Human respiratory beta coronavirus are emerging causes for Public Health Emergencies of International Concern (PHEIC). SARS-CoV2 is circulating worldwide since November 2019. We review here the cardiovascular morbidity and mortality in COVID-19, and data supporting the role for dysregulation of the RAS counterregulatory axis due to binding of SARS-CoV2 S protein to ACE2 receptor. Since this counterregulatory axis provides benefits not only on the cardiovascular front but also in acute lung injury, we speculate on potential use of ACE inhibitors and AT₁R blockers in critically ill COVID-19 patients, and report current evidences.

Covid-19 is often related to hyperinflammation that drives lung or multi-organ injury. The immunopathological mechanisms that cause excessive inflammation following SARS-Cov-2 infection are under investigation while different approaches to limit hyperinflammation in affected patients are being proposed. Here, a computational protein-protein interaction network approach was used on recently available data to identify possible Covid-19 inflammatory mechanisms and bioactive genes. First, network analysis of putative SARS-Cov-2 cellular receptors and their directly associated proteins, led to the mining of a robust neutrophil response signature and multiple relevant inflammatory genes. Second, analysis of RNA-seq datasets of lung epithelial cells infected with SARS-Cov-2 revealed that infected cells specifically expressed neutrophil-attracting chemokines, further supporting the likely role of neutrophils in Covid-19 inflammation. Third, analysis of RNA-seq datasets of bronchoalveolar lavage fluid from Covid-19 patients, identified neutrophil-specific genes and chemokines. Different immunoregulatory and neutrophil-relevant molecules mined here such as, TNFR, IL8, CXCR1, CXCR2, ADAM10, GPR84, MME-neprilysin, ANPEP and LAP3 are druggable and might be therapeutic targets in efforts to limit SARS-Cov-2 inflammation in severe clinical cases. The role of neutrophils in Covid-19 needs to be studied further.

Introduction: The Pandemic of COVID-19, an infectious disease caused by SARS-CoV-2 motivated the scientific community to work together in order to gather, organize, process and distribute data on the novel biomedical hazard. Here, we analyzed how the scientific community responded to this challenge by quantifying distribution and availability patterns of the academic information related to COVID-19. The aim of our study was to assess the quality of the information flow and scientific collaboration, two factors we believe to be critical for finding new solutions for the ongoing pandemic. Materials and methods: The RISmed R package, and a custom Python script were used to fetch metadata on articles indexed in PubMed and published on Rxiv preprint server. Scopus was manually searched and the metadata was exported in BibTex file. Publication rate and publication status, affiliation and author count per article, and submission-to-publication time were analysed in R. Biblioshiny application was used to create a world collaboration map. Results: Our preliminary data suggest that COVID-19 pandemic resulted in generation of a large amount of scientific data, and demonstrates potential problems regarding the information velocity, availability, and scientific collaboration in the early stages of the pandemic. More specifically, our results indicate precarious overload of the standard publication systems, significant problems with data availability and apparent deficient collaboration. Conclusion: In conclusion, we believe the scientific community could have used the data more efficiently in order to create proper foundations for finding new solutions for the COVID-19 pandemic. Moreover, we believe we can learn from this on the go and adopt open science principles and a more mindful approach to COVID-19-related data to accelerate the discovery of more efficient solutions. We take this opportunity to invite our colleagues to contribute to this global scientific collaboration by publishing their findings with maximal transparency.

The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.

COVID-19 pandemic provoked a number of restrictive measures, such as the closure or severe restriction of border transit for international trading traffic, quarantines and self-isolation. This caused a series of interrelated consequences that not only prevent or slow down the spread of disease, but also impact the medical systems’ capability to treat the patients and help their recovery. In particular, steeply growing demand for medical safety goods cannot be satisfied by regular suppliers due to the shortage of raw materials originating from other countries or remotely located national sources, under conditions of quarantined manpower. The current context inevitably brings back memories (and records!) of the situation 80 years ago, when WWII necessitated major effort directed at the rapid build-up of low cost mass production to satisfy all aspects of war-time need. In the present short report we document a successful case of fast mass-production of light transparent medical safety face shields (thousands per day) realized in Skolkovo Institute of Science and Technology (Skoltech) fabrication laboratory (FabLab). The demand for safety face shields by tens of hospitals in Moscow City and Region rapidly ramped up due to the need to protect medical staff during patient collection and transportation to hospitals, and within both the infected (“red”) and uninfected (“green”) zones. Materials selection for sterilizable transparent materials was conducted based on the analysis of merit indices, namely, minimal weight at given stiffness and minimal cost at given stiffness. Due to the need for permanent wear, design was motivated by low weight and comfortable head fixation, along with high production efficiency. The selection of minimal tooling in University fabrication workshops and the use of distributed volunteer labor are discussed.

This note applies the Logistic model approximation to determine the suitable start and end dates for the observed epidemic curves in the total number of cases for different countries. The Logistic model is presented and explicit relations for the beginning and end dates are obtained together with the total epidemic duration. Using data from Brazil, Germany, Italy, and South Korea, the extreme dates are calculated. Since the epidemic onset time is found, a fair comparison of the epidemic curve for these countries is obtained. The result does not depend on the poor statistics available in the early phase of the epidemic when the initial number of infectives is unknown. In fact, the total duration depends only on the characteristic time parameter of the LM model.

Covid-19 has given a halt to all the activities in the world. Europe was most affected, followed by the United States of America. It has taken more than 350000 lives until now. In this study, we have assessed the severity of Covid-19 by analyzing the mortality rate of Covid-19 and other chronic diseases. The Covid-19 data and “death rate” data caused by other diseases were downloaded from the world health organization (WHO) website. A normalized method was used to see the mortality rate of Covid-19 in comparison to other diseases. The deaths caused by Covid-19 in April 2020 have overtaken the average number of deaths caused by Cancer, Cardiovascular diseases, and other diseases in Belgium, the United Kingdom (UK), Spain, France, and Ireland. Covid-19 was found to be strongly correlated with non-communicable respiratory diseases and Cancer with correlation coefficients 0.73 and 0.67 respectively. The severity of Covid-19 in the United States of America (USA) was moderate. The severity of Covid-19 in Asian countries was found to be low. Europe showed the highest diversity in the mortality rate of Covid-19. On average, except for a few European countries, Cardiovascular diseases, cancer, and non-communicable respiratory diseases were still more lethal and caused more deaths than Covid-19.

The recently emerged coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS- CoV-2) is the newest threat to human health. It has already infected more than half a million people worldwide, leading to a lot of deaths. Although it causes mild flu-like disease in most patients, lethality may increase to more than 20% in elderly subjects, especially those with comorbidities, like hypertension, diabetes or lung and cardiac disease, and the mechanisms are still elusive. Common symptoms at the onset of illness are fever, cough, myalgia or fatigue, headache, and diarrhea or constipation. Interestingly, respiratory viruses have also placed themselves as relevant agents for CNS pathologies. Here we discuss several CNS related features, referred by several patients, especially at the beginning of the disease. Thus, we also discuss the possibility by which SARS-CoV-2 may affect the olfactive system of patients, either directly or indirectly.

The global pandemic of SARS-CoV-2, the causative viral pathogen of COVID-19, has driven the biomedical community to action – to uncover and develop anti-viral interventions. One potential therapeutic approach currently being evaluated in numerous clinical trials is the agent remdesivir, which has endured a long and winding developmental path. Remdesivir is a nucleotide analog prodrug that perturbs viral replication, originally evaluated in clinical trials to thwart the Ebola outbreak in 2014. Subsequent evaluation by numerous virology laboratories demonstrated the ability of remdesivir to inhibit coronavirus replication, including SARS-CoV-2. Here, we provide an overview of its mechanism of action, discovery, and the current studies exploring its clinical effectiveness.

The rapid spread of the coronavirus disease 2019 (COVID-19) is a serious threat to public health systems globally and is subsequently, a cause of anxiety and panic within human society. Understanding the mechanisms and reducing the chances of having severe symptoms from COVID-19 will play an essential role in treating the disease, and become an urgent task to calm the panic. However, the COVID-19 test developed to identify virus carriers is unable to predict symptom development in individuals upon infection. Experiences from other plagues in human history and COVID-19 statistics suggest that genetic factors may determine the compliance with the virus, i.e., severe, mild, and asymptomatic. Here, a hypothesis is put forward based on the epidemiological characteristics and traits of COVID-19, and our gene expression analysis. It proposes that COVID-19 inactivation in the blood by blocking virus entry into other internal organs for reproduction through the blood circulation after lung cell invasion prevents severe symptoms. Additionally, we investigated a genetic connection between candidate genes and severe COVID-19 symptoms through the utilization of strategies combining hypothesis and data-driven approaches. A list of genes and important SNPs that require further investigation to aid the screening of individuals who may suffer severe illness if exposed to the virus is present. Those individuals should be intensively safeguarded and prioritised for treatment. Concurrently to further research on the COVID-19 pathogenesis, our results also offer a new research strategy for pandemic prevention and health maintenance.

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a small fraction of unreported SARS-CoV-2 cases (19.5%; 95%CI=0%-34.7%) before 10 March lockdown. Interestingly, we estimated that the first set of restrictions reduced transmission rate in the community by 42% (95%CI=38%-46%), and that more stringent measures adopted on 23 March succeeded to drastically curb the transmission rate by 84% (95%CI=80%-88%). Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Further modeling after the adoption of control measures, moreover, indicated that restrictions reduced SARS-CoV2 transmission considerably.

Critically ill patients with COVID-19 may develop serious respiratory difficulties, causing a significant reduction in blood oxygen saturation pressure. Physical Ventilation of the lungs is one of the main methods to help critically ill patients through the acute phase of infection. During extreme situations when dysfunctional lungs are filled with sticky sputum in the alveolus or when there are simply not enough ventilators to match the need, the mortality rate can be dramatically increased. Here, we propose an intravenous injection method that may increase and maintain the blood oxygen pressure at normal levels. The intravenous (IV) infusion contains oxygen nanobubbles in physiological saline solution (ONPS), in which the dissolved oxygen content can be 2-6 times higher than the normal oxygen solubility in pure water. This makes it possible to oxygenate blood with a small limited volume of IV fluid without the risk of gaseous bubble formation in blood vessels.

The current Coronavirus Disease 19 (COVID-19) pandemic, caused by the SARS-CoV-2 virus, is unprecedented in recent history and threatens the lives and livelihoods of billions worldwide. The rapid spread and lack of modern parallels have left governments, health agencies, and the public racing to understand how to best mitigate and ultimately suppress the pandemic, but we are still working to understand the strengths and weaknesses of various interventions at our disposal. Few issues have been as contentious as the public use of face masks to control the pandemic’s spread. There is ongoing debate about their effectiveness, but an increasing body of evidence suggests that masks could be a useful in preventing the spread of coronavirus, leading several governments and health agencies to review and revise their policies. Here, we review the theory and evidence behind use of masks. The theory behind masks is that they prevent the spread of viral particles by infected persons, and inhalation of viral particles by uninfected persons. Even assuming masks are not 100% effective in preventing infection, they may reduce severity of infection by reducing viral dosing. Laboratory studies suggest masks may be effective in stopping both exhalation and inhalation of viral particles. However, real-world studies provided limited evidence for the use of masks in controlling influenza transmission and highlight potential problems associated with their misuse, such as poor compliance or improper use. Evidence for efficacy of face masks against the first SARS virus, SARS-CoV-1, implies that they may be effective against the current outbreak of SARS-Cov-2 virus. This is important as mathematical modeling suggests that even small reductions of in transmission rates can make a large difference over time, potentially slowing the pace of viral pandemics and limiting their spread. Perhaps the strongest argument for the use of masks is that countries with early adoption of masks have tended to see flatter pandemic curves, even without strict nationwide lockdowns. There is little evidence that respirators are more effective than surgical masks, but this may be due to misuse or poor compliance. Studies suggest some non-medical masks perform on par with medical masks. Improvised masks are less effective than medical masks, but may provide better protection than nothing at all. While many governments now encourage the use of improvised face coverings, more will need to be known about material, design, and who needs to wear masks, and when, to ensure effectiveness. Proper use of masks will also be important; if masks are used improperly or infrequently they may provide limited protection. It is important that public health policy makers consider the debate and the potential of masks as part of multi-faceted coronavirus control strategies.

Combating viral disease outbreaks has doubtlessly been one of the major public health challenges for the 21^st century. Here, the host entry machinery required for COVID-19 (SARS-CoV-2) infection was examined for the gene expression profiles and polymorphism. The four human population groups of Europeans, Africans, Asians, and Americans had specific and also a shared pool of variants for the X-linked locus of ACE2 receptor. Several specific and common ACE2 variants were of the utmost importance to the viral entry and infection. In the absence of gender bias for the gene expression profiles, the hemizygous rare variants of ACE2 describe the observed higher mortality rate in males. Finally, a personalized medicine strategy is conceived for isolating high-risk individuals in epidemic circumstances.

