The COVID-19 pandemic

Deep representation learning from electronic medical records identifies distinct symptom based subtypes and progression patterns for COVID-19 prognosis

OBJECTIVE

Symptoms are significant kind of phenotypes for managing and controlling of the burst of acute infectious diseases, such as COVID-19. Although patterns of symptom clusters and time series have been considered the high potential prediction factors for the prognosis of patients, the elaborated subtypes and their progression patterns based on symptom phenotypes related to the prognosis of COVID-19 patients still need be detected. This study aims to investigate patient subtypes and their progression patterns with distinct features of outcome and prognosis.

METHODS

This study included a total of 14,139 longitudinal electronic medical records (EMRs) obtained from four hospitals in Hubei Province, China, involving 2,683 individuals in the early stage of COVID-19 pandemic. A deep representation learning model was developed to help acquire the symptom profiles of patients. K-means clustering algorithm is used to divide them into distinct subtypes. Subsequently, symptom progression patterns were identified by considering the subtypes associated with patients upon admission and discharge. Furthermore, we used Fisher's test to identify significant clinical entities for each subtype.

RESULTS

Three distinct patient subtypes exhibiting specific symptoms and prognosis have been identified. Particularly, Subtype 0 includes 44.2% of the whole and is characterized by poor appetite, fatigue and sleep disorders; Subtype 1 includes 25.6% cases and is characterized by confusion, cough with bloody sputum, encopresis and urinary incontinence; Subtype 2 includes 30.2% cases and is characterized by dry cough and rhinorrhea. These three subtypes demonstrate significant disparities in prognosis, with the mortality rates of 4.72%, 8.59%, and 0.25% respectively. Furthermore, symptom cluster progression patterns showed that patients with Subtype 0 who manifest dark yellow urine, chest pain, etc. in the admission stage exhibit an elevated risk of transforming into the more severe subtypes with poor outcome, whereas those presenting with nausea and vomiting tend to incline towards entering the milder subtype.

CONCLUSION

This study has proposed a clinical meaningful approach by utilizing the deep representation learning and real-world EMR data containing symptom phenotypes to identify the COVID-19 subtypes and their progression patterns. The results would be potentially useful to help improve the precise stratification and management of acute infectious diseases.

Rapid and specific detection of nanoparticles and viruses one at a time using microfluidic laminar flow and confocal fluorescence microscopy

Mainstream virus detection relies on the specific amplification of nucleic acids via polymerase chain reaction, a process that is slow and requires extensive laboratory expertise and equipment. Other modalities, such as antigen-based tests, allow much faster virus detection but have reduced sensitivity. In this study, we introduce an approach for rapid and specific detection of single nanoparticles using a confocal-based flow virometer. The combination of laminar flow in a microfluidic channel and correlated fluorescence signals emerging from both free dyes and fluorescently labeled primary antibodies provide insights into nanoparticle volumes and specificities. We evaluate and validate the assay using fluorescent beads and viruses, including SARS-CoV-2 with fluorescently labeled primary antibodies. Additionally, we demonstrate how hydrodynamic focusing enhances the assay sensitivity for detecting viruses at relevant loads. Based on our results, we envision the future use of this technology for clinically relevant bio-nanoparticles, supported by the implementation of the assay in a portable and user-friendly setup.

Impact of tourism on metal concentrations in Phorcus sauciatus due to the COVID-19 pandemic period in Canary Islands (CE Atlantic, Spain)

The pandemic (COVID-19) had diverse effects on marine pollution. Throughout the lockdown periods, temporary enhancements in water quality and biodiversity were observed due to reduced human activity and constraints on travel and maritime transportation. The marine snail, Phorcus sauciatus, served as an indicator for marine pollution, and samples were collected in Tenerife, Canary Islands, during various months in 2020. The findings indicated that metal concentrations in Phorcus sauciatus were higher in February but declined in July and December as a result of reduced tourist activity during the pandemic. This underscores the significance of promoting sustainable tourism in the Canary Islands to mitigate high metal concentrations in the marine environment. The COVID-19 pandemic had a positive impact on reducing metal concentrations in marine pollution, underscoring the importance of adopting sustainable tourism practices to protect marine ecosystems.

Analyzing pain patterns in the emergency department: Leveraging clinical text deep learning models for real-world insights

OBJECTIVE

To determine the incidence of patients presenting in pain to a large Australian inner-city emergency department (ED) using a clinical text deep learning algorithm.

MATERIALS AND METHODS

A fine-tuned, domain-specific, transformer-based clinical text deep learning model was used to interpret free-text nursing assessments in the electronic medical records of 235,789 adult presentations to the ED over a three-year period. The model classified presentations according to whether the patient had pain on arrival at the ED. Interrupted time series analysis was used to determine the incidence of pain in patients on arrival over time. We described the changes in the population characteristics and incidence of patients with pain on arrival occurring with the start of the Covid-19 pandemic.

RESULTS

55.16% (95%CI 54.95%-55.36%) of all patients presenting to this ED had pain on arrival. There were differences in demographics and arrival and departure patterns between patients with and without pain. The Covid-19 pandemic initially precipitated a decrease followed by a sharp, sustained rise in pain on arrival, with concurrent changes to the population arriving in pain and their treatment.

DISCUSSION

Applying a clinical text deep learning model has successfully identified the incidence of pain on arrival. It represents an automated, reproducible mechanism to identify pain from routinely collected medical records. The description of this population and their treatment forms the basis of intervention to improve care for patients with pain. The combination of the clinical text deep learning models and interrupted time series analysis has reported on the effects of the Covid-19 pandemic on pain care in the ED, outlining a methodology to assess the impact of significant events or interventions on pain care in the ED.

CONCLUSION

Applying a novel deep learning approach to identifying pain guides methodological approaches to evaluating pain care interventions in the ED, giving previously unavailable population-level insights.

Impact of diffusion on synchronization pattern of epidemics in non-identical meta-population networks

In epidemic networks, it has been demonstrated that implementing any intervention strategy on nodes with specific characteristics (such as a high degree or node betweenness) substantially diminishes the outbreak size. We extend this finding with a disease-spreading meta-population model using testkits to explore the influence of migration on infection dynamics within the distinct communities of the network. Notably, we observe that nodes equipped with testkits and no testkits tend to segregate into two separate clusters when migration is low, but above a critical migration rate, they coalesce into one single cluster. Based on this clustering phenomenon, we develop a reduced model and validate the emergent clustering behavior through comprehensive simulations. We observe this property in both homogeneous and heterogeneous networks.

Prevalence of schistosomiasis and its association with anemia in Ethiopia, 2024: a systematic review and meta‑analysis

BACKGROUND

Schistosomiasis is a neglected tropical disease that affects over 250 million people, predominantly in impoverished communities, including those in Ethiopia. However, there is currently no available national data regarding its prevalence in Ethiopia or its potential association with anemia.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA-2020) guideline was followed in our study. A comprehensive search strategy was conducted using international databases (PUB Med, Embase, Scopus, and Science Direct) and websites (Google Scholar and Google) from their date of inception to April 22, 2024. The quality of the retrieved studies was assessed using an adapted version of the Newcastle-Ottawa Scale. Publication bias and statistical heterogeneity were statistically assessed. A random effects model was applied, and all analysis was performed with STATA 17 statistical software.

RESULT

The prevalence of schistosomiasis was assessed in twelve studies with 5747 participants. S. mansoni was studied in 11 research papers, while S. hematobium was assessed in one study. Using a random effect model due to high heterogeneity (I2 = 98.46%; P < 0.001), the overall pooled prevalence of schistosomiasis in Ethiopia was 22% (95% CI: 14.3, 29.6). The prevalence of schistosomiasis was about two and a half times higher in rural settings (23%) (95% CI: 15, 31) than in urban areas (10%) (95% CI: 3, 17). The burden of schistosomiasis was 23% between 2020 and 2024, compared to 16% from 2015-2019, with a higher prevalence among pediatric age groups (22%) versus 14% in mixed pediatric and adult age groups. The magnitude of schistosomiasis for good and very good-quality papers was 22% and 17%, respectively. In all the subgroup analyses, there was considerable statistically significant heterogeneity. No study was found to evaluate the association of schistosomiasis with anemia.

CONCLUSION

The study reveals Ethiopia's higher schistosomiasis prevalence. Rural areas have a high burden of schistosomiasis. No eligible study was found to evaluate the association of schistosomiasis with anemia. Therefore, prevention and control measures should focus on rural settings.

TRIAL REGISTRATION

The registration number at PROSPERO is CRD42024538522.

