A dePEGylated Lipopeptide-Based Pan-Coronavirus Fusion Inhibitor Exhibits Potent and Broad-Spectrum Anti-HIV-1 Activity without Eliciting Anti-PEG Antibodies.

We previously identified a lipopeptide, EK1C4, by linking cholesterol to EK1, a pan-CoV fusion inhibitory peptide via a polyethylene glycol (PEG) linker, which showed potent pan-CoV fusion inhibitory activity. However, PEG can elicit antibodies to PEG in vivo, which will attenuate its antiviral activity. Therefore, we designed and synthesized a dePEGylated lipopeptide, EKL1C, by replacing the PEG linker in EK1C4 with a short peptide. Similar to EK1C4, EKL1C displayed potent inhibitory activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other coronaviruses. In this study, we found that EKL1C also exhibited broad-spectrum fusion inhibitory activity against human immunodeficiency virus type 1 (HIV-1) infection by interacting with the N-terminal heptad repeat 1 (HR1) of viral gp41 to block six-helix bundle (6-HB) formation. These results suggest that HR1 is a common target for the development of broad-spectrum viral fusion inhibitors and EKL1C has potential clinical application as a candidate therapeutic or preventive agent against infection by coronavirus, HIV-1, and possibly other class I enveloped viruses.

Identification of major depression patients using machine learning models based on heart rate variability during sleep stages for pre-hospital screening.

With the COVID-19 pandemic causing challenges in hospital admissions globally, the role of home health monitoring in aiding the diagnosis of mental health disorders has become increasingly important. This paper proposes an interpretable machine learning solution to optimise initial screening for major depressive disorder (MDD) in both male and female patients. The data is from the Stanford Technical Analysis and Sleep Genome Study (STAGES). We analyzed 5-min short-term electrocardiogram (ECG) signals during nighttime sleep stages of 40 MDD patients and 40 healthy controls, with a 1:1 gender ratio. After preprocessing, we calculated the time-frequency parameters of heart rate variability (HRV) based on the ECG signals and used common machine learning algorithms for classification, along with feature importance analysis for global decision analysis. Ultimately, the Bayesian optimised extremely randomized trees classifier (BO-ERTC) showed the best performance on this dataset (accuracy 86.32%, specificity 86.49%, sensitivity 85.85%, F1-score 0.86). By using feature importance analysis on the cases confirmed by BO-ERTC, we found that gender is one of the most important factors affecting the prediction of the model, which should not be overlooked in our assisted diagnosis. This method can be embedded in portable ECG monitoring systems and is consistent with the literature results.

Host Expression Profiling From Diagnostic Coronavirus Disease 2019 Swabs Associates Upper Respiratory Tract Immune Responses With Radiologic Lung Pathology and Clinical Severity.

Background: COVID-19 presents with a breadth of symptomatology including a spectrum of clinical severity requiring intensive care unit (ICU) admission. We investigated the mucosal host gene response at the time of gold standard COVID-19 diagnosis using clinical surplus RNA from upper respiratory tract swabs. Methods: Host response was evaluated by RNA-sequencing, and transcriptomic profiles of 44 unvaccinated patients including outpatients and in-patients with varying levels of oxygen supplementation were included. Additionally, chest X-rays were reviewed and scored for patients in each group. Results: Host transcriptomics revealed significant changes in the immune and inflammatory response. Patients destined for the ICU were distinguished by the significant upregulation of immune response pathways and inflammatory chemokines, including cxcl2 which has been linked to monocyte subsets associated with COVID-19 related lung damage. In order to temporally associate gene expression profiles in the upper respiratory tract at diagnosis of COVID-19 with lower respiratory tract sequalae, we correlated our findings with chest radiography scoring, showing nasopharygeal or mid-turbinate sampling can be a relevant surrogate for downstream COVID-19 pneumonia/ICU severity. Conclusions: This study demonstrates the potential and relevance for ongoing study of the mucosal site of infection of SARS-CoV-2 using a single sampling that remains standard of care in hospital settings. We highlight also the archival value of high quality clinical surplus specimens, especially with rapidly evolving COVID-19 variants and changing public health/vaccination measures.

Dual-Network Structured Nanofibrous Membranes with Superelevated Interception Probability for Extrafine Particles.

