Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation (preprint)

The proliferation of online misinformation has posed significant threats to public interest. While numerous online users actively participate in the combat against misinformation, many of such responses can be characterized by the lack of politeness and supporting facts. As a solution, text generation approaches are proposed to automatically produce counter-misinformation responses. Nevertheless, existing methods are often trained end-to-end without leveraging external knowledge, resulting in subpar text quality and excessively repetitive responses. In this paper, we propose retrieval augmented response generation for online misinformation (RARG), which collects supporting evidence from scientific sources and generates counter-misinformation responses based on the evidences. In particular, our RARG consists of two stages: (1) evidence collection, where we design a retrieval pipeline to retrieve and rerank evidence documents using a database comprising over 1M academic articles; (2) response generation, in which we align large language models (LLMs) to generate evidence-based responses via reinforcement learning from human feedback (RLHF). We propose a reward function to maximize the utilization of the retrieved evidence while maintaining the quality of the generated text, which yields polite and factual responses that clearly refutes misinformation. To demonstrate the effectiveness of our method, we study the case of COVID-19 and perform extensive experiments with both in- and cross-domain datasets, where RARG consistently outperforms baselines by generating high-quality counter-misinformation responses.

Universal protection against SARS-CoV-2 viruses by multivalent mRNA vaccine in mice (preprint)

The ongoing emergence of new strains of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants challenges available SARS-CoV-2 vaccines for adequate control of outbreaks. Currently, there is a lack of universal vaccines for SARS-CoV-2 variants that do not necessitate strain matching between mRNA vaccines and the viruses. In this study, a nucleoside-modified twenty-valent lipid nanoparticle mRNA vaccine was designed and manufactured. The primary objective is to provide protection against various recent variants via the twenty-valent mRNA vaccine after efficacy assessment. Furthermore, the protection efficiency of bivalent and quadrivalent mRNA vaccines was compared with the universal vaccine. The neutralizing antibody activity against BA.4/5, XBB.1.5, BQ.1.1, and EG.5.1 was evaluated using enzyme-linked immunosorbent assay, pseudovirus neutralization test, and a rapid fiber-optic biolayer interferometry-based biosensor. Our universal multivalent vaccine provided robust protection against both prevailing and emerging, previously unidentified SARS-CoV-2 strains.

MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta Learning (preprint)

With emerging topics (e.g., COVID-19) on social media as a source for the spreading misinformation, overcoming the distributional shifts between the original training domain (i.e., source domain) and such target domains remains a non-trivial task for misinformation detection. This presents an elusive challenge for early-stage misinformation detection, where a good amount of data and annotations from the target domain is not available for training. To address the data scarcity issue, we propose MetaAdapt, a meta learning based approach for domain adaptive few-shot misinformation detection. MetaAdapt leverages limited target examples to provide feedback and guide the knowledge transfer from the source to the target domain (i.e., learn to adapt). In particular, we train the initial model with multiple source tasks and compute their similarity scores to the meta task. Based on the similarity scores, we rescale the meta gradients to adaptively learn from the source tasks. As such, MetaAdapt can learn how to adapt the misinformation detection model and exploit the source data for improved performance in the target domain. To demonstrate the efficiency and effectiveness of our method, we perform extensive experiments to compare MetaAdapt with state-of-the-art baselines and large language models (LLMs) such as LLaMA, where MetaAdapt achieves better performance in domain adaptive few-shot misinformation detection with substantially reduced parameters on real-world datasets.

Epidemiological and clinical characteristics of SARS-CoV-2 Omicron variant

The COVID-19 pandemic continues to rage worldwide and the SARS-CoV-2 Omicron variant has now replaced the Delta variant as the leading epidemic strain.Omicron, as one of the SARS-COV-2 variants, incorporates the most critical mutations of the Alpha and Delta variants, and is characterized by having multiple mutation sites, high viral load, stronger infectivity and immune escape, which significantly reduced the protective effect of the vaccine.However, compared with the previous SARS-CoV-2 strains, the Omicron variant is less likely to infect lung tissue, it usually causes mild clinical symptom with reduced hospitalization rate, severe disease rate and fatality rate.Three doses of allogeneic vaccine can offer better tolerance and immunogenicity, and improve the protective effect of the vaccines.The application of small-molecule antiviral drugs and neutralizing antibodies can significantly reduce the hospitalization rate and mortality rate.In this paper, the epidemiological and characteristics of the Omicron variant were reviewed in order to provide reference for clinical diagnosis and treatment of the disease.

