Impact of COVID-19 Restrictions on Acute Gastroenteritis in Children: A Regional, Danish, Register-Based Study.

This study aimed to evaluate the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) restrictions such as social distancing on the occurrence of acute gastroenteritis (AGE) among children. This study is a register-based study, including every child seen in the departments of paediatrics with the initial diagnosis of AGE in three neighbouring hospitals in Denmark, from March 2018 through February 2021. The study also included every positive stool sample for AGE-causing pathogens analysed in these three hospitals from children during the same period. The Wilcoxon rank-sum test was used to determine differences between the period during the SARS-CoV-2 restrictions and before. In all, 222,157 children were seen in the three paediatric departments during this period. Of these, 3917 children were diagnosed with AGE. We found a decrease of 46.6% in AGE-related visits per month after the SARS-CoV-2 restrictions were introduced compared to before (p-value < 0.001). Positive stool samples decreased by 38.2% (p-value = 0.008) during the restrictions. This study found that cases of paediatric AGE decreased significantly the during COVID-19 restrictions, suggesting that studies should be conducted to determine whether this reduction was a result of good hand hygiene and social distancing or just a result of altered health-seeking behaviour among children.

Longitudinal Associations of Staff Shortages and Staff Levels with Health Outcomes in Nursing Homes.

OBJECTIVES: To examine whether facility-reported staff shortages and total staff levels were independently associated with changes in nursing home (NH) outcomes in 2020. DESIGN: Longitudinal cohort study. SETTING AND PARTICIPANTS: A total of 8466 NHs with staffing and outcome data. METHODS: This study used NH COVID-19 Public File (2020), Nursing Home Compare (2019-2020), and Payroll-Based Journal data (2019-2020). Outcome measures included the percentage of long-stay residents in a facility with declines in activities in daily living (ADLs), decreases in mobility, weight loss, and pressure ulcers in 2020 Q2, 2020 Q3, and 2020 Q4. Independent variables were whether NHs reported any shortage of aides or licensed nurses and total staff hours per resident day (HPRD). Separate 2-level (NH, state) Hierarchical Generalized Linear Mixed models examined the association of facility-reported shortages and staff hours with key NH resident outcomes, controlling for NH characteristics and COVID-19 infections. RESULTS: The weekly percentage of NHs reporting any staff shortage averaged 20%. Total staff HPRD increased slightly from 3.7 in 2019 to 3.8 in 2020. Health outcomes were stable during 2019 and 2020 Q1 but worsened substantially starting in 2020 Q2. For example, the percentage of residents with mobility loss increased from 16.2% in 2020 Q1 to 27.9% in 2020 Q4. Facility-reported staff shortages were associated with an increase in the proportion of residents with an ADL decline (0.54 percentage points), mobility loss (0.80 percentage points), weight loss (0.22 percentage points), and pressure ulcers (0.22 percentage points) (all P < .01). Total staff HPRD was not associated with changes in any outcomes (all P > .05). CONCLUSIONS AND IMPLICATIONS: NHs reported worsened health outcomes among long-stay residents in 2020, with worse outcomes found among facilities that reported staff shortages but not among those with lower total staff levels. Facility-reported shortages provide important quality information during the COVID-19 pandemic.

Identifying the predictors of severe psychological distress by auto-machine learning methods.

Social stress in daily life and the COVID-19 pandemic have greatly impacted the mental health of the population. Early detection of a predisposition to severe psychological distress is essential for timely interventions. This paper analyzed 4036 samples participating in the 2019-2020 National Health Information Trends Survey (HINTS) and identified 57 candidate predictors of severe psychological distress based on univariate chi-square and t-test analyses. Five machine learning methods, namely logistic regression (LR), automatic generalized linear models (Auto-GLM), automatic random forests (Auto-Random Forests), automatic deep neural networks (Auto-Deep learning) and automatic gradient boosting machines (Auto-GBM), were employed to model synthetic minority oversampling technique-based (SMOTE) resampled data and identify predictors of severe psychological distress. Predictors were evaluated by odds ratios in logistic models and variable importance in the other models. Forty-seven variables were identified as significant predictors of severe psychological distress, including 13 sociodemographic variables and 34 variables related to individual lifestyle and behavioral habits. Among them, new potentially relevant variables related to an individual's level of concern and trust in cancer information, exposure to health care providers, and cancer screening and awareness are included. The performance of each model was evaluated using five-fold cross-validation. The optimal model performance-wise was Auto-GBM with an accuracy of 89.75%, a precision of 89.68%, a recall of 89.31%, an F1-score of 89.48% and an AUC of 95.57%. Significant predictors of severe psychological distress were identified in this study and the value of machine learning methods in predicting severe psychological distress is demonstrated, thereby enhancing pre-prediction and clinical decision-making of severe psychological distress problems.

