SARS-CoV-2 mRNA vaccination can entail chronic fatigue/dis-autonomy tentatively termed post-acute COVID-19 vaccination syndrome (PACVS). We explored receptor autoantibodies and interleukin-6 (IL-6) as somatic correlates of PACVS. Blood markers determined before and six months after first-time SARS-CoV-2-vaccination of healthy controls (N = 89, 71 females, mean/ median age 39/ 49 years) were compared with corresponding values of PACVS-affected persons (N= 191, 159 females, mean/median age: 40/39 years) exhibiting chronic fatigue/dis-autonomy (≥ three symptoms for ≥ five months after last SARS-CoV-2 mRNA vaccination) not due to SARS-CoV-2 infection and/or confounding diseases/medications. Normal vaccination response encompassed decreases of 11 receptor-antibodies (by 25 - 50 %, p < 0.0001), increases in two receptor-antibodies (by 15 - 25 %, p < 0.0001) and normal IL-6. In PACVS, serological vaccination-response appeared significantly (p < 0.0001) altered, allowing discrimination from normal post-vaccination state (sensitivity = 90%, p &lt; 0.0001) by increased angiotensin II type 1 receptor antibodies (cut-off ≤ 10.7 U/ml, ROC-AUC = 0.824 ± 0.027), decreased alpha-2B adrenergic receptor antibodies (cut-off ≥ 25.2 U/ml, ROC-AUC = 0.828 ± 0.025) and increased IL-6 (cut-off ≤ 2.3 pg/ml, ROC-AUC = 0.850 ± 0.022). PACVS is thus indicated as a somatic syndrome delineated/detectable by diagnostic blood markers

The work presented in this paper presents several novel findings from a comprehensive analysis of about 50,000 Tweets about online learning during COVID-19, posted on Twitter between November 9, 2021, and July 13, 2022. First, the results of sentiment analysis from VADER, Afinn, and TextBlob show that a higher percentage of these tweets were positive. The results of gender-specific sentiment analysis indicate that for positive tweets, negative tweets, and neutral tweets, between males and females, males posted a higher percentage of the tweets. Second, the results from subjectivity analysis show that the percentage of least opinionated, neutral opinionated, and highly opinionated tweets were 56.568%, 30.898%, and 12.534%, respectively. The gender-specific results for subjectivity analysis indicate that for each subjectivity class, males posted a higher percentage of tweets as compared to females. Third, toxicity detection was performed on the tweets to detect different categories of toxic content - toxicity, obscene, identity attack, insult, threat, and sexually explicit. The gender-specific analysis of the percentage of tweets posted by each gender in each of these categories revealed several novel insights. For instance, for the sexually explicit category, females posted a higher percentage of tweets as compared to males. Fourth, gender-specific tweeting patterns for each of these categories of toxic content were analyzed to understand the trends of the same. The results unraveled multiple paradigms of tweeting behavior, for instance, the intensity of obscene content in tweets about online learning by males and females has decreased since May 2022. Fifth, the average activity of males and females per month was calculated. The findings indicate that the average activity of females has been higher in all months as compared to males other than March 2022. Finally, country-specific tweeting patterns of males and females were also performed which presented multiple novel insights, for instance, in India a higher percentage of the tweets about online learning during COVID-19 were posted by males as compared to females.

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

The Covid-19 pandemic and the subsequent implementation of lockdown measures have significantly impacted global electricity consumption, necessitating accurate energy consumption forecasts for optimal energy generation and distribution during a pandemic. In this study, we propose a new forecasting model called the Multivariate Multilayered LSTM with Covid-19 case injection ($\proposedModel$) for improved energy forecast during the next occurrence of a similar pandemic. We utilize data from commercial buildings in Melbourne, Australia during the Covid-19 pandemic to predict energy consumption and evaluate the model's performance against commonly used methods such as LSTM, Bi-LSTM, Linear Regression, Support Vector Machine and the previously published work of Multilayered LSTM (M-LSTM). The proposed forecasting model was analyzed using the following metrics of mean percent absolute error (MPAE), normalized root mean square error (NRMSE), and $R^2$ score values. The model $\proposedModel$ demonstrates superior performance, achieving the lowest MPAE values of 0.061, 0.093, and 0.158 for data sets from 3 different buildings, respectively. Our results highlight the improved precision and accuracy of the model, providing valuable information for energy management and decision-making during the challenges posed by the occurrence of a pandemic like Covid-19 in the future.

Despite concerns about the negative effects of social distancing and prolonged school closures on children’s lifestyle and physical activity (PA) during the COVID-19 pandemic, robust evidence is lacking on the impact of the COVID-19 pandemic on children’s wellbeing and daily life. This study aimed to examine changes in the PA levels, sleep patterns and screen time of school-aged children during the different phases of COVID-19 outbreak in Hong Kong using a repeated cross-sectional design. School students (Grades 1 to 12) were asked to report their daily electronic device usage and to fill in a sleep dairy recording their daily sleep and wake-up time. They were equipped with a PA monitor, Actigraph wGT3X-BT, to obtain objective data on their PA levels and sleep patterns. Students were recruited before the pandemic (Sep 2019 – Jan 2020; n=577), during school closures (Mar 2020 – Apr 2020; n=146), and after schools partially reopened (Oct 2020 – Jul 2021; n=227). Our results indicated lower PA levels, longer sleep duration, and longer screen time among participants recruited during school closures than those recruited before the COVID-19 outbreak. Primary school students were found to sleep on average for an extra hour during school closures. Our findings illustrate the impact of social distancing policies during the COVID-19 pandemic on the sleep pattern, screen time, and PA level in school-aged children in Hong Kong. Professionals should reinforce the importance of maintaining a physically active lifestyle, good sleep hygiene, and healthy use of electronic devices to parents and school-aged children during the COVID-19 Pandemic.

Background: Online survey-based observational cross-sectional study aimed at elucidating experience and attitudes of unstructured population regarding diagnostic imaging. Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p &lt; .0001), magnetic resonance imaging (MRI) (p &lt; .001), and ultrasound (p &lt; .05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p &lt; .05). Every tenth respondent received MRI, CT, and ultrasound on paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p &lt; .05). MRI and CT availability differed between respondents in urban and rural areas (p &lt; .0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p &lt; .05). Conclusions: Preparedness to future pandemics requires development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

PURPOSE: Our research interrogates Professor Peter Doherty’s warning to Australians in April 2020 that ‘COVID-19 is just as lethal as the Spanish flu’. METHODS: We identified the epicentres of both pandemics, namely metropolitan Sydney in 1919 and metropolitan Melbourne in 2020. Using original sources, we compared the lethality of COVID-19 in these two cities. Lethality was measured by the number and rate of hospitalisations and deaths per 100,000 of population. Using these two measures, we diagnosed the waves of infection, their severity at various points in time and the cumulative impact of the viruses by the end of our in-depth study period, i.e. 30 September in 1919 and 2020. RESULTS: Spanish Flu in 1919 was more than 30 times more lethal than COVID-19 in 2020. The hospital admission and death rates of COVID-19 in Melbourne in 2020 constituted a small fraction of the devastation wrought by the Spanish Flu in Sydney in 1919. The patterns and lethality of the pandemic waves were also strikingly different. DISCUSSION AND CONCLUSION: Both pandemics broke out with the arrival of unknown pathogens against which vaccines and antivirals did not exist. Professor Doherty’s warning was perhaps taken seriously and that partly explains the findings of this study. Containing infection in 1919 and 2020 threw the burden on nonpharmaceutical interventions (NPIs) such as ‘protective sequestration’ (quarantine), contact tracing, lockdowns and masks. We discuss the effectiveness of these. Despite the failures of genomic analysis and the weaknesses of the contact tracing system due to mismanagement, it was persistent and detailed contact tracing that provided the best explanation for why NPIs in 2020 were more effective than in 1919 and therefore contributed to the lower lethality of the COVID-19 pandemic in its first year.

This study aimed to assess the differences in the importance and performance of health awareness in Korean middle school students according to the types of online physical education classes they attended during the coronavirus disease-2019 pandemic. Overall, 583 participants were selected using a convenience sampling method; the data were obtained through an online survey using Google forms. Frequency analysis, reliability analysis, independent sample t-test, and importance-performance analysis were performed. First, the differences between importance and performance were found to be the most for sleep and physical activity management, and the least for disease and hygiene management. In addition, both the groups demonstrated higher importance and performance for hygiene and disease management. There were significant differences in the importance and performance of all the sub-factors. Second, hygiene, disease management, and mental health management were found in quadrant I in both the groups, while physical activity, sleep, and dietary habit management were in quadrant III. No factors were in quadrant II and IV.

Objective: To evaluate the variables influencing the length of stay (LoS) for COVID-19 ICU patients at Tygerberg Hospital (Cape Town) and to identify the covariates that significantly influenced it and any potential risk factors associated with LoS. Methods and Results: Poisson, negative binomial (NB), Hurdle–Poisson, and Hurdle–NB regression models were used to model the LoS in this prospective cohort study. The fitted models were compared using the Akaike information criterion (AIC), Vuong’s test criteria, and Rootograms. Based on the chosen performance criteria, the NB model provided the best fit outperforming other candidate models. The baseline LoS count was 8 days. On average, antibiotics reduced LoS by 0.74-fold (95% CI 0.62-0.89) compared to not taking antibiotics. The second wave had a significant effect on the average LoS, which decreased by 0.36-fold (95% CI 0.14-0.93) compared to the first wave. Average LoS increased by 1.01-fold (95% CI 1.01-1.02) for every one-year increase in the age of the patient and by 1.02-fold (95% CI 1.01-1.03) for every 1 unit increase in neutrophils. A 1 ng/L increase in log (TropT) levels decreased the average LoS by 0.87-fold (95% CI 0.81-0.93) similarly, a unit increase in the PF ratio decreased the average LoS by 0.998-fold (95% CI 0.997-0.999) respectively. Conclusion: The study identified common clinical characteristics associated with length of stay in ICU for COVID-19 patients, including age at admission, PF ratio, neutrophils, TropT, Wave, and antibiotic use. These results can aid in identifying risk factors for increased length of stay, assist in healthcare systems planning, and aid in evaluating different models for analysing this type of data.

Abstract: COVID-19 Long Haulers, an estimated 3% to 12% of people infected globally with coronavirus having latter devasting symptoms 12 weeks after the initial infection is on the rise. We conducted a collaborative study with the long covid patient organization in Greece in order to estimate the prevalence, symptoms and problems that adult long haulers experience and then propose a management plan for these patients. Symptoms were obtained from 208 patients using unstructured qualitative free text entries in an anonymized online questionnaire. The majority of respondents (68.8%) were not hospitalized and had been diagnosed more than six months ago with lingering symptoms (66,8%). Eighteen different symptoms (fatigue, tachycardia, shortness of breath, parosmia etc) were mentioned in both hospitalized and community patients. Interestingly, patients with initial mild symptoms suffer from the same persistent symptoms as those who were hospitalized. Awareness of long covid sequelae seems to be low even among medical doctors. Treatment options incorporating targeted rehabilitation programs are either not available or still excluded from the management plan of long covid patients. Since long COVID is a multi-systemic entity, we propose a holistic interventional approach using a multidisciplinary medical team in order to securely and effectively diagnose and treat these specific patients. Academic and medical community must collaborate with long covid patients’ organizations so as to provide personalized medicine.

Vaccines decrease morbidity and mortality. Nevertheless, their benefits depend on public response. During COVID-19, vaccine hesitancy and refusal were rampant, threatening public health. A thorough understand-ing of opponents' arguments is required to address the diffusion of unreliable information on social media and prevent vaccine hesitancy from developing into vaccine refusal. Accordingly, the article examines vac-cine opponents' justifications on social media. Textual content analysis of reader comments on three health-related Israeli Facebook pages was conducted. Data collection encompassed the Israeli COVID-19 vaccination period from October 2020 to May 2022. The comments were analyzed according to the health beliefs model (HBM). We found that vaccine opponents were characterized by low perceptions of the severity of the disease combined with high perceptions of the damages of the vaccine; low perceived benefits of vac-cine compliance; vaccine hesitancy and fear along with public distrust as barriers to change; and call for ac-tion to resist the vaccine and spread related anti-establishment views on the web. As vaccination hesitancy was found to develop into public distrust in the state systems and escalate into conspiracy beliefs and an-ti-vaccination activism, its early detection may prevent future vaccine resistance.

Since its emergence, COVID-19 has caused a great impact in health and social terms. Governments and health authorities have attempted to minimize this impact by enforcing different mandates. Recent studies have addressed the relationship between various socioeconomic variables and compliance level to these interventions. However, little attention has been paid to what constitutes people's response and whether people behave differently when faced with different interventions. Data collected from different sources show very significant regional differences across the United States. In this paper, we attempted to shed light on the fact that a response may be different depending on the health system capacity and each individuals’ social status. For that, we analyzed the correlation between different societal variables (i.e. education, income levels, population density, etc.) along with healthcare capacity related variables (i.e. hospital occupancy rates, percentage of essential workers, etc.) with regards to people's level of compliance with three main governmental mandates in the United States: mobility restrictions, mask adoption, and vaccine participation. Our aim was to isolate the most influential variables impacting behavior in response to these policies. We found that there was a strong relationship between individuals' educational levels and political preferences with respect to compliance with each of these mandates.