Background: Coronavirus Disease 2019 (COVID-19) has been demonstrated to be the cause of pneumonia. Nevertheless, it has not been reported as the cause of acute myocarditis or fulminant myocarditis. Case presentation: A 63-year-old male was admitted with pneumonia and cardiac symptoms. He was genetically confirmed as having COVID-19 according to sputum testing on the day of admission. He also had elevated troponin I (Trop I) level (up to 11.37 g/L) and diffuse myocardial dyskinesia along with a decreased left ventricular ejection fraction (LVEF) on echocardiography. The highest level of interleukin-6 was 272.40 pg/ml. Bedside chest radiographs showed typical ground-glass changes indicative of viral pneumonia. Laboratory test results for viruses that cause myocarditis were all negative. The patient conformed to the diagnostic criteria of the Chinese expert consensus statement for fulminant myocarditis. After receiving antiviral therapy and mechanical life support, Trop I was reduced to 0.10 g/L, and interleukin-6 was reduced to 7.63 pg/ml. Moreover, the LVEF of the patient gradually recovered to 68%. The patient died of aggravation of secondary infection on the 33^rd day of hospitalization. Conclusion: COVID-19 patients may develop severe cardiac complications such as myocarditis and heart failure. This is the first report of COVID-19 complicated with fulminant myocarditis. The mechanism of cardiac pathology caused by COVID-19 needs further study.

In the midst of the novel coronavirus (SARS-CoV-2) epidemic, examining reported case data could lead to biased speculations and conclusions. Indeed, estimation of unreported infections is crucial for a better understanding of the current emergency in China and in other countries. In this study, we aimed to estimate the unreported number of infections in China prior to 23 March 2020 restrictions. To do that, we developed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model which estimated unreported cases and infections from the reported number of deaths. Our approach relied on the fact that observed deaths were less likely to be affected by reporting biases than reported infections. Interestingly, we estimated that R0 was 2.43 (95%CI= 2.42 – 2.44) at the beginning of the epidemic, and that 92.9% (95%CI= 92.5% - 93.1%) of total cases were not reported. Similarly, the proportion of unreported new infections by day ranged from 52.1% to 100%, with a total of 91.8% (95%CI= 91.6% - 92.1%) unreported infections. Agreement between our estimates and those from previous studies proved that our approach was reliable to estimate prevalence and incidence of undocumented SARS-CoV2 infections. Once tested on Chinese data, our model could be applied on other countries with different surveillance and testing policies.

We statistically investigate the Coronavirus Disease 19 (hereinafter Covid-19) epidemics, which is particularly invasive in Italy. We show that the high apparent mortality (or Case Fatality Ratio, CFR) observed in Italy, as compared with other countries, is likely biased by a strong underestimation of infected cases. To give a more realistic estimate of the mortality of Covid-19, we use the most recent estimates of the IFR (Infection Fatality Ratio) of epidemic, based on the minimum observed CFR, and furthermore analyse data obtained from the ship Diamond Princess, a good representation of a ‘laboratory’ case-study from an isolated system in which all the people have been tested. From such analyses we derive more realistic estimates of the real extension of the infection, as well as more accurate indicators of how fast the infection propagates. We then point out from the various explanations proposed, the dominant factors causing such an abnormal seriousness of the disease in Italy. Finally, we use the deceased data, the only ones estimated to be reliable enough, to predict the total number of infected people and the interval of time when the infection in Italy could stop.

Ligand and structure based virtual screening approaches were applied to clinical stage drugs as well as those approved for human use in an attempt to repurpose drugs for potential use against COVID-19. This approach involved ligand-based shape similarity searches, structure-based docking and pharmacophore searches with the help of pharmacophore queries derived from available ligands and receptor structures. Several compounds appeared as hits in pharmacophore and shape similarity searches and those docking to the SARS-CoV-2 viral 3CL protease were then ranked on the basis of docking scores.

The novel coronavirus, COVID-19 is now officially declared as a pandemic by the World Health Organization (WHO), and most parts of the world are taking drastic measures to restrict human movements to contain the infection. Like millions of others around the world, I am wondering, is there anything that could be done, other than keeping high personal hygiene, and be vigilant of symptoms, to reduce the chances of infection, or at least to reduce the burden of the disease. So far, the National and International health agencies, including the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC), and the WHO have provided clear guidelines for both preventive and treatment suggestions. In this opinion-based article, I want to discuss, why keeping the adequate micronutrient balance might enhance the host response and be protective of viral infections. A detailed in-depth discussion of various micronutrients is not the purpose of this article, I will mostly emphasize on the role of zinc in viral infection.

Background: COVID-19, a member of corona virus family is spreading its tentacles across the world due to lack of drugs at present. Associated with its infection are cough, fever and respiratory problems causes more than 15% mortality worldwide. It is caused by a positive, single stranded RNA virus from the enveloped coronaviruse family. However, the main viral proteinase (Mpro/3CLpro) has recently been regarded as a suitable target for drug design against SARS infection due to its vital role in polyproteins processing necessary for coronavirus reproduction.Objectives: The present in silico study was designed to evaluate the effect of Eucalyptol (1,8 cineole), a essential oil component from eucalyptus oil, on Mpro by docking study.Methods: In the present study, molecular docking studies were conducted by using 1-click dock and swiss dock tools. Protein interaction mode was calculated by Protein Interactions Calculator.Results: The calculated parameters such as RMSD, binding energy, and binding site similarity indicated effective binding of eucalyptol to COVID-19 proteinase. Active site prediction further validated the role of active site residues in ligand binding. PIC results indicated that, Mpro/eucalyptol complexes forms hydrophobic interactions, hydrogen bond interactions and strong ionic interactions.Conclusions: Therefore, eucalyptol may represent potential treatment potential to act as COVID-19 Mpro inhibitor. However, further research is necessary to investigate their potential medicinal use.

The world is puzzling over the origin of the current outbreak of the coronavirus disease (COVID-19) that is caused by a novel coronavirus-2019 (2019-nCoV). As of 26^th March 2020, the World Health Organization has reported 46,2,684 confirmed cases and 20,834 confirmed deaths in total due to COVID-19. To this end, two unique mammals namely bats and pangolins are being investigated for their potential link to COVID-19. However, the evidence so far gathered in this context is far from clear. This paper aimed to: (i) enlighten the major aspects of life of bats and pangolins; (ii) briefly discusses their potential link to COVID-19; and also (iii) to highlight the way forward. The outcomes may contribute to future research on the subject.

Importance: The rapidly expanding 2019 novel coronavirus pandemic (COVID-19, caused by the SARS-CoV-2 virus) has challenged the medical community to an unprecedented degree. Physicians and healthcare workers are at added risk of exposure and infection during the course of the patient care. Due to the rapid spread of this disease through respiratory droplets, healthcare providers such as otolaryngologists-head & neck surgeons who come in close contact with the upper aerodigestive tract during diagnostic and therapeutic procedures are particularly at risk. Here we present a set of safety recommendations based on our review of literature and communications with physicians with first-hand knowledge of safety procedures during the 2019 COVID-19 pandemic.Observations: A high number of healthcare providers were infected during the first phase of the pandemic in Wuhan province. Subsequently, by adopting strict safety precautions, other regions were able to achieve high levels of safety for healthcare providers without jeopardizing the care of patients. We reviewed the most common procedures related to the examination and treatment of upper aerodigestive tract diseases. Each category was reviewed based on the potential risk imposed to healthcare workers. Specific recommendations were made, based on the literature, when available, or consensus best practices. Specific safety recommendations were made for performing tracheostomy in COVID-19 patients. Conclusions and Relevance: Preserving highly skilled healthcare work force is a top priority for any community and healthcare system. Based on the experience of healthcare systems in Asia and Europe, by following strict safety guidelines, the risk of exposure and infection of healthcare providers could be significantly reduced, while providing high levels of care. The provided recommendations could be used as broad guidance for all healthcare workers who are involved with the care of COVID-19 patients.

The world is currently going through a serious pandemic of viral infection with SARS-CoV-2, a new isolate of coronavirus, resembling and surpassing the crisis that occurred in 2002 and 2013 with SARS and MERS, respectively. SARS-CoV-2 has currently infected more than 142,000 people, causing 5,000 deaths and reaching more than 130 countries worldwide. The very large spreading capacity of the virus clearly demonstrates the potential threat of respiratory viruses to human health, alarming governments around the world that preventive health policies and scientific research are pivotal to overcoming the crisis. Coronavirus disease 2019 (COVID-19) causes flu-like symptoms in most cases. However, approximately 15% of patients will need hospitalization, and 5% require assisted ventilation, depending on the cohorts studied. What is intriguing, however, is the higher susceptibility of elderly individuals, especially those who are more than 60 years old and have comorbidities, including hypertension, diabetes and heart disease. In fact, the death rate in this group may be up to 10-12%. Interestingly, children are somehow protected and not included as a risk group.Thus, here, we discuss some possibilities of molecular and cellular mechanisms by which elderly subjects may be more susceptible to severe COVID-19. In this sense, we raise two main points: i) increased ACE-2 expression in pulmonary and heart tissue of chronic angiotensin 1 receptor (AT1R) blocker users and hypertensive individuals and ii) antibody-dependent enhancement (ADE) after previous exposure to other circulating coronaviruses. We believe these are pivotal points for a better understanding of the pathogenesis of severe COVID-19 and must be addressed with attention by physicians and scientists in the field.

Severe COVID-19 alters the biochemical and morphological characteristics of blood cells in a wide variety of ways. To date, however, the vast majority of research has been devoted to the study of leukocytes, while erythrocyte morphological changes have received significantly less attention. The purpose of this research was to identify erythrocyte types that were unique to COVID-19, compare the number of different poikilocyte types, and measure erythrocyte sizes to provide data on size dispersion. Red blood cells obtained from 6 control donors (800-2200 cells for each donor) and 5 COVID-19 patients (800-1900 cells for each patient) were examined using low voltage scanning electron microscopy. We did not discover any forms of poikilocytes that would be unique to COVID-19. Among COVID-19 patients, we observed an increase in the number of acanthocytes (p=0.01) and a decrease in the number of spherocytes (p=0.03). In addition, our research demonstrates that COVID-19 causes an increase in the median (p=0.004) and interquartile range (p=0.009) when assessing erythrocyte size.

The COVID-19 pandemic has forced Indian engineering institutions (EIs) to bring their previous half-shut shades completely down. Fetching new admissions to EI campuses during the pandemic has become a ‘now or never’ situation for EIs. During crisis situations, institutions have struggled to return to the normal track. The pandemic has drastically changed students’ behavior and family preferences due to mental stress and the emotional life attached to it. Consequently, it becomes a prerequisite, and emergencies need to examine the choice characteristics influencing the selection of EI during the COVID-19 pandemic. The purpose of this study is to critically examine institutional influence and pandemic influence due to COVID-19 that affects students’ choice about an engineering institution (EI) and consequently to explore relationships between institutional and pandemic influence. The findings of this quantitative research, conducted through a self-reported survey, have revealed that institutional and pandemic influence have governed EI choice under the COVID-19 pandemic. Second, pandemic influence is positively affected by institutional influence. The study demonstrated that EIs will have to reposition themselves to normalize pandemic influence by tuning institutional characteristics that regulate situational influence and new enrollments. It can be yardstick for policy makers to attract new enrollments under pandemic situations.

We present a general approach to define reproduction ratios or numbers to monitor the outbreak of epidemics that are modeled by mathematical evolution equations. This provides a solution to an important topic that has not been completely settled in the literature, especially in the case of complex epidemiological models. We illustrate our procedure with a full implementation of a standard deterministic SEIR model that is applied to examine the Covid-19 outbreaks and the effects of intervention measures in several countries in America (Argentina, Brazil, Mexico, USA) and Europe (France, Italy, Spain and UK) in 2020. Our code is also used to investigate herd immunity levels for Covid-19, indicating values between 85% and 90%.

We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardia, Piemonte, and Veneto regions. We focus on the application of a stochastic approach in fitting the model numerous parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyze the official data and the predicted evolution of the epidemic in the Italian regions, and we compare the results with data and predictions of Spain and South Korea. We link the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

In this paper is proposed an analytical technique which can be used to obtain the forced response of a cantilevered tube conveying fluid. Considering the pipe subjected to an arbitrary harmonic force either distributed or concentrated, an analytical solution is found using Green’s function method. The solution obtained of the closed form satisfies the differential equations in a classical sense. The presented method giving the exact solutions is more precise than the classical eigenfunction expansion or Galerkin’s method with no need to the eigenfunctions or eigenvalues.

