Design and Synthesis of Novel Factor XIa Inhibitors with Bicyclic Isoquinoline and Naphthalene Fragments (preprint)

FXIa has emerged as a promising therapeutic target for treating thrombotic diseases. With the aim to replace the aniline motif of asundexian with novel P2’ fragments, bicyclic isoquinoline and naphthalene rings were designed. The target compounds with isoquinoline ring were synthesized via 13 steps of chemical reactions. Substituents within the rings were investigated to elucidate the structural determinants governing selective or dual inhibition of FXIa and Plasma Kallikrein (PKa). In vitro testing showed that some of designed compounds exhibited comparable potency against both FXIa and PKa, while others achieved up to 94-fold selectivity. Analysis of structure-activity relationships (SARs) uncovered the pivotal role of the carboxylic acid moiety in retaining inhibition of FXIa and PKa, and the steric hindrance and hydrogen-bond receptor functional groups were identified as key factors influencing the selectivity of FXIa inhibition over PKa. The docking study additionally unveiled different binding modes that play a significant role in the observed activity and selectivity. Furthermore, the selected compounds significantly extended the plasma coagulation time in a dose-dependent manner. Altogether, the bicyclic compounds may be promising lead compounds for the development of highly effective FXIa inhibitors.

Interruption of influenza transmission under public health emergency response based on real-world data, Beijing. (preprint)

Background: To estimate effect of COVID-19 control measures taken to mitigate community transmission in many regions, we analyzed data based on influenza surveillance system in Beijing from week 27th, 2014 to week 26th, 2020. Methods. We collected weekly number of influenza-like illness (ILI), weekly positive proportion of ILI and weekly ILI proportion in outpatients and the date of COVID-19 measures. We compared influenza activity indicators of influenza season 2019/2020 with preceding five seasons and built two ARIMAX models to estimate the effective of COVID-19 measures. Results. Compared with preceding five influenza seasons, ILIs, positive proportion of ILI, and duration of influenza epidemic period decreased from 13% to 54%, especially, the number of weeks from the peak to the end of influenza epidemic period, decreased from 12 to one. After natural decline considered, weekly ILIs decreased by 48.6% and weekly positive proportion dropped 15% in the second week after emergency response declared, and finally COVID-19 measures reduced 83%. Conclusions. We conclude public health emergency response can interrupt the transmission of influenza and other respiratory infectious diseases markedly. Keyword. COVID-19 control measures; influenza; ARIMAX

COVID-19 Caused by the Omicron Variant in Lung Transplant Recipients: A Single Center Case Series (preprint)

Background: Limited data from the Chinese experience are available regarding the infection status, clinical characteristics, treatments and early outcomes of lung transplant recipients (LTRs) afflicted with coronavirus disease 2019 (COVID-19) caused by the SARS-CoV-2 Omicron Variant. Methods: We conducted a study on LTRs with COVID-19 caused by the Omicron Variant from November 17, 2022, to May 1, 2023. Clinical information was gathered through electronic medical records, questionnaires, or follow-up telephone calls. To identify potential risk factors for severe disease progression, a multivariate logistic analysis was performed. Results: 178 LTRs with COVID-19 were included, with 50% (89/178) requiring hospitalization for an average stay of 16 days (IQR: 9.5-25.5 days). The most common symptoms were fever (79.8%), dry cough (75.3%) and fatigue (61.8%). Ultimately, 17 recipients succumbed to COVID-19-related respiratory failure or secondary multiple organ dysfunction, resulting in an overall mortality rate of 9.6%. Of the 89 hospitalized patients, 41.6% (37/89) eventually progressed to severe or critical disease, forming the Severe/Critical Group (S/C group), while the remaining 58.4% (52/89) had mild to moderate disease (M/M group). In comparison to the M/M group, the S/C group had higher CRP (59.6 vs. 16.8 mg/L, P＜0.01), ESR (45.5 vs. 22.5mm/h, P＜0.01) and D-dimer (1.09 vs. 0.65 mg/L, P＜0.05), but lower CD3+ T lymphocytes (577 vs. 962 cells/ul, P＜0.01) and CD4+ T lymphocytes (217 vs. 427 cells/ul, P＜0.01). The S/C group had significantly higher rates of combined pulmonary bacterial infection (67.6% vs. 38.5%, P＜0.01) and pulmonary fungal infection (73.0% vs. 38.5%, P＜0.01) during the course of COVID-19, nearly double that of the M/M group. In a multivariate logistic analysis, elevated CRP (>41.8mg/L), combined pulmonary fungal infection, and interstitial lung disease(ILD) as primary disease emerged as high-risk factors for developing the severe disease phenotype following Omicron variant infection in LTRs, with respective OR values of 4.23 (95% CI: 1.68-11.23), 4.76 (95% CI: 1.59-15.64), and 5.13 (95% CI: 1.19-29.17). Conclusions: LTRs displayed an increased vulnerability to combined lung bacterial or fungal infections following Omicron infection. CRP> 41.8mg/L, ILD as primary disease, and combined pulmonary fungal infection are high-risk factors for developing severe disease.

