The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an infectious virus, which has generated a global pandemic. Since December 20, 2020, Israel was one of the first countries to vaccinate its population. This study analyzes the weight of four covariates on a daily mortality growth rate from SARS-COV2 virus. These include population size, median age, a socio-economic ranking at a city level, a date variable and a dummy variable that equals 1 for post-vaccination and 0 for pre-vaccination era.

Regression analysis, where each variable is converted to the standard normal distribution function. This methodology permits the estimation of variations in daily mortality growth rates, where all the covariates are given in comparable units of measurement (one standard deviation). Consequently, the coefficients of this regression have to be measured as absolute value weights.

Findings suggest a rise in projected mortality growth rate with population-size and median age, and a drop with socio-economic ranking and vaccination availability. Of the four investigated covariates, population size and median age of the city have the highest weight, whereas socio-economic ranking and vaccination availability have the lowest weight.

In an effort to reduce the mortality of severe coronavirus disease (COVID19) patients, greater priority should be given to larger cities with a relatively older population profile. In particular, policies should strive for better coordination at a municipal level between health and municipal and welfare services, particularly in large cities.

The COVID-19 epidemic significantly impacted global education patterns. To protect the health of students, many countries and regions implemented online curricula during the peak of the epidemic, allowing teaching to continue despite the suspension of classes. However, whether all subjects, such as physical education (PE), can be effectively learned online is worth exploring.

To achieve the objective of this study, junior high school students in China were invited to fill out an online questionnaire via a snowball sampling method. The retrieved data were validated for reliability and validity, and the three types of online course engagement (behavioral, emotional, and cognitive) were validated through a structural equation model to explore the effects on physiological and psychological health promotion.

The results showed that not all types of online course engagement positively impacted physiological and psychological health promotion. Specifically, behavioral, cognitive, and emotional engagements were shown to positively influence students' perceived physiological health. While emotional and cognitive engagements were also shown to positively influence perceived psychological health, behavioral engagement did not significantly impact psychological health promotion. In addition, the analysis of the quality of online PE courses identified five main influencing factors: (1) lack of learning based on real experiences, (2) insufficient peer interaction, (3) environmental interference, (4) poor internet connection, and (5) poor learning uptake.

The findings showed how students' physical and mental health is promoted through behavioral, emotional, and cognitive engagement in the context of online physical education courses. At the same time, the major confounding factors identified will help physical education teachers to remove these influences and make them better at delivering online physical education programs.

Data on Long COVID and its associations with burnout, anxiety and depression among healthcare workers (HCW) in the United States (U. S.) is limited.

This study utilized cross-sectional data from the final survey conducted in July 2023, which was part of a longitudinal cohort study assessing COVID-19-related burnout and wellbeing among healthcare workers (HCWs) in a large tertiary academic healthcare system in the Chicago area. The survey included questions on self-reported Long COVID status, as well as the Oldenburg Burnout Inventory (OLBI) to measure burnout and the Patient-Reported Outcomes Measurement Information System (PROMIS) computer adaptive tests (CAT) to assess anxiety and depression. A total of 1,979 HCWs participated in the survey, yielding a response rate of 56.1%.

The analysis included 1,678 respondents with complete data, of whom 1,171 (70%) self-reported having had COVID-19. Of these, 90 (7.7%) reported Long COVID, with 53% indicating that their most bothersome symptoms persisted for more than 6 months, while 50% reported no longer experiencing those symptoms at the time of the survey. Multivariable linear regression analyses revealed that Long COVID was significantly associated with higher OLBI scores (β = 2.20, p = 0.004), PROMIS anxiety scores (β = 2.64, p = 0.001) and PROMIS depression scores (β = 1.98, p = 0.011) compared to those who had COVID-19 but not Long COVID. Similar patterns of associations were observed when comparing the Long COVID group to those who never had COVID-19. No significant differences were found between those who never had COVID-19 and those who had COVID-19 without developing Long COVID.

Long COVID was associated with higher levels of burnout, depression, and anxiety among healthcare workers compared to those who had COVID-19 alone or were never infected, despite its lower prevalence during the endemic phase. These findings underscore the need for continued prevention efforts and targeted support strategies in healthcare settings.

The extant literature is limited regarding the correlates of COVID-19 worry and preventive measures among diverse, older adults following the peak of the pandemic. Purpose of the study is to determine the correlates of post-COVID-19 pandemic worry and preventive practices (i.e., social distancing, masking) among older adults.

In 2022-2024, we conducted a cross-sectional survey of COVID-19 preventive behaviors, concerns, beliefs, and trusted sources of information in older adults in rural and urban/suburban settings in south-central Florida. A convenience sample of 522 English-speaking participants age 60 years or older were recruited using word-of-mouth, flyers, and recruitment events in urban, suburban, and rural settings. Comparisons were made for COVID-19 worry and preventive practices across key sociodemographic variables (e.g., age, sex, race/ethnicity, education, vaccination status, residence, and COVID-19 testing history) using multivariable linear and logistic regression models.