Unsupervised Domain Adaptation for COVID-19 Information Service with Contrastive Adversarial Domain Mixup (preprint)

In the real-world application of COVID-19 misinformation detection, a fundamental challenge is the lack of the labeled COVID data to enable supervised end-to-end training of the models, especially at the early stage of the pandemic. To address this challenge, we propose an unsupervised domain adaptation framework using contrastive learning and adversarial domain mixup to transfer the knowledge from an existing source data domain to the target COVID-19 data domain. In particular, to bridge the gap between the source domain and the target domain, our method reduces a radial basis function (RBF) based discrepancy between these two domains. Moreover, we leverage the power of domain adversarial examples to establish an intermediate domain mixup, where the latent representations of the input text from both domains could be mixed during the training process. Extensive experiments on multiple real-world datasets suggest that our method can effectively adapt misinformation detection systems to the unseen COVID-19 target domain with significant improvements compared to the state-of-the-art baselines.

Exploring the mechanism of action of licorice in the treatment of COVID-19 through bioinformatics analysis and molecular dynamics simulation

The mechanisms analysis of licorice in the treatment of COVID-19.

Do preschool teachers in Southwest China need more mental health education? An online cross-sectional survey 1 year after the COVID-19 pandemic

This study intended to explore the current status of psychological problems of preschool teachers in Southwest China 1 year after the COVID-19 pandemic and to assess the association between mental health education and psychological problems and symptoms of psychopathology. A total of 614 preschool teachers from Southwest China were enrolled to complete the questionnaires of the Chinese Symptom Checklist (SCL-90). Notably, 60% of the respondents reported psychological distress with GSI T-scores ≥ 63, especially the high score was reported on obsessive-compulsive disorder, interpersonal sensitivity, and phobic anxiety. Although less than half of the respondents have received mental health education last year, the teachers who received the mental health education reported lower GSI T-scores(β = −1.303, 95% CI: −2.208, −0.397). The results demonstrated the significance of constructing the education of promoting mental health of preschool teachers, and enlightening government or managers of kindergartens to relieve the psychological problems of preschool teachers through mental health education, especially for those with the pressure of overtime. It is recommended that local governments or kindergartens should organize more mental health education for kindergarten teachers to improve their mental health as well as their teaching professionalism.

Back Cover: Amplification‐Free Detection of SARS‐CoV‐2 and Respiratory Syncytial Virus Using CRISPR Cas13a and Graphene Field‐Effect Transistors (Angew. Chem. Int. Ed. 32/2022)

Nucleic acid detection plays a critical role in medical diagnostics, environmental monitoring, and food safety. In their Research Article (e202203826), Xue Gao, Yi Zhang and co‐workers developed a new biosensor for amplification‐free nucleic acid detection via harnessing the trans‐cleavage mechanism of Cas13a and ultrasensitive graphene field‐effect transistors (gFETs). The illustration shows the Cas13a‐mediated RNA trans‐cleavage on a gFET surface for sensor signal transduction.

Caspase-1 and Gasdermin D Afford the Optimal Targets with Distinct Switching Strategies in NLRP1b Inflammasome-Induced Cell Death.

Inflammasomes are essential complexes of innate immune system, which form the first line of host defense against pathogens. Mounting evidence accumulates that inflammasome signaling is highly correlated with coronavirus disease 2019 (COVID-19). However, there remains a significant gap in our understanding of the regulatory mechanism of inflammasome signaling. Combining mathematical modeling with experimental analysis of NLRP1b inflammasome signaling, we found that only the expression levels of caspase-1 and GSDMD have the potential to individually switch cell death modes. Reduction of caspase-1 or GSDMD switches cell death from pyroptosis to apoptosis. Caspase-1 and GSDMD present different thresholds and exert distinct pathway choices in switching death modes. Pyroptosis switches to apoptosis with an extremely low threshold level of caspase-1, but with a high threshold of GSDMD. Caspase-1-impaired cells employ ASC-caspase-8-dependent pathway for apoptosis, while GSDMD-impaired cells primarily utilize caspase-1-dependent pathway. Additionally, caspase-1 and GSDMD can severally ignite the cooccurrence of pyroptosis and apoptosis. Landscape topography unravels that the cooccurrence is dramatically different in caspase-1- and GSDMD-impaired cells. Besides pyroptosis state and apoptosis state, a potential new "coexisting" state in single cells is proposed when GSDMD acts as the driving force of the landscape. The "seesaw model" is therefore proposed, which can well describe the death states that are controlled by caspase-1 or GSDMD in single cells. Our study sheds new light on NLRP1b inflammasome signaling and uncovers the switching mechanisms among various death modes, providing potential clues to guide the development of more rational control strategies for diseases.