Airborne particulate matter (PM) pollution has caused a public health threat, including nanoscale particles, especially with emerging infectious diseases and indoor and vehicular environmental pollution. However, most existing indoor air filtration units are expensive, energy-intensive, and bulky, and there is an unavoidable trade-off between low-efficiency PM0.3/pathogen interception, PM removal, and air resistance. Herein, we designed and synthesized a two-dimensional continuous cellulose-sheath/net with a unique dual-network corrugated architecture to manufacture high-efficiency air filters and even N95 particulate face mask. Combined with its sheath/net structured pores (size 100-200 nm) consisting of a cellulose framework (1-100 nm diameter), the cellulose sheath/net filter offers high-efficiency air filtration (>99.5338%, Extrafine particles; >99.9999%, PM2.5), low-pressure drops, and a robustness quality factor of >0.14 Pa-1, utilizing their ultralight weight of 30 mg/m2 and physical adhesion and sieving behaviors. Simultaneously, masks prepared with cellulose-sheath/net filters are more likely to capture and block smaller particles than the N95 standard. The synthesis of such materials with their nanoscale features and designed macrostructures may suggest new design criteria for a novel generation of high-efficiency air filter media for different applications such as personal protection products and industrial dust removal.

Clinical risk score for early prediction of recurring SARS-CoV-2 positivity in non-critical patients.

Introduction: Recurrent positive results in quantitative reverse transcriptase-PCR (qRT-PCR) tests have been commonly observed in COVID-19 patients. We aimed to construct and validate a reliable risk stratification tool for early predictions of non-critical COVID-19 survivors' risk of getting tested re-positive within 30 days. Methods: We enrolled and retrospectively analyzed the demographic data and clinical characters of 23,145 laboratory-confirmed cases with non-critical COVID-19. Participants were followed for 30 days and randomly allocated to either a training (60%) or a validation (40%) cohort. Multivariate logistic regression models were employed to identify possible risk factors with the SARS-CoV-2 recurrent positivity and then incorporated into the nomogram. Results: The study showed that the overall proportion of re-positive cases within 30 days of the last negative test was 24.1%. In the training cohort, significantly contributing variables associated with the 30-day re-positivity were clinical type, COVID-19 vaccination status, myalgia, headache, admission time, and first negative conversion, which were integrated to build a nomogram and subsequently translate these scores into an online publicly available risk calculator (https://anananan1.shinyapps.io/DynNomapp2/). The AUC in the training cohort was 0.719 [95% confidence interval (CI), 0.712-0.727] with a sensitivity of 66.52% (95% CI, 65.73-67.30) and a specificity of 67.74% (95% CI, 66.97-68.52). A significant AUC of 0.716 (95% CI, 0.706-0.725) was obtained for the validation cohort with a sensitivity of 62.29% (95% CI, 61.30-63.28) and a specificity of 71.26% (95% CI, 70.34-72.18). The calibration curve exhibited a good coherence between the actual observation and predicted outcomes. Conclusion: The risk model can help identify and take proper management in high-risk individuals toward the containment of the pandemic in the community.

Topological structure and COVID-19 related risk propagation in TFT-LCD supply networks

Thin-film-transistor liquid-crystal displays (TFT-LCDs) have gained popularity due to their widespread use in the production of televisions, laptops, and iPads. TFT-LCD firms' activities that build relationships with suppliers and customers contribute to the emergence of supply networks. A firm's ability to identify risks, however, is complicated, as TFT-LCD supply networks are becoming increasingly global, complex, and interconnected. The extant research on the topological structure of TFT-LCD supply networks is limited, and the risks identified rely on untested assumptions about the topological structure of such networks. To fill these gaps, this study examines the topological structure and COVID-19 related risk propagation in TFT-LCD supply networks from a dynamic perspective. First, the evolution of the topological structure of TFT-LCD supply networks from 2015 to 2020 is explored by constructing a weighted and undirected supply network. Second, the hidden risky sources in TFT-LCD supply networks are revealed by the proposed risk propagation model. The results show that TFT-LCD supply networks are characterised by a ‘hub and spoke' feature and an explicit shift from geographical to global cooperation. Additionally, a ‘robust-yet-fragile' configuration in these supply networks is uncovered, and the hidden risky sources in the main TFT-LCD manufacturers and suppliers and in interfirm cooperations are revealed. These findings will help managers reduce the vulnerability of TFT-LCD supply networks to disruptions and construct more robust and resilient networks.

An integrated strategy to identify COVID-19 causal genes and characteristics represented by LRRC37A2.

Genome-wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID-19). The genes or functional DNA elements through which genetic factors affect COVID-19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome-wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID-19 were investigated by an integrated strategy that included three GWAS-eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single-cell datasets to explore the cell-specific expression of causal genes. Furthermore, associations between COVID-19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein-coding genes of COVID-19 were discussed using cell experiments. The results revealed some novel COVID-19-related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID-19.