Participants (mean age 72 ± 9 years) were predominantly women (73%), Black (74%), and rural residents (57%). Greater COVID-19 worry was higher among participants who were younger, women, less educated, vaccinated, rural residents, never testing positive for COVID-19, and trusted authorities for health information. Black and Hispanic participants, as well as vaccinated individuals, were more likely to mask in public, while women and Black and Hispanic participants were more likely to practice social distancing.

Post-COVID-19 pandemic worry and preventive practices were correlated with demographics, vaccination status, and trust in health authorities. The findings underscore the importance of targeted public health messaging and interventions that consider the distinct needs and concerns of diverse older adult populations. This study's explicit focus on sociodemographic differences provides valuable insights for designing more effective pandemic preparedness and response strategies tailored to vulnerable and diverse communities.

Higher exposure to adverse childhood experiences (ACEs) has been shown to worsen the effect of COVID-19 stress on mental health problems in the early phase of the COVID-19 pandemic among young adults. This study extends that research by examining depression, anxiety, hostility, and perceived stress trajectories across successive phases of the COVID-19 pandemic in a prospective, multi-wave panel study using data collected pre-COVID-19 pandemic onset, Early pandemic, Peak pandemic, and Post-Peak pandemic.

The baseline data come from the Niagara Longitudinal Heart Study (NLHS) and the three COVID-19 waves come from a sub-study of the NLHS examining the specific impact of the pandemic. Using a Bayesian multivariate mixed-model regression framework, 171 participants who responded to at least one wave of the COVID-19 sub-study were included.

Participants with higher ACE scores and high COVID-19 stress had elevated trajectories of several poor mental health measures that stayed higher than other groups across all waves of data collection.

Young adults who reported higher ACEs were more susceptible to subsequent stress exposure, highlighting a specific, high-risk group who may benefit from targeted intervention programs during times of crisis such as the COVID-19 pandemic.

Fractional exhaled nitric oxide (FE_NO) serves as a marker of eosinophil-mediated airway inflammation and has been used in asthma diagnosis, phenotyping, and guidance regarding selection and adjustment of asthma therapy. Studies suggested that FE_NO correlated with asthma symptoms, peripheral blood eosinophil level, blood IgE level, and spirometry indicators of airway obstruction. However, the results are inconsistent across studies.

A prospective cross-sectional study was conducted in Queen Mary Hospital among adult patients with severe asthma. Patients had spirometry with bronchodilator reversibility and same-day FE_NO. Asthma control test (ACT) score and blood eosinophil and total IgE levels were measured within 4 weeks of FE_NO and spirometry. The primary outcome was the correlation of FE_NO and spirometric values. The secondary outcomes included the correlation of FE_NO with ACT score, blood eosinophil, and total IgE levels.

One hundred thirty-five severe asthma patients with FE_NO performed were included in the study. FE_NO was negatively correlated with pre-bronchodilator FEV₁ (L) (r = -0.188, p = 0.029), pre-bronchodilator FEV₁ (% predicted) (r = -0.169, p = 0.050), pre-bronchodilator FEV1/FVC ratio (r = -0.269, p = 0.002), and post-bronchodilator FEV₁/FVC (r = -0.215, p = 0.018). FE_NO was positively correlated with bronchodilator reversibility (mL) (r = 0.248, p = 0.006) and bronchodilator reversibility (%) (r = 0.823, p = 0.002), baseline blood eosinophil level by absolute cell count (r = 0.308, p < 0.001) and by percentage (r = 0.361, p < 0.001).

In adult patients with severe asthma, FE_NO might have a negative correlation with the FEV₁, FEV₁/FVC ratio, and a positive correlation with bronchodilator reversibility, as well as with blood eosinophil levels.

Although there is a high co-occurrence of psychopathological symptoms and asthma, longitudinal studies considering asthma endotypes in childhood and adolescence are scarce. Therefore, this study examined the prospective association between psychopathology in childhood and current atopic and non-atopic asthma in adolescents, considering sex and puberty-related characteristics.

The study includes 3584 participants (1790 females, 1794 males) from two German birth cohort studies, GINIplus and LISA. Psychopathological symptoms at age 10 (M = 10.06, SD = .22) were assessed by parent-reported Strengths and Difficulties Questionnaire (SDQ) and current asthma at age 15 (M = 15.07, SD = .30) was defined as a positive parent-reported medical diagnosis, wheezing, and/or medical treatment against asthma (at least two criteria). Atopic asthma was characterized as current asthma and a positive specific immunoglobulin E (IgE) test (≥0.35 kU/L), non-atopic asthma as current asthma without sensitization. Data were analyzed by logistic regression and multinomial regression models, controlling for potential covariates and confounders.