SARS-CoV-2 Reinfection by Omicron Variant in Shaanxi Province, China, December 2022 to February 2023 (preprint)

Background Before December 2022, we had not reported a patient in Shaanxi province, China, who had been reinfected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since then, China has refined its strategy for response to coronaviruses. The purpose of this study was to determine the incidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfections and compare the severity of the first and second episodes of infection in Shaanxi Province, China.Methods We used the epidemiological survey system with the electronic questionnaires to investigated the possibility of SARS-CoV-2 reinfection among those who previously were infected with coronavirus disease 2019 during the Omicron predominant infection wave beginning in December 2022. Logistic regression model was used to test the influencing factors of SARS-CoV-2 reinfections.Results The rate of reinfection for Omicron variants was 5.92%, 1.96%, and 1.28% 7–9 months, 4–5 months, and 2–3 months after the primary infection, respectively. The rate of reinfection for Delta variations was 25.10% 11–12 months after the primary infection. There were no significant changes in the severity of infection between first infection and reinfection. Adults between the ages of 18 and 38 and being a medical worker have been associated to an increased chance of reinfection.Conclusions SARS-CoV-2 reinfections might increase over time throughout Omicron variant-dominant infection waves. Large-scale infections are less likely to prevail in the following Omicron epidemic period. It is essential to continuously monitor infection cases as well as emerging SARS-CoV-2 variants.

Online Education Isn’t the Best Choice: Evidence-Based Medical Education in the Post-epidemic Era—A Cross-Sectional Study (preprint)

Background The COVID-19 pandemic led many educational institutions to shift to online courses, making blended education a significant trend in teaching. We examined the effectiveness of blended learning in an evidence-based medicine course.Methods We compared the examination scores of a blended learning group, an online only group, and a traditional offline group and conducted a questionnaire survey on students’ preferences for different learning modes and the reasons for their preferences. A total of 2100 undergraduate students in clinical medicine were included in this cross-sectional study. Examination results were collected, and questionnaires were administered to the study participants. We compared the mean theoretical scores and exam pass rates of the three teaching groups using ANOVA and c2test for multiple comparisons.Results The blended group’s theoretical scores and pass rate were significantly higher than those of the offline and online groups. Furthermore, 71.6% preferred the blended teaching mode. Most students believed that blended teaching was the most effective mode—offline education: 7.86%; online education: 26.14%; blended education: 66%. Subsequently, in a questionnaire administered to a blended group of students, their foremost reason for liking online instruction was ‘flexible in time and space’ (99%), followed by ‘can be viewed repeatedly, facilitating a better understanding of knowledge points’ (98%). Their foremost reason for liking offline teaching was ‘helps to create a good learning atmosphere’ (97%), followed by ‘teachers can control students’ learning status in real time’ (89%).Conclusions This study explored the effectiveness of learning in evidence-based medicine courses by comparing the learning outcomes and personal perceptions of three different teaching modes. This is the first cross-sectional study in which three different teaching models are compared and discussed in an evidence-based medicine course. We also elaborate on the specific instructional protocols for each model. This study shows that using a blended education approach in evidence-based medicine courses can improve students’ learning motivation, autonomy, and satisfaction. It also enhances instructional efficiency, thereby improving students’ understanding of the course content.