The Impact of COVID-19 on Functional Capacity and Pulmonary Outcomes in the Hail Region: A Cross-Sectional Study

Background/Objectives: COVID-19, caused by the novel coronavirus SARS-CoV-2, has had a significant impact on life worldwide since its emergence in late 2019. The virus has caused a global pandemic, leading to widespread health, social, economic, and psychological effects. COVID-19 mainly affects the respiratory system. This study aimed to compare the functional capacity and pulmonary function outcomes between COVID-19 patients and individuals who have not been infected in the Hail region. Methods: Individuals of both genders above 18 years old who had been infected with COVID-19 in the previous 6 months or had never been infected were eligible to participate. Local hospitals and social media apps were used to recruit willing participants. Heart rate, pulse oxygen saturation, blood pressure, pulmonary function test, hand grip strength, and functional tests (6 min walk test, 30 s sit-to-stand test, and timed up and go test) were measured and compared between the groups. Statistical analysis was performed using SPSS Version 25. Results: Forty individuals affected with COVID-19 and forty-one healthy individuals were recruited. Our results showed that in individuals affected with COVID-19, scores on the minute ventilation, 30 s sit-to-stand, and 6 min walk tests were significantly lower than among healthy individuals. Other outcomes did not show any statistical differences between the groups. Conclusion: This study contributes to a greater understanding of the functional capacity status of individuals with COVID-19. Patients affected by COVID-19 may develop an impaired lung capacity and a decreased function capacity. These factors may negatively affect physical and cognitive health status. Future studies should evaluate the benefits of interventions with rehabilitation exercises following COVID-19. In light of the functional capacity and pulmonary function decline in individuals affected by COVID-19, interventions encompassing pulmonary and functional rehabilitation exercises are recommended to improve physical fitness and pulmonary function post-COVID-19.

Integration of a Cas12a-mediated DNAzyme actuator with efficient RNA extraction for ultrasensitive colorimetric detection of viral RNA

Developing highly sensitive and specific on-site tests is imperative to strengthen preparedness against future emerging infectious diseases. Here, we describe the construction of a Cas12a-mediated DNAzyme actuator capable of converting the recognition of a specific DNA sequence into an amplified colorimetric signal. To address viral RNA extraction challenges for on-site applications, we developed a rapid and efficient method capable of lysing the viral particles, preserving the released viral RNA, and concentrating the viral RNA. Integration of the DNAzyme actuator with the viral RNA extraction method and loop-mediated isothermal amplification enables a streamlined colorimetric assay for highly sensitive colorimetric detection of respiratory RNA viruses in gargle and saliva. This assay can detect as few as 83 viral particles/100 μL in gargle and 166 viral particles/100 μL in saliva. The entire assay, from sample processing to visual detection, was completed within 1 h at a single controlled temperature. We validated the assay by detecting SARS-CoV-2 in 207 gargle and saliva samples, achieving a clinical sensitivity of 96.3 % and specificity of 100%. The assay is adaptable for detecting specific nucleic acid sequences in other pathogens and is suitable for resource-limited settings.

Causes of Hospitalization in Children with Down Syndrome

Background and Objectives: Down syndrome (DS) is the most common chromosomal disorder in the world. It is caused by the imbalance of the chromosomal constitution of 21 by free trisomy, translocation or mosaicism. Children and adolescents with Down syndrome have immune dysregulation and are more susceptible to infections. This study aims to evaluate hospitalizations of children and adolescents with DS in the pediatric ward of Botucatu Clinics Hospital (HCFMB) and to classify the population of children included in the study according to age, diagnosis, outpatient follow-up, length of stay and need for the intensive care unit (ICU). Thus, it will be possible to improve care for these children, aiming to reduce these hospitalizations. Materials and Methods: This study was an observational, cross-sectional study, with retrospective data collected from the last nine years of hospitalization, from January 2013 to December 2021, from children and adolescents with DS in the pediatric ward, emergency room, and the ICU of HCFMB. Children hospitalized in this period in the pediatric ward and ICU, in the age range of 30 days to 15 years, were included in this study. The evaluation of comorbidities that culminated in the need for hospitalization in this population can be the focus of actions to improve the diagnoses and conducts for this population, which can prevent worsening illness and hospitalizations in future populations. Results: In this analysis, 80 children with DS were evaluated, with a total of 283 hospitalizations. The most prevalent age group was 1 to 3 years, and the main cause was due to problems in the respiratory system (99 cases). Among the respiratory causes, the main cause of hospitalization was due to pneumonia in 50% of cases, followed by acute respiratory failure in 14%. The average hospitalization time was 8 days, and in 49 hospitalizations, the children required the ICU. The main cause of hospitalization in the ICU was due to respiratory causes (36%), followed by cardiac malformations (14%). During the ICU hospitalizations, there were 13 deaths, and we observed a higher prevalence of heart conditions and, in some cases, positive urine cultures in these children. Conclusions: The Hospital serves as a reference for pediatric hospitalizations within its region and beyond, owing to its specialized capabilities. The main causes of hospitalization were those related to the respiratory system and cardiac malformations. Roughly one-third of the children required admission to the intensive care unit.

Investigation of the Relationship between Vitamin D Deficiency and Vitamin D-Binding Protein Polymorphisms in Severe COVID-19 Patients

This study explores the association of vitamin D-binding protein (VDBP) gene polymorphisms, vitamin D levels, and the severity of COVID-19, including the need for intensive care unit (ICU) hospitalization. We analyzed a cohort of 56 consecutive age- and gender-matched adult COVID-19-positive patients and categorized them into three groups: outpatients with mild illness, inpatients with moderate disease, and ICU patients. We measured levels of free, total, and bioavailable 25-hydroxyvitamin D [25(OH)D], VDBP, and albumin. VDBP polymorphisms rs5488 and rs7041 were identified using real-time PCR. A significant proportion of ICU patients were vitamin D-deficient (56.25%) compared to outpatients (10%) and inpatients (5%) (p = 0.0003). ICU patients also had notably lower levels of VDBP (median: 222 mg/L) and total 25(OH)D (median: 18.8 ng/mL). Most patients carried heterozygous rs7041 (60.7%) and wild-type rs4588 (58.9%) genotypes. The distribution of rs7041 SNP varied significantly among groups (p = 0.0301), while rs4588 SNP distribution did not (p = 0.424). Heterozygous rs4588 patients had significantly lower VDBP levels (p = 0.029) and reduced bioavailable 25(OH)D compared to those with wild-type rs4588 (p = 0.020). Our findings indicate that VDBP gene polymorphisms, particularly rs7041 and rs4588, are associated with vitamin D status and the severity of COVID-19. The lower VDBP levels and bioavailable vitamin D in ICU patients suggest that these genetic variants may influence disease severity and hospitalization needs. These results highlight the potential role of VDBP polymorphisms in COVID-19 severity, suggesting that genetic screening could be valuable in assessing the risk of severe outcomes and guiding personalized treatment strategies.

The Effect of the COVID-19 Pandemic on Suicide Trends in Pretoria, South Africa

ABSTRACT

Suicide is one of the worldwide leading causes of unnatural death. Pretoria is a capital city of South Africa and is the fourth most populated city in South Africa. Between 16 and 22 suicide cases are recorded daily in South Africa.Case files from the Pretoria Medico-Legal Laboratory were reviewed between 1 January 2015 to 31 December 2021, which spanned the COVID-19 pandemic. All cases of possible and probable suicides were included. One-way analysis of variance and Pearson chi 2 tests were conducted to determine statistical significance in the observed trends.A total of 1820 possible and probable suicide cases were identified. The year following the outbreak of the COVID-19 pandemic accounted for the largest number of suicides. White males were the most heavily represented population, followed by Black males. Hanging was the most common method for males, whereas poisoning via ingestion and/or overdose was more commonly used by females.Suicides in Pretoria have increased since previous studies from 9.74% and 10.2% to 13.32%. Methods used have changed among various population groups over the past two decades. This paper examined changes in suicide trends in Pretoria compared to previous studies and highlighted correlations between suicide trends and COVID-19 lockdown measures.

Data-driven mathematical modeling approaches for COVID-19: A survey

In this review, we successively present the methods for phenomenological modeling of the evolution of reported and unreported cases of COVID-19, both in the exponential phase of growth and then in a complete epidemic wave. After the case of an isolated wave, we present the modeling of several successive waves separated by endemic stationary periods. Then, we treat the case of multi-compartmental models without or with age structure. Eventually, we review the literature, based on 260 articles selected in 11 sections, ranging from the medical survey of hospital cases to forecasting the dynamics of new cases in the general population. This review favors the phenomenological approach over the mechanistic approach in the choice of references and provides simulations of the evolution of the number of observed cases of COVID-19 for 10 states (California, China, France, India, Israel, Japan, New York, Peru, Spain and United Kingdom).