Engineering of Biodegradable and Excretable Inflammation‐Resolving Materials

Uncontrolled or chronic inflammation contributes to the pathogenesis of many acute/chronic diseases, such as acute organ injury, COVID‐19, and atherosclerosis. Intrinsically bioactive materials are promising for regulating the response magnitude and duration of inflammation, but their translation remains challenging. Herein, the engineering of a series of inflammation‐resolving materials by rationally integrating different functional modules into a hydrolyzable scaffold is reported. The obtained functional materials can assemble into potent anti‐inflammatory micelles capable of eliminating different types of reactive oxygen species, releasing bioactive molecules, and simultaneously hydrolyzing into water‐soluble and excretable compounds. Cellularly, these micelles effectively inhibit the migration, activation, and production of molecular mediators in inflammatory cells. Benefiting from the small size and high bioactivity, the developed micelles efficiently accumulate in the kidneys of mice with acute kidney injury (AKI) and efficaciously alleviate AKI. Bioactive micelles also demonstrate desirable targeting and superior efficacies in mice with acute liver failure. Mechanistically, inhibition of oxidative damage, attenuation of inflammatory cell infiltration and activation, and promoting resolution of inflammation mainly account for beneficial therapeutic effects of micelles. Moreover, preliminary studies reveal the excellent safety of micelles. Consequently, the bioactive materials represent a new type of efficacious, safe, scalable, and affordable therapy for a broad spectrum of inflammatory diseases. [ FROM AUTHOR] Copyright of Advanced Functional Materials is the property of John Wiley & Sons, Inc. 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.)

Analysis on a nosocomial infection event in a designated COVID-19 hospital in Shandong from the perspective of disease control

Objective: To analyze a nosocomial infection event in a designated hospital of coronavirus disease 2019 (COVID-19) in Shandong province retrospectively from the perspective of disease control and provide evidence to prevent the incidence of similar event.

Progressive assembly of multi-domain protein structures from cryo-EM density maps

Progress in cryo-electron microscopy has provided the potential for large-size protein structure determination. However, the success rate for solving multi-domain proteins remains low because of the difficulty in modelling inter-domain orientations. Here we developed domain enhanced modeling using cryo-electron microscopy (DEMO-EM), an automatic method to assemble multi-domain structures from cryo-electron microscopy maps through a progressive structural refinement procedure combining rigid-body domain fitting and flexible assembly simulations with deep-neural-network inter-domain distance profiles. The method was tested on a large-scale benchmark set of proteins containing up to 12 continuous and discontinuous domains with medium- to low-resolution density maps, where DEMO-EM produced models with correct inter-domain orientations (template modeling score (TM-score) >0.5) for 97% of cases and outperformed state-of-the-art methods. DEMO-EM was applied to the severe acute respiratory syndrome coronavirus 2 genome and generated models with average TM-score and root-mean-square deviation of 0.97 and 1.3 Å, respectively, with respect to the deposited structures. These results demonstrate an efficient pipeline that enables automated and reliable large-scale multi-domain protein structure modelling from cryo-electron microscopy maps.

Mass screening is a key component to fight against SARS-CoV-2 and return to normalcy

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had highly transmissible and pathogenic, which caused serious economic loss and hazard to public health. Different countries have developed strategies to deal with the COVID-19 pandemic that fit their epidemiological situations, capacities, and values. Mass screening combined with control measures rapidly reduced the transmission of the SARS-CoV-2 infection. The COVID-19 pandemic has dramatically highlighted the essential role of diagnostics capacity in the control of communicable diseases. Mass screening has been increasingly used to detect suspected COVID-19 cases and their close contacts, asymptomatic case, patients attending fever clinics, high-risk populations, employees, even all population to identify infectious individuals. Mass screening is a key component to fight against SARS-CoV-2 and return to normalcy. Here we describe the history of mass screening, define the scope of mass screening, describe its application scenarios, and discuss the impact and challenges of using this approach to control COVID-19. We conclude that through a comprehension screening program and strong testing capabilities, mass screening could help us return to normalcy more quickly.

Amplification-Free Detection of SARS-CoV-2 and Respiratory Syncytial Virus Using CRISPR Cas13a and Graphene Field-Effect Transistors

Der Nachweis von Nukleinsäuren spielt eine wichtige Rolle in der medizinischen Diagnostik, der Umweltüberwachung und der Lebensmittelsicherheit. In ihrem Forschungsartikel (DOI: 10.1002/ange.202203826) entwickelten Xue Gao, Yi Zhang und Mitarbeiter einen neuen Biosensor für den amplifikationsfreien Nukleinsäurenachweis, indem sie den trans-Spaltungsmechanismus von Cas13a und ultrasensitive Graphen-Feldeffekttransistoren (gFETs) nutzten. Die Abbildung zeigt die Cas13a-vermittelte RNA-trans-Spaltung auf der gFET-Oberfläche für die Sensorsignalübertragung.