SPUR: A Patient-Reported Medication Adherence Model as a Predictor of Admission and Early Readmission in Patients Living with Type 2 Diabetes.

Purpose: Poor medication adherence (MA) is linked to an increased likelihood of hospital admission. Early interventions to address MA may reduce this risk and associated health-care costs. This study aimed to evaluate a holistic Patient Reported Outcome Measure (PROM) of MA, known as SPUR, as a predictor of general admission and early readmission in patients living with Type 2 Diabetes. Patients and Methods: An observational study design was used to assess data collected over a 12-month period including 6-month retrospective and 6-month prospective monitoring of the number of admissions and early readmissions (admissions occurring within 30 days of discharge) across the cohort. Patients (n = 200) were recruited from a large South London NHS Trust. Covariates of interest included: age, ethnicity, gender, level of education, income, the number of medicines and medical conditions, and a Covid-19 diagnosis. A Poisson or negative binomial model was employed for count outcomes, with the exponentiated coefficient indicating incident ratios (IR) [95% CI]. For binary outcomes (Coefficient, [95% CI]), a logistic regression model was developed. Results: Higher SPUR scores (increased adherence) were significantly associated with a lower number of admissions (IR = 0.98, [0.96, 1.00]). The number of medical conditions (IR = 1.07, [1.01, 1.13]), age ≥80 years (IR = 5.18, [1.01, 26.55]), a positive Covid-19 diagnosis during follow-up (IR = 1.83, [1.11, 3.02]) and GCSE education (IR = 2.11, [1.15,3.87]) were factors associated with a greater risk of admission. When modelled as a binary variable, only the SPUR score (-0.051, [-0.094, -0.007]) was significantly predictive of an early readmission, with patients reporting higher SPUR scores being less likely to experience an early readmission. Conclusion: Higher levels of MA, as determined by SPUR, were significantly associated with a lower risk of general admissions and early readmissions among patients living with Type 2 Diabetes.

Causal association of the brain structure with the susceptibility, hospitalization, and severity of COVID-19: A large-scale genetic correlation study.

Brain structure is related to its ability to resist external pathogens. Furthermore, there are several abnormal anatomical brain events and central system symptoms associated with COVID-19. This study, which was conducted based on genetic variables, aimed to identify the causal association between brain structure and COVID-19 phenotypes. We performed a two-sample bidirectional Mendelian randomization analysis using genetic variables obtained from large genome-wide association studies as instruments to identify the potential causal effects of various brain imaging-derived phenotypes (BIDPs) traits on susceptibility, hospitalisation, and severity of COVID-19. We explored the genetic correlations of 1325 BIDPs with the susceptibility, hospitalisation, and severity of COVID-19 using Linkage Disequilibrium Score Regression. We observed a causal relationship between increased cortical thickness of the left inferior temporal area and an increased risk of increased COVID-19 infection (p = 4.29 × 10-4) and hospitalisation (p = 3.67 × 10-3). Moreover, the larger total surface area of the whole brain was negatively correlated with the risk of hospitalisation for COVID-19. Furthermore, there was a significant causal association between increased cerebrospinal fluid volume and decreased severity of COVID-19 (p = 3.74 × 10-3). In a conclusion, we provide new insights into the causal association between BIDPs and COVID-19 phenotypes, which may help elucidate the aetiology of COVID-19.

Development and Testing of the Smart Healthcare Prototype System through COVID-19 Patient Innovation.

Since the outbreak of the novel coronavirus disease 2019 (COVID-19), the epidemic has gradually slowed down in various countries and people's lives have gradually returned to normal. To monitor the spread of the epidemic, studies discussing the design of related healthcare information systems have been increasing recently. However, these studies might not consider the aspect of user-centric design when developing healthcare information systems. This study examined these innovative technology applications and rapidly built prototype systems for smart healthcare through a systematic literature review and a study of patient innovation. The design guidelines for the Smart Healthcare System (SHS) were then compiled through an expert review process. This will provide a reference for future research and similar healthcare information system development.

Supercoiling Structure-Based Design of a Trimeric Coiled-Coil Peptide with High Potency against HIV-1 and Human ß-Coronavirus Infection.