Navigating the waves: A systematic review of telemedicine interventions and health service access challenges in epilepsy during COVID-19

INTRODUCTION

The COVID-19 pandemic has dramatically reshaped the landscape of healthcare delivery, prompting a surge in the adoption of telemedicine as a means to ensure continuity of care. During the pandemic, patients with epilepsy experienced difficulties accessing healthcare and obtaining necessary medications, with a substantial percentage facing obstacles in acquiring anti-seizure medication and reaching healthcare professionals. Disruptions in the supply and distribution of medication, due to COVID-19-related actions, further caused more problems for people with epilepsy and their caregivers like increasing seizure frequency. The pandemic has also accelerated the adoption of telemedicine, with evidence suggesting its potential benefits in various medical fields. In this systematic review and meta-analysis, we aim to investigate the challenges faced by patients with epilepsy during the COVID-19 pandemic, including healthcare access and medication acquisition, as well as evaluate changes in seizure frequency. Additionally, we will synthesize existing evidence on the use of telemedicine to address the healthcare needs of these patients, exploring its advantages and limitations.

METHODS

This systematic review was prepared using PRISMA reporting guidelines. The databases searched were PubMed, Scopus, Web of Science, and Cochrane. Risk of Bias was assessed using Joanna Briggs Institute (JBI). Following rigorous application of eligibility criteria, relevant data, covering both telemedicine-related and health service access information, were methodically extracted and organized using Microsoft Excel spreadsheets. The analytical procedures were executed through the utilization of Comprehensive Meta-Analysis (CMA) software.

RESULTS

A total of 70 articles included in this review. Regarding difficulties in accessing healthcare, 34% of PWE and 41% of caregivers experienced cancelled, changed or postponed appointments. Following issues with obtaining medicine, 13% of patients and 16% of caregivers had difficulties in medicine availability and 11% of patients and 10% of caregivers in medicine accessibility. A very high rate of 90% satisfaction with telemedicine was reported by PWE. 17.6% of PWE experienced an escalation, 9% a decrease and 67% no changes in seizure frequency.

CONCLUSION

This review and meta-analysis revealed that telemedicine and virtual communications have been helpful but not sufficient for meeting healthcare needs for PWE during the COVID-19 pandemic. Additionally, there was a significant increase in seizure frequency among PWE who had difficulty obtaining medicine and access to healthcare.

Impact of narcotics information management system on inappropriate benzodiazepine receptor agonist prescriptions: A quasi-experimental analysis in South Korea

AIMS

The South Korean government implemented the narcotics information management system (NIMS) on 18 May 2018 to manage benzodiazepine receptor agonists (BzRAs) and narcotics effectively and establish a reporting mechanism for these drugs. This study assessed the effects of NIMS on inappropriate use of BzRAs.

METHODS

Using national patient sample data from 2016 to 2020, we analysed adult outpatients who were prescribed oral BzRAs. We conducted a time series and segmented regression analysis using selected indicators to analyse the monthly variations related to the inappropriate use of these medications.

RESULTS

The study revealed no significant changes in the indicators of inappropriate BzRA use following the NIMS implementation. Contrary to expectations, there was a significant increase in the proportion of patients exceeding defined daily dose (DDD) and in those receiving concurrent prescriptions of multiple BzRAs, following the implementation of NIMS. The immediate impact of the COVID-19 pandemic was an increase in DDD exceedance; however, overall, this did not significantly affect BzRA use.

CONCLUSIONS

The introduction of NIMS did not significantly enhance the management of BzRA misuse. Additional measures, including continuous monitoring, system improvements and comprehensive education for prescribers and patients, are recommended to ensure the appropriate use of psychotropic medications.

An emerging network for COVID-19 CT-scan classification using an ensemble deep transfer learning model

Over the past few years, the widespread outbreak of COVID-19 has caused the death of millions of people worldwide. Early diagnosis of the virus is essential to control its spread and provide timely treatment. Artificial intelligence methods are often used as powerful tools to reach a COVID-19 diagnosis via computed tomography (CT) samples. In this paper, artificial intelligence-based methods are introduced to diagnose COVID-19. At first, a network called CT6-CNN is designed, and then two ensemble deep transfer learning models are developed based on Xception, ResNet-101, DenseNet-169, and CT6-CNN to reach a COVID-19 diagnosis by CT samples. The publicly available SARS-CoV-2 CT dataset is utilized for our implementation, including 2481 CT scans. The dataset is separated into 2108, 248, and 125 images for training, validation, and testing, respectively. Based on experimental results, the CT6-CNN model achieved 94.66% accuracy, 94.67% precision, 94.67% sensitivity, and 94.65% F1-score rate. Moreover, the ensemble learning models reached 99.2% accuracy. Experimental results affirm the effectiveness of designed models, especially the ensemble deep learning models, to reach a diagnosis of COVID-19.

Investigating the pathogenesis of vitreous in postmortem COVID patients via untargeted metabolomics based bioinformatics model

SARS-CoV-2 virus has become a worldwide pandemic causing millions of death. This severe disaster lead to a immense panic and stress all over the world. Several studies were dedicated to understand its mechanism, pathogenesis and spreading characteristics. By this way, scientists try to develop different therapy and diagnose strategies. For these reasons, several metabolomics, proteomics and genomics studies were also carried out to improve knowledge in this newly identified virus. In this study, we are aimed to explain the pathogenesis of SARS-CoV-2 exposure on postmortem COVID (+) patients via untargeted metabolomics analysis. To carry out this study, a Data Independent Acquisition SWATH method is optimized and performed. Vitreous samples were analyzed in both MS1 and MS2 ESI(+) mode. An orthogonal Partial Least Square Discriminant Analysis were performed for classification. It was observed that lipid metabolism, several amino acids and oxidative stress biomarkers were strongly affected due to high inflammation and possible cytokine storm.

Long COVID patients' brain activation is suppressed during walking and severer symptoms lead to stronger suppression

This research aims to study the factors contributing to Long COVID and its effects on motor and cognitive brain regions using population surveys and brain imaging. The goal is to provide new insights into the neurological effects of the illness and establish a basis for addressing neuropsychiatric symptoms associated with Long COVID. Study 1 used a cross-sectional design to collect data on demographic characteristics and factors related to Long COVID symptoms in 551 participants. In Study 2, subjects with Long COVID and SARS-CoV-2 uninfected individuals underwent fNIRS monitoring while performing various tasks. Study 1 found that gender, age, BMI, Days since the first SARS-CoV-2 infection, and Symptoms at first onset influenced Long COVID performance. Study 2 demonstrated that individuals in the SARS-CoV-2 uninfected group exhibited greater activation of cognitive function-related brain regions than those in the Long COVID group while performing a level walking task. Furthermore, individuals in the Long COVID group without functional impairment displayed higher activation of brain regions associated with motor function during a weight-bearing walking task than those with functional impairment. Among individuals with Long COVID, those with mild symptoms at onset exhibited increased activation of brain regions linked to motor and cognitive function relative to those with moderate symptoms at onset. Individuals with Long COVID exhibited decreased activation in brain regions associated with cognitive and motor function compared to SARS-CoV-2 uninfected individuals. Moreover, those with more severe initial symptoms or functional impairment displayed heightened inhibition in these brain regions.

Public perception on face mask wearing during COVID-19 pandemic in Malaysia: A cross sectional study

INTRODUCTION

Since the emergence of COVID-19, the Malaysian government has made wearing a face mask in public mandatory since August 1, 2020, as an effort by the government to control the transmission of COVID-19. However, Malaysians' willingness to wear face masks in public is unknown.

OBJECTIVE

Thus, this study aimed to evaluate their perception of face mask wearing during COVID-19 and its contributing factors.

METHODOLOGY

A total of 1024 respondents, aged ≥ 18 years, participated in this online cross-sectional survey from October 2021 to December 2021. The Face Mask Perception Scale (FMPS) was used to measure their perceptions.

RESULTS

Most of the respondents perceived wearing a face mask as uncomfortable. Our findings also revealed statistically significant differences and a small effect (f2 = 0.04) in which respondents who were concerned about being infected by the virus perceived face mask wearing appearance positively (B = - 0.09 units of log-transformed, 95% CI = - 0.15, - 0.04), whereas married respondents perceived it negatively (B = 0.07 units of log-transformed, 95% CI = 0.03, 0.09). There were no statistically significant differences in other domains of FMPS.