Classroom transformation during pandemic disruption: A personal response: APJM

The COVID-19 pandemic disrupted classroom instruction at every level, in every field, around the world. Graduate business programs, which are largely centered on "high-touch” interaction and exchanges among peers and with instructors via student-oriented learning approaches, faced a common challenge: a possible compromised learning experience resulting from the suspension of in-person education. This paper chronicles personal and professional transformations experienced by the authors while teaching four second-year electives at a graduate business school during the 2020–21 academic year. We reflect on how a particular mindset and specific strategic choices led to effective online teaching, mitigating the negative impact of the upheaval. We also consider this experience as a basis for developing online/offline "ambicultural” teaching methods for adoption in the post-pandemic world. Academics may find this account to be a useful learning tool and a guide for transforming their teaching in both the virtual and in-person classroom environments.

Can corporate social responsibility protect firm value during the COVID-19 pandemic?

The novel coronavirus (COVID-19) pandemic has caused a significant decline in the stock market worldwide, and hospitality companies are experiencing serious financial problems. Protecting and preserving firm value is a critical way of helping hospitality companies survive the crisis. The influence of corporate social responsibility (CSR) on firm value has been widely investigated. However, little is known about the stock price movement following CSR activity adoption during an industrial crisis. Using event study and difference-in-difference method, this study reveals that engaging in CSR activities can increase the stock returns and stakeholder attention of hospitality firms during the pandemic. Community-related CSR has a stronger and more immediate effect on stock returns than customer- and employee-related CSR. Results also indicate that hospitality firms that pursue improved stock market performance during a pandemic can invest in CSR to protect communities, customers, and employees for attracting further stakeholder attention.

DCACorrCapsNet: A deep channel‐attention correlative capsule network for COVID‐19 detection based on multi‐source medical images

The raging trend of COVID‐19 in the world has become more and more serious since 2019, causing large‐scale human deaths and affecting production and life. Generally speaking, the methods of detecting COVID‐19 mainly include the evaluation of human disease characterization, clinical examination and medical imaging. Among them, CT and X‐ray screening is conducive to doctors and patients' families to observe and diagnose the severity and development of the COVID‐19 more intuitively. Manual diagnosis of medical images leads to low the efficiency, and long‐term tired gaze will decline the diagnosis accuracy. Therefore, a fully automated method is needed to assist processing and analysing medical images. Deep learning methods can rapidly help differentiate COVID‐19 from other pneumonia‐related diseases or healthy subjects. However, due to the limited labelled images and the monotony of models and data, the learning results are biased, resulting in inaccurate auxiliary diagnosis. To address these issues, a hybrid model: deep channel‐attention correlative capsule network, for channel‐attention based spatial feature extraction, correlative feature extraction, and fused feature classification is proposed. Experiments are validated on X‐ray and CT image datasets, and the results outperform a large number of existing state‐of‐the‐art studies. [ABSTRACT FROM AUTHOR] Copyright of IET Image Processing (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Host-mediated RNA editing in viruses.

Viruses rely on hosts for life and reproduction, cause a variety of symptoms from common cold to AIDS to COVID-19 and provoke public health threats claiming millions of lives around the globe. RNA editing, as a crucial co-/post-transcriptional modification inducing nucleotide alterations on both endogenous and exogenous RNA sequences, exerts significant influences on virus replication, protein synthesis, infectivity and toxicity. Hitherto, a number of host-mediated RNA editing sites have been identified in diverse viruses, yet lacking a full picture of RNA editing-associated mechanisms and effects in different classes of viruses. Here we synthesize the current knowledge of host-mediated RNA editing in a variety of viruses by considering two enzyme families, viz., ADARs and APOBECs, thereby presenting a landscape of diverse editing mechanisms and effects between viruses and hosts. In the ongoing pandemic, our study promises to provide potentially valuable insights for better understanding host-mediated RNA editing on ever-reported and newly-emerging viruses.

Early Identification of Crop Type for Smallholder Farming Systems Using Deep Learning on Time-Series Sentinel-2 Imagery.