Hexameric structure formation through packing of three C-terminal helices and an N-terminal trimeric coiled-coil core has been proposed as a general mechanism of class I enveloped virus entry. In this process, the C-terminal helical repeat (HR2) region of viral membrane fusion proteins becomes transiently exposed and accessible to N-terminal helical repeat (HR1) trimer-based fusion inhibitors. Herein, we describe a mimetic of the HIV-1 gp41 HR1 trimer, N3G, as a promising therapeutic against HIV-1 infection. Surprisingly, we found that in addition to protection against HIV-1 infection, N3G was also highly effective in inhibiting infection of human ß-coronaviruses, including MERS-CoV, HCoV-OC43, and SARS-CoV-2, possibly by binding the HR2 region in the spike protein of ß-coronaviruses to block their hexameric structure formation. These studies demonstrate the potential utility of anti-HIV-1 HR1 peptides in inhibiting human ß-coronavirus infection. Moreover, this strategy could be extended to the design of broad-spectrum antivirals based on the supercoiling structure of peptides.

Emotional disturbance and risk factors among COVID-19 confirmed cases in isolation hotels.

Patients with coronavirus disease 2019 (COVID-19) has been isolated in hospital-managed isolation hotels under a policy of the Taiwan government. Centrally isolation patients are more likely to experience psychological symptoms. The purpose of the study was to investigate emotional disturbance during their isolation period and then pinpoint the factors during their isolation period associated with the emotional disturbance. We retrospectively analysed the medical charts of the patients confined to a Banqiao isolation hotel between May 28 and July 3, 2021. The 5-item brief symptom rating scale (BSRS-5) was used to evaluate emotional disturbance levels. Descriptive and logistic regression was used for the data analysis. In total, 197 complete medical records were reviewed, and of these 84 (42.6%) showed emotional disturbance. The majority of them reported only minor disturbance (n = 49, 58.3%). After controlling for confounding factors, being satisfied about medical information was the only protective factor associated with emotional disturbance (OR = 0.2, P = 0.018). Being a male patient (OR = 3.0, P = 0.005), worrying about stigmatization (OR = 2.2, P = 0.041) and being unable to contact family members (OR = 2.9, P = 0.018) increased the risk of experiencing emotional disturbance. Patients with clinical symptoms, namely sore throat (OR = 3.4, P = 0.013) and muscle aches (OR = 6.3, P = 0.005), were also found to be more likely to report emotional disturbance. Mental disturbance commonly occurs among patient with COVID-19 who are isolated in a hospital-managed hotel. Being a male patient, having symptoms, namely a sore throat and muscle pain, being unable to contact family and/or a failure to receive sufficient medical information were found to be associated with emotional disturbance. In order to help isolated patients, government officials should provide a clear rationale for isolation and recognize the patients' efforts to follow the government's policy, which will help to minimize social stigma.

Advances And Challenges In Using Nirmatrelvir And Its Derivatives Against Sars-Cov-2 Infection.

On 22 December 2021, the United States Food and Drug Administration (FDA) approved the first Mpro inhibitor, i.e., oral antiviral nirmatrelvir (PF-07321332)/ritonavir (Paxlovid), for the treatment of early severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Nirmatrelvir inhibits SARS-CoV-2 infection, but high doses or long-term treatment may cause embryonic developmental toxicity and changes in host gene expression. The chiral structure of nirmatrelvir plays a key role in its antiviral activity. Ritonavir boosts the efficacy of nirmatrelvir by inactivating cytochrome P450 3A4 (CYP3A4) expression and occupying the plasma protein binding sites. Multidrug resistance protein 1 (MDR1) inhibitors may increase the efficacy of nirmatrelvir. However, paxlovid has many contraindications. Some patients treated with paxlovid experience a second round of coronavirus disease 2019 (COVID-19) symptoms soon after recovery. Interestingly, the antiviral activity of nirmatrelvir metabolites, such as compounds 12-18, is similar to or higher than that of nirmatrelvir. Herein, we review the advances and challenges in using nirmatrelvir and its derivatives with the aim of providing knowledge to drug developers and physicians in the fight against COVID-19.

Automatic detection of indoor occupancy based on improved YOLOv5 model.