CONCLUSION

In conclusion, discomfort was a major complaint. Marital status and fear of COVID-19 infection affected their perceptions. The public health implications of these findings highlight the importance of addressing discomfort and societal perceptions, particularly those influenced by factors such as marital status and COVID-19 experience, to promote widespread acceptance and consistent usage of face masks, which is crucial in mitigating the spread of COVID-19.

Novel SARS-CoV-2 inhibition properties of the anti-cancer Kang Guan Recipe herbal formula

The ongoing COVID-19 pandemic is a persistent challenge, with continued breakthrough infections despite vaccination efforts. This has spurred interest in alternative preventive measures, including dietary and herbal interventions. Previous research has demonstrated that herbal medicines can not only inhibit cancer progression but also combat viral infections, including COVID-19 by targeting SARS-CoV-2, indicating a multifaceted potential to address both viruses and cancer. Here, we found that the Kang Guan Recipe (KGR), a novel herbal medicine formula, associates with potent inhibition activity against the SARS-CoV-2 viral infection. We demonstrate that KGR exhibits inhibitory activity against several SARS-CoV-2 variants of concern (VOCs). Mechanistically, we found that KGR can block the interaction of the viral spike and human angiotensin-converting enzyme 2 (ACE2). Furthermore, we assessed the inhibitory effect of KGR on SARS-CoV-2 viral entry in vivo, observing that serum samples from healthy human subjects having taken KGR exhibited suppressive activity against SARS-CoV-2 variants. Our investigation provides valuable insights into the potential of KGR as a novel herbal-based preventive and therapeutic strategy against COVID-19.

Seafood Consumption Trends among U.S. Consumers: Influences of the COVID-19 Pandemic

The Dietary Guidelines for Americans (DGA) recommend twice-weekly consumption of seafood for health benefits, yet many U.S. consumers have historically fallen short of this target. The economic and societal impacts of the COVID-19 pandemic brought concern about further declines in seafood intake. This study evaluated the influence of COVID-19 on seafood intake among U.S. residents, toward understanding potential public health implications. A nationally representative cross-sectional survey of 1200 U.S. residents conducted in June 2021 evaluated the frequency and types of seafood consumed, and purchase methods used, before and during the early stages of the COVID-19 pandemic. The results (weighted data) indicate most U.S. consumers (90%) eat seafood, yet only 19% meet the seafood DGA. The likelihood of meeting the DGA was higher among consumers who were Asian, Black, or Hispanic; older; unmarried; of higher income; familiar with the DGA; choosing seafood for health reasons; and living in Atlantic or Gulf coast states. During COVID-19, some increased seafood intake for health reasons (45%), while others reduced intake due to factors such as cost (29%), limited availability (16%), and challenges with preparation (11%). Fresh salmon (68%), frozen shrimp (59%), and cooked oysters (41%) were most frequently purchased by consumers of these foods. More consumers indicated purchasing wild salmon (62%), shrimp (44%), and oysters (51%) than farm-raised products, though many were unsure. Fewer consumers included seafood in online grocery orders (36%) than meal kit orders (61%) when using these services. Though many consumers continued to eat seafood despite decreased restaurant patronage, most did not reach the intake level needed to maximize health benefits. Educational and marketing efforts promoting the health benefits of seafood and the convenience of procurement via online purchase methods may encourage intake across demographic groups to benefit public health outcomes in the U.S.

Hyperglycemia induced cathepsin L maturation linked to diabetic comorbidities and COVID-19 mortality

Diabetes, a prevalent chronic condition, significantly increases the risk of mortality from COVID-19, yet the underlying mechanisms remain elusive. Emerging evidence implicates Cathepsin L (CTSL) in diabetic complications, including nephropathy and retinopathy. Our previous research identified CTSL as a pivotal protease promoting SARS-CoV-2 infection. Here, we demonstrate elevated blood CTSL levels in individuals with diabetes, facilitating SARS-CoV-2 infection. Chronic hyperglycemia correlates positively with CTSL concentration and activity in diabetic patients, while acute hyperglycemia augments CTSL activity in healthy individuals. In vitro studies reveal high glucose, but not insulin, promotes SARS-CoV-2 infection in wild-type cells, with CTSL knockout cells displaying reduced susceptibility. Utilizing lung tissue samples from diabetic and non-diabetic patients, alongside Leprdb/dbmice and Leprdb/+mice, we illustrate increased CTSL activity in both humans and mice under diabetic conditions. Mechanistically, high glucose levels promote CTSL maturation and translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. Our findings underscore the pivotal role of hyperglycemia-induced CTSL maturation in diabetic comorbidities and complications.

Epidemiological changes in respiratory pathogen transmission among children with acute respiratory infections during the COVID-19 pandemic in Kunming, China

BACKGROUND

Acute respiratory infections are a leading cause of morbidity and mortality in children. However, studies on the prevalence of respiratory viruses among children with acute respiratory infections in Kunming, China, are lacking. Therefore, we aimed to investigate the epidemiological characteristics of respiratory pathogens among children with acute respiratory infections in Kunming during the coronavirus disease 2019 pandemic.

METHODS

Nasopharyngeal swab samples were collected from 4956 children with acute respiratory infections at Yunnan Provincial First People's Hospital between January 2020 and December 2022, patients with COVID-19 were excluded from the study. Multiplex reverse transcription polymerase chain reaction was used to detect respiratory pathogens.

RESULTS

The frequency of respiratory pathogens among children was significantly lower in 2020 than in 2021 and 2022. The following pathogens had the highest prevalence rates (in descending order) from 2020 to 2022: HRV > RSV > PIV > ADV > MP; HRV > RSV > HADV > PIV > MP and HRV > Mp > HADV > H3N2 > HMPV. The overall frequency of respiratory pathogens exhibited an inverted U-shape with increasing age among the children. Human bocavirus, human parainfluenza virus, and human respiratory syncytial virus were the dominant respiratory viruses in children aged ≤ 3 years, whereas Mycoplasma pneumoniae was the dominant respiratory pathogen in children aged > 3 years. HRV has the highest prevalence and is the main pathogen of mixed infection. The prevalence of the influenza A virus has decreased significantly, whereas HRSV and Mp are found to be seasonal.

CONCLUSIONS

Our findings offer an objective evaluation of transmission dynamics and epidemiological shifts in respiratory pathogens during the coronavirus disease 2019 pandemic in Kunming, serving as a basis for informed decision-making, prevention, and treatment strategies.

Cerebellitis following COVID-19 infection: A case-based systematic review and pooled analysis

Background

The COVID-19 pandemic has been linked to neurological complications, including Cerebellitis. This study aims to investigate the clinical features, and consequences of Cerebellitis following COVID-19 infection, informing medical management strategies.

Methods

A systematic search was conducted through PubMed, Web of Science, Embase, ProQuest, and Cochrane databases from January 2018 to September 12, 2023, on cases post-COVID-19. Demographics, clinical characteristics, and diagnostic techniques were analyzed using descriptive statistics. Chi-Square tests assessed associations between diagnoses and treatments, with visualizations including heatmaps and scatter plots.

Results

After the final Screening, the analysis of 18 cases revealed Cerebellitis post-COVID-19 spanned 9 countries, predominantly from the USA (27.8 %), with a mean patient age of 40.1 years (±24.6). Males comprised 94.4 % of cases. Common underlying conditions included hypertension (22.2 %) and diabetes (11.1 %). Neurological symptoms presented on average 15.15 ± 12.7 days post-COVID-19 infection. A moderate negative correlation (r = -0.358) was observed between age and symptom onset. Blood and CSF biomarkers showed weak correlations with symptom onset intervals. Treatment efficacy varied, with most cases achieving symptom-free outcomes. The Chi-Square test for diagnosis-treatment associations yielded a p-value of 0.089, and for follow-up outcomes, a p-value of 0.283, indicating no significant statistical associations.

Conclusion

This systematic review highlights increased reports of Cerebellitis in males in their fourth decade of life, with the highest comorbidities being vascular diseases. Marker assessments show a decrease in CSF protein in half of patients, along with complete recovery following combination treatment with antivirals and steroids in acute Cerebellitis.

Tracking Antibiotic Resistance Trends in Central Iran Amidst the COVID-19 Pandemic From 2021 to 2023: A Comprehensive Epidemiological Study

Background

The emergence of coronavirus disease in 2019 (COVID-19) appears to be having an impact on antibiotic resistance patterns. Specific circumstances during the COVID-19 era may have played a role in the spread of antimicrobial resistance (AMR). This study aimed to look at the changes in AMR patterns of Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii at Al-Zahra Hospital.