Cardiovascular Calcium Scoring by Deep Learning is Predictive of Mortality in Emergency Department Patients

Introduction: Computed tomography (CT) imaging is widely used in the emergency department (ED) setting. Calcifications of the coronary arteries, heart valves, and aorta are common incidental findings that may herald clinical or subclinical cardiovascular disease. Hypothesis: We sought to determine whether the quantitative burden of cardiovascular calcifications, as measured by a CT-based deep learning pipeline, would be predictive of short-term mortality in a diverse population of ED patients. Method(s): We conducted a prospective single-center cohort study nested in the Quebec COVID-19 Biobank from March 2020 to September 2021. For the purposes of this study, we enlisted adult patients presenting to the ED with cardiopulmonary symptoms who were tested for COVID-19 and underwent CT imaging of the chest. We used a deep learning model previously developed by our team to automate the quantitative scoring of coronary artery calcification (CAC), aortic valve calcification (AVC), mitral annular calcification (MAC), and thoracic aorta calcification (TAC) from the CT images. These calcium scores were categorized as sex-stratified tertiles plus a zero-score referent category. The primary outcome was all-cause mortality at 30 and 90 days adjusted for age, sex, and COVID-19 status using multivariable logistic regression. Result(s): The study sample consisted of 731 ED visits among 271 unique patients with a mean age of 66 years and 47% females. COVID-19 illness was the main diagnosis in 29% of ED visits. The prevalence of any quantifiable calcification was 51% for CAC, 33% for AVC, 23% for MAC, and 80% for TAC. The statistically significant adjusted odds ratios for mortality were 2.50 (1.08, 5.81) in the highest AVC tertile at 30 days, 2.73 (1.37 5.47) in the highest CAC tertile at 90 days, and 4.42 (1.01, 19.4) in the highest TAC tertile at 90 days. These odds ratio remained similar after further adjustment for past history of myocardial infarction or heart failure. Conclusion(s): High calcium scores in the coronary arteries, aortic valve, and thoracic aorta are associated with heightened 30-day mortality in ED patients. Deep learning quantification of calcium scores from clinical CT scans is an opportunistic approach for risk stratification.

Evaluation of photocathode coupling-mediated hydroxychloroquine degradation in a single-chamber microbial fuel cell based on electron transfer mechanism and power generation

A photocathode-microbial electrochemical coupling system (PC-MFC) using black phosphorus-doped titanium dioxide nanobelt (BP/TB) as a photocatalyst is constructed for the degradation of hydroxychloroquine (HCQ, used to treat COVID-19). The degradation efficiency of HCQ (100 mg/L) in coupling system is 73.7% within 8 h, higher than that of photocatalysis (69.5%), MFC (25.6%), and adsorption (9.6%). The photocathode coupling facilitates subsequent bioelectric treatment, resulting in complete degradation of HCQ (100 mg/L) within 96 h in PC-MFC, much higher than in MFC (51.1%). Illumination of PC-MFC significantly increases the cathodic abundance of Pseudomonadales ord. (from 1.83% to 66.30%), accumulates biomass, improves the electrochemical behaviors of photocathode and bioanode, and finally increases the maximum power from 241 to 280 mW/m2. The electron transfer pathways depende on nicotinamide adenine dinucleotide dehydrogenase, succinate dehydrogenase and terminal oxidase. The coupled system enhances the dechlorination reduction of HCQ and reduces the biotoxicity of its degradation pathway. PC-MFC represents a new strategy for the treatment and energy recovery of refractory organic compounds in wastewater.

Exploring the Transmission Dynamics of the COVID-19 Outbreaks after Dec. 2022 in Shaanxi Province, China: Analysis of Baseline Data from A Large Scale Cohort (preprint)