The Parecis Basin is one of the largest intracratonic basins in Brazil. Despite its considerable size, the basin has yet to be extensively explored, with only five wildcat wells drilled for hydrocarbons. So far, no commercial discoveries have been announced. Regional studies have suggested Paleozoic sedimentation, while recent studies indicate a Neoproterozoic fill. However, no tectonic model accurately describes the basin’s development, and no detailed structural map for the entire basin has been published. The present work presents a new detailed structural map of the Parecis Basin based on a four-step interpretation workflow integrating seismic and gravimetric data. The first step includes converting the public 2D seismic lines to the depth domain. The second step is estimating the residual Bouguer anomaly, where the computed residual anomalies should relate to the basin’s tectonic features. The third step comprises the 2D forward modeling of the gravimetric anomalies using the 2D seismic interpretation as a constraint. The final step compiled all the interpreted features into our new structural map. This map reveals the top of the basement, forming a complex framework of horsts and grabens. Normal faults define the main structural style in the basin. Further, we could recognize thick, high-density bodies embedded in the crystalline basement. These bodies consist of Orosian-Calimian (1.8-1.6 Ga) mafic and ultramafic rocks, which may be a potential source for hydrogen exploration in the basin. Subsequent geophysical and geochemical surveys will assess the hydrogen potential in the area.

Millions of children in developing countries face preventable deaths due to inadequate vaccination and malnutrition, in part due to insufficient monitoring and the absence of official identification. A reliable fingerprint recognition system can be a practical solution to address this issue. However, the scarcity of longitudinal fingerprint datasets for young children leads to unresolved questions regarding the earliest age for fingerprint biometric use, the frequency of enrollment required for reliable recognition, and the methods to accommodate agerelated changes. A few recent studies introduced high-resolution fingerprint scanners and showed promising recognition performance for young children. However, these studies were conducted on a small dataset over a shorter period with limited diversity; further evaluation of their finding is essential. This study assessed the effectiveness of a high-resolution contactless scanner in a controlled, diverse longitudinal dataset of children (0-15 years). Our results indicate that infants can be enrolled at five days old and reliably recognized after two months with a TAR= 100% @ FAR = 0.1%, and children aged 4-15 years can be recognized after one year with a TAR= 98.72% @ FAR = 0.1%.

Antimicrobial resistance (AMR) poses a critical global health threat, leading to approximately 1.27 million deaths annually from infectious diseases resistant to existing antibiotics. Factors such as antibiotic misuse and environmental contamination have accelerated AMR, with the COVID-19 pandemic exacerbating the issue due to increased antibiotic usage. However, the development of new antibiotics has stagnated, with only a few approved in recent years, and many facing resistance. Among the priority pathogens identified by the WHO, Pseudomonas aeruginosa stands out as a significant concern due to its multidrug resistance and virulence. P. aeruginosa infections are challenging to treat due to intrinsic and acquired resistance mechanisms, as well as its ability to form biofilms. Additionally, P. aeruginosa produces a plethora of virulence factors, including proteases, siderophores, and toxins, further complicating treatment. Quorum sensing (QS) systems play a crucial role in regulating bacterial physiology and virulence factor expression. P. aeruginosa employs three QS systems, making it an attractive target for quorum quenching (QQ) strategies. Enzymes such as AHL lactonases, acylases, and oxidoreductases have shown promise in inhibiting QS, thus reducing virulence without impacting bacterial growth. Furthermore, natural QS inhibitors produced by various organisms offer potential therapeutic alternatives. Despite promising results in vitro, translating QQ strategies to clinical settings remains challenging. Nevertheless, QQ represents a novel approach in combating multidrug-resistant infections and warrants further investigation as a complementary therapeutic strategy alongside traditional antibiotics. This review summarizes enzymes with Qurorum Quenching activity evaluated against the pathogen P. aeruginosa and their potential applications in combination therapies.

The integration of artificial intelligence (AI) into academic settings in Sabah, Malaysia, is transforming education and research landscapes. While AI technologies promise to enhance teaching, learning, and scholarly activities, they also pose challenges such as ethical concerns and skill gaps among academic staff. This study addresses the multifaceted impacts of AI adoption on academicians in Sabah, focusing on two key research questions: the impact of AI-based intelligent tutoring systems on student engagement, learning outcomes, and educational equity, and the challenges and opportunities in building academicians' capacity to integrate AI technologies effectively. Through a multidisciplinary approach, incorporating insights from education, computer science, social sciences, and ethics, this research aims to evaluate the effectiveness of AI tools in educational settings and identify strategies for skill development and infrastructure support. The study recommends empirical assessments within Sabah's educational institutions, considering contextual factors and fostering collaborative partnerships with local communities. Professional development programs, collaboration with industry partners, and improved access to AI infrastructure are proposed strategies. Longitudinal studies and interdisciplinary research initiatives are suggested for future research, along with qualitative methods to capture diverse perspectives. Ultimately, by embracing a collaborative and multidisciplinary approach, Sabah's academic community can harness the transformative potential of AI to advance education, research, and scholarship while promoting ethical and inclusive practices.

Diabetic foot is a serious complication that poses significant risks for diabetic people. The resulting reduction in protective sensitivity in the plantar region requires early detection to prevent the imminent ulceration and amputation. The primary method employed for evaluating this sensitivity loss is the 10 g f Semmes-Weinstein monofilament test, commonly used as a first-line procedure. However, the lack of calibration in existing devices often introduces decision errors due to unreliable feedback. In this paper, a new equipment designed to address these limitations and enhance the assessment of the sensitivity loss using the 10 g f monofilament is introduced. The proposed system automates metrological verification and evaluation processes, ensuring accurate and reliable results. Furthermore, it simulates the practitioner’s procedure, serving both as a valuable training tool and a means to provide force-feedback information. An analytical model of the monofilament buckling and deflection is also presented. The obtained results showed that the tested monofilaments had a very high error compared to the 10 g f declared by the manufacturers. It is aimed, by introducing this advanced equipment, to improve the precision and reliability of assessing the sensitivity loss. The integration of automated verification, simulation capabilities, and precise measurements shows great promise for diabetic patients, reducing the likelihood of adverse outcomes such as ulceration and amputation.

A proof is given showing the Collatz Conjecture is true for all positive integers. The proof was possible once the perspective of the proof was changed from looking at the pattern of the positive integers to looking at the conjecture rules. The conjecture rule for even numbers organizes all positive integers into unique sets and the rule for odd numbers interconnects the unique sets into dendritic pathways to “1.” Infinite loops, other than the minor 4-2-1 loop after reaching “1,” and pathways to infinity are shown to be mathematically impossible. The proof predicted a general equation that shows all positive integers ultimately reach a final value of “1," and calculates the values and locations of the odd positive integers during the iterations for each tested positive integer.

Blockchain technology has emerged as a necessity for the decentralization of payment methods and transactions, but it has brought with it many properties of distributed systems that have made it a crucial technology for overcoming some of society's challenges, especially in the context of decentralizing services, transparency of information, availability, and security. Its architecture and communication methods, although possessing some complex nuances to understand, particularly for the lay audience in the field of distributed systems, protocols, and computer networks. In this article, we will explore some topics of distributed systems related to blockchain technology.

Background: The resurgence of syphilis, primarily in MSM populations, has necessitated novel prophylactic strategies, such as the use of doxycycline post-exposure prophylaxis (doxy-PEP). However, the potential for increased doxycycline use to select for tetracycline resistance represents significant challenges in managing this sexually transmitted infection. This study aims to identify chromosomal mutations associated with tetracycline resistance in Spirochaetales to inform treatment strategies and surveillance measures.Methods: Whole genome sequences (WGS) from the Spirochaetales order, including 4,355 genomes, were analyzed for the presence of mutations in 16S rRNA and non-synonymous mutations in the rpsC and rpsJ genes. The study utilized WGS from GenBank® and sequence data from the PubMLST Treponema pallidum isolate collection. Genetic resistance to tetracycline was detected using a combination of BLASTN searches and gene-gene analysis. Results: A transition mutation TGA to TGG at positions 965-967 in the 16S rRNA gene was detected in 5.6% of Treponema spp. and 3.97% of Spirochaeta spp. genomes. The rpsJ gene exhibited a V57G amino acid substitution across a significant subset of Treponema spp. Notably, the V57K mutation was common in Spirochaeta spp. The rpsC gene had the H178Q mutation and was found to be present in the Spirochaetales bacterium.Conclusion: The identification of mutations associated with tetracycline resistance in Spirochaetales provides a foundation for the development of rapid molecular diagnostics and guides the clinical selection of antibiotics for syphilis treatment. This study underscores the complexity of antibiotic resistance mechanisms and the critical importance of surveillance in the era of antibiotic prophylaxis for STI management.

Parkinson's disease is a neurodegenerative disorder resulting from progressive damage to specific brain regions. Key symptoms encompass involuntary movements (tremor), slowness of movements (bradykinesia), and muscle rigidity. Although the precise cause remains uncertain, a combination of genetic and environmental factors is believed to contribute to its development. This study focuses on the interaction of the E3 ubiquitin-protein ligase parkin with natural compounds. Docking investigations revealed that Amentoflavone exhibited an excellent binding energy score of approximately -10 kcal/mol. The E3 ubiquitin-protein ligase parkin displayed a robust binding affinity with docked amentoflavone, evident from a high binding energy of -10 kcal/mol. Nonetheless, additional biological studies are crucial not only to validate its potential efficacy against Parkinson's and assess safety in terms of toxicity but also to perform further computational analyses confirming these preliminary assessments.

This study delves into the therapeutic potential of two natural compounds, Amentoflavone and Bilobetin, by investigating their interactions with the BPIFB4 protein. BPIFB4, a member of the BPI fold-containing superfamily, has been associated with various biological processes, particularly in longevity and cardioprotection( LAV-BPIFB4). Molecular docking analyses revealed promising binding energies for Amentoflavone and Bilobetin with BPIFB4, suggesting favorable interactions.Additionally by pKCSM database are showed the predicted toxicity properties of Amentoflavone and Bilobetin respectively.This research contributes to the growing body of knowledge on natural compounds and their therapeutic implications in the context of vital biological processes. However, these findings underscore the need for further investigations, including in vivo studies and clinical trials, to validate the observed effects and explore the translational potential of Amentoflavone and Bilobetin in promoting cardiovascular health and longevity.

Diabetes mellitus is acknowledged as a significant contributor to severe complications. The present work has explorated the potential role amentoflavone as an aldose reductase inhibitor through Docking Simulations. From these results this compound has shown excellent results with this enzyme with a high binding energy of -11 kcal/mol. If amentoflavone,a natural biflavonoid, proves effective in inhibiting aldose reductase, it could hold therapeutic promise for managing diabetic complications. However, it's crucial to emphasize that while computational studies offer valuable insights, experimental validation is essential to confirm the actual inhibitory effects and to establish the safety and efficacy of amentoflavone for this purpose. Further research and clinical studies are warranted to fully understand and harness the potential therapeutic benefits of amentoflavone in the context of diabetes.

Cells respond to DNA double-strand breaks by initiating DSB repair and ensuing a cell cycle checkpoint. The primary responder to DSB repair is non-homologous end joining, an error prone repair pathway. However, when DSBs are generated after DNA replication in the G2 phase of the cell cycle, a second DSB repair pathway, homologous recombination, can come into action. Both ATM and ATR are important for DSB-induced DSB repair and checkpoint responses. One method of ATM and ATR working together is through the DNA end-resection of DSBs. As a readout and marker of DNA end-resection, RPA is phosphorylated at Ser4/Ser8 of the N-terminus of RPA32 in response to DSBs. Here, the significance of RPA32 Ser4/Ser8 phosphorylation in response to DNA damage, specifically in S phase to G2 phase of the cell cycle is examined. RPA32 Ser4/Ser8 phosphorylation in G2 synchronized cells is necessary for increases in TopBP1 and Rad9 accumulation on chromatin and full activation of the ATR-dependent G2 checkpoint. In addition, our data suggest RPA Ser4/Ser8 phosphorylation modulates ATM-dependent KAP-1 phosphorylation and Rad51 chromatin loading in G2 cells.

Summary— Introduction: HIV (human immunodeficiency virus) is a virus that attacks and destroys one type of white blood cell, in particular, the CD4 lymphocytes, which are responsible for the body's immune response. This weakens the immune system to such an extent that it can no longer fight other viruses, bacteria, protozoa, fungi, and tumors. Methods: We investigated the potential biological role of the natural compound Polydatin (or piceid) using SwissDock, a web service to predict the molecular interactions that can occur between a target protein and a small molecule. Discussion: For the first time, we have investigated the role of polydatin against HIV-1 protease and HIV-2 protease through a computational approach by comparing their estimated ΔG values (kcal/mol) and the nature of the interactions between the residues in the catalytic center of the HIV proteases.Conclusion: From these simulations, Polydatin has excellent physical properties and an excellent estimated ΔG value (kcal/mol) of about -9.9 kcal/mol against HIV-2 protease and ΔG value (kcal/mol) of about -9.5 kcal/mol against HIV-1 protease. In addition, Polydatin was able to bind to two key amino acids of the catalytic triad sequence common to asparagine proteases (Asp25 and Gly27)

The impact of the climate crisis on urban environments and life within them is evident. In the face of challenges like heatwaves, floodings and other extreme events, pollution, and declining quality of life in cities, there is a growing demand for the preservation and expansion of urban green spaces, often driven by citizen-led transformations. This paper examines 100 urban greening projects initiated or supported by citizens globally, categorizing them according to the type of greenery, the stakeholders involved, the mode of implementation and the use of smart technologies incorporated. We notice variations in green endeavors based on the stakeholders spearheading them, however most of entirely citizen-led initiatives aimed at the creation of urban farms and food growing, demonstrating the pressuring needs for food securing and self-determination in communities. More than half of the assessed initiatives that managed to scale up and multiply had public authorities providing a framework or a type of support for their development or an NGO or other organization providing expertise and mobilize citizens at various stages. In terms of technological use, we find mostly websites and social media platforms easing participatory endeavors and knowledge sharing of best practices, accelerating scaling efforts, while there is a low integration of more advanced digital technologies, which if used, could enable real-time monitoring of green spaces, inform evidence-based decision-making, and streamline processes in scaling up green initiatives.