Materials and Methods

From March 2021 to January 2023, 3651 clinical samples were collected from patients hospitalized at Isfahan's Al-Zahra Hospital. The Clinical and Laboratory Standards Institute recommended procedures for detecting gram-negative bacteria and assessing antibiotic susceptibility were used. We divided the information into three years.

Results

Highest resistance rates were seen in A. baumannii to Ciprofloxacin (98.0%) and Ampicillin-Sulbactam (97.0%). For P. aeruginosa the resistance rate for Ceftazidime (36.1), Levofloxacin (37.8), and Meropenem (47.1) dropped seriously in 2022.

Conclusion

During the second year of the pandemic in central Iran, all three species studied showed rising rates of AMR. This can be attributable to two peaks within Iran on May 6, 2021 and August 27, 2021. The results of this study show that P. aeruginosa, K. pneumoniae, and A. baumannii bacteria in central Iran have a higher level of antibiotic resistance than previously studied strains before the pandemic.

CO-19 PDB 2.0: A Comprehensive COVID-19 Database with Global Auto-Alerts, Statistical Analysis, and Cancer Correlations

Biological databases serve as critical basics for modern research, and amid the dynamic landscape of biology, the COVID-19 database has emerged as an indispensable resource. The global outbreak of Covid-19, commencing in December 2019, necessitates comprehensive databases to unravel the intricate connections between this novel virus and cancer. Despite existing databases, a crucial need persists for a centralized and accessible method to acquire precise information within the research community. The main aim of the work is to develop a database which has all the COVID-19-related data available in just one click with auto global notifications. This gap is addressed by the meticulously designed COVID-19 Pandemic Database (CO-19 PDB 2.0), positioned as a comprehensive resource for researchers navigating the complexities of COVID-19 and cancer. Between December 2019 and June 2024, the CO-19 PDB 2.0 systematically collected and organized 120 datasets into six distinct categories, each catering to specific functionalities. These categories encompass a chemical structure database, a digital image database, a visualization tool database, a genomic database, a social science database, and a literature database. Functionalities range from image analysis and gene sequence information to data visualization and updates on environmental events. CO-19 PDB 2.0 has the option to choose either the search page for the database or the autonotification page, providing a seamless retrieval of information. The dedicated page introduces six predefined charts, providing insights into crucial criteria such as the number of cases and deaths', country-wise distribution, 'new cases and recovery', and rates of death and recovery. The global impact of COVID-19 on cancer patients has led to extensive collaboration among research institutions, producing numerous articles and computational studies published in international journals. A key feature of this initiative is auto daily notifications for standardized information updates. Users can easily navigate based on different categories or use a direct search option. The study offers up-to-date COVID-19 datasets and global statistics on COVID-19 and cancer, highlighting the top 10 cancers diagnosed in the USA in 2022. Breast and prostate cancers are the most common, representing 30% and 26% of new cases, respectively. The initiative also ensures the removal or replacement of dead links, providing a valuable resource for researchers, healthcare professionals, and individuals. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://www.co-19pdb.habdsk.org/. Database URL: https://www.co-19pdb.habdsk.org/.

Encoder-decoder convolutional neural network for simple CT segmentation of COVID-19 infected lungs

This work presents the application of an Encoder-Decoder convolutional neural network (ED-CNN) model to automatically segment COVID-19 computerised tomography (CT) data. By doing so we are producing an alternative model to current literature, which is easy to follow and reproduce, making it more accessible for real-world applications as little training would be required to use this. Our simple approach achieves results comparable to those of previously published studies, which use more complex deep-learning networks. We demonstrate a high-quality automated segmentation prediction of thoracic CT scans that correctly delineates the infected regions of the lungs. This segmentation automation can be used as a tool to speed up the contouring process, either to check manual contouring in place of a peer checking, when not possible or to give a rapid indication of infection to be referred for further treatment, thus saving time and resources. In contrast, manual contouring is a time-consuming process in which a professional would contour each patient one by one to be later checked by another professional. The proposed model uses approximately 49 k parameters while others average over 1,000 times more parameters. As our approach relies on a very compact model, shorter training times are observed, which make it possible to easily retrain the model using other data and potentially afford "personalised medicine" workflows. The model achieves similarity scores of Specificity (Sp) = 0.996 ± 0.001, Accuracy (Acc) = 0.994 ± 0.002 and Mean absolute error (MAE) = 0.0075 ± 0.0005.

Dietary diversity and nutritional status of adults living with HIV during the COVID-19 era

BACKGROUND

The coronavirus Disease 2019 (COVID-19) pandemic has brought about unique challenges in healthcare and nutrition, particularly for people living with HIV (PLHIV). Understanding their dietary patterns and nutritional status is crucial for developing targeted interventions and improving health outcomes. Therefore, this study assessed the dietary diversity and nutritional status of PLHIV during the COVID-19 era.

METHODS

We adopted a facility-based cross-sectional study design to enroll 220 PLHIV from two hospitals in the Central Region of Ghana. Dietary intakes were assessed using 24-hour recall. Anthropometric and body composition data were collected with a stadiometer and a body composition monitor. Dietary diversity was evaluated using the FAO's Individual Dietary Diversity Score (IDDS). Data analysis was conducted with SPSS version 20. Significance level was set p-value less than 0.05.

RESULTS

A significant proportion (33.2%) of PLHIV had low dietary diversity, with the majority (55.5%) categorized as needing dietary improvement. Approximately 2 out of every 10 of the participants were identified as underweight. Participants aged 40 to 59 years were more likely to exhibit higher dietary diversity (adjusted odds ratio (AOR) = 1.966, 95% Confidence Interval (CI): 1.045-4.987). Participants who consumed meals at least three times daily were more likely to have a high IDDS (AOR = 1.641, 95% CI: 1.221, 8.879). Employed participants (public sector and private sector) were also more likely to have a high IDDS compared to unemployed participants (AOR = 1.448, 95% CI: 1.028-3.042; AOR = 1.165, 95% CI: 1.030-9.329, respectively). Factors associated with undernutrition included being female (AOR = 1.829, 95% CI: 1.294, 3.872) and first-line antiretroviral therapy ART (AOR = 1.683, 95% CI: 1.282-2.424).

CONCLUSION

The study emphasizes the need for nutritional interventions for PLHIV, particularly during crises. It advocates for a policy collaboration to address food insecurity and promote resilient health outcomes.

The seroconversion history to SARS-CoV-2 in Indigenous people from Brazil - the interplay between exposure, vaccination, and tuberculosis

The COVID-19 pandemic caused a significant loss of human lives and a worldwide decline in quality of life. Although our understanding of the pandemic has improved significantly since the beginning, the natural history of COVID-19 and its impacts on under-represented populations, such as Indigenous people from America, remain largely unknown. We performed a retrospective serological survey with two Brazilian Indigenous populations (n=624), Tupiniquim and Guarani-Mbyá. Samples were collected between September 2020 and July 2021: a period comprising the dissemination of SARS-CoV-2 variants and the beginning of COVID-19 vaccination in Brazil. Seroconversions against S and N antigens were assessed using three different commercially available ELISA kits. Samples were also used to assess the prevalence of tuberculosis (TB) in the same population (n=529). Seroconversion against SARS-CoV-2 antigens was considered positive if at least one of the three ELISA kits detected levels of specific antibodies above the threshold specified by the manufacturer. In this sense, we report 56.0% (n=349/623) of seroconverted individuals. Relative seroconversion peaked after introduction of the Coronavac vaccine in February 2021. Vaccination increased the production of anti-S IgG from 3.9% to 48.6%. Our results also indicated that 11.0% (n=46/417) of all individuals were positive for TB. Seroconversion to SARS-CoV-2 was similar between individuals with positive tuberculosis test results to those with negative test results. Most vaccinated individuals seroconverted to SARS-CoV-2, indicating that Coronavac may be as protective in individuals from these indigenous groups as observed in the general Brazilian population. COVID-19 severity was minimal regardless of incomplete vaccine coverage, suggesting that vaccination may not be the only factor protecting individuals from severe COVID-19. Tuberculosis is highly prevalent and not associated with increased seroconversion to SARS-CoV-2.