Backgrounds: The goal of this study is to explore the transmission dynamics for recent large-scale COVID-19 outbreaks in Shaanxi Province on the Chinese mainland. Furthermore, the potential effects of the Spring Festival travel rush on the ongoing COVID-19 pandemic were depicted. Methods This study uses baseline data from a large cohort to investigate the characteristics of the recent COVID-19 epidemic in Shaanxi province. A cluster sampling method was used to recruit the study participants during the COVID-19 pandemic in Shaanxi province since Dec. 1st, 2022. A total of 44 sampling cluster (11 village in rural areas and 33 residences in urban areas) were chosen for enrollment of study participants. A self-developed questionnaire was applied to data collection of socio-demographic and COVID-19 pandemic related information. Results A total of 14,744 study participants were enrolled in the baseline survey and 12,111 completed survey data were extracted for analysis. The cumulative infection attack rate (IAR) of COVID-19 among the study participants was 84.7%. The cumulative IAR in urban and rural areas were 85.6% and 83.7%, respectively. A peak of COVID-19 self-reported diagnosis could be observed from Dec. 15th, 2022 to Jan. 1st, 2023 in the provincial level. Beside this major peak of the recent epidemic (around Dec.20th, 2022), a small but steep rise could also be identified between Jan 13th to 14th, 2023. Individuals who escaped the first wave of COVID-19 outbreaks may face danger of infection from returnees during the 2023 Spring Festival. Conclusion According to the COVID-19 cumulative IAR data, the herd community was primarily achieved in Shaanxi province's urban and rural areas. The epidemic in Shaanxi province has been exacerbated by mass population movement during the Spring Festival travel rush in both urban and rural areas. Further surveillance should be performed to monitor the spread of SARS-CoV-2 infections.

Nurses’ Humanistic Care Behaviour in China: A Cross-sectional Survey (preprint)

Background More attention has been focused on the development of nurses' humanistic care behavior during the COVID-19 outbreak in China. However, its level is unknown.Method A cross-sectional study was conducted with an online questionnaire administered in August 2020. Descriptive statistics and binary logistics regression analyses were conducted using the SPSS 26.0.Results The total score of nurses' humanistic care behaviour is 117.59 ± 22.434. Different genders, age, marital status, nursing ages, professional titles, and attention degrees of hospital humanities have a varied impact on the nurses' humanistic care behaviour (p < 0.05). The binary logistic regression model was statistically significant (p < 0.01).Conclusion This study reported the level and influencing factors of caring behavior among Chinese nurses and provided evidence-based strategies to improve its level.

Genome-wide screening of sex-biased genetic variants potentially associated with COVID-19 hospitalization

Sex-biased difference in coronavirus disease 2019 (COVID-19) hospitalization has been observed as that male patients tend to be more likely to be hospitalized than female patients. However, due to the insufficient sample size and existed studies that more prioritized to sex-stratified COVID-19 genome-wide association study (GWAS), the searching for sex-biased genetic variants showing differential association signals between sexes with COVID-19 hospitalization was severely hindered. We hypothesized genetic variants would show potentially sex-biased genetic effects on COVID-19 hospitalization if they display significant differential association effect sizes between male and female COVID-19 patients. By integrating two COVID-19 GWASs, including hospitalized COVID-19 patients vs. general population separated into males (case = 1,917 and control = 221,174) and females (case = 1,343 and control = 262,886), we differentiated the association effect sizes of each common single nucleotide polymorphism (SNP) within the two GWASs. Twelve SNPs were suggested to show differential COVID-19 associations between sexes. Further investigation of genes (n = 58) close to these 12 SNPs resulted in the identification of 34 genes demonstrating sex-biased differential expression in at least one GTEx tissue. Finally, 5 SNPs are mapped to 8 genes, including rs1134004 (GADD45G), rs140657166 (TRIM29 and PVRL1), rs148143613 (KNDC1 and STK32C), rs2443615 (PGAP2 and TRIM21), and rs2924725 (CSMD1). The 8 genes display significantly differential gene expression in blood samples derived from COVID-19 patients compared to healthy controls. These genes are potential genetic factors contributing to sex differences in COVID-19 hospitalization and warranted for further functional studies.

Safety, Tolerability, and Immunogenicity of PIKA-Adjuvanted Re-combinant SARS-CoV-2 Spike (S) Protein Subunit Vaccine in Healthy Adults: Interim results of an open-label and randomised Phase 1 clinical trial. (preprint)