Background: The mortality and severity in COVID-19 is increased in patients with comorbidities. The aim of this study was to evaluate the unknown risk of severity and mortality in COVID-19 patients with underlying kidney and liver diseases. Method: We retrieved data on the clinical features and primary composite end point of COVID-19 patients released from inception till 16^th of April 2020 from Medline and Embase. The data on two comorbidities, liver diseases and chronic kidney disease, present in COVID-19 were pooled and statistically analysed to explain the associated severity and mortality rate. Results: 142 abstracts were screened, and 41 full articles were then read. In total, 22 studies including 5595 COVID-19 patients were included in this study with case fatality rate of 16%. The prevalence of liver diseases and CKD were 3% (95%CI; 2%-3%) and 1% (95%CI; 1%-2%) respectively. In patients with COVID-19 and underlying liver diseases, 57.33% (43/75) cases were severe with 17.65% mortality. While in CKD patients with COVID-19, 83.93% (47/56) severity and 53.33% (8/15) mortality were reported. Conclusion: This study found an increased risk of severity and mortality in COVID-19 patients with liver diseases and CKD. This will allow for better clinical management and inform more stringent preventative measures for this group of patients.

All vaccines exhibit both specific and non-specific effects. The specific effects are measured by the efficacy against the target pathogen, while the non-specific effects can be detected by the change in all-cause mortality . All-cause mortality data (gender, age band, vaccination history, month of death) between January 2021 and May 2022 was compiled by the Office for National Statistics. COVID–19 vaccination gave good protection on many occasions but less so for younger ages. Each gender and age group shows its own unique vaccination benefit/disbenefit time profile. Individuals are free to make vaccination decisions. For example, women aged 18-39 show a cohort who do not progress beyond the first or second dose. The all-cause mortality outcomes for the Omicron variant showed a very poor response to vaccination with 70% of sex/age/vaccination stage/month combinations increasing all-cause mortality, probably due to unfavorable antigenic distance between the first-generation vaccines and this variant, and additional non-specific effects. The all-cause mortality outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated, and virus vector appear better than the mRNA vaccines in this specific respect. The latter are seemingly more likely to increase all-cause mortality especially in younger age groups. An extensive discussion/literature review is included to provide potential explanations for the observed unexpected vaccine effects.

Many individuals are wearing face masks improperly at ‘half mask’ and potentially breathing out microbes that can contaminate the air as well as anything below the nose. This note provides the first report that bacteria and fungi breathed out during nasal air exhalation are able to be cultured after landing on blood agar plates. The CFU’s are higher after both 10 breaths and extremely significant for 20 breaths compared to the control plates exposed to the air. Implications of this finding are that going ‘nose commando’ may be able to continue the spread of respiratory diseases such as COVID-19.

Since mid-December of 2019, coronavirus disease 2019 (COVID-19) has been spreading from Wuhan, China. As of February 21, total 75,773 confirmed cases worldwide have spread to more than two dozen countries. Transmission of COVID-19 can occur early in the course of infection since SARS-CoV-2 viral loads in asymptomatic patients are similar to that in the symptomatic patients. Therefore, more sensitive diagnostic methods are needed to detect early phase of the infection to prevent secondary or tertiary spreads. Here, we compare the RT-PCR confirmatory test results using two different SARS-CoV-2 viral RNAs from two Korean COVID-19 confirmed cases.RT-PCR method targeting the RdRP gene, which was recommended by WHO guideline, was less sensitive than targeting N genes (as per CDC guideline). Because many countries follow the WHO guideline, our findings may contribute to the early diagnosis of COVID-19.

Purpose: Acute kidney injury (AKI) is a severe symptom of the 2019 novel coronavirus disease (COVID-19), especially for patients in a critical condition.This study explored the potential mechanism of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on AKI at the single-cell level. Methods: 15 normal human kidney samples were collected and analyzed using single-cell RNA sequencing (scRNA-seq). Subsequently, we analyzed the components and proportions of kidney cells expressing the host cellular receptor ACE2 and the key protease TMPRSSs family, and analyzed the expression differences in Occidental and Asian populations. Results: We drafted the currently available world's largest human kidney cell atlas with 42,589 cells and identified 19 clusters through unsupervised hierarchical clustering analysis. ACE2 and TMPRSSs genes were significantly co-expressed in podocytes and proximal convoluted tubules as potential host cells targeted by SARS-CoV-2. Comparative analysis showed that ACE2 expression in kidney cells was no less than that in the lung, esophagus, small intestine and colon, suggesting that the kidney may be an important target organ for SARS-CoV-2. In addition, given the high expression of ACE2 and kidney disease-related genes in Occidental donors relative to Asian donors, Occidental populations with SARS-CoV-2 infection might be a higher risk of of kidney injury.

The objective of the study was to examine the effects of perceived stress on depression and subsequently to examine the effects of depression on alcohol use disorders. The data were obtained by an electronic questionnaire survey during the coronavirus disease 2019 (COVID-19) pandemic (n=1523 Slovak college students). Descriptive, regression and correlation analysis were used in the analytical processing, while the analyses included students' scores in three diagnostic tools (Perceived Stress Scale (PSS), Patient Health Questionnaire for depression (PHQ 9) and Alcohol Use Disorders Identification Test (AUDIT)), as well as gender and income characteristics. The PSS identified an increased level of perceived stress in female students, in contrast, the AUDIT showed an increased level of alcohol use disorders in male students. Differences in mental and behavioural disorders between the gender and income categories were significant in most of the analysed cases. In terms of gender-income characteristics, it was possible to confirm a significant positive effect of the PSS score on the PHQ 9 score, as well as a significant positive effect of the PHQ 9 score on the AUDIT score. As a result, efforts to reduce stress will be reflected in a reduction of depressive disorders as well as a reduction of excessive alcohol consumption among students.

Nebulized thrombolysis offers locally targeted therapy with potentially lower bleeding risk than systemic administration for coronavirus disease 2019 (COVID-19) respiratory failure. In a proof-of-concept safety study, adult patients with COVID-19-induced respiratory failure and a <300mmHg PaO2/FiO2 (P/F) ratio, requiring invasive mechanical ventilation (IMV) or non-invasive respiratory support (NIRS) received nebulized rt-PA in two cohorts (C1 and C2), alongside standard of care during the first two UK COVID-19 waves. Matched historical controls (MHC; n=18) were used in C1. Safety co-primary endpoints were treatment-related bleeds and fibrinogen reduction to <1.0–1.5 g/L. A dose escalation strategy for improved efficacy with the least safety concerns was determined in C1 for use in C2; patients were stratified by ventilation type to receive 40–60 mg rt-PA per day for ≤14 days. Nine patients in C1 (IMV, 6/9; NIRS, 3/9) and 26 in C2 (IMV, 12/26; NIRS, 14/26) received nebulized rt-PA for a mean (SD) of 6.7 (4.6) and 9.1(4.6) days, respectively. Four bleeding events (one severe and three mild) in three patients were considered treatment-related. No significant fibrinogen reductions were reported. Greater improvement in mean P/F ratio from baseline to end of study was observed in C1 compared with MHC [C1; 154 to 299 vs MHC; 154 to 212). In C2, there was no difference in the baseline P/F ratio of NIRS and IMV patients. However, a larger improvement in P/F ratio was observed in NIRS patients [NIRS; 126 to 240 vs IMV; 120 to 188) and they required fewer treatment days (NIRS; 7.86 vs IMV; 10.5). Nebulized rt-PA appears to be well-tolerated, showing a trend of improved oxygenation and faster recovery in patients with acute COVID-19-induced respiratory failure requiring respiratory support; this effect was more pronounced in the NIRS group. Further investigation is required to study the potential of this novel treatment approach.

Researchers have reported various impacts of the COVID-19 outbreak on small-scale fishers, such as stagnating market demands, reduction of market price and income, etc. While literature have heeded to these impacts in a relatively short time frame, scant evidence exists on the changing impacts over time and on the detailed processes of how fishers have been coping with the challenges in a longer time period. Furthermore, few studies have comprehensively analysed the impacts and strategies from multiple perspectives. This study aims to explore the perceived impacts of the COVID-19 outbreak on small-scale fishing communities and to highlight the coping strategies adopted by fishers over a year since the initial outbreak, through a case study in Trang Province, Thailand. Analysis of both qualitative and quantitative data obtained through semi-structured interviews indicated that fishers wisely utilised natural, financial and social capitals at the early stages of the outbreak, while human capitals were essential for recovering from the impacts in the later stages. Our findings suggest that the adaptive capacity to flexibly change livelihood strategies are crucial, while alternative income source may not necessarily help small-scale fishers under stagnating global economy.

Background: To investigate the effects of the COVID-19 lockdowns on the vasculopathic population. Methods: The Divisions of Vascular Surgery of the southern Italian peninsula joined this multicenter retrospective study conducted through cross-sectional survey. Each received a 13-point questionnaire, investigating the hospitalization rate of vascular patients in the first 11 months of the COVID-19 pandemic and in the preceding 11 months. Results: 27 out of 29 Centers were enrolled. April-December 2020 (7092 patients) vs 2019 (9161 patients): post-EVAR surveillance, treatment for Rutherford category 3 peripheral arterial disease, and asymptomatic carotid stenosis revascularization significantly decreased [1484 (16.2%) vs 1014 (14.3%), p=0.0009; 1401 (15.29%) vs 959 (13.52%), p=0.0006; and 1558 (17.01%) vs 934 (13.17%), p<0.0001, respectively]; while revascularization or major amputations for chronic limb-threatening ischemia, and urgent revascularization for symptomatic carotid stenosis significantly increased [1204 (16.98%) vs 1245 (13.59%), p<0.0001; 355 (5.01%) vs 358 (3.91%), p=0.0007; and 153 (2.16%) vs 140 (1.53%), p=0.0009, respectively]. Conclusions: The suspension of elective activities during the COVID-19 pandemic caused a significant reduction in asymptomatic carotid stenosis revascularization, treatment for Rutherford 3 peripheral arterial disease, post-EVAR surveillance. Contestually, we observed a significant increase in urgent revascularization for symptomatic carotid stenosis, and revascularization or major amputations for chronic limb-threatening ischemia.

This study aimed to determine whether the EQ-5D-5L tool captures the most common persistent symptoms, such as fatigue, memory/concentration problems and dyspnea in patients with post COVID-19 conditions, and if adding these symptoms improves the explained variance of the health-related quality of life (HRQoL). In this exploratory cross-sectional study, two cohorts of Swedish patients (n=177) with a history of COVID-19 infection answeared a questionnaire covering sociodemographic characteristics, clinical factors and HRQoL assessed using EQ-5D-5L with the Visual Analogue Scale (EQ-VAS). Spearman rank correlation and multiple regression analyses were employed to investigate the extent to which the most common persistent symptoms such as fatigue, memory/concentration problems and dyspnea were explained by the EQ-5D-5L. The explanatory power of EQ-5D-5L for EQ-VAS was also analysed, both with and without inclusion of symptom(s). We found that the EQ-5D-5L dimensions partly captured fatigue and memory/concentration problems but performed poorly in capturing dyspnea. Specifically, the EQ-5D-5L explained 55% of the variance in memory/concentration problems, 47% in fatigue and only 14% in dyspnea. Adding fatigue to the EQ-5D-5L increased the explained variance of the EQ-VAS by 5.7%, while the addition of memory/concentration problems and dyspnea had a comparatively smaller impact on the explained variance. Our study highlights the EQ-5D-5L’s strength in capturing fatigue and memory/concentration problems in post COVID-19 patients. However, it also underscores the challenges in assessing dyspnea in this group. Fatigue emerged as a notably influential symptom, significantly enhancing the EQ-5D-5L's predictive ability to for the EQ-VAS score in these patients.

Lutein, a plant-derived xanthophyl-carotenoid, is an exceptional antioxidant and anti-inflammatory constituent found in food. Elevated concentrations of lutein found in human blood and plasma, due to high dietary intake, are beneficial against eye disease and improve cardiometabolic health. Lutein plays an important protective role against the development of neurological disorders, including Alzheimer’s disease (AD), multiple sclerosis (MS) and Parkinson’s disease (PD). It has also been shown to be beneficial for liver, kidney and respiratory health. Lutein, acting as a very strong antioxidant, can alleviate oxidative stress and downgrade reactive oxygen species (ROS). Oxidative stress is one of the key pathogenic mechanisms in post-COVID and mRNA vaccine injury syndromes. Recent in silico studies suggest that lutein and other naturally derived antioxidants, by docking at the site where the SARS-CoV-2 spike protein (SP) binds to the angiotensin enzyme type 2 (ACE2) receptor, may neutralize the SP-ACE2 interactions. Lutein can be added to a detoxification regimen to aid in clearing Spike protein and relieving symptoms. In agreement with Hippocrates’ dictum to “Let food be thy medicine,” this review establishes dietary lutein as a valuable therapy in the treatment of post-COVID syndrome, mRNA vaccine injury syndromes, and a wide range of other chronic illnesses.

