction of human alveolar macrophages and SARS-CoV-2 was refined by incorporating the latest information about the virus’s structural proteins and the mutant variants B.1.1.7 and B.1.351. We confirmed the initially identified guanylate kinase as a potential antiviral target with this refined model and identified further potential targets from the purine and pyrimidine metabolism. The model was further extended by incorporating the virus’ lipid requirements. This opened new perspectives for potential antiviral targets in the altered lipid metabolism. Especially the phosphatidylcholine biosynthesis seems to play a pivotal role in viral replication. The guanylate kinase is even a robust target in all investigated mutation variants currently spreading worldwide. These new insights can guide laboratory experiments for the validation of identified potential antiviral targets. Only the combination of vaccines and antiviral therapies will effectively defeat this ongoing pandemic.