Background: This COVID-19 pandemic has caused unprecedented morbidity, mortality, and global economic instability. Several approved vaccines demonstrated to be effective prevention against COVID-19. We aimed to evaluate the safety and immunogenicity of the PIKA-adjuvanted recombinant SARS-C0V-2 Spike (S) protein subunit vaccine in adults as a primary immunization and as a booster dose against SARS-C0V-2 infection. Methods: This was a Phase I, open label, dose-escalation study of 3 dose levels of the SARS-CoV-2 spike antigen administered intramuscularly in combination with a fixed dosage of PIKA adjuvant vaccine to evaluate the safety, tolerability, and immunogenicity of PIKA COVID-19 vaccine candidate in healthy adults. The study planned to have 3 arms: Arm A included subjects who had never received any Covid 19 vaccination or have had Covid 19 infection for > 6 months prior to enrolment, Arm B1 included subjects who had completed their primary series of Covid 19 vaccination with an inactivated Covid 19 vaccine and Arm B2 which included subjects whose primary series was completed with mRNA Covid 19 vaccine. The primary safety outcome was adverse events and safety laboratory parameters, and the secondary immunogenicity outcome was neutralizing antibody geometric mean titers and seroconversion rates against the wild type virus, Delta and Omicron variants. Findings: This interim analysis report presented the results of Arm A and Arm B1 who completed Day 35 for 2 doses in Arm A and Day 28 for a single booster dose in Arm B1. Safety results: Arm A: 60% of participants reported mainly solicited AEs after first and second vaccine. Most of those were local (mainly pain/tenderness) with few systemic (mainly fever and headaches). The majority of participants reported unsolicited events after vaccine which were mainly investigations in hematology/hepatobiliary/ Renal or Urine tract infection urine analysis. At least 80% of the participants reported mild AEs. There were 4 SAEs that were mild and were resolved. Also there were 2 medically attended AEs. Arm B1: Less than 50% of the participants reported solicited adverse events which were mainly local (pain and tenderness) and were mild. Also, less than half of the participants reported unsolicited events which were mainly investigations in hematology/hepatobiliary/ Renal or Urine tract infection urine analysis. There were no SAE and Medically attended AEs reported. Immunogenicity results: Arm A: The neutralizing antibody GMTs at day 35 were substantially higher than those at baseline for all dose groups and all variants. Seroconversion rates at 35 days ranged between 85.7% and 92.9% for 5microgram dose group, 92.9% and 100% for the 10microgram dose group and between 70% and 80% for the high dose group. Arm B1: Similar to Arm A, neutralizing antibody GMTs at day 28 were substantially higher than those at baseline for all dose groups and all variants. Seroconversion rates at 28 days ranged between 92.9% and 100% for 5microgram dose group, 80% and 100% for the 10microgram dose group and between 50% and 64.3% for the high dose group. Conclusion: The findings demonstrated that the PIKA Covid 19 vaccine is safe, well tolerated, immunogenic and can be used as a primary vaccination or as a booster dose in participants who had completed an inactivated Covid 19 vaccination series. A comparison of the immune responses presented in this interim analysis showed that geometric mean titer (GMTs) of neutralizing antibody against wild type of SARS-CoV-2 virus, Delta and Omicron of the 5microgram group was higher than the 10 microgram and 20 microgram, therefore the 5microgram was selected as the recommended dose for the Phase II and III clinical development of the PIKA Covid 19 vaccine.

Effects of Social Media Usage on Job Crafting for Female Employees during the COVID-19 Pandemic: Evidence from China

During the COVID-19 pandemic, the use of social media platforms for working online has become a global phenomenon. For female employees, social media usage has made it easier to balance work and family, but the pressures have also multiplied. Especially in China, the COVID-19 prevention policies led to dramatic changes in working patterns, which significantly affected the emotions, cognitions, and behaviors of female employees. Based on the job demands resource theory, this study explores the double-edged effect of social media usage on job crafting for female employees. Survey data were collected from 563 female employees in Chinese enterprises. Hierarchical regression analysis and the bootstrap method by SPSS and AMOS software were used to test the hypotheses. The results show that work-related social media usage has a negative effect on job crafting, while social-related social media usage has a positive effect. Moreover, job autonomy and workplace friendship mediate the relationship between them. This study extends the research on the double-edge effect of female employees' social media usage and enriches the antecedents and influencing mechanisms of job crafting. It also provides theoretical and practical guidance for managers on how to promote the sustainability of human capital during the COVID-19 pandemic.