The COVID-19 pandemic measures have negatively impacted education worldwide via travel restrictions, student visas, and physical attendanc,e among many other fac-tors. As one of the first places to impose strict pandemic measures and one of the last places to lift the measures, Mainland China provided a unique venue to investigate the effect of public health pandemic control policies on tertiary education. Considering the large portion of international students in medical schools and the higher susceptibility to the pandemic measures due to the natural synergy with teaching hospitals, medical schools can be an early forefront indicator of the impact of the pandemic on tertiary education. We surveyed 513 participants international medical students from Wen-zhou Medical University’s school of international studies in 2019 and 2022 about their satisfaction and demographic and cultural adaptation parameters. We found that the pandemic restrictions did not generally impact student satisfaction. Further analyzing the associated parameters, we found teaching satisfaction to be independent of age (P=.159), years in China (P=.896) and Chinese Level (P=.577) in the medical university. Teaching satisfaction is associated with the region of origin (P <0.001), acceptance of local social norms (P <0.001), satisfaction with the core values of Chinese culture (P <0.001), acclimatization to life in China (P <0.001), can easily make Chinese friends (P <0.001) among other factors. The findings of this study provide an understanding of the effects of pandemic measures on tertiary education satisfaction and other factors that can aid in international student satisfaction.

The coronavirus of severe acute respiratory syndrome 2 (SARS-CoV-2), known as COVID-19, has spread rapidly around the world, leading to social detachment and the home office replacing face-to-face work. The performance of police officers faces limitations to the new requirements, while recognizing the need to ensure health and quality of life. Thus, the present study aimed to verify the panorama of the spread of COVID-19 among federal police officers by analyzing the presence of symptoms, individual protection measures (IPM), suspect screening measures (SSM) and examination for total antibodies (IgA, IgG and IgM). For this, data were collected through a questionnaire customized for this situation, blood for serological testing and measurements of clinical data from 56 federal police officers in the municipality of Marília (São Paulo, Brazil). There was no positive result in the Anti-SARS-CoV-2 serological test in any sample participant. The mean value of the Body Mass Index (27.2 ± 5.4 kg / m2) suggests overweight and obesity, in addition to the presence of hypertension in 16.1%, diabetes in 3.6%, asthma in 3.6 % and obesity by 25%, which represents an important risk of complications for COVID-19. The use of a mask is the most frequent IPM (96.4%) and most of the sample has used a cloth or home mask (90.9%). However, 47.3% have not performed the correct cleaning of the masks and 5.5% have not taken any care with mask hygiene. It can be concluded that care in relation to the professional activities of federal police to date has prevented the spread of SARS-CoV-2 and that they must be maintained or increased because risk factors, which involve quality of life and worsening of the contamination condition, were detected in the participants.

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

Frailty is a common condition in older adults that negatively impacts health and quality of life. This study evaluated a comprehensive, personalized, and coordinated intervention under the Value-Based Care approach to address frailty's multidimensional nature in older people. It em-ployed a pre-post randomized controlled design, involving frail individuals over 65 years in Valencia, Spain. Assessments were conducted at baseline, 12 months (immediately post-intervention), and 18 months. The intervention included a personalized care plan supported by technology, with monthly motivational follow-ups and plan updates by health professionals and participants. Outcomes were measured using an assessment questionnaire that included the International Consortium for Health Outcomes Measurement dataset for the older population: physical health, physical functioning, general mental health, satisfaction with social activities and relationships, ability to carry out usual social roles and activities, pain, general quality of life, loneliness, physical frailty, psychological frailty and social frailty. The study found signifi-cant improvements in physical frailty, quality of life, reduced health resource use and hospitali-zations, and lower levels of pain and depression/anxiety compared to baseline. The findings suggest further research into value-based care approaches, emphasizing the development and activation of personalized, comprehensive programs for older individuals with frailty.

This study focuses on enhancing controllable fibrin-based hydrogels for tissue engineering, addressing existing weaknesses. By integrating a novel copolymer, we improve the foundation for cell-based angiogenesis with adaptable structural features. Tissue engineering often faces challenges like waste disposal and nutrient supply beyond the 200 µm diffusion limit. Angiogenesis breaks through this limitation, allowing the construction of larger constructs. Our innovative scaffold combination significantly boosts angiogenesis, resulting in longer branches and more capillary network junctions. The copolymer attached to fibrin fibers enables precise adjustment of hydrogel mechanical-dynamic properties for specific applications. Our material proves effective for angiogenesis, even under suppression factors like suramin. In our study, we prepared fibrin-based hydrogels with and without the copolymer PVP12400-co-GMA10mol%. Using a co-culture system of human umbilical vein endothelial cells (HUVEC) and mesenchymal stem cells (MSC), we analyzed angiogenetic behavior on and within the modified hydrogels. Capillary-like structures were reproducibly formed on different surfaces, demonstrating the general feasibility of three-dimensional endothelial cell networks in fibrin-based hydrogels. This highlights the biomaterial's suitability for in vitro pre-vascularization of biohybrid implants.

Over the last decade, highly pathogenic avian influenza (HPAI) has severely affected poultry production systems across the globe. In particular, massive pre-emptive depopulation of all poultry within the certain distance has raised concerns regarding animal welfare and food security. Thus, alternative approaches to reducing unnecessary depopulation, such as risk-based depopulation, are highly demanded. This paper proposes a data-driven method to generate a rule table and risk score for each farm to identify preventive measures against HPAI. To evaluate the proposed method, 105 cases of HPAI occurring in a total of 381 farms in Jeollanam-do from 2014 to 2023 were evaluated. The accuracy of preventive measure identification was assessed for each case using both the conventional culling method and the proposed data-driven method. The evaluation showed that the proposed method achieved an accuracy of 84.19%, significantly surpassing the previous 10.37%. The result was attributed to the proposed method reducing the false-positive rate by 83.61% compared with the conventional method, thereby enhancing the reliability of identification. The proposed method is expected to be utilized in selecting farms for monitoring and management of HPAI.

AgW materials exhibit excellent properties and are widely used as contact materials in low- and medium-voltage switches. In this study, a pre-sintering and infiltration method was employed to pre-sinter W powder with Cu, Ni, and (Cu+Ni) addition in the low temperature range of 950–1050 °C. The low-temperature sintering behaviours of W skeletons with different additives were investigated. Subsequently, AgW70, AgW75, AgW80, and AgW85 materials were prepared through infiltration at 1050 °C. The microstructure morphology and physical properties of high-W contact materials were investigated using a metallographic microscope and scanning electron microscope. The mechanism of low-temperature sintering-infiltration of high-W contact materials was elucidated. The results indicated that pure W and 1% Cu-added W skeletons experience minimal linear shrinkage within the temperature range of 950–1050 °C. The linear shrinkage curves of W skeletons with different additives coincided under the conditions of 950–1000 °C/90 min. At 1050 °C, after sintering for 150 min, the particle boundaries in the W skeleton were fully spheroidised, with a dihedral angle of 120°. At 1050 °C and after 150 min of infiltration, cross-sectional micrographs of the AgW material revealed the presence of irregular Ni layers, where Ni spatially enveloped/encapsulated Ag. With an increase in the W content, the electrical conductivity and relative density of AgW(70–85) materials decreased, whereas the hardness of the materials increased.

The disruptive application of ChatGPT (GPT-3.5, GPT-4) to a variety of domains has become a topic of much discussion in the scientific community and society at large. Large Language Models (LLMs), e.g., BERT, Bard, Generative Pre-trained Transformers (GPTs), LLaMA, etc., have the ability to take instructions, or prompts, from users and generate answers and solutions based on very large volumes of text-based training data. This paper assesses the impact and potential impact of ChatGPT on the field of digital forensics, specifically looking at its latest pre-trained LLM, GPT-4. A series of experiments are conducted to assess its capability across several digital forensic use cases including artefact understanding, evidence searching, code generation, anomaly detection, incident response, and education. Across these topics, its strengths and risks are outlined and a number of general conclusions are drawn. Overall this paper concludes that while there are some potential low-risk applications of ChatGPT within digital forensics, many are either unsuitable at present, since the evidence would need to be uploaded to the service, or they require sufficient knowledge of the topic being asked of the tool to identify incorrect assumptions, inaccuracies, and mistakes. However, to an appropriately knowledgeable user, it could act as a useful supporting tool in some circumstances.

Bone metastasis detection and quantification on bone scintigraphy is challenging and clinical important for treatment and patient’s life quality. To develop a CNN based diagnostic system for automated segmentation on bone metastasis regions is non-trivial, especially for a small dataset. A dataset in house comprising 100 breast cancer patients and 100 prostate cancer patients is utilized for this research. The Double U-Net model is adapted through the integration of background removal, adding negative samples, and transfer learning methods for bone metastasis detection. The performance is investigated via 10-fold cross-validation and computed in pixel-wise scale. The best model we achieved has precision of 63.08%, sensitivity of 70.82%, and F1-score of 66.72%. The developed system has the potential to provide pre-diagnostic reports for physicians in final decisions and the calculation of the bone scan index (BSI) with the combination with bone skeleton segmentation.

Parkinson's Disease (PD) is a neurodegenerative disorder that affects the motor system of the human body. Currently, the available treatments are limited and often have undesirable side effects. In this context, the aim of this study was to develop a novel combinational formulation of Apomorphine and Quetiapine and evaluate its efficacy in a rat model of PD. The formulation was prepared using the solvent evaporation technique and characterized for its physicochemical properties. The in-vitro drug release was evaluated using the Franz diffusion cell method, and the pharmacokinetics of the combination was studied in rats. The behavioural and biochemical parameters were evaluated in the rats using the Rotarod, pole test, and biochemical assays. The results showed that the developed formulation had satisfactory physicochemical properties and exhibited sustained drug release. The pharmacokinetic studies showed that the combination exhibited a longer residence time than the individual drugs. The behavioural and biochemical parameters showed that the combination was effective in improving motor function and reducing oxidative stress. In conclusion, the developed Apomorphine and Quetiapine combination formulation showed promising results in improving motor function and reducing oxidative stress in rat model of PD. Further studies are required to evaluate the safety and efficacy of the developed formulation in humans.

Cryptococcosis is one of the most serious opportunistic diseases in patients living with HIV. For this reason, it is important to have early diagnosis and appropriate treatment. Objectives. The aim of the study was to know the evolution of patients diagnosed with cryptococcosis by detection of Cryptococcus antigen in serum by lateral flow (CrAg LFA) without nervous system involvement and with treatment in accordance with the results. Materials and Methods. A retrospective, longitudinal, analytical study was performed. Seventy patients with cryptococcosis initially diagnosed by serum CrAg LFA without meningeal involvement between January 2019 and April 2022 were analyzed for medical records. The treatment regimen was adapted to the results of blood culture, respiratory material or pulmonary tomography imaging. Results. Seventy patients were included, 13 had probable pulmonary cryptococcosis, 4 had proven pulmonary cryptococcosis, 3 had fungemia and 50 had pre-emptive therapy without microbiological or imaging findings compatible with cryptococcosis. Among the 50 patients with pre-emptive therapy, none had meningeal involvement or cryptococcosis recurrences to date. Conclusion. Pre-emptive therapy avoided progression to meningitis in patients with CrAg LFA-positive patients. Pre-emptive therapy with dose adjustment of fluconazole in patients with the mentioned characteristics was useful despite the use of lower doses than recommended.

This research investigates the effect of pre-soaking treatment on plant-based aggregate using a wet grout binder to formulate a high-strength lightweight concrete (HSLWC). The surface modification utilising a novel grout soaking technique with various water-to-cement (w/c) ratios indicated a new method of approach for the recent development of lightweight plant-based aggregate (LWPA). In this experiment, the fresh and hardened properties of modified LWPA lightweight concrete were assessed by verifying their workability, densities, compressive and split tensile strengths towards the modulus of elasticity. The results showed that pre-soaking plant-based lightweight aggregate (w/c: 0.6, 0.8, 1.0, and 1.2) slightly increased the density of the samples compared to untreated LWPA. The oven-dry density of treated and untreated LWPA is controlled in the range of HSLWC. The outcomes indicated that the workability of the surface- modified LWPA has significant improvement up to 40% in 6 min for (TDS)/0.6 sample compared to the original LWPA. The mechanical properties of the LWPA concrete with surface modification method exhibit substantial increment of compressive strength, split tensile strength, and modulus of elasticity were recorded at 22%, 26%, and 34%, respectively. Significantly, the findings from this scientific method revealed that the pre-soaking treatment method on LWPA has shown to be a highly recommended technique in improving interfacial bonding while performing as one of the most promising solutions to improve the properties of lightweight concrete.

The implementation of green roofs as sustainable urban drainage systems provides benefits for stormwater control and the environment and is always more encouraged. In this paper, the estimation of the probability of vegetation survival without irrigation has been proposed as a guide to choose the proper values for the design parameters; in particular the growing medium thickness has been related to the average return interval of the water content at the end of the dry period. Moreover the study represents an improvement of the analytical probabilistic approach since a chain of consecutive rainfall events has been considered, in order to take into account the possibility that the storage capacity is not completely available at the beginning of each event because of the pre-filling from more than one previous rainfall as typically happens for green roofs. Finally, developed equations have been validated by means of their application to two case studies, respectively in northern and southern Italy.