Aerobic glycolysis in cancer cells, originally observed by Warburg 100 years ago, which involves production of lactate as the end product of glucose breakdown even in the presence of adequate oxygen, is the foundation for the current interest in cancer cell-specific reprograming of metabolic pathways. The renewed interest in cancer cell metabolism has now gone well beyond the original Warburg effect related to glycolysis to other metabolic pathways to include amino acid metabolism, one-carbon metabolism, pentose phosphate pathway, nucleotide synthesis, antioxidant machinery, etc. Since glucose and amino acids constitute the primary nutrients that fuel the altered metabolic pathways in cancer cells, the transporters that mediate the transfer of these nutrients and their metabolites not only across the plasma membrane but also across the mitochondrial and lysosomal membranes have become an integral component of expansion of the Warburg effect. In this review, we focus on the interplay between these transporters and metabolic pathways that facilitates the metabolic reprogramming which has become the hallmark of cancer cells. The beneficial outcome of this recent understanding of the unique metabolic signature surrounding the Warburg effect is the identification of novel drug targets for development of a new generation of therapeutics to treat cancer.

Long COVID, a name often given to the persistent symptoms following acute SARS-CoV-2 infection, poses a multifaceted challenge for health. This review explores the intrinsic relationship between comorbidities and autoimmune responses in shaping the trajectory of long COVID. Autoantibodies have emerged as significant players in COVID-19 pathophysiology, with implications for disease severity and progression. Studies show immune dysregulation persisting months after infection, marked by activated innate immune cells and high cytokine levels. The presence of autoantibodies against various autoantigens suggests their potential as comorbid factors in long COVID. Additionally, the formation of immune complexes may lead to severe disease progression, highlighting the urgency for early detection and intervention. Furthermore, long COVID is highly linked to cardiovascular complications and neurological symptoms, posing challenges in diagnosis and management. Multidisciplinary approaches, including vaccination, tailored rehabilitation, and pharmacological interventions, are used for mitigating long COVID's burden. However, numerous challenges persist, from evolving diagnostic criteria to addressing the psychosocial impact and predicting disease outcomes. Leveraging AI-based applications holds promise in enhancing patient management and improving our understanding of long COVID. As research continues to unfold, unravelling the complexities of long COVID remains paramount for effective intervention and patient care.

Background There is a considerable overlap between clinical presentation of post-COVID-19 condition (PCC) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) . Many of their common symptoms can be linked to dysregulation of the autonomic nervous system (dysautonomia). This study aimed to objectively assess autonomic function in patients with PCC and in patients with ME/CFS whose disease was not related to COVID-19. Methods Synchronous recordings of an electrocardiogram, continuous dynamics of blood pressure in the digital artery using the Penaz method and ultrasound pneumotachography with the spirography function were obtained with spiroarteriocardiorhythmography method in 34 patients diagnosed with ME/CFS, in whom the onset of the disease was not associated with COVID-19, 29 patients meeting PCC definition and 32 healthy controls. Heart rate variability (HRV), systolic and diastolic blood pressure variability (RV), respiration variability were assessed at rest and in tests with fixed respiratory rates. At rest, indicators of baroreflex regulation were additionally determined (baroreflex effectiveness index and baroreflex sensitivity). Results The total power, power of very low frequency, low-frequency and high-frequency of RR interval variability at rest as well as baroreflex effectiveness index in up-ramps of arterial blood pressure and baroreflex sensitivity were significantly lower both in PCC and ME/CFS patients compared to HC. Several diagnostic prediction models for ME/CFS were developed based on HRV parameters. During slow breathing HRV parameters return to normal in PCC, but not in ME/CFS. Correlation analysis revealed a close relationship of HRV, RV parameters and baroreflex sensitivity with fatigue, but not with HADS depressive/anxiety symptoms in ME/CFS and PCC. Conclusion A similar pattern of HRV and baroreflex failure with signs of a pathological acceleration of age-dependant dysautonomia was identified in ME/CFS and PCC. The clinical, diagnostic and therapeutic implications of these findings are discussed, in light of previously described relationship between inflammation, vascular pathology, atherosclerotic cardiovascular disease and autonomic dysfunction.

Autonomic dysfunction is an increasingly recognised complication in chronic neurological conditions such as Parkinson’s disease , and other medical conditions, including diabetes mellitus, chronic fatigue syndrome, postural tachycardia syndrome with and without Ehlers-Danlos syndrome, fibromyalgia and recently Long Covid. Despite laboratory-based tests to evaluate normal and abnormal autonomic function, there are no home-based tests to record neuro-cardiovascular autonomic responses to common stimuli in daily life that are dependent on the normal functioning of the autonomic nervous system. We have developed an adapted blood pressure/heart Autonomic Profile (aAP) that can be used by an individual independently and repeatedly in a domiciliary setting to determine the physiological and symptomatic response to standing, food, and physical and mental (cognitive, emotional) activities. The aAP aids separating autonomic failure (often irreversible) from autonomic dysfunction. This helps the individual and attending healthcare professional understand the relationship between symptoms and common triggers in daily life and informs on self-management in debilitating conditions such as the postural tachycardia syndrome (PoTS) and Long Covid.

In New Orleans, Louisiana the population’s poor baseline health led to its establishment as an early epicenter for severe acute COVID-19. Antici-pating future outbreaks of COVID-19 and other respiratory viruses, we need to identify correlates of outcome, from real clinical experience. 89 patients were recruited into the ClinSeqSer acute COVID-19 longitudinal observational study, from the beginning of the outbreak in March to July 2020. Patients admitted for acute COVID-19 were enrolled in person. The cohort is unique as it is 68% Black, 53% female, of average age of early 60s, and prevalence of obesity and hypertension respectively of 55% and 83%. The outcomes are: 53% severe (20% fatal, 33% non-fatal) and 47% non-severe, with severe defined as death or requiring mechanical ventila-tion or high flow oxygen. Obesity and admit systolic blood pressure (SBP) >140mmHg are each associated with severe outcome and, despite respective sensitivity of 71% and 76%, specificity ~66% for both, and ac-curacy of 60% and 70% by ROC analysis, would likely provide useful predictors of outcome in critically stressed health care systems. We discuss pathophysiologic hypotheses to explain why high admit SBP is observed only in half of patients with pre-COVID hypertension and is associated with severe outcome.

The world has been highly impacted by the COVID-19 as the virus has spread to all continents – about 200 countries in total. The latest update claims about 4,000,000 confirmed cases and about 300,000 confirmed deaths owing to the COVID-19 pandemic. This probably makes the COVID-19 as the most dangerous contagious disease in the era 2000s. Apart from massive publications on this topic, there is no available qualitative analysis that describes the dynamic spreads of the COVID-19 and its impacts on healthcare and the economy. Through the system archetypes analysis, this paper explains that the dynamic spread of the COVID-19 consists of the limits to growth and the success to successful structures. The limits to growth elucidates that more symptomatic and asymptomatic patients owing to infected droplets may be bounded by self-healing and isolated treatments. The success to successful structure explains that once the COVID-19 affects the economy through the lockdown, there will be a limited fund to support the government aids and the aggregate demand. In overall, this paper gives readers simplified holistic insights into understanding the dynamic spread of the COVID-19.

In this article, we investigate both the Schrödinger and continuity equations in the presence of nonlocal potential that arising from electron-electron interaction and local one in the context of minimal uncertainty in momentum within commutative and noncommutative frameworks. Furthermore, the Frahn–Lemmer potential type is used. Interestingly, the combined effects of both the phase-space noncommutativity and nonlocality on the current density while considering a minimal uncertainty in momentum are examined. We find that the current density, as conventionally defined, does not fulfil the condition of current conservation, thus, a new definition of the current density that encompasses the aforementioned contributions is given. Thereafter, it is shown that the computed current using the new definition of the current density satisfies the current conservation. Noting that using both the $★$product and linear Bopp-Shift, the noncommutativity is inserted.

We investigated and quantified bacterial accumulation in facemasks used by the general population, using 16S rRNA (Sanger Sequencing), culture and biochemical analysis along with Rose Bengal staining. Additionally, a systematic overview of the literature on face mask contamination was undertaken. We found an average bacterial load of 4.24 × 10⁴ CFU recovered/mask, with a maximum load of 2.85 × 10⁵ CFU. This maximum is 310 times higher than the limit value for contamination of ventilation system outlet surfaces specified by the German standard VDI 6022. Biochemical and molecular identification predominantly found Staphylococcus species (80%), including Staphylococcus aureus, along with endospore-forming Bacillus spp. Literature reports also indicate contamination of masks by bacterial and fungal opportunists of the genera Acinetobacter, Aspergillus, Alternaria, Bacillus, Cadosporium, Candida, Escherichia, Enterobacter, Enterococcus, Klebsiella (including K. pneumoniae), Micrococcus, Microsporum, Mucor, Pseudomonas, Staphylococcus and Streptococcus. Bacterial counts increase linearly with wearing duration, and prolonged use may affect the skin and respiratory microbiomes, promoting consequential eye, skin, oral and airway conditions. These aspects underscore the urgent need for further research and a risk-benefit analysis in respect of mask use, particularly given their unproven efficacy in disrupting the transmission of respiratory viruses and their adverse social consequences.

Emerging molecular and computational techniques may allow construction and computational treatment of dynamic digital twins on the scale of populations to individuals. This approach may pave the way for predictive, preventive, and personalized treatment. Because digital twins are independent of geographical location, this may also contribute to global equitable health.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.

Color image binarization plays a pivotal role in image preprocessing work, significantly impacting subsequent tasks, particularly in text recognition. This paper concentrates on Document Image Binarization (DIB), aiming to separate a image into foreground (text) and background (non-text content). Through a thorough analysis of conventional and deep learning-based approaches, we conclude that prevailing DIB methods leverage deep learning technology. Furthermore, we explore the receptive fields pre- and post-network training to underscore the Transformer model's advantages. Subsequently, we introduce a lightweight model based on the U-Net structure, enhanced with the Mobile ViT module to better capture global information features in document images. Given its adeptness at learning both local and global features, our proposed model exhibits superior performance on two standard datasets (DIBCO2012 and DIBCO2017) compared to state-of-the-art methods. Notably, our proposed DIB method presents a straightforward end-to-end model devoid of additional image preprocessing or post-processing. Moreover, its parameter count is less than a quarter of the HIP'23 model, which achives best results on three datasets(DIBCO2012, DIBCO2017 and DIBCO2018). Finally, two sets of ablation experiments were conducted to verify the effectiveness of the proposed binarization model.

India has pledged ambitious initiatives to mitigate its growing economies’ impact on the climate, including a goal of net zero emissions by 2070. The transportation sector is one of the key sources of emissions. Therefore, fostering e-mobility within this sector is a key priority for the Indian government. The lifecycle of LiBs raises numerous concerns regarding its sustainability in production, use of rare materials, and most importantly waste management. Furthermore, this paper will highlight the case for EV battery recycling as a growing sector that also has the potential to foster circularity in the EV sector. Through the introductory section, this paper lays out rationale for battery recycling in a circular EV economy. The subsequent sections discuss the current and emerging battery technologies and their link to recycling methods whilst overviewing domestic and foreign battery recycling companies. Finally, the paper concludes with a gap assessment of the battery recycling ecosystem in India and makes recommendations to further integrate this industry into the EV supply chain. As India steers towards a sustainable future, it is imperative that the country integrates battery recycling to enhance circularity in the EV ecosystem, closing the gap between a growing number of EVs and waste management.

This paper provides an overview of modelling and simulation methods for complex systems, including queuing and life support systems. To realize and capture every aspect of a system or situation, a model is used in place of the actual one. Using a model and simulation, we may create scenarios and make decisions. Computer experiments with the model can save costs, time, and effort once its validity has been shown. A model of the thing under study is created by computer simulation, which then runs the model on a digital computer and examines the results. It's interesting to note that a knowledge base of data includes information about predicted behaviour of the model as well as coordinated determination of external variables and parameters. Selecting the precise model creation technique is the first and most difficult task in simulation. A review of techniques used in simulation model execution (serial and parallel discrete-event simulation), simulation model analysis (calibration, validation, verification, goal-seeking), and conceptual, declarative, functional, constraint, and multimodal design are presented in this paper.