Psychopathological symptoms at age 10 were associated with asthma at age 15 (odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.04-2.92, p = .035). When examining the endotypes, this effect was replicated only for non-atopic asthma at age 15 (relative risk ratio (RRR) = 2.92, 95% CI = 1.13-7.60, p = .028), but not for atopic asthma (p = .381). Regarding the SDQ subscales, an association between peer problems at age 10 and atopic asthma at age 15 was revealed (RRR = 2.00, 95% CI 1.01-3.97, p = .048). Furthermore, significant interaction effects of puberty onset with psychopathological symptoms (p = .020), and particularly with peer problems (p = .029), were found on atopic asthma.

The findings highlight the importance of early recognition and treatment of psychopathological symptoms to prevent and reduce development, persistence and exacerbation of asthma endotypes, and point to the necessity for further research into hormonal mechanisms linking psychopathology with atopy.

Predicting T-cell receptor (TCR) recognizing antigen peptides is crucial for understanding the immune system and developing new treatments for cancer, infectious and autoimmune diseases. As experimental methods for identifying TCR-antigen recognition are expensive and time-consuming, machine-learning approaches are increasingly used. However, existing computational tools often struggle with generalization due to limited data and challenges in acquiring true non-recognition pairs and rarely integrate multiple biological features into unified frameworks. To address these challenges, we propose a two-step framework for predicting TCR-antigen recognition. The first step focuses on feature engineering: neural network-based embeddings of letter-based TCR and peptide sequences inspired by language models, and categorical encoding of Human Leukocyte Antigen types and Variable/Joining genes. In the second step, we built a prediction model to assess the likelihood of TRC-antigen recognition by a Bayesian Feedforward Neural Network. We trained and validated the framework using large public databases. Our results demonstrate that our advanced feature engineering delivers strong predictive performance both internally and externally. We applied the framework to a real-world case for predicting whether specific TCRs can recognize SARS-CoV-2 epitope peptides, demonstrating that our framework can function as a de novo TCR-antigen prediction tool applicable to infectious diseases.

Research on the sex trade during COVID-19 has documented the intertwined material and emotional hardships faced by individuals in the sex trade. Building on these insights, this article examines how self-care practices functioned as relational and strategic responses to crisis. Drawing on twenty semi-structured interviews conducted in Israel between May and December 2020, findings highlight two intersecting themes: the emotional burden caused by isolation, surveillance, and financial insecurity; and the self-care strategies participants employed to sustain themselves. These included reaching out for support, engaging in mutual aid, returning to work under duress, and setting protective boundaries. Rather than viewing self-care as a personal wellness practice, the article conceptualises it as a situated form of agency shaped by structural neglect. While the data reflect a specific historical moment, the insights they generate speak to broader questions of crisis governance, marginality, and the everyday production of resilience. By centreing the voices and practices of individuals in the sex trade, the article offers a politically attuned understanding of self-care under systemic disruption. This study offers empirical insight into how marginalised individuals navigated crisis conditions, advances a relational understanding of self-care shaped by systemic forces, and suggests the policy relevance of peer-informed, community-based approaches.

Rural hospitals struggling with prepandemic financial instability faced heightened challenges during COVID-19. While Provider Relief Funds (PRFs) offered essential support, their impact varied, highlighting the need to examine how prepandemic financial health influenced rural hospitals' financial performance during the pandemic. This study evaluates PRF's role across three hospital categories: financially strained (low operating margin), financially vulnerable (midrange operating margin), and financially strong (high operating margin).

A cohort study with a pre-post research design analyzed 2243 US rural hospitals from 2017 to 2022. The sample included short-term general acute nonfederal hospitals and Critical Access Hospitals in nonmetropolitan counties and rural tracts within metropolitan counties. Financial health was assessed using operating margin measures and total margins with and without PRF across four time periods: pre-COVID-19 (2017-2019), COVID-19 Year 1 (2020), Year 2 (2021), and Year 3 (2022).

Financially strained and vulnerable hospitals represented 85% of rural hospitals. Financially strained hospitals had the lowest average operating margins from patient services (-17.36%), trailing financially vulnerable (-3.09%), and financially strong (8.04%). In COVID-19 Year 1, operating margins declined across all categories. PRF increased total margins for financially strained hospitals to 8.39% in 2021 before dropping to 0.76% in 2022. Financially vulnerable hospitals also benefited, while financially strong hospitals remained profitable even without PRF.

PRF played a critical role in stabilizing rural hospitals, mitigating financial declines, and preventing closures. Its expiration leaves many hospitals facing renewed financial pressures. Addressing long-term financial challenges through sustainable funding strategies and operational adaptations will be essential to preserving health care access in rural communities.