Purpose The gradual increase in geriatric issues and global imbalance of the ratio between patients and healthcare professionals has created a demand for intelligent systems with the least error-prone diagnosis results to be used by less medically trained persons and save clinical time. This paper aims at investigating the development of an image-based colourimetric analysis. The purpose of recognising such tests is to support wider users to begin a colourimetric test to be used at homecare settings, telepathology, etc. Design/methodology/approach The concept of an automatic colourimetric assay detection is delivered by utilising two cases. Training Deep Learning (DL) models on thousands of images of these tests using transfer learning, this paper i) classifies the type of the assay, and ii) classifies the colourimetric results. Findings This paper demonstrated that the assay type can be recognised using DL techniques with 100% accuracy within a fraction of a second. Some of the advantages of the pre-trained model over the calibration-based approach are robustness, readiness and suitability to deploy for similar applications within a shorter period of time. Originality/value To the best of our knowledge, this is the first attempt to provide Colourimetric Assay Type Classification (CATC) using DL. Humans are capable to learn thousands of visual classifications in their life. Object recognition may be a trivial task for humans, due to photometric and geometric variabilities along with the high degree of intra-class variabilities it can be a challenging task for machines. However, transforming visual knowledge into machines, as proposed, can support non-experts to better manage their health and reduce some of the burdens on experts.

Kersting’s groundnut is an important source of protein and essential nutrients that contribute to food security in West Africa. However, the crop is still underexploited by the populations and under-researched by the scientific community. This study aimed to investigate the genetic diversity and population structure of 217 Kersting’s groundnut accessions from five origins using 886 DArTseq markers. Gene diversity was low and ranged from 0.049 to 0.064. The number of private alleles greatly varied among populations (42–192) and morphotypes (40–339). Moderate to very high levels of selfing and inbreeding were observed among populations (s=56–85%, F_IS=0.389–0.736) and morphotypes (s=57–82%, F_IS=0.400–0.691). Moreover, little to very high genetic differentiations were observed among populations (0.006≤F_IS≤0.371) and morphotypes (0.029≤F_IS≤0.307). Analysis of molecular variance partitioned 38.5% of the genetic variation among and 48.7% within populations (P<0.001). Significant isolations by distance were detected between populations (R²=0.612, P=0.011) and accessions (R²=0.499, P<0.001). Discriminant analysis of principal components and neighbour joining consistently distinguished eight distinct clusters. These data provide a global picture of the existing genetic diversity for Kersting’s groundnut and will guide the choice of breeding strategies to increase production.

The zebrafish is now an important model organism for cancer biology studies and provides some unique and complementary opportunities in comparison to the mammalian equivalent. The translucency of zebrafish has allowed in vivo live imaging studies of tumour initiation and progression at the cellular level thus providing novel insights into our understanding of cancer. Here we summarise and discuss available transgenic zebrafish tumour models and what we have gleaned from them with respect to cancer inflammation. In particular, we focus on the host inflammatory response toward transformed cells during the pre-neoplastic stage of tumour development. We discuss features of tumour associated macrophages and neutrophils in mammalian models and present evidence which supports the idea that these inflammatory cells promote early stage tumour development and progression. Direct live imaging of tumour initiation in zebrafish models has shown that the intrinsic inflammation induced by pre-neoplastic cells is tumour promoting. Signals mediating leukocyte recruitment to pre-neoplastic cells in zebrafish correspond to signals mediating leukocyte recruitment in mammalian tumours. The activation state of macrophages and neutrophils recruited to pre-neoplastic cells appears to be heterogenous, as seen in mammalian models, which provides an opportunity to study the plasticity of innate immune cells during tumour initiation. Although several potential mechanisms are described that might mediate the trophic function of innate immune cells during tumour initiation in zebrafish, there are several unknowns that are yet to be resolved. Rapid advancement of genetic tools and imaging technologies for zebrafish will facilitate research into the mechanisms that modulate leukocyte function during tumour initiation and identify targets for cancer prevention.

Calibrating ecological models or making decisions with them is an optimisation problem with challenging methodological issues. Depending on the optimisation formulation, there may be a large variety of optimisation configurations (e.g. multiple objectives, constraints, stochastic criteria) and finding a single acceptable solution may be difficult. The challenges are exacerbated by the high computational cost and the non linear or elusive mathematical properties that increased with the complexity of numerical models. From the feedbacks of practitioners, the need for a guideline for conducting optimisation of complex models has emerged. In this context, we propose a practical guide for the complex model optimisation process, covering both calibration and decision-making. The guide sets out the workflow with recommendations for each step based on existing tools and methods usually scattered throughout the literature. This guide is accompanied with an ODDO template (Overview, Design, Details of Optimisation) to standardise the published description of model-based optimisation and suggests research directions.

Background. We aimed to assess the validity of the Mat-O-Covid Job Exposure Matrix (JEM) on SARS-CoV2 using compensation data from the French National Health Insurance compensation system for occupational-related COVID-19. Methods. Deidentified compensation data for occupational COVID-19 in France were obtained between August 2020 and August 2021. The acceptance was considered as the reference. Mat-O-Covid is an expert based French JEM on workplace exposure to SARS-CoV2. Bivariate and multivariate models were used to study the association between the exposure assessed by Mat-O-Covid and the reference, as well as the Area Under Curves (AUC), sensitivity, specificity, predictive values, and likelihood ratios. Results. In the 1140 cases included, there was a close association between the Mat-O-Covid index and the reference (p&lt;0.0001). The overall predictivity was good, with an AUC of 0.78 and an optimal threshold at 13 per thousand. Using Youden’s J statistic resulted in 0.67 sensitivity and 0.87 specificity. Both positive and negative likelihood ratios were significant: respectively 4.9 [2.4-6.4] and 0.4 [0.3-0.4]. Discussion. It was possible to assess Mat-O-Covid’s validity using data from the national compensation system for occupational COVID-19. Though further studies are needed, Mat-O-Covid exposure assessment appears to be accurate enough to be used in research.

The aim of this study was to build a tool to analyze, using artificial intelligence, the sentiment perception of users who answered two questions from the CSQ – 8 questionnaires with raw Spanish free-text. Their responses are related to mindfulness, which is a novel technique used to control stress and anxiety caused by different factors in daily life. As such, we proposed an online course where this method was applied in order to improve the quality of life of health care professionals in COVID 19 pandemic times. We also carried out an evaluation of the satis-faction level of the participants involved, with a view to establishing strategies to improve fu-ture experiences. To automatically perform this task, we used Natural Language Processing (NLP) models such as swivel embedding, neural networks and transfer learning, so as to classify the inputs into the following 3 categories: negative, neutral and positive. Due to the lim-ited amount of data available - 86 registers for the first and 68 for the second - transfer learning techniques were required. The length of the text had no limit from the user’s standpoint, and our approach attained a maximum accuracy of 93.02 % and 90.53 % respectively based on ground truth labeled by 3 experts. Finally, we proposed a complementary analysis, using com-puter graphic text representation based on word frequency, to help researchers identify relevant information about the opinions with an objective approach to sentiment. The main conclusion drawn from this work is that the application of NLP techniques in small amounts of data using transfer learning is able to obtain enough accuracy in sentiment analysis and text classification stages

Mental health and emotional responses to the effects of COVID-19 lockdown in sub-Saharan Africa (SSA) are of serious public health concern and may negatively affect the mental health status of people. Hence, this study assessed the prevalence of mental health symptoms as well as emotional reactions among sub-Saharan Africans (SSAs) and associated factors among SSAs during the COVID-19 lockdown period. This was a web-based cross-sectional, a study on mental health and emotional features from 2005 respondents in seven SSA countries. This study was conducted between April 27 and May 17, 2020 corresponding to the lockdown period in most SSA countries. Respondents aged 18 years and above and the self-reported symptoms were feeling anxious, being worried, angry, bored and frustrated. These were the main outcomes and were treated as dichotomous variables. Univariate and multivariate logistic regression analyses were used to identify the factors associated with these symptoms. We found that over half (52.2%) of the participants reported any of the mental health symptoms in SSA and the prevalence of feeling bored was 70.5% followed by feeling anxious (59.1%), being worried (57.5%), frustrated (51.5%) and angry (22.3%) during the COVID-19 pandemic. Multivariate analysis revealed that males, those aged >28 years, Central and Southern Africans, those who were not married, the unemployed, those living with more than six persons in a household, had higher odds of mental health and emotional symptoms. Similarly, people who perceived low risk of contracting the infection, and those who thought the pandemic would not continue after the lockdown had higher odds of mental health and emotional symptoms. Health care workers had lower odds for feeling angry than non-healthcare workers. During COVID-19 lockdown periods in SSA, about one in two participants reported mental health and emotional symptoms. Public health measures can be effectively used to identify target groups for prevention and treatment of mental health and emotional symptoms. Such interventions should be an integral component of SSA governments’ response and recovery strategies of any future pandemic.

We report the results of our study of approved drugs as potential treatments for COVID 19, based on the application of various bioinformatics predictive methods. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). Our results indicate that these small molecules selectively bind to stable, kinetically active residues and residues adjoining them on the surface of proteins and inside protein pockets, and that some prefer hydrophobic over other active sites. Our approach is not restricted to viruses and can facilitate rational drug design, as well as improve our understanding of molecular interactions, in general.

Abstract: A primary action of vitamin D is regulation of gene transcription. Many cell types possess genes that make antimicrobial peptides (AMPS) (endogenous antibiotics), recently discovered to be regulated by vitamin D. Two examples are cathelicidin and beta defensins, both bioactive against many different bacteria, fungi, mycobacteria, parasites and viruses. The signal transduction pathway is triggered by sensing microorganisms via cell surface receptors, causing intracellular production of calcitriol (1,25(OH)2D) and vitamin D receptors, leading to upregulation of AMP production. Serum 25(OH)D concentrations required to sustain adequate AMP production to eradicate infections are unknown. Vitamin D3 is photosynthesized in skin in amounts ranging from 10,000 (250 mcg) to 25,000 (625 mcg) International Units (IU) from 7-dehydrocholesterol after whole-body exposure to one minimal erythemal dose (MED) of ultraviolet B (UVB) radiation, and is impacted by many factors including geographic localities, seasonal changes and skin pigmentation. We and others have reported extended daily oral dosing with these amounts of vitamin D3 safe. We routinely observe serum 25(OH)D concentrations below 20ng/ml on new admissions, which have been reported insufficient to sustain AMP production. In contrast serum 25(OH)D concentrations above 100ng/ml have been reported after serial UVB treatments for psoriasis. Little vitamin D naturally occurs in food, and insufficient sun exposure may be causing worldwide deficiency. We review evidence suggesting that higher daily intakes of vitamin D3 than the currently recommended 600 (15 mcg) IU/day may be necessary to sustain AMP production in the face of an overwhelming infection, particularly in non-Hispanic blacks, a high risk population suffering the worst outcomes from COVID-19. We propose that increased vitamin D supplementation could provide a safe and cost-effective way to protect all populations from infections, in particular those from pandemic COVID-19.

Background: Brief Resolved Unexplained Events (BRUEs), formerly known as Apparent Life-Threatening Events (ALTE), are concerning episodes of short duration (typically &lt; 1 min) characterized by a change in breathing, consciousness, muscle tone, and/or skin color. In some cases, SARS-CoV-2 infection has been associated with episodes of BRUEs in previously healthy children.This study aimed to compare the demographic, respiratory, perinatal, and infectious characteristics in children affected by BRUE before the COVID-19 pandemic and after the spread of SARS-CoV-2. Methods: We conducted a retrospective observational study covering January 2018 to March 2020 (pre-COVID-19) and April 2023 (during the ongoing COVID-19 pandemic). Collected variables included clinical information during pregnancy and neonatal details of children with BRUE. Results: The number of children in the pre-COVID-19 period was 186 (41%); after the emergence and spread of SARS-CoV-2, it was 268 (59%). The risk of infection at birth for children developing BRUE was higher during the pandemic. Children were less likely to have ongoing symptomatic infection during BRUE during the pandemic (coefficient B = 0.783; p=0.009). Respiratory symptoms during BRUE were more frequent during the pandemic (coefficient B = 0.654; p=0.052). Fever during BRUE was less likely during the pandemic (coefficient B = -0.465, p=0.046). Conclusions: The study suggests that the COVID-19 pandemic has significantly impacted children with BRUE, potentially due to changes in hygiene practices and maternal-fetal infections.

Background: Coronavirus disease 2019 (COVID-19) has emerged as a global threat to human health and disease risk increases with advancing age. The regulation of the ACE2 gene that codes for COVID-19 host receptor ACE2 has been shown to be under epigenetic regulation. Here, we examined whether intensive DNA methylation profiling of the ACE2 gene differed by human host tissue and cell type, gender, and age. Results: Accessing four public datasets, we observed unique human cell-type-specific ACE2 DNA methylation patterns. In human lung tissues, gender differences in DNA methylation at 2 sites related to the ACE2 gene were identified. Further, in freshly isolated airway epithelial cells, DNA methylation near the transcription start site of the ACE2 gene associated with biological age. Conclusion: Epigenetic profiling of host tissue may permit discovery of age and gender-related potential risk factors for COVID-19. How perturbations in ACE2 methylation relate to clinical severity across the ages and gender needs to be determined to guide screening tools and potential epigenetic modification targeting to alleviate COVID-19 morbidity in the elderly.