_{he present study was conducted to quantify the heavy metals cadmium, lead, copper, chromium, nickel, and zinc in the bivalve mollusk concha prieta (Anadara tuberculosa) using in- ductively coupled plasma optical emission spectroscopy (ICP-OES). This research aims to identify whether the bioaccumulate content of heavy metals exceeds the maximum limits established by various public health bodies such as the ONU, FAO, Codex Alimentarius, EEC, and NHI. Samples of the species were collected randomly from three locations in Puerto El Morro, Playas Municipal Market, and La Libertad Seafood Market in the Gulf of Guayaquil. Thirty-three soft tissue samples of (Anadara tuberculosa) were evaluated, and the values quantified in mg/kg were in the following order: Zn>Cu>Cd>Ni>Cr>Pb.}

This study focused on the investigation of myeloperoxidase through a Molecular Docking approach with various natural compounds to identify potential substances for cardiovascular research. Recent research has linked elevated myeloperoxidase levels to the severity of coronary artery disease. The results of the docking analysis revealed Polydatin, Daidzin, Astringin, Ginkgetin, and Amentoflavone as promising compounds with excellent binding capacity. To complement this, toxicity prediction studies were conducted using pkCSM. Overall, all four investigated molecules (Amentoflavone, Daidzin, Ginkgetin, and Astringin) were found to be non-toxic, exhibiting high maximum tolerated doses (human) and favorable values for Oral Rat Acute Toxicity and Oral Rat Chronic Toxicity. Moreover, they showed non-AMES toxicity and non-hepatotoxicity. Astringin, in particular, stood out with the highest positive effects, including a high maximum tolerated dose (human) and favorable values for Oral Rat Chronic Toxicity, along with dual inhibition of hERG II and hERG I. These findings suggest the potential utility of these compounds in cardiovascular research with minimized unwanted effects.

“Energy” is probably the most important term in science and technology. The reason is energy can be converted while it is overall conserved, and thereby correlates changes of a wide variety. Despite its successful use in many areas over more than a century, an analysis of current literature shows that definitions of what energy is and explanations why it is conserved are inconsistent. With regard to energy forms not even a definition was found, and examples given are often wrong. Looking at two interacting objects in the most simple situations, with energy conservation but without conversion, a consistent understanding of energy and its conservation can be derived. Based on it, the systematic set of energy forms with a clear definition of each is then presented.

Passive marine listening, involving the acoustic monitoring of underwater environments, has become increasingly vital for scientific research, environmental monitoring, and defense applications. However, the success of such applications critically depends on the ability to extract meaningful information from the often noisy and dynamic underwater acoustic environment. In this context, Mel-frequency cepstral coefficients (MFCCs) have emerged as an essential tool for feature extraction, capturing the spectral characteristics of marine sounds and making them ideal for species identification and sound event detection. This research presents an innovative approach to enhance the robustness of MFCC-based passive marine listening through adaptive noise reduction techniques. The proposed approach utilizes dynamic spectral subtraction to counter underwater noise, resulting in enhanced signal-to-noise ratios for desired sounds. This adaptive system adjusts to dynamic underwater noise, allowing it to concentrate on target sounds and suppress interference effectively. The experimentation further validates the effectiveness of the proposed approach, with results reaching 99% on the full dataset of 570 mammals and vessels, demonstrating the effectiveness of SVM and Random Forests in the classification of underwater audio.

This theoretical study presents a novel perspective on the potential anti-inflammatory properties of Bromelain, a natural agent extracted from pineapple stems. The investigation explores the binding capabilities of Bromelain to Apoptosis-associated speck-like containing CARD (ASC), a crucial adapter molecule known for its involvement in inflammatory processes and inflammasome formation. For the first time, these findings suggest that Bromelain exhibits a notable affinity for ASC, indicating its promising role as a natural anti-inflammatory agent. This study sheds light on the molecular interactions that may contribute to Bromelain's therapeutic potential in modulating inflammatory responses.

We use the Stefan-Boltzmann law to derive and investigate what we will call the black hole CMB temperature luminosity. Interestingly, the CMB luminosity is always the same for every black hole at a luminosity distance equal to the Schwarzschild radius, which is fully valid in black hole cosmology, a topic that is actively discussed to this day. The CMB black hole luminosity is always the same , regardless of the mass of the black hole. This is in contrast to the Bekenstein-Hawking luminosity, which is linked to the Hawking temperature, that is mass dependent.

Developmental stability (DS) is indicated by the ability of individuals to resist random environmental and/or genetic perturbations during their development. Fluctuating Asymmetry (FA) is the commonest mean of assessing DS in bilateral traits. FA is defined as small random deviations from an ideal morphological symmetry. To date, little attention has been paid to sexual differences in FA among tortoises. With this issue in mind, we assessed levels of carapace scutation symmetries in a sample of 45 wild adult red-footed tortoise, Chelonoidis carbonarius (13 males and 32 females) from Arauca plains, East Colombia. Procrustes ANOVA reflected statistically significative sex-related FA, with males tending to exhibit a more pronounced asymmetry. Although we cannot identify the potential sources responsible for detected developmental instability, our results suggest a high degree of stress and highlight that human intervention in Arauca are affecting wildlife. Similar studies in the future, correlated with an estimate of human impact, could provide irrefutable proof of causality between FA and environmental stressors. The results of this study can represent an estimate of the fitness status of the studied population at present.

The use of artificial intelligence technologies may help companies obtain the optimal use of resources and accomplish more activities with an increase in productivity by 40%. With access to real-time data and the ability to learn from patterns and behaviors, AI can perform these routine tasks more efficiently. Ambient intelligence, Ami, is one of the applications of artificial intelligence, which is called artificial environmental intelligence, which is a concept that focuses on using technology to create an environment that is intelligent and responsive to the needs of its users. This technology has the potential to revolutionize disaster response and management, which in turn facilitates access to necessary information and resources. necessary vitality in the event of a crisis. It may use ambient intelligence to create a network of sensors that can detect and respond to changes in the environment. So that this network can be used to monitor the environment for potential disasters, such as floods, fires and earthquakes. Sensors can also be used to detect changes in temperature, humidity, and other environmental factors that may indicate a potential disaster. This information can then be used to alert emergency responders and provide them with the information needed to respond quickly and effectively. Ambient intelligence can also be used to create a comprehensive database of resources and information that can be accessed in times of crisis. This database may include information about the location of shelters, medical facilities, and other resources that can be used to assist those affected by a disaster. It may also provide information about the condition of roads, bridges, and other infrastructure that may be affected by a disaster. This information can be used to inform response and management decisions, helping to ensure that resources are used in the most efficient way possible. Ambient intelligence can be used to create a communication platform between emergency responders and those affected by a disaster. This platform can also be used to provide updates on the emergency situation, in addition to providing information about available resources to those affected. This can help ensure that those affected by a disaster can access the resources they need in a timely manner.

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Seismic vulnerability assessment in urban areas would in principle require the detailed modeling of each single building and the implementation of complex numerical calculations. This procedure is clearly difficult to apply at urban scale where many buildings have to be considered and therefore it is essential to have simplified, but at the same time reliable, approaches to vulnerability assessment. Among the proposed strategies, one of the most interesting concerns the application of machine learning algorithms, able to classify buildings according to their vulnerability on the basis of training procedures applied to existing datasets. In this paper machine learning algorithms will be applied to a dataset which collects and catalogs the structural characteristics of a large number of buildings and reports the damage observed in L’Aquila territory during the intense seismic activity occurred in 2009. A combination of a trained neural network and a random forest algorithm allows to identify an opportune “a-posteriori” vulnerability score, deduced from the observed damage, which is compared to an “a-priori” vulnerability one, evaluated taking into account characteristic indexes for building’s typologies. By means of this comparison an inverse approach to seismic vulnerability assessment, which can be extended to different urban centers, is proposed.

This paper studies the dividend optimization problem in the entropy regularization framework by following the same continuous-time reinforcement learning setting as in Wang et al. (2020). The exploratory HJB is established and the optimal exploratory dividend policy is a truncated exponential distribution. We show that, for suitable choices of the maximal dividend paying rate and the temperature parameter, the value function of the exploratory dividend optimization problem could be significantly different from the value function in the classical dividend optimization problem. In particular, the value function of the exploratory dividend optimization problem could be classified into three cases based on its monotonicity. Numerical examples are also presented to show the impact of temperature parameter on the solution.

Glial cells provide physical and chemical support and protection for neurons. Secreted neurotrophic factors, scaffolds and vesicles regulate in addition to normal homeostasis, repair following neural tissue injury or degeneration. We previously demonstrated that human CNS glia have revascularization capacity by inducing endothelial cell sprouting and microchanneling driven by glial cell secreted components. The clinical potential of using secreted factors and vesicles generated by glial cells in conditioned media was shown by their re-normalization of pathological blood vessels and 3D tissue wound healing and remodeling capacity. To identify secreted components of glial cells and how CNS and PNS glial cells differentially regulate neural tissue homeostasis, disease and injury response, we developed a novel culture method for various types of glial cells that allow for isolating and characterizing secreted glial components, free of animal factors and contaminants normally associated with serum-based culture conditions. Our culture method will enable to identify secreted components using ultrasensitive RNA, glycoconjugate and protein analysis technologies. The characterization of glial secreted factors involved microchanneling may help in development of new clinical therapies for glial and neural cells or axons to migrate and reform connections.

Fatigue and dyspnea are the most commonly presented long-term complaints in individuals previously infected with SARS-CoV-2. The purpose of the study was to comprehensively evaluate diaphragm muscle function in COVID-19 survivors, as well as investigate whether potential diaphragm dysfunction will contribute to physical functioning impairment. 46 patients qualified to pulmonary rehabilitation were examined. Diaphragm muscle function parameters were evaluated using ultrasonography, while severity of dyspnea, aerobic capacity and amount of energy used by the body during physical activity were assessed by 6-minute walk test, mMRC scale and Metabolic Equivalent Task (MET), respectively. We identified 69.5% patients with diaphragm atrophy and 6.5% with diaphragm paralysis. Percentage of atrophy was not related to age, gender, BMI index, oxygen therapy use during COVID-19 infection course and severity of disease. Patients with presence of cough, fever and without loss of smell during COVID-19 course had a significantly greater values of diaphragm inspiratory thickness, while patients with cough and no smell disorders had a significantly lower percentage of diaphragm atrophy. Diaphragm functional parameters were strongly associated with selected variables of person's exercise tolerance, such as distance in 6-minute walk test, saturation level, fatigue and exertion in Borg scale. In conclusion, diaphragm muscle dysfunction is a serious long-term post-COVID aftermath and can be viewed as a major contributing factor of prolonged functional impairments.

This study explored differences in student-athletes’ symptoms of depression, anxiety, and stress pre- to post-COVID-19 pandemic. The WHO reported a 25% increase in depression and anxiety rates worldwide with young people disproportionately affected. Student-athletes face many stressors related to their sporting and academic feats but what is not known is how the COVID-19 pandemic affected their experiences of mental illness. A multiple cohort cross-sectional study design was employed, and data collected using physical and online surveys. Participants (M age = 19.98 years, SD = 1.50) were recruited from UK universities (N = 807; 427 pre-pandemic cohort, 380 post-pandemic cohort). Results revealed statistically significant differences in mean depression, anxiety, and stress scores between cohorts. Scores for the post-pandemic cohort were significantly higher than pre-pandemic, suggesting a worsening of symptom severity. Distributions of student-athletes across categories of symptom severity also worsened for depressive and anxiety symptoms post-pandemic and were skewed towards more severe categories. Symptoms of de-pression, anxiety, and stress were a concern pre-pandemic. Rates are higher in the post-pandemic cohort, suggesting a worsening of symptoms. This data adds to evidence on student-athletes’ symptoms of mental illness by exploring a UK sample and comparing scores pre- and post-pandemic.

: Cytokine storm is usually described as one of the main reasons behind COVID-associated mor-tality. Cytokines are essential protein molecules engaged in immune responses; they play a critical role in protection against infections. However, they also contribute to inflammatory reactions and tissue damage, becoming a double-edged sword in the context of COVID-19. Recent studies have suggested various cytokines and chemokines that play a crucial role in the immune response to SARS-CoV-2 infection. One such cytokine is Interleukin 27 (IL-27), which has been found to be elevated in the blood plasma of patients with COVID-19. Within this study, we will explore the role of IL-27 in immune responses and address our own findings concerning this cytokine in COVID-19. It affects a wide variety of immune cells; regardless of the pathological process it is involved in, IL-27 is critical for upholding the necessary balance between tissue damage and cytotoxicity against in-fectious agents and/or tumors. In COVID-19, it is involved in multiple processes, including antiviral cytotoxicity via CD8+ cells, IgG subclass switching, and even the activation of Tregs.