Bibliometric analysis on CRISPR/Cas: a potential Sherlock Holmes for disease detection

CRISPR has revolutionized illness detection by using precision gene editing to identify specific sequences in recent years. Using the Scopus database, this study performs a comprehensive bibliometric analysis, looking at academic papers on CRISPR that were published between 1992 and 2023. After screening a dataset of 1407 articles using Zotero, trends in annual publishing, citation patterns, author affiliations, and keyword co-occurrence are revealed using analysis tools such as VOSviewer, RStudio, and MS Excel. According to the report, there was only one CRISPR publication in 1992. By 2017, there were a meager 64 papers. Nonetheless, there is a notable upsurge between 2018 and 2023. Leading nations involved in CRISPR-based illness detection research include Germany, the United States, China, India, and the United Kingdom. Chongqing University Three Gorges Hospital, Chongqing University Medical University, and Chongqing University Bioengineering College are a few of the top institutions. With the greatest publication numbers (1688 and 1616) and strong total link strengths (TLS) of 42 and 77, respectively, authors Liu, C., and Li, Y., stand out. The field with the greatest citation counts as of 2023 is Broughton's 2020 study on CRISPR-based SARS-CoV-2 detection in Nature Biotechnology, with 1598 citations. Biosensors and Bioelectronics comprise 14.99% of papers. Researchers, decision-makers, and interested parties can use this thorough summary to help them make well-informed decisions about future CRISPR-based disease detection studies.

Physical Chemistry Lab for Data Analysis of COVID-19 Spreading Kinetics in Different Countries

The COVID-19 pandemic has passed. It gives us a real-world example of kinetic data analysis practice for our undergraduate physical chemistry laboratory class. It is a great example to connect this seemingly very different problem to the kinetic theories for chemical reactions that the students have learned in the lecture class. At the beginning of the spring 2023 semester, we obtained COVID-19 kinetic data from the "Our World in Data" database, which summarizes the World Health Organization (WHO) data reported from different countries. We analyzed the effective spreading kinetics based on the susceptible-infectious-recovered-vaccinated (SIR-V) model. We then compared the effective rate constants represented by the real-time reproduction numbers (R t ) underlining the reported data for these countries and discussed the results and the limitations of the model with the students.

Learning from an experience, challenges and approaches in the workplace during COVID-19 pandemic: a content analysis of international documents

BACKGROUND

This study aims to investigate international measures for pandemic control in the workplace based on guidelines from international organizations to learn from their experiences.

METHODS

We conducted a qualitative study using content analysis. The search method involved reviewing published guidelines on preventing and responding to the COVID-19 pandemic in workplaces. After the screening process, ten guidelines were included in the content analysis. During the analysis, 200 meaning codes, 49 subcategories, and eleven categories were identified. Trustworthiness criteria were utilized to ensure the accuracy and strength of the findings.

RESULTS

Eleven categories of international content during the COVID-19 pandemic were legal requirements and duties of employees and employers, structural and program changes, risk assessment, risk communication, information and training, internal and external consultation and cooperation, provision of facilities and tools for workplace hygiene, special conditions, special groups, closing and reopening workplaces, reducing contact and exposure and mental health.

CONCLUSIONS

Protecting employees during a pandemic requires a multifaceted approach and strong advocacy. The operational plan for pandemic control should be developed based on the level of risk, with support tailored to employees' conditions and needs. Cooperation among international organizations is essential to develop a standardized plan and issue comprehensive guidelines in response to health emergencies with a global perspective and local implementation, drawing from the lessons learned during the COVID-19 pandemic.

Adapted generative latent diffusion models for accurate pathological analysis in chest X-ray images

Respiratory diseases have a significant global impact, and assessing these conditions is crucial for improving patient outcomes. Chest X-ray is widely used for diagnosis, but expert evaluation can be challenging. Automatic computer-aided diagnosis methods can provide support for clinicians in these tasks. Deep learning has emerged as a set of algorithms with exceptional potential in such tasks. However, these algorithms require a vast amount of data, often scarce in medical imaging domains. In this work, a new data augmentation methodology based on adapted generative latent diffusion models is proposed to improve the performance of an automatic pathological screening in two high-impact scenarios: tuberculosis and lung nodules. The methodology is evaluated using three publicly available datasets, representative of real-world settings. An ablation study obtained the highest-performing image generation model configuration regarding the number of training steps. The results demonstrate that the novel set of generated images can improve the performance of the screening of these two highly relevant pathologies, obtaining an accuracy of 97.09%, 92.14% in each dataset of tuberculosis screening, respectively, and 82.19% in lung nodules. The proposal notably improves on previous image generation methods for data augmentation, highlighting the importance of the contribution in these critical public health challenges.

Mass spectrometry imaging of N-linked glycans: Fundamentals and recent advances

With implications in several medical conditions, N-linked glycosylation is one of the most important posttranslation modifications present in all living organisms. Due to their nontemplate synthesis, glycan structures are extraordinarily complex and require multiple analytical techniques for complete structural elucidation. Mass spectrometry is the most common way to investigate N-linked glycans; however, with techniques such as liquid-chromatography mass spectrometry, there is complete loss of spatial information. Mass spectrometry imaging is a transformative analytical technique that can visualize the spatial distribution of ions within a biological sample and has been shown to be a powerful tool to investigate N-linked glycosylation. This review covers the fundamentals of mass spectrometry imaging and N-linked glycosylation and highlights important findings of recent key studies aimed at expanding and improving the glycomics imaging field.

Advances in virus-like particle-based SARS-CoV-2 vaccines

The Coronavirus Disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has incurred devastating human and economic losses. Vaccination remains the most effective approach for controlling the COVID-19 pandemic. Nonetheless, the sustained evolution of SARS-CoV-2 variants has provoked concerns among the scientific community regarding the development of next-generation COVID-19 vaccines. Among these, given their safety, immunogenicity, and flexibility to display varied and native epitopes, virus-like particle (VLP)-based vaccines represent one of the most promising next-generation vaccines. In this review, we summarize the advantages and characteristics of VLP platforms, strategies for antigen display, and current clinical trial progress of SARS-CoV-2 vaccines based on VLP platforms. Importantly, the experience and lessons learned from the development of SARS-CoV-2 VLP vaccines provide insights into the development of strategies based on VLP vaccines to prevent future coronavirus pandemics and other epidemics.

Effectiveness of Computer-Mediated Educational Counseling for Tinnitus Relief: A Randomized Controlled Trial

Counseling can help alleviate tinnitus-caused emotional distress and correct misconceptions, making it an effective rehabilitation option for people with tinnitus. Advances in communication technology have increased the demand for computer-mediated tinnitus counseling; however, the effectiveness of such counseling in reducing tinnitus is unclear. Thus, this study aimed to determine the tinnitus-relieving effects of computer-mediated counseling. Thirty-six participants with tinnitus were randomly assigned to online counseling (15 participants) or video-based counseling (21 participants) groups, defining how remote counseling was conducted. Tinnitus counseling, comprising 100 items, lasted 2 weeks and was separated into six sessions for the online counseling group and 8-9 items daily for 12 days for the video-based counseling group. The effectiveness of counseling was determined based on score changes between baseline and 2-week follow-up using the Korean version of the Tinnitus Primary Function Questionnaire and Visual Analog Scales for annoyance and loudness. While no significant improvements were observed in other domains, average emotional aspect-related scores showed significant improvements in both groups. Regarding individual results, four and seven participants in the online and video-based counseling groups reported significant improvements in the emotional domain, respectively. Overall, computer-mediated educational counseling might be a rehabilitation option for individuals with tinnitus.

National Beef Quality Audit-2022: in-plant assessments of quality and yield determining carcass characteristics of fed steers and heifers

The National Beef Quality Audit - 2022 serves as a benchmark of the current fed steer and heifer population of the U.S. beef industry and allows comparison to previous audits as a method of monitoring industry progress. In-plant cooler assessments and collections of beef carcass data took place from July 2021 to November 2022. During in-plant evaluations, 10% of 1-d production was surveyed for quality and yield indicating characteristics of fed beef carcasses (n = 9,746 beef carcasses). Distributions of sex classes among sampled carcasses were steer (65.0%) and heifer (35.0%), whereas distributions of breed type were native (87.7%), dairy (11.3%), and Bos indicus (0.9%). Mean values were observed for USDA Yield Grades (YG; 3.3), USDA Quality Grade (QG; Choice16), marbling score (Small98), ribeye area (91.0 cm2), adjusted fat thickness (1.49 cm), hot carcass weight (401.9 kg), and KPH (2.5%). Mean overall maturity was A66, with a mean lean maturity of A56 and mean skeletal maturity of A72. There were 28.1% of carcasses identified for use in a USDA-certified beef G-Schedule Program. Defects, such as dark cutting and blood splash, were observed at 1.8% and 0.5%, respectively. Distributions of USDA YG were YG 1 (8.2%), YG 2 (30.7%), YG 3 (40.2%), YG 4 (16.6%), and YG 5 (4.3%). USDA QGs were observed at 7.5% Prime, 69.2% Choice, 16.4% Select, and 6.8% other. The results of this study provide an updated look at the current grading trends of beef carcasses in the United States to drive progress in the fed beef industry.