We investigated how Artificial Intelligence (AI) reveals factors shaping COVID-19 vaccine hesitancy among healthcare providers by examining their open-text comments. We conducted a longitudinal survey starting in spring of 2020 with 38,788 current and former female nurses in three national cohorts to assess how the pandemic has affected their livelihood. In January and March-April 2021 surveys, participants were invited to contribute open-text comments and answer specific questions about COVID-19 vaccine uptake. A closed-ended question in the survey identified vaccine-hesitant (VH) participants who either had no intention or were unsure of receiving a COVID-19 vaccine. We collected 1,970 comments from VH participants and trained two Machine Learning (ML) algorithms to identify behavioral factors related to VH. The first predictive model classified each comment into one of three Health Belief Model (HBM) constructs (barriers, severity, and susceptibility) related to adopting disease prevention activities. The second predictive model used the words in January comments to predict the vaccine status of VH in March-April 2021; vaccine status was correctly predicted 89% of the time. Our results showed that 35% of VH participants cited barriers, 17% severity, and 7% susceptibility to receiving a COVID-19 vaccine. Out of the HBM constructs, the VH participants citing a barrier, such as allergic reactions and side effects, had the most associated change in vaccine status from VH to later receiving a vaccine.

Qatar experienced five SARS-CoV-2 waves dominated sequentially by the original virus, Alpha, Beta, Omicron BA.1 and BA.2, and Omicron BA.4 and BA.5, in addition to a prolonged low-incidence phase dominated by the Delta variant. The two-dose primary series of BNT162b2 (Pfizer-BioNTech) COVID-19 vaccine against SARS-CoV-2 infection has been approved for use in 10µg formulations among children and adolescents aged 12-17 years as of May 16, 2021. This study aimed at estimating the effectiveness of the 30µg BNT162b2 Pfizer-BioNTech mRNA COVID-19 vaccine against the pre-Omicron variants of SARS-CoV-2 infection in children and adolescents aged 12-17 years residing in Qatar. A test-negative matched case-control study was conducted where any child or adolescent aged 12-17 years who had been tested for SARS-CoV-2, RT-PCR tests performed on nasopharyngeal or oropharyngeal swabs, as part of contact tracing, between June and November 2021 and eligible to receive the BNT162b2 vaccine as per the national guidelines. Data regarding 14,161 children/adolescents meeting inclusion-exclusion criteria were retrieved from the national Surveillance and Vaccine Electronic System (SAVES). Of the total, 3.1% (444) were positive for SARSCoV-2. More than half (55.96%) were vaccinated with two doses of Pfizer-BioNTech-mRNA COVID-19 vaccine. Amongst those immunized with two doses, 1.2% tested positive for SARS CoV2, while 5.6% amongst the unvaccinated tested positive. The vaccine effectiveness was calculated to be 79%. Pfizer-BioNTech mRNA COVID-19 vaccine provides protection from COVID-19 infection for children/adolescents, hence it is crucial to ensure they receive the recommended vaccines.

Invasive fungal infections, notably candidemia, have been associated with COVID-19. The epidemiology of candidemia has significantly changed during the COVID-19 pandemic. We aim to identify the microbiological profile, resistance rates, and outcomes of COVID-19 associated candidemia (CAC) compared to patients with candidemia not associated with COVID-19. We retrospectively collected data on patients with candidemia admitted to the American University of Beirut Medical Center between 2004 and 2022. We compared the epidemiology of candidemia during and prior to the COVID-19 pandemic. Additionally, we compared the outcomes of critically ill patients with CAC to those with candidemia without COVID-19 from March 2020 till March 2022. Among 245 candidemia episodes, 156 occurred prior to the pandemic and 89 during the pandemic. Of the latter, 39 (43.8%) were CAC, most of which (82%) were reported from intensive care units (ICU). Non-albicans Candida (NAC) spp. were predominant throughout the study period (67.7%). Candida auris infection was the most common cause of NAC spp. in CAC. C. glabrata had decreased susceptibility rates to fluconazole and caspofungin during the pandemic period (46.1% and 38.4% respectively). Mortality rate in the overall ICU population during the pandemic was 76.6%, much higher than the previously reported mortality of candidemia from previous studies at our center. There was no significant difference in 30-day mortality between CAC and non-CAC (75.0% vs 78.1%; P =0.76). Performing ophthalmic examination (P = 0.002), CVC removal during the 48 hours following the candidemia (P = 0.008) and identifying the Candida spp. (P = 0.028) were significantly associated with a lower case-fatality rate. The epidemiology of candidemia has been significantly affected by the COVID-19 pandemic at our center. Rigorous infection control measures and proper antifungal stewardship are essential to combat highly resistant species like C. auris.

This study aimed to identify changes in visitor behavior and visitor interest in healing forests before and after the COVID-19 pandemic. The study used text mining analysis techniques to identify changes in visitation behavior over time, divided into three periods: pre-COVID-19 (January 1 to December 31, 2019), during the COVID-19 pandemic (November 1, 2020 to October 31, 2022), and post-COVID-19 (November 1, 2022 to October 31, 2023 ). After the COVID-19 outbreak, healing forest use behavior did not regress to pre-COVID-19 levels. Activity-based keywords such as "hiking," "trekking," and "walking" stood out as the main drivers of this change in behavior. Therefore, related authorities must examine the scalability of the functions, services, and programs of healing forests from a general healing space to a space for leisure and tourism. These findings will contribute to the development of future marketing strategies and programs for healing forests.

COVID-19 pandemic has the potential to adversely affect the mental health of healthcare workers (HCWs). The public healthcare system in Greece was already facing serious challenges at the outset of the outbreak following years of austerity and an escalating refugee crisis. The multi-center, cross-sectional study aims to assess the levels and associated risk factors of anxiety, depression, traumatic stress and burnout of frontline staff in Greece. A total of 464 HCWs in six reference hospitals completed a self-administered questionnaire comprising of sociodemographic and work-related information and psychometric scales. The proportion of HCWs with symptoms of moderate/severe depression, anxiety and traumatic stress were 30%, 25% and 33% respectively. Burnout levels were particularly high with 65% of respondents scoring moderate/severe in Emotional Exhaustion, 92% severe in Depersonalization and 51% low/moderate in Personal Accomplishment. Predictive factors of adverse psychological outcomes included fear, perceived stress, risk of infection, lack of protective equipment and low social support. The psychological burden associated with Covid-19 in healthcare professionals in Greece is considerable with more than half experiencing at least mild mental health difficulties. Findings signal the need for immediate organizational and individually tailored interventions to enhance resilience and support wellbeing under pandemic conditions.

The purpose of this article is to present the COVID-19 pandemic disruptions occurring in the supply chain of automotive companies, taking into account the type of business. The specific objectives are: to identify and characterise the types of enterprises operating in automotive supply chains, to identify changes during the pandemic in automotive enterprises, depending on the type of activity, to show disruptions in automotive supply chains and ways to counteract these disadvantages depending on the type of activity. Automotive enterprises operating in Poland were selected for the study purposefully. A random selection method was used to select 500 automotive companies for the study. The data sources were surveys conducted in June 2023 among 500 enterprises in the form of a face-to-face telephone interview. Automotive companies experienced supply chain disruptions, regardless of the type of business. Most often, these were caused by lockdowns and official closures, low stocks of materials and products, and problems with employees. There was no difference by type of business. Disruptions were most often short-lived, up to 1 year. Companies countered disruptions by using mostly operational measures, which were short-lived. Only a small percentage of operators made strategic decisions and countered disruptions over a longer period. The scale of these actions was greater among manufacturers than among dealers and car service companies.

While the global COVID-19 pandemic has been widely acknowledged to affect the mental health of health care workers (HCWs), attention to measures that protect those on the front lines of health outbreak response has been limited. In this cross-sectional study, we examine workplace contextual factors associated with how psychological distress was experienced in a South African setting where a severe first wave was being experienced with an objective of identifying factors that can protect against HCWs experiencing negative impacts. Consistent with mounting literature on mental health effects, we found a high degree of psychological distress (57.4% above General Health Questionnaire cut-off value) and a strong association between perceived risks associated with the presence of COVID-19 in the healthcare workplace and psychological distress (adjusted OR = 2.35, p <.01). Our research indicates that both training (adjusted OR 0.41, 95% CI 0.21 – 0.81) and the reported presence of supportive workplace relationships (adjusted OR 0.52, 95% CI 0.27 – 0.97) were associated with positive outcomes. This evidence that workplace resilience can be reinforced to better prepare for the onset of similar outbreaks in the future suggests that pursuit of further research into specific interventions to improve resilience is well merited.

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

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

Building on the job demands-resources (JD-R) and the allostatic load (AL) models, in this study we investigated the role of smart working (SW) in the longitudinal association between workload/job autonomy (JA) and a possible biomarker of work-related stress (WRS) in the hair, namely the cortisol to dehydroepiandrosterone sulphate (DHEA(S)) ratio, during the COVID-19 pandemic. Overall, 124 workers completed a self-report questionnaire (i.e., psychological data) at Time 1 (T1) and collected a strand of hair (i.e., biological data) three months later (Time 2, T2). Results from moderated multiple regression analysis showed that smart working at T1 was negatively associated with hair cortisol/DHEA(S) ratio at T2. Additionally, the interaction between workload and SW was significant, with workload at T1 being positively associated with hair cortisol/DHEA(S) ratio at T2 among smart workers. Overall, this study indicates that SW can be conceived as a double-edged sword, with both positive and negative consequences on employee well-being. Furthermore, our findings suggest that hair cortisol/DHEA(S) ratio is a promising biomarker of WRS. Practical implications that organizations and practitioners can adopt to promote organizational well-being are discussed.

On February 24, 2022 Russia started the full-scale invasion of Ukraine, which created an unprecedented number of refugees. To estimate the influence of this humanitarian disaster on the COVID-19 pandemic dynamics, the averaged daily numbers of cases and reproduction numbers in Ukraine, the UK, Poland, Germany, the Republic of Moldova, and in the whole world were calculated for the period February-April 2022. The registered numbers of cases were compared with ones calculated with the use of the generalized SIR-model and corresponding parameter identification procedure for the previous epidemic waves in Ukraine, Poland, Germany, and the world. Since before February 24, 2022 the estimation of the number of infectious persons per capita in Ukraine 3.6 times exceeded the global figure, the increase of the number the new cases and the pandemic duration was expected. In March 2022 the increase of the averaged number of new cases in the UK, Germany, and worldwide was visible. A simple formula to estimate the effective reproduction number based on the smoothed accumulated numbers of cases is proposed. The results of calculations agree with the figures presented by John Hopkins University and demonstrate a short-term growth of the reproduction number in the UK, Poland, Germany, Moldova, and worldwide in March 2022.

Although most cases of COVID-19 are paucisymptomatic, severe disease is characterized by immune dysregulation, with a decreased type I interferon response, increased inflammatory indicators, surging IL-6, IL-10 and TNFα suggestive of cytokine storm, progressive lymphopenia, and abnormal blood clotting. Factors determining susceptibility to severe disease are poorly understood, although mortality correlates with increasing age and co-morbidities including diabetes and cardiovascular disease (CVD). Pyridoxal 5'-phosphate (PLP) tends to be insufficient in populations particularly vulnerable to COVID-19, including the elderly, the institutionalized, and people with diabetes and CVD, and PLP becomes further depleted during infection and inflammation. In turn, low PLP results in immune imbalance, as PLP is an essential cofactor in pathways regulating cytokine production, in particular type I interferons and IL-6, and in lymphocyte trafficking and endothelial integrity. Furthermore, normalizing PLP levels attenuates abnormalities in platelet aggregation and clot formation. Finally, PLP insufficiency induces excess secretion of renin and angiotensin, and hypertension. In inflammatory disease, pharmacological doses of PLP decrease circulating TNFα, IL-6 and D-dimer, and animal studies demonstrate that supplemental PLP shortens the duration and severity of viral pneumonia. Severe COVID-19 manifests as an imbalance in the immune response and the clotting system. Pharmacological PLP supplementation may therefore mitigate COVID-19 symptoms by alleviating both the immune suppression underlying viral spread and the pathological hypersecretion of inflammatory cytokines, as well as directly bolstering endothelial integrity and preventing hypercoagulability.

Health innovations are generally oriented on a techno-economic vision. In this perspective, technologies are seen as an end in themselves, and there is no arrangement between the technical and the social values of innovation. This vision prevails in sanitary crises, in which management is carried out based on the search for punctual, reactive, and technical solutions to remedy a specific problem without a systemic/holistic, sustainable, or proactive approach. This paper attempts to contribute to the literature on the epistemological orientation of innovations in the field of public health. Taking the Covid-19 and Ebola crises as examples, the primary objective is to show how innovation in health is oriented towards a techno-economic paradigm. Second, we propose a repositioning of public health innovation towards a social paradigm that will put more emphasis on the interaction between social and health dimensions in the perspective of social change.

Evidence was brought forward in England and the USA that Black, Asian, Latino and Minority Ethnic people exhibit higher mortality risk from COVID-19 than White people. While socioeconomic factors were suggested to contribute to this trend, they arguably do not explain the range of the differences observed, allowing for possible genetic implications. Almost concurrently, the analysis of a cohort in Chinese COVID-19 patients proposed an association between the severity of the disease and the presence of the minor allele of rs12252 of the Interferon-induced transmembrane protein 3 (IFITM3) gene. This SNP, together with rs34481144, are the two most studied polymorphisms of IFITM3 and have been associated in the past with increased severity in Influenza, Dengue, Ebola, and HIV viruses. IFITM3 is an immune effector protein that is pivotal for the restriction of viral replication, but also for the regulation of cytokine production. Following up to these two developments in the ongoing SARS-CoV-2 pandemic, the present study investigates a possible association between the differences in mortality of ethnic groups in England and the combined haplotypes of rs12252 and rs34481144. The respective allele frequencies were collected for 26 populations from 1000 Genomes Project and subgroups were pooled wherever possible to create correspondences with ethnic groups in England. A significant correlation (r=0.9687, p= 0.0003) was observed between the reported Standardized Mortality Ratios and the frequency of the combined haplotype of both reference alleles, suggesting that the combination of reference alleles of the specific SNPs may be implicated in more severe outcomes of COVID-19. This study calls for further focus on the role of IFITM3 variants in the mechanism of cellular invasion of SARS-CoV-2, their impact in COVID-19 severity and their possible implications in vaccination efficacy.