Regardless of the SARS-CoV-2 pandemic containment, it remains paramount to comprehensively understand its underlying mechanisms to mitigate potential future health and economic impacts, comparable to those experienced throughout the course of the pandemic. The angiotensin-converting enzyme 2 (ACE2) provide anchorage for SARS-CoV-2 binding, thus implicating that ACE and ACE2 might contribute to the variability in infection severity. This study aimed to elucidate predisposing factors influencing the disease course among people infected by SARS-CoV-2, focusing on angiotensin-converting enzyme (ACE) and ACE2 polymorphisms. Notably, despite similar demographics and comorbidities, COVID-19 patients exhibit substantial differences in prognosis. Genetic polymorphisms in ACE and ACE2 have been implicated in disease progression, prompting our investigation into their role in COVID-19 evolution. Using next-generation sequencing (NGS), we analyzed ACE and ACE2 genes in a sample group comprising six subjects infected by SARS-CoV-2. Our findings revealed a correlation between specific polymorphisms and COVID-19 outcomes. Specifically, ACE and ACE2 intronic deletions were observed in all deceased patients, suggesting a potential association with mortality. These results highlight the significance of genetic factors in shaping the clinical course of COVID-19, emphasizing the importance of further research into the impact of genetic variations on COVID-19 severity.

Pandemics, and other risk-related contexts, require dynamic changes in behavior as situations develop. Human behavior is influenced by both explicit (cognitive) and implicit (intuitive) factors. In this study, we used psychological distance as a lens to understand what influences our decision-making with regards to risk in the context of COVID-19. The study was based on the rationale that our relational needs are more concrete to us than the risk of the virus. First, we explored the impact of social-psychological distance on participants’ risk perceptions and behavioral willingness. As hypothesized, we found that close social relationships of agents promoted willingness to engage in risky behavior. In the second phase, we tested an intervention designed to increase the concreteness of information about virus transmission as a mechanism to mitigate the bias of social influence. We found that the concreteness intervention resulted in significantly reduced willingness to engage in risky behavior. As such, communications aimed at changing the behavior of citizens during times of increased risk or danger, should consider conceptually concrete messaging when communicating complex risk, and hence may provide a valuable tool in promoting health-related behavior.

Abstract: (1) Background: After the COVID-19 pandemic, there is increasing concern regarding the immunity of population to SARS-CoV-2 variants, particularly the Omi-cron variant and its sub-lineages. (2) Methods: The study involved analyzing the im-mune response and symptomatology of 27 vaccinated individuals who were subse-quently infected by Omicron sub-lineages. Blood samples were collected for serological analysis, including the detection of IgG antibodies reactive to the Nucleocapsid (N) and Spike (S) antigens of SARS-CoV-2. Additionally, participants were interviewed to assess the intensity of symptoms during the infection. (3) Results: Despite the high levels of anti-Spike IgG observed after vaccination, all participants were infected by Omicron sub-lineages. The most common symptoms reported by participants were fever or chills, sore throat, and cough. Surprisingly, the levels of anti-Spike IgG found prior to infection did not correlate with symptom severity post-infection. However, it was observed that high post-infection anti-Nucleocapsid IgG levels correlates with mild symptoms during the course of the disease, suggesting a potential role for anti-N antibodies in disease resolution. (4) Conclusions: The high levels of IgG anti-Spike resulting from vaccination may not provide complete protection against infection by the Omicron variant. Addi-tionally, our data suggest that anti-Nucleocapsid IgG titers are negatively correlated with the intensity of the symptoms during mild infections. These findings underscore the importance of ongoing surveillance of viral variants and continuous adaptation of vaccination strategies to ensure efficacy against SARS-CoV-2 variants.

Objectives: To study the differences between malignant hypermetabolic axillary lymphadenopathy (MHL) and COVID-19 vaccine-associated axillary hypermetabolic lymphadenopathy (VAHL) using clinical imaging. Methods: A total of 1,096 patients underwent Positron Emission Tomography-Computed Tomography (PET-CT) between June 1, 2021 and April 30, 2022, at Ehime University Hospital. In total, 188 patients with axillary lymphadenopathy after the COVID-19 vaccination were evaluated. The patients were classified into three groups such as VAHL (n=27), MHL (n=21), and equivocal hypermetabolic axillary lymphadenopathy (EqHL; n=140). Differences in lymph nodes (LNs) swellings were statistically analyzed using clinical imagings (echography, CT, and 18F-FDG PET) statistically. Results: MHL included a higher female population (90.5%) owing to a higher frequency of breast cancer frequency (80.9%). Axillary LNs of MHL did not show any LN fatty hilums (0%); however, those of VAHL and EqHL did (15.8 and 36%, respectively). After the logistic regression analysis of the patients who had axillary lymphadenopathy without any LN fatty hilums, the minor axis length and ellipticity (minor axis/major axis) in the largest axillary LN, SUVmax, and Tissue-to-Background Ratio (TBR) were useful in distinguishing malignant lymphadenopathies. Receiver-operating characteristic (ROC) analysis indicated that a cut-off value of ≥7.3 mm for the axillary LN minor axis (sensitivity: 0.714, specificity: 0.684) and of ≥0.671 for ellipticity (0.667 and 0.773, respectively) in the largest LN with the highest SUVmax and TBR were predictive of MHL. Conclusion: Axillary lymphadenopathy ≥7.3 mm of the minor axis and ≥0.671 of ellipticity in LN without fatty hilum suggests malignancy even in patients who have received COVID-19 vaccination. Further examinations such as 18F-FDG PET are recommended for such patients

Rationale - From the year 1 anno Domini until 1855 with the third Plague, major pandemics occurred on average every 348 years. Since then, they have occurred on average every 33 years, with Coronavirus disease 2019 (COVID-19) now underway.Even though current technologies have greatly improved the way of life of human beings, COVID-19, with more than 700 000 000 cases and 6 950 000 deaths worldwide by the end of 2023, reminds us that much remains to be done. Objective - Given the frequency and duration of recent pandemics, it might be wise to start thinking about preventative methods to minimize the impact of future pandemics. This report looks back at 18 months of COVID-19, from March 2020 to August 2021, with the aim of highlighting potential solutions that could prove practical, or even essential, for the future. Material - COVID-19 data, including case and death reports, were extracted daily from the Worldometer platform to build a database for macroscopic analysis of the spread of the virus around the world. Demographic data were integrated into the COVID-19 database for a better understanding of the spatial spread of the SARS-CoV-2 virus in cities/municipalities. Method - Without loss of generality, we only analyzed data from the top 30 (out of 200 and above) countries ranked by total number of COVID-19 cases. Statistics (regression, t-test (p < 0.05), correlation, mean ± std, etc.) were carried out with Excel software. Spectral analysis, using Matlab software, was also used to try to better understand the temporal spread of COVID-19. Results - A good linear correlation was observed between the number of cases and the respective number of deaths depending on the country, i.e. y = 0.0121x + 19559 with R² = 0.8042. The analysis then focused mainly on the number of cases.This study showed that COVID-19 mainly affects G20 countries. The most interesting result is that cities/municipalities with high population density are a powerful activator of the spread of the virus. The current demographic context seems to be becoming a societal problem that must be addressed adequately.Spectral analysis highlighted that the very first months of spread of COVID-19 were the most notable with a strong expansion of the SARS-CoV-2 virus. On the other hand, the following six months showed a certain stability due mainly to multiple preventive measures such as confinement, closure of non-essential services, wearing of masks, distancing of 2 meters, etc. Discussion - Analysis of case and death data showed that COVID-19 mainly affects G20 countries. Nevertheless, the most interesting result of this study is that cities and municipal areas with population densities of several thousand inhabitants per square kilometer largely favored the spread of the SARS-CoV-2 virus. It is believed that such a demographic context is becoming a societal problem that developed countries around the world will sooner or later face and therefore needs to be adequately addressed. Conclusion - COVID-19 has made us understand that it is time to act both preventatively and curatively. Phenomenological insights suggest that the next pandemic could occur in less than 50 years. It may be time to launch new societal projects aimed at relieving congestion in densely populated regions.

Analysis of immediate effects of the COVID-19 pandemic on SMEs in Rwanda aims to assess and quantify the economic and financial impacts of the pandemic during the lockdown and presents options adopted by SMEs to reopen their business opera-tions. It also seeks to recommend options for sustainable and resilient economic recovery from the scars of COVID-19. This analysis used data collected from nearly 220 SMEs located across the country and applied an Exploratory Data Analysis (EDA) and multivariate linear regression models to measure the pandemic effects. The study revealed that firms downsized employment by 36.4 per cent, but data depict significant deviation within SMEs by their size. The COVID-19 pandemic has had a greater magni-tude of negative effects on sales levels among small businesses. Tax amounts were reduced amidst the crisis however, data do not show any significant variations among SMEs. Additionally, SMEs owners applied various coping mechanisms during re-opening. The study used firm-level data, providing detailed and reliable effects of the shocks on business performance. This analysis recommends establishing the medium-term financing and technical support for SMEs to ensure steady and sustainable recovery from pandemic effects as well as strengthening their resilience to any other socio-economics shocks.

With the rapid evolution of SARS-CoV-2, the emergence of new strains is an intriguing question. This paper presents an evolutionary theory to analyze the mutations of the virus and identify the conditions that lead to the generation of new strains. We represent the virus variants using a 4-letter sequence based on amino acid mutations on the spike protein and employ an n-distance algorithm to derive a variant phylogenetic tree. We show that the theoretically-derived tree aligns with experimental data on virus evolution. Additionally, we propose an A-X model, utilizing the set of existing mutation sites (A) and a set of randomly generated sites (X), to calculate the emergence of new strains. Our findings demonstrate that a sufficient number of random iterations can predict the generation of new macro-lineages when the number of sites in X is large enough. These results provide a crucial theoretical basis for understanding the evolution of SARS-CoV-2.

To elucidate the cellular immune response to coronavirus disease (COVID-19) among children, we assessed cellular immunity in 8 children post-vaccination for COVID-19 and 11 children after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, using the T-SPOT®.COVID assay for both the spike (S) and nucleocapsid (N) proteins. In the vaccinated group, the T-SPOT®.COVID assay for the S protein yielded positive results in all eight children. In contrast, in the post-infection group, the assay for the N protein was positive in 5 of 11 children, with 3 of these 5 children requiring hospital admission, including 2 who needed mechanical ventilation. Therefore, the T-SPOT®.COVID assay is valuable for assessing cellular immunity against COVID-19, and most children infected with COVID-19 may not develop such immunity unless the disease severity is significant.

Background: Accurate estimation of the spread of SARS-CoV-2 is crucial for guiding public health strategies. Underreporting from PCR-based testing, especially in low- and middle-income countries, often obscures the true extent of exposure and immunity to coronavirus disease 2019 (COVID-19). This study aimed to determine the seroprevalence and antibody levels against SARS-CoV-2 among patients visiting hospital-based sentinel sites in Kenya's Rift Valley region following the Omicron wave. Method: We conducted a cross-sectional study in four hospital-based sentinel sites among patients with acute respiratory infection symptoms. Patients aged six months or older visiting the sites between January 2022 and December 2022, presenting with symptoms of acute respiratory infection, were enrolled. Clinical and sociodemographic data were collected using a structured questionnaire. We used a quantitative ELISA kit to detect IgG antibodies against SARS-CoV-2 S protein in serum samples. Results: Among 557 individuals enrolled in the study, the seroprevalence of SARS-CoV-2 antibodies was 97.8% (n=545). Vaccinated individuals demonstrated significantly higher odds of seropositivity compared to unvaccinated counterparts, with an odds ratio of 3.33 (95% CI: (0.4, 27.87)). While seropositivity remained consistent across age groups, older adults exhibited the highest odds. Site-specific differences in enrolment and vaccination rates highlight potential access-related disparities. Conclusion: Our findings indicate widespread prior exposure to SARS-CoV-2 within the study region, underscoring the significant impact of both natural infection and vaccination efforts in driving SARS-CoV-2 seroprevalence within the Rift Valley region. Despite the underestimation of infections and disparities in vaccination access, this study demonstrates the effectiveness of vaccination for conferring SARS-CoV-2 immunity. Targeted interventions are crucial to address accessibility barriers and vaccine hesitancy, ensuring equitable vaccination coverage.