Climate change and the COVID-19 pandemic have disrupted the food supply chain across the globe and adversely affected food security. Early estimation of staple crops can assist relevant government agencies to take timely actions for ensuring food security. Reliable crop type maps can play an essential role in monitoring crops, estimating yields, and maintaining smooth food supplies. However, these maps are not available for developing countries until crops have matured and are about to be harvested. The use of remote sensing for accurate crop-type mapping in the first few weeks of sowing remains challenging. Smallholder farming systems and diverse crop types further complicate the challenge. For this study, a ground-based survey is carried out to map fields by recording the coordinates and planted crops in respective fields. The time-series images of the mapped fields are acquired from the Sentinel-2 satellite. A deep learning-based long short-term memory network is used for the accurate mapping of crops at an early growth stage. Results show that staple crops, including rice, wheat, and sugarcane, are classified with 93.77% accuracy as early as the first four weeks of sowing. The proposed method can be applied on a large scale to effectively map crop types for smallholder farms at an early stage, allowing the authorities to plan a seamless availability of food.

Racial and Socioeconomic Characteristics Associated with the use of Telehealth Services Among Adults With Ambulatory Sensitive Conditions.

Introduction: The COVID-19 pandemic led to a major transition for patients from routine ambulatory-care-based in-person primary care visits to telehealth visits to manage chronic diseases. However, it remains unclear the extent to which individuals access telehealth services and whether such utilization varies along neighborhood characteristics, especially among racial minorities. This study aims to examine the association of outpatient telehealth utilization with sociodemographic, clinical, and neighborhood characteristics among adults with ambulatory care sensitive conditions (ACSCs) during the COVID-19 pandemic. Methods: We included adults treated for an ACSC between March 5, 2020, and December 31, 2020, at a single ambulatory-care-based healthcare system, which serves a large population of low-income patients in the South region of the United States (i.e., Memphis, TN, Metropolitan Statistical Area). Telehealth utilization was defined by outpatient procedural codes and providers' notes on the type of visits. Generalized linear mixed models were used to examine the association of sociodemographic, clinical, and neighborhood factors with telehealth utilization in the overall cohort and the racial subpopulations. Results: Among the 13,962 adults with ACSCs, 8583 (62.5%) used outpatient telehealth services. Patients who were older, female, with mental disorders, and who had more comorbidities had higher rates of telehealth services (p < .05). Controlling for covariates, we observed 75.2% and 23.1% increased use of telehealth services among Hispanics and other race groups, respectively, compared to Whites. Patients who commuted more than 30 minutes to health facilities were slightly less likely to use telehealth services [OR: 0.994 (0.991,0.998)]. Racial minorities (Blacks and Hispanics) with mental disorders were more likely to use telehealth service when compared to Whites. Discussion: We found that among patients being treated for ACSCs, the use of telehealth services was highly prevalent in Hispanic patients in general and were more pronounced among both Hispanics and Black patients who have mental disorders.

Investigation of Neurological Complications after COVID-19 Vaccination: Report of the Clinical Scenarios and Review of the Literature.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), broke out in 2019 and became a pandemic in 2020. Since then, vaccines have been approved to prevent severe illness. However, vaccines are associated with the risk of neurological complications ranging from mild to severe. Severe complications such as vaccine-induced immune thrombotic thrombocytopenia (VITT) associated with acute ischaemic stroke have been reported as rare complications post-COVID-19 vaccination. During the pandemic era, VITT evaluation is needed in cases with a history of vaccination within the last month prior to the event. Cerebral venous sinus thrombosis (CVST) should be suspected in patients following immunization with persistent headaches who are unresponsive to analgesics. In this article, we investigated neurological complications after COVID-19 vaccination and provided more subsequent related clinical studies of accurate diagnosis, pathophysiological mechanisms, incidence, outcome, and management.

AabHLH113 integrates jasmonic acid and abscisic acid signaling to positively regulate artemisinin biosynthesis in Artemisia annua.

Artemisinin, a sesquiterpene lactone isolated from Artemisia annua, is in huge market demand due to its efficient antimalarial action, especially after the COVID-19 pandemic. Many researchers have elucidated that phytohormones jasmonic acid (JA) and abscisic acid (ABA) positively regulate artemisinin biosynthesis via types of transcription factors (TFs). However, the crosstalk between JA and ABA in regulating artemisinin biosynthesis remains unclear. Here, we identified a novel ABA- and JA-induced bHLH TF, AabHLH113, which positively regulated artemisinin biosynthesis by directly binding to the promoters of artemisinin biosynthetic genes, DBR2 and ALDH1. The contents of artemisinin and dihydroartemisinic acid increased by 1.71- to 2.06-fold and 1.47- to 2.23-fold, respectively, in AabHLH1113 overexpressed A. annua, whereas they decreased by 14-36% and 26-53%, respectively, in RNAi-AabHLH113 plants. Furthermore, we demonstrated that AabZIP1 and AabHLH112, which, respectively, participate in ABA and JA signaling pathway to regulate artemisinin biosynthesis, directly bind to and activate the promoter of AabHLH113. Collectively, we revealed a complex network in which AabHLH113 plays a key interrelational role to integrate ABA- and JA-mediated regulation of artemisinin biosynthesis.