Indoor occupancy detection is essential for energy efficiency control and Coronavirus Disease 2019 traceability. The number and location of people can be accurately identified and determined through classroom surveillance video analysis. This information is used to manage environmental equipment such as HVAC and lighting systems to reduce energy use. However, the mainstream one-stage YOLO algorithm still uses an anchor-based mechanism and couples detection heads to predict. This results in slow model convergence and poor detection performance for densely occluded targets. Therefore, this paper proposed a novel decoupled anchor-free VariFocal loss convolutional network algorithm DFV-YOLOv5 for occupancy detection to tackle these problems. The proposed method uses the YOLOv5 algorithm as a baseline. It uses the anchor-free mechanism to reduce the number of design parameters needing heuristic tuning. Afterwards, to reduce the coupling of the model, speed up the model's convergence ability, and improve the model detection performance, the detection head is decoupled based on the YOLOv5 model. It can resolve the conflict between classification and regression tasks. In addition, we use the VariFocal loss to assign more weights to difficult data points to optimize the class imbalance problem and use the training target q to measure positive samples, treating positive and negative samples asymmetrically. The total loss function is redesigned, the L 1 loss is increased, and the ablation experiment verifies the effect of the improved loss. By applying a hybrid activation function of the sigmoid linear unit and rectified linear unit, we improved the model's nonlinear representation and reduced the model's inference time. Finally, a classroom dataset was constructed to validate the occupancy detection performance of the model. The proposed model was compared with mainstream target detection models regarding average mean precision, memory allocation, execution time, and the number of parameters on the VOC2012, CrowdHuman and self-built datasets. The experimental results show that the method significantly improves the detection accuracy and robustness, shortens the inference time, and proves the practicality of the algorithm in occupancy detection compared with the mainstream target detection model and related variants of the model.

Berberine in Sepsis: Effects, Mechanisms, and Therapeutic Strategies.

Sepsis is defined as a dysregulated immune response to infection that leads to multiple organ dysfunction. To date, though a growing body of knowledge has gained insight into the clinical risk factors, pathobiology, treatment response, and recovery methods, sepsis remains a significant concern and clinical burden. Therefore, further study is urgently needed to alleviate the acute and chronic outcomes. Berberine (BBR), a traditional Chinese medicine with multiple actions and mechanisms, has been investigated in cellular and rodent animal models of sepsis mainly based on its anti-inflammatory effect. However, the practical application of BBR in sepsis is still lacking, and it is imperative to systematically summarize the study of BBR in sepsis. This review summarized its pharmacological activities and mechanisms in septic-related organ injuries and the potential BBR-based therapeutic strategies for sepsis, which will provide comprehensive references for scientific research and clinical application.

Parents' willingness to vaccinate themselves and their children with the booster vaccine against SARS-CoV-2: A cross-sectional study in Puyang city, China.

We aimed to investigate the hesitancy and willingness of parents to vaccinate themselves and their children with a booster dose against severe acute respiratory syndrome coronavirus 2 and related factors. We conducted a cross-sectional study in Puyang city, China. The information was collected, including demographic characteristics, willingness to receive a booster dose of coronavirus disease 2019 (COVID-19) vaccine, and attitudes and concerns toward COVID-19 and vaccines. Vaccine hesitancy was assessed in individuals completing the first two doses and booster eligible, while vaccine willingness was assessed in those completing the first two doses and not yet booster eligible. Among the participants completing two primary doses while not meeting the booster criteria, 95.4% (1465/1536) and 95.0% (1385/1458) had a willingness to a booster dose of COVID-19 vaccine for themselves and their children, respectively. Among the participants who met the booster criteria, 40.3% had vaccine hesitancy. Vaccine hesitancy and unwillingness tended to occur in people who were younger, less educated, less healthy, and with unsureness of vaccines' efficacy and adverse events (AE). The younger age of children, children in poorer health, and concern about the efficacy and AE of vaccines contributed to the participants' unwillingness to vaccinate their children. We observed a high willingness to the booster dose of COVID-19 vaccine both for the parents and their children, regardless of the eligibility to a booster dose. However, 40% of people had delayed vaccination behaviors. The promotion of scientific knowledge of vaccines' effectiveness and safety is needed, especially for people in poor health and parents with young children. Timely disclosure of AE caused by COVID-19 vaccines and proper aiding offered to people encountering AE are suggested.

Differences in incidence and fatality of COVID-19 by SARS-CoV-2 Omicron variant versus Delta variant in relation to vaccine coverage: A world-wide review.