Evaluation of awareness and performance towards COVID-related disinfectant use: a comparative study between Jordan and United Arab Emirates

BACKGROUND

The World Health Organization recommended the use of chemical-based disinfectants as an effective prevention of the COVID-19 pandemic. However, calls for poisoning were reported in several medical centers. The widespread use of chemical-based disinfectants as a preventive measure during the COVID-19 pandemic has underscored potential gaps in community awareness and performance, posing health risks. This study evaluates and compares levels of awareness and performance regarding the safe use of disinfectants in Jordan and UAE.

METHODS

The study was conducted between October 2022 and June 2023 via an online questionnaire. Data of respondents from Jordan (n = 828) and UAE (n = 619) were analyzed using SPSS. ANOVA, Mann-Whitney, and Kruskal-Wallis tests evaluated significant differences in awareness and performance levels across different demographic groups in Jordan/UAE and between them. Spearman's correlation test examined the correlation between awareness and performance among respondents. Multinomial logistic regression analysis explored associations between various variables and awareness/performance levels within each population.

RESULTS

Findings reveal weak awareness (72.4% and 9.03% in UAE and Jordan, respectively) and moderate performance level (98.8% in UAE and Jordan), with a weak correlation (UAE, rho = 0.093; Jordan, rho = 0.164) observed between the two countries (P < 0.05). Multinomial logistic regression analysis indicates gender-related associations with awareness levels and education-related associations with performance levels.

CONCLUSIONS

The study emphasizes the urgent need for awareness campaigns and workshops to promote safer disinfectant practices to develop effective interventions aligning with sustainable development goals.

Sambou Bamboo salt™ down-regulates the expression levels of angiotensin-converting enzyme 2 in activated human mast cells

Mast cells have a detrimental impact on coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Sambou Bamboo salt™ (BS) suppresses mast cell-mediated inflammatory response and enhances immunity. In this study, we investigated the regulatory effects of BS on expression of angiotensin-converting enzyme 2 (ACE2) and transmembrane protease/serine subfamily member 2 (TMPRSS2) in human mast cell line (HMC)-1 cells. BS resulted in significant reductions in expression levels of ACE2 and TMPRSS2 in activated HMC-1 cells. Levels of tryptase were reduced by BS. In addition, BS blocked activation of activator protein 1 (AP-1), c-Jun NH2-terminal kinases (JNK), p38, and phosphatidylinositide-3-kinase (PI3K) in activated HMC-1 cells. Therefore, these results show that BS reduces levels of ACE2, TMPRSS2, and tryptase by inhibiting AP-1/JNK/p38/PI3K signaling pathways in mast cells. These findings can serve as valuable foundational data for the development of therapeutic agents aimed at preventing SARS-CoV-2 infection.

Impact of vitamin D supplementation as COVID-19 vaccine adjuvant on sperm parameters and sex hormones in men with idiopathic infertility: Two separate pre-post studies

OBJECTIVE

Vitamin D deficiency is a major problem for human health worldwide. The mechanisms of vitamin D in the male reproductive system are unknown. After coronavirus disease 2019 (COVID-19) vaccines were developed, doubts were raised about their possible effects on male fertility. Based on vitamin D's function in the immune system, its potential role as an adjuvant for COVID-19 vaccines is intriguing. The aims of this study were to assess the effects of vitamin D first on sperm parameters and sex hormones, and then as an immune adjuvant on sperm parameters and sex hormones after study participants had received their second doses of COVID-19 vaccines.

METHODS

Phase 1 (before the COVID-19 pandemic) included 72 men with idiopathic infertility, and phase 2 had 64 participants who received two doses of COVID-19 vaccines. Both groups were instructed to take 50,000 IU of vitamin D twice monthly for 3 months. Sperm parameters and sex hormones were assessed pre- and post-supplementation.

RESULTS

Regular vitamin D intake for 3 months significantly increased the participants' vitamin D levels (p=0.0001). Both phases showed a positive correlation between vitamin D intake and sperm parameters. Vaccination had no negative effects on sperm parameters and sex hormones. Vitamin D was associated with follicle-stimulating hormone (p=0.02) and testosterone (p=0.0001) in phase 2 after treatment.

CONCLUSION

Our results support vitamin D supplementation as an immune adjunct to COVID-19 vaccination for improving sperm parameters and hormone levels. COVID-19 vaccination is not harmful for male fertility potential, and vitamin D is an effective factor for male fertility.

COVID-19 post-pandemic reflections from sub-Saharan Africa: what we know now that we wish we knew then

The commonly heard aphorism about history repeating itself suggests an endless cycle of recurring events. However, George Santayana offered a similar sentiment when he said, "Those who do not learn from history are doomed to repeat it". This emphasises that the responsibility for the recurrence of events lies not with history itself, but with humanity. It underscores that if we desire change, it is our responsibility to initiate it, rather than attributing it to external forces such as fate, luck, or time. With this thought in mind, here we offer a narrative view from sub-Saharan Africa, focusing primarily on our own experiences in Nigeria and Uganda, on what harsh lessons can be learnt from the COVID-19 pandemic regarding emergency preparedness to respond effectively to the next major infectious disease outbreak. Four strategies are suggested, the implementation of which may contribute substantially to safeguarding against an experience similar to the catastrophic public health, social and economic costs borne by African nations during COVID-19 and in its immediate aftermath.

Kikuchi-Fujimoto disease following SARS-CoV-2 infection: A rare disease with increased incidence during the COVID-19 pandemic?

Kikuchi-Fujimoto Disease (KFD), also known as Kikuchi disease or Kikuchi histiocytic necrotizing lymphadenitis, is a rare and self-limiting condition characterized by cervical lymphadenopathy and fever, primarily affecting young Asian adults. The aetiology of KFD remains unknown, although various infectious agents have been suggested as potential triggers. With the emergence of the COVID-19 pandemic, cases of post-COVID-19 KFD and post-COVID-19 vaccine KFD have been reported. In this article, we present the first case of post-COVID-19 KFD in Hong Kong. A 24-year-old man developed fever and painful neck swelling 1 month after recovering from COVID-19. Diagnostic evaluation, including ultrasound-guided fine needle aspiration cytology (FNAC), confirmed the diagnosis of KFD. The patient's symptoms resolved spontaneously with supportive care. This case underscores the importance of considering KFD as a potential differential diagnosis in patients presenting with cervical lymphadenopathy and fever following COVID-19 recovery or vaccination.

Current Status of Vaccines for Porcine Reproductive and Respiratory Syndrome: Interferon Response, Immunological Overview, and Future Prospects

Porcine reproductive and respiratory syndrome (PRRS) remains a formidable challenge for the global pig industry. Caused by PRRS virus (PRRSV), this disease primarily affects porcine reproductive and respiratory systems, undermining effective host interferon and other immune responses, resulting in vaccine ineffectiveness. In the absence of specific antiviral treatments for PRRSV, vaccines play a crucial role in managing the disease. The current market features a range of vaccine technologies, including live, inactivated, subunit, DNA, and vector vaccines, but only modified live virus (MLV) and killed virus (KV) vaccines are commercially available for PRRS control. Live vaccines are promoted for their enhanced protective effectiveness, although their ability to provide cross-protection is modest. On the other hand, inactivated vaccines are emphasized for their safety profile but are limited in their protective efficacy. This review updates the current knowledge on PRRS vaccines' interactions with the host interferon system, and other immunological aspects, to assess their current status and evaluate advents in PRRSV vaccine development. It presents the strengths and weaknesses of both live attenuated and inactivated vaccines in the prevention and management of PRRS, aiming to inspire the development of innovative strategies and technologies for the next generation of PRRS vaccines.

Influence of Healthcare Delivery Type on Patients' Mental Health: Is Hospitalization Always a Stressful Factor? Can Allostatic Load Help Assess a Patient's Psychological Disorders?

BACKGROUND

Psychological distress is a predictor of future health and disease data, with consequent implications for both the patient and the healthcare system. Taking advantage of the unprecedented situation caused by the COVID-19 pandemic we aimed to assess whether the type of medical care received by patients during the initial months of the pandemic influenced their evolution, particularly at the psychological level. Additionally, we investigated whether allostatic load was associated not only with physical but also psychological alterations.