International recommendations for plasma Epstein-Barr virus DNA measurement in nasopharyngeal carcinoma in resource-constrained settings: lessons from the COVID-19 pandemic.

The effects of the COVID-19 pandemic continue to constrain health-care staff and resources worldwide, despite the availability of effective vaccines. Aerosol-generating procedures such as endoscopy, a common investigation tool for nasopharyngeal carcinoma, are recognised as a likely cause of SARS-CoV-2 spread in hospitals. Plasma Epstein-Barr virus (EBV) DNA is considered the most accurate biomarker for the routine management of nasopharyngeal carcinoma. A consensus statement on whether plasma EBV DNA can minimise the need for or replace aerosol-generating procedures, imaging methods, and face-to-face consultations in managing nasopharyngeal carcinoma is urgently needed amid the current pandemic and potentially for future highly contagious airborne diseases or natural disasters. We completed a modified Delphi consensus process of three rounds with 33 international experts in otorhinolaryngology or head and neck surgery, radiation oncology, medical oncology, and clinical oncology with vast experience in managing nasopharyngeal carcinoma, representing 51 international professional societies and national clinical trial groups. These consensus recommendations aim to enhance consistency in clinical practice, reduce ambiguity in delivering care, and offer advice for clinicians worldwide who work in endemic and non-endemic regions of nasopharyngeal carcinoma, in the context of COVID-19 and other airborne pandemics, and in future unexpected settings of severe resource constraints and insufficiency of personal protective equipment.

Rapid Evaluation of Vaccine Booster Effectiveness against SARS-CoV-2 Variants.

As the COVID-19 pandemic continues, countries around the world are switching toward vaccinations and boosters to combat the pandemic. However, waning immunity against SARS-CoV-2 wild-type (WT) and variants have been widely reported. Booster vaccinations have shown to be able to increase immunological protection against new variants; however, the protection observed appears to decrease quickly over time suggesting a second booster shot may be appropriate. Moreover, heterogeneity and waning of the immune response at the individual level was observed suggesting a more personalized vaccination approach should be considered. To evaluate such a personalized strategy, it is important to have the ability to rapidly evaluate the level of neutralizing antibody (nAbs) response against variants at the individual level and ideally at a point of care setting. Here, we applied the recently developed cellulose pulled-down virus neutralization test (cpVNT) to rapidly assess individual nAb levels to WT and variants of concerns in response to booster vaccination. Our findings confirmed significant heterogeneity of nAb responses against a panel of SARS-CoV-2 variants, and indicated a strong increase in nAb response against variants of concern (VOCs) upon booster vaccination. For instance, the nAb response against current predominant omicron variant was observed with medians of 88.1% (n = 6, 95% CI = 73.2% to 96.2%) within 1-month postbooster and 70.7% (n = 22, 95% CI = 66.4% to 81.8%) 3 months postbooster. Our data show a point of care (POC) test focusing on nAb response levels against VOCs can guide decisions on the potential need for booster vaccinations at individual level. Importantly, it also suggests the current booster vaccines only give a transient protective response against some VOC and new more targeted formulations of a booster vaccine against specific VOC may need to be developed in the future. IMPORTANCE Vaccination against SARS-CoV-2 induces protection through production of neutralization antibodies (nAb). The level of nAb is a major indicator of immunity against SARS-CoV-2 infection. We developed a rapid point-of-care test that can monitor the nAb level from a drop of finger stick blood. Here, we have implemented the test to monitor individual nAb level against wild-type and variants of SARS-CoV-2 at various time points of vaccination, including post-second-dose vaccination and postbooster vaccination. Huge diversity of nAb levels were observed among individuals as well as increment in nAb levels especially against Omicron variant after booster vaccination. This study evaluated the performance of this point-of-care test for personalized nAb response tracking. It verifies the potential of using a rapid nAb test to guide future vaccination regimens at both the individual and population level.