We aim to evaluate the evolution differences in the incidence and case fatality rate (CFR) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta and Omicron variants. The average incidence and CFRs were described between different countries. A gamma generalized linear mixed model (GLMM) was used to compare the CFRs of Delta and Omicron variants based on vaccination coverage. Totally, 50 countries were included for analyses. The incidence of coronavirus disease 2019 (COVID-19) ranged from 0.16/100,000 to 82.95/100,000 during the Delta period and 0.03/100,000 to 440.88/100,000 during the Omicron period. The median CFRs were 8.56 (interquartile range [IQR]: 4.76-18.39) during the Delta period and 3.04 (IQR: 1.87-7.48) during the Omicron period, respectively. A total of 47 out of 50 countries showed decreased CFRs of the Omicron variant with the rate ratio ranging from 0.02 (95% confidence interval [CI]: 0.01-0.03) (in Cambodia) to 0.97 (95% CI: 0.87-1.08) (in Ireland). Gamma GLMM analysis showed that the decreased CFR was largely a result of the decreased pathogenicity of Omicron besides the increased vaccination coverage. The Omicron variant shows a higher incidence but a lower CFR around the world as a whole, which is mainly a result of the decreased pathogenicity by SARS-CoV-2's mutation, while the vaccination against SARS-CoV-2 still acts as a valuable measure in preventing people from death.

Safety and Efficacy of Paxlovid Against Omicron Variants of Coronavirus Disease 2019 in Elderly Patients.

INTRODUCTION: Elderly patients are the most affected and vulnerable to COVID-19 and effective therapeutic interventions are urgently required. We clarified the safety and efficacy of Paxlovid in the treatment of elderly patients with coronavirus disease 2019 (COVID-19). METHODS: Patients aged over 60 years and with mild to moderate COVID-19 were admitted to the Zhongshan Hospital MinHang MeiLong Branch, Fudan University and received either Paxlovid treatment or only conventional therapy, between April 1 and May 31, 2022. Viral shedding time, duration of hospital stay, disease progression, and adverse events were analyzed, and multivariate Cox regression analysis was performed to detect the independent high-risk factors for COVID-19 progression in the patients. RESULTS: A total of 163 (82 and 81 in the treatment and control groups, respectively) patients had a median age of 82 (71-89) years, and 89.0% had at least one concomitant disease. The duration of hospitalization reduced from 15 to 13 days, and viral shedding time reduced from 20 to 16.5 days after Paxlovid treatment. The differences of these two variables between the groups were significant (p < 0.01). Moreover, no serious adverse events or obvious changes in laboratory test results were observed in patients treated with Paxlovid. One patient (1.2%) treated with Paxlovid experienced rebound 56 days after negative measurement. Multivariate analysis showed that Paxlovid therapy, age, hemoglobin, and nucleic acid Ct values at admission were independent risk factors for hospitalization within 14 days, and the differences were significant (p < 0.01). CONCLUSION: The use of Paxlovid in elderly patients may promote recovery from COVID-19 and reduce the viral load without adverse events. CLINICAL TRIAL REGISTRATION: www. CLINICALTRIALS: gov , ID: ChiCTR2200066990.

Impact of air pollutants on influenza-like illness outpatient visits under COVID-19 pandemic in the subcenter of Beijing, China.

This study aimed to explore the association between air pollutants and outpatient visits for influenza-like illnesses (ILI) under the coronavirus disease 2019 (COVID-19) stage in the subcenter of Beijing. The data on ILI in the subcenter of Beijing from January 1, 2018 to December 31, 2020 were obtained from the Beijing Influenza Surveillance Network. A generalized additive Poisson model was applied to examine the associations between the concentrations of air pollutants and daily outpatient visits for ILI when controlling meteorological factors and temporal trend. A total of 171 943 ILI patients were included. In the pre-coronavirus disease 2019 (COVID-19) stage, an increased risk of ILI outpatient visits was associated to a high air quality index (AQI) and the high concentrations of particulate matter less than 2.5 (PM2.5 ), particulate matter 10 (PM10 ), sulphur dioxide (SO2 ), nitrogen dioxide (NO2 ), and carbon monoxide (CO), and a low concentration of ozone (O3 ) on lag0 day and lag1 day, while a higher increased risk of ILI outpatient visits was observed by the air pollutants in the COVID-19 stage on lag0 day. Except for PM10 , the concentrations of other air pollutants on lag1 day were not significantly associated with an increased risk of ILI outpatient visits during the COVID-19 stage. The findings that air pollutants had enhanced immediate effects and diminished lag-effects on the risk of ILI outpatient visits during the COVID-19 pandemic, which is important for the development of public health and environmental governance strategies.

Association Between COVID-19 Vaccination and Artificial Insemination Outcomes for Couples Experiencing Infertility.

This cohort study investigates the association between COVID-19 vaccination status and artificial insemination by partner outcomes among couples experiencing infertility in China.