METHODS

All the patients diagnosed with COVID-19 infection at HM Madrid Hospital during the month of March 2020 were studied, both those hospitalized (110) and those treated on an outpatient basis (46). They were psychologically evaluated using the Profile of Mood States (POMS) test. We calculated the allostatic load using different laboratory parameters.

RESULTS

Outpatient patients had significantly higher scores than hospitalized ones in Tension-Anxiety (52 ± 19.3 vs. 38 ± 4.3; p < 0.001). So, 36.9% of the outpatient patients exhibited anxiety. Allostatic load has not been correlated with patients' psychological alterations.

CONCLUSIONS

Psychological distress of outpatient patients should be taken into account in their management to improve mental health planning. This knowledge could provide comprehensive care to patients including their mental health, in the face of subsequent epidemics/pandemics.

Bayesian Spatio-Temporal Modeling of the Dynamics of COVID-19 Deaths in Peru

Amid the COVID-19 pandemic, understanding the spatial and temporal dynamics of the disease is crucial for effective public health interventions. This study aims to analyze COVID-19 data in Peru using a Bayesian spatio-temporal generalized linear model to elucidate mortality patterns and assess the impact of vaccination efforts. Leveraging data from 194 provinces over 651 days, our analysis reveals heterogeneous spatial and temporal patterns in COVID-19 mortality rates. Higher vaccination coverage is associated with reduced mortality rates, emphasizing the importance of vaccination in mitigating the pandemic's impact. The findings underscore the value of spatio-temporal data analysis in understanding disease dynamics and guiding targeted public health interventions.

Reduction of hemagglutination induced by a SARS-CoV-2 spike protein fragment using an amyloid-binding benzothiazole amphiphile

COVID-19 infection is associated with a variety of vascular occlusive morbidities. However, a comprehensive understanding of how this virus can induce vascular complications remains lacking. Here, we show that a peptide fragment of SARS-CoV-2 spike protein, S192 (sequence 192-211), is capable of forming amyloid-like aggregates that can induce agglutination of red blood cells, which was not observed with low- and non-aggregated S192 peptide. We subsequently screened eight amyloid-binding molecules and identified BAM1-EG6, a benzothiazole amphiphile, as a promising candidate capable of binding to aggregated S192 and partially inhibiting its agglutination activity. These results provide new insight into a potential molecular mechanism for the capability of spike protein metabolites to contribute to COVID-19-related blood complications and suggest a new therapeutic approach for combating microvascular morbidities in COVID-19 patients.

The impact of distance education on the socialization of college students in the Covid-19 era: problems in communication and impact on mental health

BACKGROUND

The problems of students' social interaction and psychological well-being associated with online learning dependent on self-directed learning have become an important topic of research in recent years worldwide due to the COVID-19 pandemic, affecting their Social Emotional Learning. This paper aimed to compare the students' loneliness, social anxiety, social interaction, and general psychological well-being at different stages of online learning (at the beginning and the height of the pandemic), considering their criteria (presence/absence of a job and own family).

METHODS

For this, the researchers conducted an electronic survey of students (n = 320) twice, in February and May 2020, using four questionnaires: UCLA loneliness scale-3, Social Anxiety Scale for E-Learning Environments, Social Interaction Scale, and Brief Adjustment Scale. The responses at different stages of online learning were compared using Student's t-test. Differences between employed and unemployed students with or without their own families were determined using the analysis of variance (ANOVA).

RESULTS

The findings showed that unemployed students without their families suffered the most from loneliness. Social interaction online was rated higher by students with their own families; psychological well-being at the beginning of the distance period and social anxiety at the height of the distance period were higher among unemployed students.

CONCLUSIONS

This research can become a theoretical basis for a phase-by-phase study of social predictors for the psychological well-being of higher education students and is of practical value for teachers and administrators of online learning aimed at students' socialization. In addition, it provides education officials with information about how students perceive psychological well-being, anxiety, social interaction, and loneliness during distance learning, which can help officials direct their decisions and reforms to improve interaction in the online environment.

Evaluating qigong as integrative support for COVID-19 and Long-COVID-19 rehabilitation: a systematic review

Introduction

Amidst the ongoing global impact of COVID-19 on public health, there is an increasing focus on holistic strategies encompassing integrative therapies and rehabilitation techniques, particularly in addressing the challenges posed by Long-COVID-19. This review investigates the potential of Qigong, an ancient Chinese practice characterized by gentle movements, controlled breathing, and meditative elements, within the context of COVID-19.

Methods

A systematic search of PubMed, EMBASE, Web of Science, Scopus, and Google Scholar was conducted to identify pertinent clinical studies.

Results

Following thorough database scrutiny, nine studies were identified as meeting the eligibility criteria. Across the spectrum of COVID-19 severity, individuals engaging in qigong practice exhibited notable enhancements in both physical and psychological wellbeing, evidenced by ameliorated respiratory symptoms, reduced anxiety levels, enhanced sleep quality, bolstered mental wellbeing, and augmented health-related quality of life. Moreover, qigong training, whether employed independently or in conjunction with other therapies, demonstrated beneficial effects on Long-COVID-19 symptoms, encompassing persistent respiratory issues, dizziness, sleep disturbances, and compromised health-related quality of life.

Discussion

This review underscores the necessity for further investigation to quantify and standardize the contribution of Qigong to COVID-19 recovery and rehabilitation. Such endeavors aim to integrate this accessible and low-impact practice into public health strategies and comprehensive treatment regimens.

Systematic review registration

The review protocol was registered in the Open Science Framework under the following doi: 10.17605/OSF.IO/7K5X6 (URL: https://osf.io/7k5x6).

From the bar to the cowshed: the impact of COVID-19 on female sex workers in Pattaya, Thailand

The COVID-19 pandemic had a devastating impact on the health and wellbeing of populations around the world, with vulnerable groups, including sex workers, being disproportionately affected. This study explored the effects of COVID-19 lockdown restrictions on the lives of female sex workers in Pattaya, Thailand. In-depth interviews with ten women were used to explore the ways in which they sought to cope during the crisis using Lazarus and Folkman's transactional model of stress and coping. Findings suggest that those who could, tended to seek economic shelter with their parents in rural parts of the country during the pandemic. However, those who could not relocate to be with family were forced to try to eke out a living in other ways, which could be both challenging and dangerous. None reported receiving any financial support from national or local authorities, to whom they were invisible, and this placed tremendous pressure on both them and their families. The authors conclude that the pandemic further highlights the need for the Thai Government to accept the reality of sex work and seek to both legitimise and protect vulnerable women and their labour.

Assessment of Suitable Habitat of the Demoiselle Crane (Anthropoides virgo) in the Wake of Climate Change: A Study of Its Wintering Refugees in Pakistan

The inevitable impacts of climate change have reverberated across ecosystems and caused substantial global biodiversity loss. Climate-induced habitat loss has contributed to range shifts at both species and community levels. Given the importance of identifying suitable habitats for at-risk species, it is imperative to assess potential current and future distributions, and to understand influential environmental factors. Like many species, the Demoiselle crane is not immune to climatic pressures. Khyber Pakhtunkhwa and Balochistan provinces in Pakistan are known wintering grounds for this species. Given that Pakistan is among the top five countries facing devastating effects of climate change, this study sought to conduct species distribution modeling under climate change using data collected during 4 years of field surveys. We developed a Maximum Entropy distribution model to predict the current and projected future distribution of the species across the study area. Future habitat projections for 2050 and 2070 were carried out using two representative concentration pathways (RCP 4.5 and RCP 8.5) under three global circulation models, including HADGEM2-AO, BCC-CSM1-1, and CCSM4. The most influential factors shaping Demoiselle Crane habitat suitability included the temperature seasonality, annual mean temperature, terrain ruggedness index, and human population density, all of which contributed significantly to the suitability (81.3%). The model identified 35% of the study area as moderately suitable (134,068 km2) and highly suitable (27,911 km2) habitat for the species under current climatic conditions. Under changing climate scenarios, our model predicted a major loss of the species' current suitable habitat, with shrinkage and shift towards western-central areas along the Pakistan-Afghanistan boarder. The RCP 8.5, which is the extreme climate change scenario, portrays particularly severe consequences, with habitat losses reaching 65% in 2050 and 85% in 2070. This comprehensive study provides useful insights into the Demoiselle Crane habitat's current and future dynamics in Pakistan.