Making use of an App (Tawakkalna) to track and reduce COVID transmission in KSA (preprint)

Since March 2020, the Kingdom of Saudi Arabia (KSA) has launched several digital applications to support the intervention response to reduce the spread of SARS-CoV-2. At the beginning of 2021, the KSA Government introduced a mandatory immunity passport to regulate access to public venues. The passport was part of the strategy of resuming public activities before reaching high vaccination coverage. The passport was implemented as a new service in the Tawakkalna mobile phone application (App). The immunity passport allowed access to public locations only for the users who recovered from COVID-19 or those who were double vaccinated. Our study aimed to evaluate the effectiveness of the immunity passport, implemented through the Tawakkalna App, on SARS-CoV-2 spread. We built a spatial-explicit individual-based model to represent the whole KSA population (IBM-KSA) and its dynamic on a national scale. The IBM-KSA was parameterized using country demographic, remote sensing, and epidemiological data. The model included non-pharmaceutical interventions and vaccination coverage. A social network was created to represent contact heterogeneity and interaction among age groups of the population. The IBM-KSA also simulated the movement of people across the country based on a gravity model. We used the IBM-KSA to evaluate the effect of the immunity passport on the COVID-19 epidemics outcomes. The IBM-KSA results showed that implementing the immunity passport through the Tawakkalna App mitigated the SARS-CoV2 spread. In a scenario without the immunity passport, the KSA could have reported 1,515,468 (95% confidence interval [CI]: 965,725-1,986,966) cases, and 30,309 (95% CI: 19,314-39,739) deaths from March 2021 to November 2021. The comparison of IBM-KSA results with COVID-19 official reporting estimated that the passport effectively reduced the number of cases, hospitalizations, and deaths by 8.7 times, 13.5 times, and 11.9 times, respectively. These results showed that the introduction of the immunity passport through the Tawakkalna App was able to control the spread of the SARS-COV-2 until vaccination reached high coverage. By introducing the immunity passport, The KSA was able to allow to resume most of public activities safely.

Quarantine and demographic characteristics as predictors of perceived stress and stress responses during the third year of COVID-19 in China

Background Quarantine as one of the most effective epidemic prevention measures, significantly increased people's stress levels. Ongoing monitoring of the stress status of people under quarantine during the pandemic is an important part of assessing the long-term impact of COVID-19 on mental health. This study aimed to gain a more comprehensive understanding of the stress status of people under quarantine, including perceived stress and stress responses, during the third year of the COVID-19 pandemic in China. Methods An anonymous online survey was conducted among 464 participants from 39 cities in China from March 31 to April 12, 2022. The survey included three questionnaires: a self-designed questionnaire collecting demographic information and quarantine characteristics, the Perceived Stress Scale (PSS-10) and the Stress Response Questionnaire (SRQ). The t-test or one-way ANOVA or the Welch F-test were used to examine the differences among demographic and quarantine variables of perceived stress and stress responses, then multiple linear regressions were performed to identify the predictors of perceived stress and stress responses. Results 428 valid respondents were finally included. The average scores of perceived stress, total stress response, emotional response, physical response, and behavioral response were 14.70 ± 7.02, 50.24 ± 22.48, 20.35 ± 9.99, 15.23 ± 7.25, and 11.39 ± 5.27, respectively. The regression analysis showed that the degree of financial worries and days of continuous quarantine were the predictors of perceived stress. The degree of financial worries was a vital factor in predicting total stress response, emotional response, physical response and behavioral response, and in predicting emotional response, age was also a significant predictor. Conclusion The stress status of individuals under quarantine was generally stable but still needs further attention during the third year of the COVID-19 pandemic. People who are young, have a high degree of financial worries and have been quarantined for a long time may be at a higher risk of perceived stress and stress responses. Relevant authorities should pay closer attention to the risk groups, and additional support and assistance might be required for those mostly worried about their financial situations under quarantine.