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

This study explores the role of inflammation and oxidative stress, hallmarks of COVID-19, in accelerating cellular biological aging. We investigated early molecular markers—DNA methylation age (DNAmAge) and telomere length (TL)—in blood leukocytes, nasal cells (NC), and induced sputum (IS) one-year post-infection in pauci- and asymptomatic healthcare workers (HCWs) infected during the first pandemic wave (February-May 2020), compared to COPD patients, model for "aged lung". Data by questionnaires, Work Ability Index (WAI), blood analyses, autonomic cardiac balance assessments, heart rate variability (HRV), and pulmonary function tests were collected. Elevated leukocyte DNAmAge significantly correlated with advancing age, male gender, daytime work, and an aged phenotype characterized by chronic diseases, elevated LDL and glycemia levels, medications affecting HRV, and declines in lung function, WAI, lymphocyte count, hemoglobin levels, and HRV (p&lt;0.05). Increasing age, LDL levels, job positions involving intensive patient contact, and higher leukocyte counts collectively contributed to shortened leukocyte TL (p&lt;0.05). Notably, HCWs exhibited accelerated biological aging in IS cells compared to both blood leukocytes (p≤0.05) and NC (p&lt;0.001), and were biologically older than COPD patients (p&lt;0.05). These findings suggest the need for monitoring aging in pauci- and asymptomatic COVID-19 survivors, who represent the majority of the general population.

COVID-19 is a severe global problem, and AI can play a significant role in preventing losses by monitoring and detecting infected persons in early-stage. This paper aims to propose a high-speed and accurate fully-automated method to detect COVID-19 from the patient's CT scan images. We introduce a new dataset that contains 48260 CT scan images from 282 normal persons and 15589 images from 95 patients with COVID-19 infections. At the first stage, this system runs our proposed image processing algorithm to discard those CT images that inside the lung is not properly visible in them. This action helps to reduce the processing time and false detections. At the next stage, we introduce a novel method for increasing the classification accuracy of convolutional networks. We implemented our method using the ResNet50V2 network and a modified feature pyramid network alongside our designed architecture for classifying the selected CT images into COVID-19 or normal with higher accuracy than other models. After running these two phases, the system determines the condition of the patient using a selected threshold. We are the first to evaluate our system in two different ways. In the single image classification stage, our model achieved 98.49% accuracy on more than 7996 test images. At the patient identification phase, the system correctly identified almost 234 of 245 patients with high speed. We also investigate the classified images with the Grad-CAM algorithm to indicate the area of infections in images and evaluate our model classification correctness.

This study aimed to evaluate whether primary school classroom teachers reported changes in physical education teaching self-efficacy (SE-PE) and work engagement (WE) during the first COVID-19 wave. Six-hundred-twenty-two classroom teachers filled in an online questionnaire on SE-PE and WE, referring to before and during the lockdown, and on perceived digital competence. While controlling for perceived digital competence, a mixed between-within Repeated Measures Multivariate Analysis of Covariance (RM-MANCOVA) was performed, with a two-time (before vs. during the lockdown) and three age-categories (≤40 vs. 41-50 vs. ≥51 years) factorial design. The RM-MANCOVA revealed that perceived digital competence significantly adjusted teachers’ SE-PE and WE values (p&lt;0.001). The analysis yielded a significant multivariate main effect by time (p&lt; 0.001) and by time × age-categories (p=0.001). Follow-up univariate ANCOVA showed significant differences by time in teachers’ SE-PE (p&lt;0.001) and WE (p &lt; 0.001), with a reduction of both values from before to during the lockdown. A Bonferroni post hoc pairwise comparisons showed teachers’ SE-PE significantly decreased in all age categories (p&lt;0.001). The present findings confirm the importance of promoting SE-PE among primary school teachers, regardless of the crisis due to the COVID-19 pandemic. Teachers’ self-efficacy and WE are essential to master the challenges of PE teaching.

AI is leveraging all aspects of life. Medical services are not untouched. Especially in the field of medical image processing and diagnosis. Big IT and Biotechnology companies are investing millions of dollars in medical and AI research. The recent outbreak of SARS COV-2 gave us a unique opportunity to study for a non interventional and sustainable AI solution. Lung disease remains a major healthcare challenge with high morbidity and mortality worldwide. The predominant lung disease was lung cancer. Until recently, the world has witnessed the global pandemic of COVID19, the Novel coronavirus outbreak. We have experienced how viral infection of lung and heart claimed thousands of lives worldwide. With the unprecedented advancement of Artificial Intelligence in recent years, Machine learning can be used to easily detect and classify medical imagery. It is much faster and most of the time more accurate than human radiologists. Once implemented, it is more cost-effective and time-saving. In our study, we evaluated the efficacy of Microsoft Cognitive Service to detect and classify COVID19 induced pneumonia from other Viral/Bacterial pneumonia based on X-Ray and CT images. We wanted to assess the implication and accuracy of the Automated ML-based Rapid Application Development (RAD) environment in the field of Medical Image diagnosis. This study will better equip us to respond with an ML-based diagnostic Decision Support System(DSS) for a Pandemic situation like COVID19. After optimization, the trained network achieved 96.8% Average Precision which was implemented as a Web Application for consumption. However, the same trained network did not perform like Web Application when ported to Smartphone for Real-time inference, which was our main interest of study. The authors believe, there is scope for further study on this issue. One of the main goals of this study was to develop and evaluate the performance of AI-powered Smartphone-based Real-time Applications. Facilitating primary diagnostic services in less equipped and understaffed rural healthcare centers of the world with unreliable internet service.

Access to nasopharyngeal swabs for sampling remain a bottleneck in some regions for COVID-19 testing. This study develops a distributed manufacturing solution using only an open source manufacturing tool chain consisting of two types of open source 3-D printing and batch UV curing, and provides a parametric fully free design of a nasopharyngeal swab. The swab was designed using parametric OpenSCAD in two components (a head with engineered break point and various handles), which has several advantages: i) minimizing print time on relatively slow SLA printers, ii) enabling the use of smaller print volume open source SLA printers, iii) reducing the amount of relatively expensive UV resin, and iv) enabling production of handle on more accessible material extrusion 3-D printers. A modular open source UV LED box was designed, fabricated for $45 and tested for batch curing. Swabs can be fabricated for $0.06-$0.12/swab. The results of the mechanical validation tests showed that the swabs could withstand greater forces than would be expected in normal clinical use. The swabs were also able to absorb a significant amounts of synthetic mucus materials and passed abrasion and handling tests. The results show the open source swab are promising candidates for clinical trials.

Coronavirus disease 2019 (COVID-19) affected not only individuals but also families. The purpose of this study was to clarify the temporal changes in the impact of the COVID-19 pandemic on entire families with older adults susceptible to infection living on small islands in Japan over the duration of the pandemic. Family ethnographic research was conducted from 2021 to 2023, using the Concentric Sphere Family Environment Theory as the theoretical framework. Formal interviews were conducted with 20 families. In addition, data from informal interviews, participant observation and other sources were compiled into field notes. All data on the impact on the entire family were extracted and content analysis was conducted. Five categories and a total of 85 subcategories were extracted. The results show that COVID-19 exerted not only negative but also positive impacts on the entire family, and their temporal changes are clarified. The impact on families is believed to have been influenced by the family external environment, such as increases and decreases of infection cases or events that occurred outside the family. The knowledge acquired from these studies will help healthcare professionals in providing appropriate family support.

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

Cross-sectional survey was conducted to capture the true extent of COVID-19 exposure among students and staff of Polytechnic High School (PHS). Random cluster sampling was carried out between May 19 and August 18, 2022, after the fourth wave of COVID-19 transmission. IgM and IgG SARS-CoV-2 antibodies were screened using WANTAI SARS-CoV-2 ELISA assays. Seroprevalence and descriptive statistics were calculated. Moreo-ver, the association between seropositivity and different factors (age, gender, preventive measures comorbidity, and symptoms, etc.) was determined using Logistic Regression. The overall IgG and IgM seroprevalence were 92% and 6.91% respectively. We found a higher IgM seroprevalence in men than women (9.4% vs. 5.6%) and a lower IgM seroprevalence in (18-25) age group compared to (55-65) years. Low compliance with preventive measures was found with a significant IgM seroprevalence depending on non-respect of social distancing (p = 0.008). A total of 70% of participants presented symptoms linked to COVID-19 at the moment of the survey. Results revealed a significant difference according to IgG seroprevalence among participants who declared fa-tigue symptoms 92.06% compared to those who did not 80.39% (p = 0.0027). IgM seropositivity was associated with Body Mass Indice (BMI) categorized (O.R. 0.238, p = 0.043), ethnic group (O.R. 0.723, p = 0.046) and marital status (O.R. 2.399, p = 0.021). Moreover, IgG seropositivity was associated with Chronic sinusitis comorbidity (O.R. 0.238, p = 0.043) and vaccination status (O.R. 4.741, p < 0.001). The majority of students and staff have al-ready been exposed to SARS-CoV-2 and confirm the circulation of SARS-CoV-2 in PHS at the time of the survey. Our results underline the importance of sero-epidemiological surveys to estimate the real impact of the COVID-19 pandemic in a community and to monitor disparities in antibody response in the population.

Coronavirus Disease-19 (COVID-19) is caused by the infection of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The virus enters host cells through receptor-mediated endocytosis of angiotensin-converting enzyme-2 (ACE2), leading to systemic inflammation, also known as a “cytokine storm,” and neuroinflammation. COVID-19’s upstream regulator, interferon-gamma (IFNG), is downregulated upon the infection of SARS-CoV-2, which leads to the downregulation of ACE2. The neuroinflammation signaling pathway (NISP) can lead to neurodegenerative diseases, such as Parkinson's disease (PD), which is characterized by the formation of Lewy Bodies made of α-Synuclein protein encoded by synuclein alpha (SNCA). This study presents the pathways involved in the downregulation of ACE2 following SARS-CoV-2 infection and its effect on PD progression. Through QIAGEN’s Ingenuity Pathway Analysis, the study identifies the NISP as a top-five canonical pathway/signaling pathway and SNCA as a top-five upstream regulator. Core Analysis was also conducted on the associated molecules between COVID-19 and SNCA to construct a network connectivity map. The Molecule Activity Predictor tool was used to simulate the infection of SARS-CoV-2 by downregulating IFNG, which leads to the predicted activation of SNCA, and subsequently PD, through a dataset of intermediary molecules. Downstream Effect analysis was further used to quantify the downregulation of ACE2 on SNCA activation.

The outbreak of coronavirus disease 2019 (COVID-19) was identified in Wuhan, China, in December 2019. As of April 17, 2020, more than 2 million cases of COVID-19 have been reported worldwide. Northern Italy is one of the world’s centers of active coronavirus cases. In this study, we predicted the spread of COVID-19 and its burden on hospital care under different conditions of social distancing in Lombardy and Emilia-Romagna, the two regions of Italy most affected by the epidemic. To do this, we used a Susceptible-Exposed-Infectious-Recovered (SEIR) deterministic model, which encompasses compartments relevant to public health interventions such as quarantine. A new compartment L was added to the model for isolated infected population, i.e., individuals tested positives that do not need hospital care. We found that in Lombardy restrictive containment measures should be prolonged at least until early July to avoid a resurgence of hospitalizations; on the other hand, in Emilia-Romagna the number of hospitalized cases could be kept under a reasonable amount with a higher contact rate. Our results suggest that territory-specific forecasts under different scenarios are crucial to enhance or take new containment measures during the epidemic.

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

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

Since its inception in 2019, COVID-19 has been associated with significant changes in lifestyle-related behavior, including physical activity, diet, and sleep, which are vital to maintaining our well-being. This study measures lifestyle-related behavior during the COVID-19 pandemic lockdown using a 21-item questionnaire. The responses were collected from March 2021 to September 2021. Four hundred sixty-seven participants were engaged in assessing the changes caused by the pandemic and their effect on BMI. The validity and reliability of the questionnaire were tested for 71 participants. Cronbach's alpha values for the questionnaire all exceeded 0.7, demonstrating good validity and internal consistency for it. The effect of each question regarding physical activity and dietary habits over the BMI difference was studied using ANOVA. The study shows that more than half of the participants reported snacking more between meals and increased their sitting and screen time, while 74% felt more stressed and anxious. These indications were the cause of the increase in the BMI rate for individuals in the lockdown. In contrast, 62% of the participants showed more awareness about their health by increasing the intake of immunity-boosting foods, and 56% of the participants showed an increase in the consumption of nutrition supplements. Females and married individuals tended to be healthier, so their BMI showed stability compared to others based on their gender and marital status.