Investigation of Major Flavonoids from Artemisia argyi as a Potential COVID-19 Drug: Molecular Docking and DFT Calculations

Flavonoids from natural products are well-identified as potential antiviral agents in the treatment of SARS-CoV-2 (COVID-19) infection and related diseases. However, some major species of flavonoids from Chinese traditional folk medicine, such as of Artemisia argyi (A. argyi), have not been evaluated yet. Here, we choose five major flavonoids obtained from A. argyi, namely, Jaceosidin (1), Eupatilin (2), Apigenin (3), Eupafolin (4), and 5,6-Dihydroxy-7,3′,4′-trimethoxyflavone (5), compared to the well-studied Baicalein (6), as potential inhibitors analogs for COVID-19 by computational modeling strategies. The frontier molecular orbitals (FMOs), chemical reactivity descriptors, and electrostatic surface potential (ESP) were performed by density functional theory (DFT) calculations. Additionally, these flavonoids were docked on the main protease (PDB: 6LU7) of SARS-CoV-2 to evaluate the binding affinities. Computational analysis predicted that all of these compounds show a high affinity and might serve as potential inhibitors to SARS-CoV-2, among which compound (5) exhibits the least binding energy (−155.226 kcal/mol). The high binding affinity could be enhanced by increasing the electron repulsion due to the valence shell electron pair repulsion model (VSEPR). Consequently, the major flavonoids in Artemisia argyi have a significant ability to reduce the deterioration of COVID-19 in the terms of DFT calculations and molecular docking.

Discussion about the prevention of Coronavirus disease 19 based on the thought of treating non-disease and the theory of constitution of traditional Chinese medicine

Objective To summarize and analyze the susceptible constitution of coronavirus disease 19(COVID-19), put forward the diet prescription of traditional Chinese medicine for prevention based on the thought of treating non-disease and the theory of constitution, and to provide reference for COVID-19's prevention. Methods The relevant literatures in the past 5 years were reviewed, and the current situation of COVID-19's clinical manifestations, etiology, pathogenesis, disease location, disease transmission, susceptible physique, physique differentiation and prevention were summarized. Results The symptoms of COVID-19 were similar in the initial stage of infection, which was caused by damp pathogen. People with different physique were different in susceptibility to COVID-19 and the development and outcome of syndrome type after infection. The susceptible constitution was phlegm-dampness, dampness-heat, Qi deficiency and yang deficiency, blood stasis and Qi depression. Invigorating vital Qi, dispelling dampness, and nourishing lung are the basic treatment principles. Combined with physical differences and dialectical prevention, tonifying, invigorating spleen and stomach, and aromatic dampness-transforming drugs are major drugs, which are supplemented by drugs for promoting lung-Qi. Conclusion The formulation of preventive prescriptions of traditional Chinese medicine according to different physique can provide some guidance for the clinical prevention of COVID-19.

Female analysts and COVID-19 corporate donation

This paper examines the impact of female analysts' coverage on firm's philanthropic activities amidst the outbreak of the COVID-19 pandemic in China. Using a hand-collected dataset of corporate philanthropy, the paper provides robust evidence that firms covered by female analysts are more likely to contribute actively to the well-being of societies by providing corporate donation. This positive relationship is more pronounced if the company is privately controlled or covered by female analysts with more working experience, or located in more infectious provinces. Overall, our findings call for more female analyst recruitment, yielding benefits of pressuring firms to engage in philanthropy.

Prevention and Control of COVID-19 Risks for Long-Term Care Facilities Based on the Prospect Theory

Given the complexity and uncertainty of the current COVID-19 risks, the elderly people in long-term care facilities are at the highest risk for infection. In order to study the prevention and control strategies of COVID-19 risks in long-term care facilities, this paper uses the prospect theory to construct the decision-making model of COVID-19 risk behavior of long-term care facilities, analyses the risk behavior strategies of the caregivers and managers, and reveals the impact of risk management cost, risk loss and external supervision on the risk behavior decision-making of the caregivers and managers. Furthermore, from the perspective of long-term care facilities, this paper analyzes the constraints that enable it to achieve optimal risk management strategy. Combined with the simulation analysis, it is found that the decision of risk behavior of the caregivers and managers is positively related to the risk behavior choice, risk loss, and supervision. Then, only when the incentives set by the supervision are within a reasonable range can the caregivers and managers be motivated to take proactive risk management strategies. The study has important theoretical and practical significance for the management of COVID-19 risks in long-term care facilities.