Real-time detection of viruses in aerosols with weak light imaging based on Tesla discharge

The analysis and detection of nucleic acid and specific antigens and antibodies are the most basic technologies for virus monitoring. However, the potential window for applying these technologies exists within a late specific period in the early monitoring and control of unknown viruses, especially human and animal pathogenic viruses transmitted via aerosols, e.g., SARS-CoV-2 and its variants. This is because early, real-time, and convenient monitoring of unknown viruses in the air or exhaled gas cannot be directly achieved through existing technologies. Herein, we report a weak light spectral imaging technology based on Tesla discharge (termed T-DAI) that can quickly monitor for viruses in real time in simulated aerosols with 71% sensitivity and 76% specificity for aerosol virus concentrations exceeding approximately 2800 vp/μl. This technology realizes the rapid detection of low concentrations of viruses in aerosols and could provide an important means for predicting, screening, and monitoring unknown or pandemic pathogenic viruses in the air or exhaled breath of humans and animals. [ FROM AUTHOR] Copyright of Applied Physics Letters is the property of American Institute of Physics 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 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 . (Copyright applies to all s.)

Study protocol: Social Health Impact of Network Effects (SHINE) Study (preprint)

Humans are a fundamentally social species whose well-being depends on how we connect with and relate to one another. As such, scientific understanding of factors that promote health and well-being requires insight into causal factors present at multiple levels of analysis, ranging from brain networks that dynamically reconfigure across situations to social networks that allow behaviors to spread from person to person. The Social Health Impacts of Network Effects (SHINE) study takes a multilevel approach to investigate how interactions between the mind, brain, and community give rise to well-being. The SHINE protocol assesses multiple health and psychological variables, with particular emphasis on alcohol use, how alcohol-related behavior can be modified via self-regulation, and how thoughts, feelings, and behaviors unfold in the context of social networks. An overarching aim is to derive generalizable principles about relationships that promote well-being by applying multilayer mathematical models and explanatory approaches such as network control theory. The SHINE study includes data from 711 college students recruited from social groups at two universities in the northeastern United States of America, prior to and during the COVID-19 pandemic. Participants completed at least one of the following study components: baseline self-reported questionnaires and social network characterization, self-regulation intervention assignment (mindful attention or perspective taking), functional and structural neuroimaging, ecological momentary assessment, and longitudinal follow-ups including questionnaires and social network characterization. The SHINE dataset enables integration across modalities, levels of analysis, and timescales to understand young adults’ well-being and health-related decision making. Our goal is to further our understanding of how individuals can change their thoughts, feelings, and behaviors, and of how these changes unfold in the context of social networks.

Metabolite profile of COVID-19 revealed by UPLC-MS/MS-based widely targeted metabolomics

The metabolic characteristics of COVID-19 disease are still largely unknown. Here, 44 patients with COVID-19 (31 mild COVID-19 patients and 13 severe COVID-19 patients), 42 healthy controls (HC), and 42 patients with community-acquired pneumonia (CAP), were involved in the study to assess their serum metabolomic profiles. We used widely targeted metabolomics based on an ultra-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The differentially expressed metabolites in the plasma of mild and severe COVID-19 patients, CAP patients, and HC subjects were screened, and the main metabolic pathways involved were analyzed. Multiple mature machine learning algorithms confirmed that the metabolites performed excellently in discriminating COVID-19 groups from CAP and HC subjects, with an area under the curve (AUC) of 1. The specific dysregulation of AMP, dGMP, sn-glycero-3-phosphocholine, and carnitine was observed in the severe COVID-19 group. Moreover, random forest analysis suggested that these metabolites could discriminate between severe COVID-19 patients and mild COVID-19 patients, with an AUC of 0.921. This study may broaden our understanding of pathophysiological mechanisms of COVID-19 and may offer an experimental basis for developing novel treatment strategies against it.

A multispecific antibody confers pan-reactive SARS-CoV-2 neutralization and prevents immune escape (preprint)

Continued evolution of the SARS-CoV-2 spike poses a challenge to immune interventions. To develop antibodies that protect against evolving SARS-CoV-2 viruses, we combined antibodies that recognize different RBD sites to generate a trivalent antibody that potently neutralized all major variants, including the most recent Omicron lineages. Negative stain electron microscopy suggests that this multispecific achieves synergistic neutralization by engaging different epitopes in specific orientations that facilitate inter-spike binding. These interactions resulted in not only improved potency but also importantly prevented virus escape, a feature not seen with parental antibody cocktails or the most potent clinical mAb. Such multispecific antibodies simplify treatment, maximize coverage, decrease the likelihood of SARS-CoV-2 escape, and provide the basis for building universal SARS-CoV-2 antibody therapies that are more likely to maintain broad reactivity for future variants.