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

Background: The manifestations, severity, and mortality of COVID-19 are considered to be associated with the changes in various hematological parameters and in immunity. Associations of immunoglobulin G antibodies against severe acute respiratory syndrome-linked coronavirus (IgG-SARS)-positive status with cardiac function and hematological and biochemical parameters in apparently health subjects are poorly understood. Methods: The present cross-sectional study included 307 healthy volunteers (24-69 years of age; 44.8±8.6 years; 80.4% men) and was initiated in 2019 before the COVID-19 pandemic. COVID-19 episodes were confirmed by detection of IgG-SARS against SARS-CoV-2 S1 RBD to reveal 70 IgG-SARS-positive and 237 negative participants. Numerous ultrasound characteristics were assessed by echocardiography, and 15 hematological and biochemical parameters were assayed in the blood. Descriptive and comparative analysis was based on the IgG-SARS status of the participants. Results: The left ventricular mass index, mitral ratio of peak early to late diastolic filling velocity or flow velocity across the mitral valve, and deceleration time of early mitral inflow were decreased (P<0.05) in IgG-SARS-positive participants versus those in IgG-SARS-negative participants according to multivariate logistic regression analysis. Erythrocyte sedimentation rate and platelet count were slightly increased, and blood hemoglobin was decreased in IgG-SARS-positive participants compared with those in IgG-SARS-negative participants. Conclusions: LV filling, inflammation, blood coagulation, and hemoglobin appear to be influenced by COVID-19 infection in healthy participants. These observations contribute to the development of a population recovery strategy after the episodes of COVID-19.

Objectives To develop and validate a prediction model for 28-day in-hospital mortality among adult patients critically ill with COVID-19 in the UK. Design Observational cohort study. Setting 287 adult critical care units in England, Wales and Northern Ireland, of which 260 admitted at least one eligible patient. Participants 10,933 patients with confirmed COVID-19 of whom 10,401 were eligible (excluding 532 patients with a duration of critical care less than 24 hours and 1 patient with unknown 28-day outcome): 8,666 development (March-April 2020) and 1,735 temporal validation (May-August 2020). Main outcome measures 28-day in-hospital mortality from start of critical care. Results Two models were developed using 14 patient level predictors selected from 30 candidate predictors, with and without adjustment for calendar time. In the temporal validation data, the model discrimination was maintained (c index 0.78) but calibration was poor, particularly for the model not adjusted for calendar time (ratio of observed to predicted mortality 0.74 versus 0.88 for the model adjusted for calendar time). Conclusions We developed and validated a prediction model for 28-day in-hospital mortality for patients critically ill with COVID-19. Although absolute predictions were inaccurate due to changing outcomes, the models will support risk-adjustment in analyses and monitoring changes in risk-adjusted outcome over time.

To ensure high-quality care, operationalize resilience and fill the knowledge gap regarding how to improve the prerequisites for resilient performance, it is necessary to understand how adaptive capacity unfolds in practice. Coronavirus 2019 stress-tested complex healthcare systems, and intensive care was driven to an unprecedented escalation. The main aim of this research was to explain the escalation process of intensive care from a microlevel perspective, including expressions of resilient performance, intervening conditions at the micro-meso-macrolevels and short- and long-term consequences. A secondary aim was to provide clinical recommendations regarding how to optimize the prerequisites for resilient performance in intensive care. A grounded theory methodology was used. First-person stories from different healthcare professionals (n70) in two Swedish regions were analyzed using the constant comparative method. A novel conceptual model of the escalation process of intensive care emerged, and 41 clinical recommendations concerning the optimal prerequisites for resilient performance were identified. Escalation was conceptualized as a transition from threatening chaos to temporary order through a complex process of adaptation. To prepare for the future, the components space, stuff, staff, system and science with associated continuity plans must be implemented, anchored and communicated to actors at all levels of the system.

This paper presents our approaches for the SMM4H’24 Shared Task 5 on the binary classification of English tweets reporting children’s medical disorders. Our first approach involves fine-tuning a single RoBERTa-large model, while the second approach entails ensembling the results of three fine-tuned BERTweet-large models. We demonstrate that although both approaches exhibit identical performance on validation data, the BERTweet-large ensemble excels on test data. Our best-performing system achieves an F1-score of 0.938 on test data, outperforming the benchmark classifier by 1.18%.

Motivation is essential in education, with highly motivated learners engaging more deeply with content and more ably transferring knowledge to new contexts. However, the validity of scales to measure motivation has been underexplored in pre-clerkship medical education. This study evaluates the validity of the Situational Motivation Scale (SIMS) for measuring motivation among pre-clerkship medical students in post-situational and short-term contexts. Using a sample of n = 156 students from the Frank H. Netter MD School of Medicine at Quinnipiac University, SIMS was tested for construct validity with attention paid to content, response process, internal structure, relationships to other variables, and consequences of use evidence. Small modifications from present to past tense in English were made for clarity following focus group feedback, and content validity was ensured via expert consultation. SIMS demonstrated strong internal consistency with a satisfactory Cronbach’s alpha for all subscales and anticipated patterns of correlations. Factor analysis confirmed appropriate factor loadings, with a stronger model fit for the short-term context, and no observed adverse effects on student engagement. These findings support the robustness of SIMS in capturing intrinsic, extrinsic, and amotivation in pre-clerkship medical students, highlighting its applicability for short-term and situational motivational assessment.

Evaluation of the patients after the surgical correction of idiopathic scoliosis in long-term follow-up with the clinical neurophysiology methods has not been presented in detail. This study aimed to compare the results of the neurophysiological studies in 45 girls with scoliosis of Lenke 1-3 types performed pre- (T0), postoperatively (T1, one week after surgery), and 6 months after the surgery (T2). Parameters of surface electromyography during the attempt of maximal contraction (mcsEMG) and transcranially evoked motor evoked potentials (MEP) recorded from anterior tibial muscles, as well as the electroneurography (ENG) of peripheral transmission in the peroneal nerve motor fibers were compared. The results indicate that efferent neural conduction function both centrally and peripherally as well as TA muscle function improve immediately after surgical correction of scoliosis (at p=0.05) and further normalization appears after six months in long-term follow-up (at p=0.03). It has been found in sEMG recordings, that the TA muscle motor unit recruitment function after half a year from surgical treatment in IS patients is comparable to the normal condition. ENG recordings results indicated the gradual retreat of the motor fibers injury symptoms mainly of the axonal type in peroneal nerves, the surgeries improved also the lumbar ventral roots’ neural transmission to the functional status considered as normal. MEP amplitude parameters recorded after the surgical scoliosis correction in T1 indicated a slight improvement in the efferent transmission of neural impulses within the fibers of the spinal tracts; in long-lasting T2 observation, they reached values comparable to those recorded in healthy volunteers bilaterally. Preoperatively (T0) the results of all neurophysiological study parameters in IS patients were asymmetrical at p=0.036-0.05 and recorded as worse on the concave side, suggesting the lateralization of neurological motor deficits. One week postoperatively (T1), this asymmetry was recorded as gradually reduced, showing almost no difference between the right and left sides six months later (T2). The presented algorithm of the diagnostic proceeding pre-, early post-, and long-lasting postoperatively using mcsEMG, MEP, and ENG neurophysiological examinations can be significant not only in making the final decision regarding surgical treatment and its personalization but also helps in precise ascertaining its effects as well as in predicting the final result of IS treatment.

A community-level nutrition intervention was implemented among tribal children (3 to 6 years) in Telangana, India. The one-year intervention involved six nutrient-rich formulations of millet-pulse-groundnut based products, suited to local taste preferences. Anthropometric measurements of height, weight and Mid-Upper-Arm -Circumference (MUAC) along with haemoglobin (Hb) levels were monitored at baseline and endline. The treatment group showed considerable gain in height (3.2 cm), weight (1.68 kg) and MUAC (0.33 cm), over the control group. Paired t-test indicated significant differences (p<.01) between pre- and post-intervention anthropometric measurements. Positive shifts were observed in wasting (WHZ; -1.2 ±1.3 to -0.9± 1), stunting (HAZ; -1.8±1.6 to -0.3±1.3) and underweight (WAZ; -1.9±1.2 to -0.7±1) among treatment group. Hb levels in the treatment group also improved significantly from 9.70 ± 0.14 g/dl (moderately-anaemic) to 11.08 ± 0.13 g/dl (non-anaemic). Post-intervention Focus Group Discussions (FGDs) involving mothers and teachers confirmed the positive impact. Thus, nutritional intervention formulated using climate resilient millets, pulses and groundnut, promotes dietary diversity and improves the nutrition & health status of children.

Empowering teachers with Critical Thinking and understanding of sustainability is vital for guiding students’ informed decisions and actions in today’s world. Higher education needs innovative, student-centered methods like case-based teaching in order to promote Critical Thinking and the principles of Education for Sustainable Development. The aim of the study was to explore and evaluate pre-service teachers' Critical Thinking when engaged with case studies in a practicum preparation course centered on Education for Sustainable Development. Nine undergraduate students in Teacher Education participated in the study and answered four case studies. The case studies’ responses were analyzed through a bottom-up content analysis revealing eight higher-order categories. While approaching the case studies, student-teachers followed thinking processes similar to the processes proposed by the iterative models of Critical Thinking as perceived by Garrison (1991) and/or Brookfield (1987). Nevertheless, in some cases, pre-service teachers’ disengagement was evident. The rubric assessment highlighted that the responses fell under three profiles, namely the “Deficient Critical Thinker”, the “Emerging Critical Thinker” and the “Competent Critical Thinker”. The findings emphasize the need for targeted and individualized teaching interventions in teacher higher education programs aiming at Education for Sustainable Development complying with the learning needs of student-teachers’ Critical Thinking profiles.

Agriculture is one of the indispensable fields for the survival of mankind. Potatoes also have a significant role in the field of agriculture. The quality and quantity of potatoes are significantly impacted by several diseases, such as early blight and late blight, and manual interpretation of these leaf diseases is time-consuming and inconvenient. Fortunately, leaf appearance is used to detect diseases in potato plants. Productivity will considerably rise if the infections are detected early. Different types of image processing methods and machine learning methods are used for early recognition of those diseases from leaf images so that the product losses are decreased significantly. For the incredible and marvelous performance of CNN, it is the most popular deep learning method that is used immensely for the recognition of leaf diseases from images. Several pretrained deep learning models, such as VGG16, ResNet50, InceptionV3, MobileNetV2, Xception, and a deep learning model developed using CNN, are employed for potato leaf disease classification and recognition on the same dataset. The transfer learning technique is applied to the pretrained model and the data augmentation technique is applied to the Proposed CNN model for potato disease classification from leaf samples. Compared to pretrained models, the proposed CNN model offers the lowest loss and highest accuracy for potato leaf disease detection while using fewer parameters and layers. It achieves the best performance with a test accuracy of 99.33% compared to other Pretrained models used in the diagnosis of potato leaf disease.

Lung cancer is the leading cause of global cancer-related mortality resulting in ~1.8 million deaths annually. Systemic, molecular targeted, and immune therapies have provided significant improvements of survival outcomes for patients. However, drug resistance usually arises and there is an urgent need for novel therapy screening and personalized medicine. 3D patient-derived organoid (PDO) models have emerged as a more effective and efficient alternative for ex vivo drug screening than 2D cell culture and patient-derived xenograft (PDX) models. In this review, we performed an extensive search of lung cancer PDO-based ex vivo drug screening studies. Lung cancer PDOs were successfully established from fresh or biobanked sections/biopsy of lung tumors, PDXs, and pleural affusion. PDOs were subject to ex vivo drug screening with chemotherapy, targeted therapy and immune therapy agents. PDOs mainly recapitulated the genomic alterations, transcriptomic landscape and drug sensitivity of primary tumors. Although sample sizes of the previous studies were limited and some technical challenges remained, PDOs showed promise to screen novel therapy drugs. With the technical advance of high throughput, tumor-on-chip, combined microenvironment, and air-liquid interface (ALI), the drug screening using PDOs would serve better for precision care of lung cancer patients.

Passive and forced drinking harm was prevalent but less recognized in Chinese adolescents. We educated adolescents on such harm to reduce their intention to drink. Students (n=1244) from 7 secondary schools in Hong Kong participated in a video-based health talk on passive and forced drinking harm. Paired t-test was used to assess their change in knowledge of passive and forced drinking, health and social harm of drinking after the health talk. McNemar's chi-squared test and adjusted multivariable logistic regression (AOR) were used to assess their change in intention to drink and intention to quit. Students were less likely to drink (OR 0.29, 95% CI 0.19-0.42) and more likely to quit drinking (OR 3.50, 1.10-14.6) after the health talk. Increased knowledge of passive drinking was associated with less intention to drink (AOR 0.93, 0.90-0.97), increased knowledge of health harm (adjusted b 0.06, 0.05-0.08), and social harm of drinking (adjusted b 0.12, 0.10-0.16). Similar associations were observed in forced drinking (intention to drink: AOR 0.87, 0.79-0.96; health harm: adjusted b 0.16, 0.12-0.19; social harm: adjusted b 0.36, 0.28-0.43). We showed preliminary evidence that the health talk on passive and forced drinking reduced the intention to drink in adolescents.