ABSTRACT Background: To date, the COVID-19 pandemic has been the foremost health concern for humankind in the new millennia. This paper aims to describe the related hospitalizations in Italy during the first two years of the health emergency. Design and methods: This is a retrospective, population-based study of Italian hospitalizations for patients diagnosed with COVID-19 during the 2020-2021 period, extracted from the National Hospital Discharge Registry. The outcome variables considered include hospital admissions, costs, and length of stay, among other hospitalization-level variables. Costs were estimated through the charges associated with the Diagnosis-Related Group and Major Diagnostic Categories coding system, plus an additional cost attributed to COVID-19 admissions. To these charges was added an extra cost defined by the ministry of health. Results: In Italy, there were 357,354 hospitalizations for COVID-19 attributed to 298,856 patients in 2020 and 399,043 hospitalizations for COVID-19 attributed to 333,447 patients in 2021. COVID-19 patients faced a transfer rate thrice that of other patients. Hospitalizations were concentrated predominantly in the northern regions, particularly in the first year. Hospitalization rates varied by age in a sine wave pattern, peaking in the youngest and oldest age groups, with mortality rates escalating with age— tending to remain below 3% for those under 44 but surging to 40% in individuals over 75. The financial impact of COVID-19 hospitalizations was substantial, with total costs reaching €3.97 billion in 2020 and €4.99 billion in 2021. Costs per admission and per day also rose, from €11,112 and €807 in 2020 to €12,503 and €844 in 2021, respectively. Excluding the added financial burden of COVID-19, costs would have been notably lower. Hospitalizations involving continuous invasive mechanical ventilation were particularly costly (about 24.000 euros x admission), reflecting the significant resources required for these treatments. Conclusion: Implementing a protective pad around the entire health system that leverages networks of family doctors and nurses, connected in real time to the entire health system, can be crucial. Such a network, tasked with monitoring the local epidemiological situation, protecting vulnerable individuals also through telehealth visits, and establishing a triage system for infections in the initial phase, may effectively help in managing virus spread and protecting hospitals from unpredictable waves of admission demand. Strengthening primary health care could be a decisive factor for the future and enhance the system's resilience in facing new challenges.

The purpose of this study is to examine the match-related performance (scores and penalties) of the athletes in the Junior EJC (European Judo Championship) and U23 EJC categories before and immediately after the Covid-19 quarantine, according to gender and weight category groups. Our sample was based on the junior and U23, male and females, 2019-2020 Junior European Judo Championships and 2019-2020 U23 European Judo Championships. A total of 1431 matches in these tournaments were analyzed: male (n=812) and female (n=619). The main findings of this study showed that most matches in both the male and female categories resulted in ippon (2019-2020 average: 64,35% for Junior male, 70,55% for U23 male and 69,3% for Junior female, 64,4% for U23 female). No significant differences (p &gt; 0.05) were observed between gender and age groups concerning the match scores. In the formation phase of the technique, considerations of high- and low-intensity actions, and analysis of the speed of athletes during matches in official competitions can help to better understand the dynamics of the variability of movements in judo matches. In addition, suggestions are presented to be applied to athletes in different age categories who are on the way to become Olympic athletes.

Nurses have experienced several psychological and work-related issues during the COVID-19 pandemic including pandemic burnout and job burnout. The aim of the study was to examine the impact of social support and resilience on COVID-19 pandemic burnout and job burnout among nurses. We conducted a cross-sectional study in Greece. Study population included 963 nurses. We measured social support, resilience, COVID-19 pandemic burnout, and job burnout with the Multidimensional Scale of Perceived Social Support, Brief Resilience Scale, COVID-19 burnout scale, and single item burnout measure respectively. Nurses received high levels of social support, while their resilience was moderate. Additionally, nurses experienced moderate levels of COVID-19 burnout and job burnout. Increased social support (adjusted beta = -0.075, 95% CI = -0.125 to -0.024) and increased resilience (adjusted beta = -0.399, 95% CI = -0.491 to -0.308) were associated with reduced COVID-19 pandemic burnout. We found a negative relationship between social support and job burnout (adjusted beta = -0.263, 95% CI = -0.405 to -0.121). A similar negative relationship was found between resilience and job burnout (adjusted beta = -0.529, 95% CI = -0.785 to -0.272). Social support and resilience can act as protective factors against COVID-19 pandemic burnout and job burnout among nurses. Policy makers should develop and implement appropriate strategies to improve nurses’ social support and resilience since they are the backbone of healthcare systems worldwide.

Purpose: This study analysed the impact of the COVID-19 pandemic on the diagnosis of malignant neoplasia of the bronchus and lung. Cases diagnosed in the Burgos region in the year prior to the official declaration of the pandemic were compared with those in the year after the pandemic. The research sought to identify whether there was a decrease in the number of cases during the pandemic, and whether this may have led to a delay in diagnosis, reflected in more advanced stages of the disease. Mortality and survival time in each of the periods were also analysed.

Aims: The study aims to take the COVID-19 pandemic as an example to provide a scientific reference for diabetic patients’ self-health management and nurses’ work for these patients when facing future pandemics. Review Methods: It conducted a comprehensive literature search and analysed relevant texts. This article reviews the daily health management of diabetic patients in the context of the COVID-19 pandemic and the role that nurses should play in this process. Results: Diabetic patients face challenges in self-health management during the pandemic, including disruptions in healthcare access, increased mental problems, and unhealthy lifestyles. Nurses serve as the front-line interface between these patients and the healthcare system. Adopting telehealth and remote consultation has effectively bridged the gap created by social distancing measures. Conclusion: Daily self-health management can significantly improve glycemic control and reduce the risk of diabetes-related complications, which is vital during the pandemic when patients may be experiencing disruptions to their routine care. Moreover, empowering patients through educational initiatives led by nurses can bring better self-monitoring, medication adherence, and lifestyle modifications, all of which are crucial in mitigating the effects of diabetes on the body’s immune response, thus reducing the severity of COVID-19 if contracted.

The COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS- CoV-2) infection has required a complete change in the management of patients with gastrointestinal disease who needed to undergo endoscopic procedures. In the second year of the COVID-19 pandemic, due to restrictions for elective endoscopic procedures a large number of cancer patients were prevented from early diagnosis of several digestive cancers, which has led to a serious burden in the health system which nowadays needs to be dealt with. We designed a prospective study that included patients in whom access to elective endoscopic examinations during the COVID-19 pandemic has been delayed. Our aim was to investigate the impact of the COVID-19 pandemic on the diagnosis rate of digestive tract malignancies in the context of a health crisis management that generates an ethical dilemma regarding the balance of utilitarianism versus deontology. Our study shows that the decrease in the number of newly diagnosed gastrointestinal cancers by endoscopy and biopsy during the pandemic restrictions and the delay in diagnosis have hads a clear impact on stage migration due to disease progression.

Introduction: The viral respiratory disorder known as severe acute respiratory syndrome (SARS) is caused by the SARS-associated coronavirus. End of May 2021, there have been over 170 million reported cases and more than 3.53 million deaths worldwide. In the field of cardiovascular performance, the shock index (SI) is a simple and widely used formula that measures the physiological response prior to systemic hypotension. It is obtained by dividing the heart rate by the systolic blood pressure. Another parameter, the modified shock index (MSI), is defined as the ratio of heart rate to mean arterial pressure (MAP). Methods: In this retrospective study, we examined the data of COVID-19 patients who were admitted to the ICU between June 1st, 2020, and January 31st, 2021. The patient details were collected from the Medical Records Department (MRD) in a tertiary care center. A case-recorded proforma was used to record the patient information, which was then analyzed using SPSS software. Results: The mean age of the patients was 67 years, consisting of 64 males (68.9%) and 29 females (31.1%). The standard deviation was calculated as 13.557. Among the patients, the minimum age recorded was 28, while the maximum age was 97. Patients with known CAD (Coronary Artery Disease) had a higher mortality rate among comorbidities. The p-value for Shock Index and Mortality Status was 0.205 (with an alpha value greater than 0.05), indicating no significant association. However, the modified shock index (MSI) showed a significant association with mortality status. The Pearson chi-square value for MSI and Mortality Status was 4.19, with a p-value of 0.041 (with an alpha value less than 0.05). These results suggest that there is a higher risk of mortality for patients with a Modified Shock Index of less than 0.7 or greater than 1.3. The MSI Odds ratio was found to be 4.500, indicating that such patients have a 4.5 times higher risk of mortality compared to others. Conclusion: In conclusion, our study found that there is no significant association between the Shock Index (SI) and mortality, as the p-value was greater than 0.05. However, the Modified Shock Index (MSI) showed a significant association with mortality status, with a p-value less than 0.05. This suggests that patients with a Modified Shock Index less than 0.7 or greater than 1.3 are at a higher risk of mortality. It is important to consider these findings when assessing the prognosis and potential interventions for COVID-19 patients.

Despite the crucial role the COVID-19 vaccine played in curbing the pandemic, a significant portion of Black and African American individuals expressed hesitancy in being vaccinated. This review aimed to identify the determinants of COVID-19 vaccine hesitancy among Black and African American individuals in the USA. The literature search was conducted in December 2022 according to the PRISMA criteria focusing on empirical studies. Data extraction methods, critical appraisal, and secondary thematic analysis were conducted on both quantitative and qualitative studies. Sixteen quantitative studies identified key factors associated with vaccine hesitancy such as confidence in vaccine effectiveness, safety, and trust in the healthcare system. 14 qualitative studies revealed major themes of mistrust, fear, and information needs, including historical mistrust, concerns about the vaccine development process, and contemporary institutional mistrust. The synthesis of quantitative and qualitative findings derived from this review provides a nuanced understanding of determinants of vaccine hesitancy in Black and African American communities in the USA, offering a foundation for the development of evidence-based interventions. Mistrust in the healthcare system, fear, and informational gaps on vaccine safety and effectiveness have been identified as significant barriers to vaccination, demanding targeted interventions.

We assessed the association between cirrhosis and severe COVID-19-related outcomes among people with laboratory-diagnosed COVID-19 infection in British Columbia, Canada. We used data from the British Columbia (BC) COVID-19 Cohort, a population-based cohort that integrates data on all individuals tested for COVID-19 with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions, and deaths in the Canadian province of BC. We included all individuals, aged ≥ 18 who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction, from January 01, 2021, to December 31, 2021. Multivariable logistic regression models were used to assess the associations between cirrhosis status and COVID-19-related hospitalization and ICU admission. Of the 162,509 individuals who tested positive for SARS-CoV-2 and were included in the analysis, 768 (0.5%) had cirrhosis. In the multivariable models, cirrhosis was associated with increased odds of hospitalization (aOR=1.97, 95% CI: 1.58 – 2.47) and ICU admission (aOR=3.33, 95% CI: 2.56 – 4.35). In the analyses stratified by age, we found that the increased odds of ICU admission among people with cirrhosis were present in all the assessed age-groups. Cirrhosis is associated with increased odds of hospitalization and ICU admission among COVID-19 patients.

The aim of this study was to analyze the profile of IgG subclasses in COVID-19 convalescent Puerto Rican subjects and compare this profile with those exhibited by no-infected immunocompetent or immunocompromised subjects that received the mRNA vaccine. The most notable find-ngs from this study are: 1) Convalescent subjects that were not hospitalized developed high and long-lasting antibody response. 2) Both, IgG1 and IgG3 are the subclasses more prevalent in the SARS-CoV-2 infected population whereas IgG1 is more prevalent after vaccination. 3) Individuals that first had the infection and further received two doses of mRNA vaccines exhibited more robust neutralizing capacity against Omicron than those that were never infected and received two doses of Pfizer-BioNTech vaccine. 4) A class switch toward the “anti-inflammatory” anti-body isotype IgG4 is induced a few weeks after the third dose, which peaked abruptly and remained at high levels for a long period. Moreover, the high levels of IgG4 are concurrent with high neutralizing percentages against various VOC including Omicron. 5) Subjects with IBD also develop IgG4 after the third dose, although these antibody levels have limited effect on the neutralizing capacity. Knowing that the mRNA vaccines do not prevent reinfections, all Omicron sub-variants that are dominant worldwide have shown to be less pathogenic, and the IgG4 levels have been associated to immunotolerance and causative of numerous negative effects, the recommendations of successive administration of booster vaccinations to people should be revised.

The rapid emergence of COVID-19 necessitated policy responses worldwide, focusing on vaccination and mobility restrictions. However, studies on individual non-pharmacological preventive measures are less common. In particular, Chile represents a unique scenario for analyzing the adoption of preventive measures and changes amid aggressive communication and vaccination campaigns. This study aims to provide insights into public adherence to non-pharmacological measures in the face of diseases, using a cohort of 386 participants from 2021 to 2022. This was achieved by employing a questionnaire to measure adherence to self-care practices and by analyzing contact tracing data from health authorities. We performed bivariate analysis and a linear regression model. Mask-wearing in public places was the most commonly used measure (95.9% in 2021 and 89.9% in 2022). The median adherence score increased from 18 to 19 for both measurements, respectively. The regression model shows that women are more likely to adopt preventive behaviors in both waves and being a young adult (30-49 years) predicted the adoption of behavioral precautions in 2022. Adherence to preventive measures increased even with high vaccination coverage, likely due to the epidemiological situation with the Omicron variant circulating in 2022.