Prussian Blue@Zeolitic Imidazolate Framework Composite Toward Solar-triggered Biodecontamination

Metal-organic frameworks (MOFs) featuring composition and bandstructure diversity, are an emerging class of photoresponsive disinfectants. In this study, we demonstrated the superiority of core-shell arranged photoactive MOFs (prussian blue (PB) and zeolitic imidazolate framework (ZIF-8)) for pathogen inactivation in terms of biocidal efficiency and broad-spectrum sensitivity. Reactive oxygen species (ROS) production was significantly promoted after the integration of PB due to the photosensitization effect and initiation of in situ Fenton reaction. Favorably, another inactivation channel was also opened owing to the unique photothermal effect of PB. Attributed to the facilitated ROS intracellular penetration by heat, the composite outperforms not only individual component but anatase TiO2 in pathogen elimination. Specifically, the Staphylococcus aureus (S. aureus) inactivation efficiency of the composite (6.6 log) is 2, 1.8 and 5.1 times higher than that of PB (3.3 log), ZIF-8 (3.7 log) and TiO2 (1.3 log) over 45 min of simulated sunlight illumination. Significantly, the infectivity of Bacillus anthracis and murine coronavirus in droplets on composite-coated filter surface could be greatly reduced (approximately 3 log reduction in colony number/coronavirus titer) within few minutes of solar exposure, indicative of the great potential of MOF composites toward life-threatening microbial infection prevention.

Influence factors of COVID-19 in Shandong Province based on geographically weighted generalized linear model. (Special Issue: Spatio-temporal dynamics analysis, risk assessment and emergency management for COVID-19 epidemic.) [Chinese]

Objective: To explore the related influence factors of coronavirus diseases 2019(COVID-19)in Shandong Province and understand the regional distribution characteristics of the epidemic situation, and to provide a scientific basis for guiding prevention and control strategies.

Clinical Manifestation, Management, and Outcomes in Patients with COVID-19 Vaccine-Induced Acute Encephalitis: Two Case Reports and a Literature Review.

INTRODUCTION: Vaccination is one of the best strategies to control coronavirus disease 2019 (COVID-19), and multiple vaccines have been introduced. A variety of neurological adverse effects have been noted after the implementation of large-scale vaccination programs. METHODS: We reported two rare cases of possible mRNA-1273 vaccine-induced acute encephalitis, including clinical manifestations, laboratory characteristics, and management. RESULTS: The clinical manifestations might be related to hyperproduction of systemic and cerebrospinal fluid (CSF) cytokines. mRNA vaccines are comprised of nucleoside-modified severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA, which is translated into SARS-CoV-2 spike protein by the host's ribosomes, activating the adaptive immune response. Exposed mRNA or vaccine components may also be detected as antigens, further resulting in aberrant proinflammatory cytokine cascades and activation of immune signaling pathways. Both patients exhibited significant clinical improvement after a course of steroid therapy. CONCLUSIONS: The use of COVID-19 vaccines to prevent and control SARS-CoV-2 infections and complications is the most practicable policy worldwide. However, inaccurate diagnosis or other diagnostic delays in cases of vaccine-induced acute encephalitis may have devastating and potentially life-threatening consequences for patients. Early diagnosis and timely treatment can result in a favorable prognosis.

CoVM2: Molecular Biological Data Integration of SARS-CoV-2 Proteins in a Macro-to-Micro Method.

The COVID-19 pandemic has been a major public health event since 2020. Multiple variant strains of SARS-CoV-2, the causative agent of COVID-19, were detected based on the mutation sites in their sequences. These sequence mutations may lead to changes in the protein structures and affect the binding states of SARS-CoV-2 and human proteins. Experimental research on SARS-CoV-2 has accumulated a large amount of structural data and protein-protein interactions (PPIs), but the studies on the SARS-CoV-2-human PPI networks lack integration of physical associations with possible protein docking information. In addition, the docking structures of variant viral proteins with human receptor proteins are still insufficient. This study constructed SARS-CoV-2-human protein-protein interaction network with data integration methods. Crystal structures were collected to map the interaction pairs. The pairs of direct interactions and physical associations were selected and analyzed for variant docking calculations. The study examined the structures of spike (S) glycoprotein of variants Delta B.1.617.2, Omicron BA.1, and Omicron BA.2. The calculated docking structures of S proteins and potential human receptors were obtained. The study integrated binary protein interactions with 3D docking structures to fulfill an extended view of SARS-CoV-2 proteins from a macro- to micro-scale.