The likelihood of pre-hypertensive young adults developing hypertension has been steadily increasing over the past few years. Despite the fact that aerobic exercise training (AET) has demonstrated positive results in lowering high blood pressure, the efficacy of different types of AET among pre-hypertensive young adults has not been well-established. The objective of this study was to evaluate the effectiveness of high-intensity interval training (HIIT) and continuous moderate-intensity training (CMT) on blood pressure (BP) of physically inactive pre-hypertensive young adults. 32 adults (age 20.0±1.1 years and BMI 21.5±1.8) were randomly assigned into 3 groups: HIIT, CMT and control (CON). HIIT and CMT groups participated in 5 weeks of AET; while the CON group followed a DASH diet plan only. The HIIT protocol consisted of 1:4 minute work to rest ratio of participants 80%-85% heart rate reserve (HR-reserve) and 40%-60% HR-reserve respectively for 20-minutes, CMT group exercised at 40%-60% of HR-reserve continuously for 20-minutes. In both HIIT and CMT groups, systolic blood pressure (SBP) (3.8±2.8 mmHg, P=0.002 VS 1.6±1.5 mmHg, P=0.011) was significantly reduced. While, significant reductions in the diastolic blood pressure (DBP) (2.9±2.2 mmHg, P=0.002) and mean arterial pressure (MAP) (3.1±1.6mmHg, P<0.0005) were noted only in the HIIT group. No significant differences in SBP (-0.4±3.7 mmHg, P=0.718), DBP (0.4±3.4 mmHg, P=0.714), or MAP (0.1±2.5mmHg, P= 0.892) were observed in the CON group. Both HIIT and CMT decreased the BP in physically inactive pre-hypertensive young adults; however, HIIT yielded more beneficial results in terms of reducing the SPB, DBP and MAP.

The basic principles of geological risk calculation through Probability of Success (PoS) are mostly applied for numerical estimation of additional hydrocarbon existence in proven reservoirs or potential hydrocarbon discoveries in selected geological regional subsurface volume. It can be tailored and validated for a comprehensive input dataset collected in the selected petroleum province, adapted by dividing up geological events into several probability categories and classes. The most applied categories are (existence of) reservoir rocks, traps and isolators, source rocks, migration pathways and preservation conditions for hydrocarbons The methodology results in unique probability values as multiplication of independent statistical events, which can also be applied in the assessment of a potential hydrocarbon discovery of desired minimal volume and its value in any virtual currency like risk-neutral dollars. Such methodology has been extensively developed in the last decades in the Croatian subsurface, mostly in the Croatian part of the Pannonian Basin System (CPBS). Through the adaptation of geological categories, it was also applied in hybrid, i.e., stochastical, models developed in the CPBS (Drava Depression). Stochastically estimation of porosity was already applied. As the robustness of this methodology is very high, it was also modified to estimate the influence of water-flooding in increasing oil recovery in some proven Neogene sandstone reservoirs in the CPBS (Sava Depression). This new modification is being presented to be applied to geological risk calculation, intending to assess the safety of geological environment in deep wells, where depleted radioactive fuel would be disposed, a subject of great importance. The case study encompassed the magmatic and metamorphic rocks in the pre-Neogene basement of the CPBS. For disposal purpose, these are regionally lithologies considered as to be the safest ones considering petrophysical values, water saturation, recent weathering and tectonic activity.

This study was aimed at investigating the protective effects of glass ionomer cement (GIC) and surface pre-reacted glass ionomer (S-PRG) fillers used as dental restorative materials on demineralization of bovine enamel. GlasIonomer FX ULTRA (FXU), Fuji IX GP Extra (FIXE), CAREDYNE RESTORE (CDR) were used as GICs. PRG Barrier Coat (BC) was used as the S-PRG filler. They were incubated in a lactic acid solution (pH = 4.0) for 6 d at a temperature of 37 °C. The mineral was etched from the enamel surface, and a large number of Ca and P ions were detected in solution. The Al, F, Na, Sr, and Sr ions were released in GICs and S-RPG fillers. The Zn ion was released only in CDR and the B ion was released only in BC. The presence of apparent enamel prism peripheries was observed after 6 d of treatment for the group containing only enamel blocks. pH values for the FXU, FIXE, CDR, BC, and enamel block groups after 6 d were 6.5, 6.6, 6.7, 5.9, and 5.1, respectively. Therefore, the observed pH neutralization effect suppressed progression of caries due to the release of several ions from the restoratives.

Prestress loss evaluation in prestressed strand is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strand inside the duct also have several problems, such as inadequate durability in an aggressive environment, vulnerable damage at tensioning and so on. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensor to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.

We propose a notion of $(q,\sigma,\tau)$-differential graded algebra, which generalizes the notions of $(\sigma,\tau)$-differential graded algebra and $q$-differential graded algebra. We construct two examples of $(q,\sigma,\tau)$-differential graded algebra, where the first one is constructed by means of generalized Clifford algebra with two generators (reduced quantum plane), where we use a $(\sigma,\tau)$-twisted graded $q$-commutator. In order to construct the second example, we introduce a notion of $(\sigma,\tau)$-pre-cosimplicial algebra.

The purpose of current study was to investigate the expression characteristic of circular RNAs (circRNAs) in peripheral blood of type 2 diabetes mellitus (T2DM) patients and their potentials as diagnostic biomarkers for pre-diabetes and T2DM. In present study, the circRNAs in the peripheral blood from 6 healthy individuals and 6 T2DM patients were collected for microarray analysis. The results indicated that there were 489 differentially expressed circRNAs, of which 78 were upregulated and 411 were downregulated in the T2DM group. Then we selected 5 circRNAs as the candidate biomarkers under a stricter screening criteria and further verified them in another cohort (control group, n=20; pre-diabetes group, n =20; T2DM group; n=20). 3 of the 5 circRNAs presented upregulated expression in the experimental groups, including 2 circRNAs of the T2DM group that had higher expression than the pre-diabetes group. Hsa_circ_0054633 was identified to have the largest area value under the carve (AUC). In another independent cohort (control group, n=60; pre-diabetes group, n=63; T2DM group, n=64), the diagnostic capacity of hsa_circ_0054633 was tested. The results showed that the AUC for the diagnosis of pre-diabetes was 0.751(95% confidence interval=[0. 666-0.835], P＜0.001) while it was 0.793 ([0.716-0.871], P＜0.001) for the diagnosis of T2DM. After including the risk factors of T2DM, the AUC increased to 0.841 ([0.773-0.910], P <0.001) and 0.834 ([0.762-0.905], P <0.001), respectively. Hsa_circ_0054633 presented a certain diagnostic capability for pre-diabetes and T2DM.

Our aim is at three feels: i) study safe haven properties of sectoral CDS; ii) study hedging effectiveness and measure the diversification benefits of introducing them in both Conventional and Islamic stock markets portfolios and iii) compare these results with VSTOXX, Gold and Bitcoin indices. To do this, we estimate time varying hedge ratio using (A)DCC and GOGARCH models and then deduce hedging effectiveness.. We follow the same methodology for each sub-period and each refit to test the effect of bubble crypto currency and COVID-19 pandemic on hedging effectiveness. Empirical results show the superiority of industrial CDS sectoral index to hedge both conventional and Islamic stock markets whether long or short term despite that their performances were reduced slightly during the second and third periods. VSTOXX and Others sectoral CDS indices offers Hedging performances that are generally better than Bitcoin and gold.

Background: Routine childhood vaccination, e.g., for diphtheria-tetanus-pertussis (DTP), might provide an additional protection towards SARS-CoV-2 infection. This concept of heterologous immunity was explored in healthy children receiving both DTP and inactivated SARS-CoV-2 vaccines. Methods: A cross-sectional study was performed on 154 healthy children aged 6–8 years old in Jakarta, Indonesia. Their vaccination status of DTP (including diphtheria-tetanus booster vaccine at 5 years old) and CoronaVac (from 6 years old) were recorded. Peripheral blood samples were collected from all participants, in which anti-diphtheria toxoid IgG, anti-SARS-CoV-2 S-RBD antibodies and T cell-derived IFN-g were measured. Results: Study participants with complete DTP vaccination had significantly higher titer of anti-diphtheria toxoid IgG than the ones without (median=0.9349 versus 0.2113 IU/mL; p<0.0001). Upon stratification based on DTP and CoronaVac vaccination statuses, participants with complete DTP and CoronaVac vaccinations had the highest titer of anti-SARS-CoV-2 S-RBD antibodies (median=1,196 U/mL) and the highest concentration of SARS-CoV-2-specific T cell-derived IFN-g (median=560.9 mIU/mL) among all groups. Conclusion: Healthy children aged 6-8 years old with complete DTP and CoronaVac vaccinations exhibited higher SARS-CoV-2-specific adaptive immune responses, particularly on their T-cell response. This suggests an additional benefit of routine childhood vaccination to generate protection against novel pathogens, presumably via heterologous immunity.

We report neutralization titer data against contemporary SARS-CoV-2 sublineages from an ongoing, open-label, phase 2/3 trial of a single 30-μg dose of monovalent Omicron XBB.1.5-adapted BNT162b2 vaccine. Healthy participants had previously received ≥3 doses of a US-authorized mRNA vaccine, with the most recent being a bivalent Omicron BA.4/BA.5-adapted vaccine administered ≥150 days before study vaccination. In this analysis, Omicron XBB.1.5, BA.2.86, and JN.1 serum neutralizing titers were assessed at baseline and 1 month after vaccination in a subset of ≥18-year-olds (N = 40) with evidence of previous SARS-CoV-2 infection. Immunogenicity was also evaluated in a demographically matched group of participants who received bivalent BA.4/BA.5-adapted BNT162b2 in another study (ClinicalTrials.gov Identifier: NCT05472038). The XBB.1.5-adapted BNT162b2 vaccine elicited higher XBB.1.5, BA.2.86, and JN.1 neutralizing titers than those elicited by bivalent BA.4/BA.5-adapted BNT162b2. Overall geometric mean fold rises in neutralizing titers from baseline to 1 month after vaccination were higher among participants who received XBB.1.5-adapted BNT162b2 than those who received bivalent BA.4/BA.5-adapted BNT162b2 for XBB.1.5 (7.6 vs 5.6), slightly higher for JN.1 (3.9 vs 3.5), and similar for BA.2.86 (4.8 vs 4.9). ClinicalTrials.gov Identifier: NCT05997290.

The aim of this study was to investigate the spatio-temporal association between socio-economic deprivation and the incidence of COVID-19 and how this association changes through the seasons and due to the existence of restrictive public health measures. A retrospective observational study was conducted among COVID-19 cases that occurred in the Apulia region from 29 February 2020 to 31 December 2021, dividing the period into four phases with different levels of restrictions. A generalized estimating equations model was applied to test the independent effect of deprivation on the incidence rate of COVID-19, taking into account age, sex, and regional incidence rate as possible confounding effects and covariates such as season and levels of restrictions as possible modifying effects. The highest incidence rate was in areas with a Very High deprivation Index (DI) in winter (107.2 for 100,000 ab. ± 7.5), while in autumn, the highest Rate Ratio (RR) was estimated between Very High vs. Low DI (3.83, p<.001). During total lockdown, no RR between areas with different levels of DI was significant, while during soft lockdown, areas with Very High DI were more at risk than all other areas. The effects of social inequalities on incidence rate of COVID-19 change in as-sociation with the seasons and restrictions on public health. Disadvantaged areas showed a higher incidence rate of COVID-19 in the cold seasons and in the phases of soft lockdown.

On 9 March 2020, two cases of COVID-19 were reported in Burkina Faso. As of 10 April 2020, a total number of 484 cases (404 cases in the Kadiogo province) were reported nationwide. Real-time forecasts of COVID-19 are important to inform decision-making in the country. Here, we propose an approach that tests the performance of four models (Exponential Growth model, the Generalized Growth model (GGM), the Generalized Logistic Growth, and Richards Growth model) to select the model that best fit data and to generate short-term forecasting (5-, 10-, and 15-day forecasts from 11 to 25 April 2020) in Kadiogo, the epicenter of the outbreak. Using daily number of confirmed COVID-19 cases, the results suggests that GGM performed the best out of the 4 models. Overall, our GGM predictions suggested an average total number of cumulative cases of 514 (95% CI, 464–559), 629 (95% CI, 559–691), and 750 (95% CI, 661–840) between 11 to 15 April, 16 to 20 April, and 20 to 25 April 2020, respectively. COVID-19 in this province was best approximated by sub exponential growth rather than exponential or logistic growth. Current data suggest that COVID-19 cases would continue to increase over the next 15-days.

Background: According to metacognitive theory, Cognitive–Attentional Syndrome (CAS) is a transdiagnostic factor and main mechanism of psychopathology maintenance. The main goal of this study was to examine whether CAS predicted symptoms of stress and trauma-related symptomatology in the first months of the COVID-19 pandemic and three months later. Methods: Initially 1,792 participants were recruited online via social media; data was collected at two time points. Measures included the Cognitive–Attentional Syndrome Questionnaire, Adjustment Disorder – New Module 20, the International Trauma Questionnaire, and additional measures. Results: Structural equation modeling was conducted in order to determine relations between reported stressors, CAS, and symptomatology. At both time points, CAS was a significant mediator between stressors and symptoms of adjustment disorder. Despite the decrease in the intensity of adjustment disorder symptoms between waves, it was a significant predictor of other psychopathology at both time points, except for traumatic stress. Conclusions: The findings confirm the assumption that CAS is a transdiagnostic factor of psychopathology, and has a mediating role in the relationship between stressors and adjustment disorder and co-occurring symptomatology. The effect was particularly significant in the initial phase of the pandemic, which was highly stressful for many people.

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