The COVID-19 pandemic has raised concerns about its impact on maternal and neonatal health. This study aimed to investigate the influence of maternal COVID-19 infection during pregnancy on neonatal inflammatory parameters. A retrospective cohort study was conducted at Premiere Hospital in Timisoara between May 2021 and January 2022. Participants were categorized into two groups: the COVID-19 positive group, consisting of patients with confirmed SARS-CoV-2 in-fection during pregnancy, and the control group, which comprised COVID-19-free pregnant women. The primary outcome was the assessment of inflammatory markers (NLR, dNLR, PLR, and SII) in neonates born to mothers with COVID-19. The results suggest that maternal COVID-19 infection during pregnancy significantly impacts certain neonatal inflammatory parameters. Spe-cifically, newborns exposed to maternal COVID-19 exhibited elevated white blood cell counts, particularly when infection occurred during the first trimester. Lymphocyte counts were dimin-ished in neonates born to COVID-19-positive mothers, irrespective of infection trimester. Gesta-tional age played a role in altering neonatal immune profiles, with correlations observed between GA and parameters in the Control Group (COVID-19 negative during pregnancy). However, the influence of neonatal immunoreactivity on laboratory parameters remained generally non-significant after adjusting for GA and infection trimester. In conclusion, maternal COVID-19 infection during pregnancy has a discernible impact on neonatal inflammatory parameters, in-cluding WBC and lymphocyte counts, which may have clinical implications.

The teaching and learning environment have changed significantly over the last decade with the integration of an increasing amount of information and communication technologies, especially in distance education due to global pandemics, total lockdowns, isolation, and quarantine periods. The number of numerous virtual and non-virtual tools involved in educational processes is growing day by day. In terms of technological innovations used in learning environments, many researchers and educators are trying their best to bring more creative ideas into the technology- based learning environments. Although higher educational institutions have greatly benefited from the growing number of hardware and software resources in the educational process, they have also faced some setbacks that have harmed the learning processes. These technologies have in turn complicated some of the processes in the learning atmosphere. Therefore, we take Spanish teaching course as an example to present the challenging smarter teaching and learning systems that higher educational institutions face today.

his quantitative study investigates teachers' perceptions of self-efficacy during the COVID-19 pandemic and explores the correlation between these perceptions and the preservice training they received. The research addresses the cognitive connection between teachers' current self-efficacy, particularly their satisfaction with and appreciation of preservice lecturers. Utilizing a retrospective lens, the study reveals a significant correlation between teachers' evaluation of their preservice training, especially their appreciation of lecturers, and their present self-efficacy. The findings highlight that teachers, amidst the challenges of the pandemic, evaluated their self-efficacy at a remarkably high level. This underscores their resilience during a period of unprecedented uncertainty, demanding substantial personal and professional adaptability. The nuanced interplay observed suggests that teachers' sense of self-efficacy serves as a predictive variable of their mental and professional resilience when confronting uncertainty and navigating rapid and profound changes, as exemplified by the exigencies of the COVID-19 pandemic.

The SARS-CoV-2 have caused a devastating pandemic of all times in the recent human history. However, there is a serious paucity in high quality data on aggravating factors and mechanisms of co-infection. This study aimed to identify the trending patterns of bacterial co-infections and types and associated outcomes in three phases of the pandemic. Using quality hospital data, we have investigated the SARS-CoV-2 fatality rates, profiles, and types of bacterial co-infections before, during, and after COVID-19 vaccinations. Out of 389 isolates used in different aspects, 298 was examined before and during the pandemic (n=149 before, n=149 during), death rates were 32% during compared to only 7.4% before pandemic with significant association (P value = 0.000000075). Death rate was 34% in co-infected (n = 170) compared to non-co-infected patients (n = 128) indicating a highly significant value (P value = 0.00000000000088). However, analysis of patients without other respiratory problems (n=28) indicated that among the remaining 270 patients, death was 30% in co-infected patients (n=150) and only 0.8% in non-coinfected (n=120) with high significant P value= 0.00000000076. The trending patterns of co-infections before, during, and after vaccinations showed a significant decline in Staphylococcus aureus with concomitant peaks in Gram-negatives in totals of (n= 149 before/n= 149 during): Klebsiella pneumonia (n = 11/49 before/during; E. coli n=10/24, A. baumannii n=8/25, and Ps. Aeruginosa n= 5/16, and S. aureus 13/1. Nevertheless, in post vaccination phase, (n= 91) gender-specific co-infections were examined for potential differences in susceptibility. Methicillin resistant S. aureus (MRSA) dominated both genders followed by E. coli in males and females with the latter gender showing higher rates of isolations in both species. Klebsiella pneumoniae declined to third place mostly in male patients. The drastic decline in K. pneumoniae and Gram-negatives post-vaccination strongly imply a potential co-protection in vaccines. Future analysis would gain more insights into molecular mimicry.

Severe cases of SARS-CoV-2 infection are characterized by an immune response that leads to the overproduction of pro-inflammatory cytokines, resulting in damage to the lungs and other organs. This remarkable increase in cytokines and other inflammatory molecules is primary caused by viral proteins, in particular ORF8, a unique accessory protein specific to SARS-CoV-2. In addition to its role in cytokine induction, ORF8 is attributed with various other functions, including its ability to evade type I interferon responses. Despite the evidence, the mechanisms through which ORF8 exerts these functions remains a subject of controversy. In this mini review, we discuss the multifaceted roles of ORF8 as a modulator of cytokine response, focusing on type I interferon and IL-6. We also discuss data from our studies indicating that ORF8 augments production of IL-6 induced by Poly(I:C) in human embryonic kidney (HEK)-293 and monocyte-derived dendritic cells (mono-DCs).

The COVID-19 pandemic has had a substantial impact on global health, notably the virus's association with autoimmune illnesses. Autoimmune illnesses occur when the immune system of the body targets healthy cells, causing damage and inflammation. The potential impact of COVID-19 on autoimmune disorders, the hazards of COVID-19 vaccinations for persons with autoimmune diseases, and the potential risks of COVID-19 vaccines are all discussed in this essay. COVID-19 can cause autoimmune illnesses by causing inflammation, organ and tissue damage, and molecular mimicry, in which the immune system mistakenly assaults healthy cells for the virus. However, not everyone infected with COVID-19 develops autoimmune disorders. While some research has found a link between COVID-19 and autoimmune illnesses, this does not always suggest causation. Other factors, such as genetics and environment, may also play a role in the emergence of autoimmune illnesses. COVID-19 can aggravate existing autoimmune disorders by causing the immune system to attack healthy cells, making management more difficult and increasing the risk of consequences. People with autoimmune disorders, on the other hand, may not be at a higher risk of severe COVID-19 than the general population. Some research has found that persons with autoimmune disorders are more likely to have severe COVID-19, whereas others have found no difference. COVID-19 vaccinations may represent dangers to persons with autoimmune illnesses since they contain antigens that can activate the immune system. Furthermore, due to their already overactive immune systems, some vaccines may not perform as well for people with autoimmune disorders, and some people with autoimmune diseases may have severe reactions to immunizations, producing inflammation and other symptoms. COVID-19 may not be any more hazardous to those with autoimmune illnesses than it is to the general population. The connection between COVID-19 and autoimmune disorders is complicated and under investigation. While some research implies that people with autoimmune disorders have a higher risk of severe COVID-19, others demonstrate no difference in death rates between them and the general population. There are also counterarguments that COVID-19 can induce and exacerbate autoimmune disorders, as well as worries about COVID-19 vaccine hazards for people who have autoimmune diseases. More research is required to completely understand the influence of COVID-19 on autoimmune illnesses, as well as the dangers and benefits of vaccinations for these people.

The COVID-19 pandemic caused by the virus SARS-CoV-2 has been the greatest global threat to human health in the last three years. The most widely used methodologies for the diagnosis of COVID-19 are quantitative reverse transcription polymerase chain reaction (RT-qPCR), used to detect the viral genome, and rapid antigen tests (RATs), also known as lateral flow tests, that employ specific antibodies to detect the viral spike protein. While PCR is considered the gold standard test in terms of specificity and sensitivity, it is time-consuming and requires specialized instrumentation operated by skilled personnel. In contrast, RATs can be used in-home or at point-of care but are less sensitive leading to a higher rate of false negative results. An alternative methodology for the detection of virus is the use of electrochemical biosensors that employ disposable strip electrodes to which binding of viral components elicits a change in electrical signal. Laser-scribed graphene (LSG) electrodes are attractive candidates for use as biosensors electrodes suitable for SARS-COV-2 detection due to their low-cost, patternability and ease of fabrication. In this work, we describe the development of a biosensor for COVID-19 detection that exploits a split-ester bond ligase system (termed ‘EsterLigase’) for immobilization of a virus-specific nanobody to maintain the out-of-plane orientation of the probe to ensure the efficacy of the probe-target recognition process. An anti-spike VHH E nanobody, genetically fused with the EsterLigase domain, was used as the specific probe for the spike receptor-binding domain (SP-RBD) protein as the target. The recognition between the two was measured by the change in the charge transfer resistance, determined by fitting the electrochemical impedance spectroscopy (EIS) spectra. The developed LSG-based biosensor achieved a linear detection range for the SP-RBD from 15 pM to 150 nM with a sensitivity of 0.0866 [log(M)]-1 and a limit of detection (LOD) of 7.68 pM.

AbstractBackground: The World Health Organization (WHO) said the situation in India was a "devastating reminder" of what the coronavirus could do. COVID-19 cases suddenly spiked across India. Union Health Minister Harsh Vardhan has said that one of the major reasons for the spike in coronavirus cases was people not following COVID-appropriate behaviour. The Union minister noted that the sudden rise in cases is largely or maybe event-driven comprising local body elections, grand weddings, and farmers' protest. These events may cause asymptomatic covid-19 carriers to spread wide covid-19 to others. Malaysia is also facing a surge in Covid-19 may due to the spread of covid-19 by asymptomatic covid-19 carriers. Therefore, it is important to develop an application that can publicize information on asymptomatic covid-19 carriers. The purpose of this application is to provide sufficient information and scientific research evidence to ensure that prevention strategies for asymptomatic covid-19 carriers must be implemented. The app is also open to anyone who uses it to educate others so that information can be shared more quickly to prevent other countries from becoming "Second India or Malaysia".Method: The homepage of the app shows that asymptomatic covid-19 carriers may have a lower viral load, the same viral load, or a higher viral load than symptomatic covid-19 carriers. When the user app is pressed by each category, they will see sufficient information and scientifically based research evidence about each category. These apps also show the evidence that on January 13, 2021 - Malaysian Health Department Director Dr Noor Hisham Abdullah instructs test Only those Close Contacts With Symptoms and The Malaysian Medical Association (MMA) has urged the Health Ministry to urgently improve the management of mild Covid-19 cases and revert to its policy of testing all close contacts. In addition, These apps also show App raise public awareness of the importance of COVID-19 vaccination(version 4) [Peter Chew, 2021] can intuitively see that countries with high vaccination rates can solve the problem of asymptomatic transmission of covid-19 carriers.Result: This application displays sufficient information and scientifically based research evidence to prove asymptomatic covid-19 carriers are the main key to the outbreak of covid-19. Some countries are using covid-19 symptom prevention strategies. They are only testing the symptomatic closed contact of covid-19 patients, because they may think that asymptomatic covid-19 carrier is just a low viral load and a low transmission rate, which is wrong. Some asymptomatic covid-19 carriers of covid-19 have high viral loads. The accumulation of asymptomatic covid-19 carriers with high viral load is the main cause of the covid-19 outbreak. Conclusion: Three apps have been developed to educate the public about the importance of asymptomatic covid-19 carriers. The asymptomatic covid-19 carrier education app (1) will provide sufficient information and scientific research evidence to educate citizens of any country to ensure that preventive strategies must be implemented for asymptomatic carriers to prevent the country’s Covid-19 outbreak. App, Game Base Learning to Prevent Infection from COVID-19 (version 3) [Peter Chew, 2020 ]. The app allows anyone to intuitively see that when the second wave covid-19 arrives, the accumulation of a large number of asymptomatic carriers in some countries has led to the high infection rate of covid-19. This is what is happening in India now. App raise public awareness of the importance of COVID-19 vaccination(version 4) can intuitively see that countries with high vaccination rates can solve the problem of asymptomatic transmission of covid-19 carriers. This is what is happening in Israel now.

The study aimed to evaluate the after-effects of the COVID-19 pandemic on the sleep quality and patterns of women across different cultural settings within Iraq, spanning the period of 2022. A cross-sectional survey was administered to a diverse cohort of women from multiple provinces in Iraq. The survey measured various parameters, including sleep duration, onset latency, and disturbances. The post-pandemic period has seen a notable decline in sleep quality among the female population. Contributing factors include psychological stress, lifestyle changes due to the pandemic, and ongoing socio-economic challenges. The impact on sleep quality exhibited variation across different cultural groups, indicating a significant cultural influence on the pandemic's psychological aftermath. The study concludes that the post-pandemic phase has adversely affected the sleep health of women in Iraq, with cultural factors playing a critical role in these changes. There is a pressing need for culturally sensitive public health strategies to address sleep disturbances and mitigate their long-term effects on women's health. Public health initiatives should be tailored to address the specific cultural contexts within Iraq to improve sleep health among women. Further research is warranted to explore the long-term consequences of disturbed sleep patterns and the effectiveness of different intervention strategies.

Laboratory analyses reveal significant differences between vaccinated and unvaccinated patients in parameters like C-reactive protein, ferritin, and white blood cell counts. Univariate and multivariate Cox proportional hazards regression analyses identify several factors influencing mortality, including comorbidities, pneumonia development, and various inflammatory markers.