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

Global Adaptive Histogram Feature Network for Automatic Segmentation of Infection Regions in CT Images (preprint)

We applied deep learning techniques in lung CT image diagnosis of COVID-19 for accurate segmentation of disease diagnosis. We propose a new deep learning framework, GAHFNet, specifically designed for automatic segmentation of COVID-19 lung CT images. GAHFNet outperforms other traditional and the state-of-the-art methods in various evaluation metrics, demonstrating the effectiveness and the efficiency of the proposed method in this task. This article discusses the limitations of current diagnostic methods, such as RT-PCR, and highlights the advantages of deep learning, including its ability to automatically learn features and handle complex lesion morphology and texture. Furthermore, the proposed method addresses the challenges in lung CT image segmentation, such as the complex image structure and difficulties of distinguishing COVID-19 pneumonia lesions from other pathologies. We provide the detailed description of the proposed GAHFNet. Finally, comprehensive experiments are carried out to evaluate the performance of GAHFNet, demonstrating that GAHFNet is able to facilitate the application of artificial intelligence in COVID-19 diagnosis and achieve accurate automatic segmentation of infected areas in COVID-19 lung CT images.

Hyperglycemia-induced cathepsin L maturation: Implications for diabetic comorbidities and COVID-19 susceptibility (preprint)

Diabetes is the second most frequent chronic comorbidity for COVID-19 mortality, yet the underlying mechanism remains unclear. Previous studies suggest that Cathepsin L (CTSL) is implicated in diabetic complications such as nephropathy and retinopathy. Our previous research identified CTSL as a critical protease that promotes SARS-CoV-2 infection and a potential drug target. Here, we show that individuals with diabetes have elevated blood CTSL levels, which facilitates SARS-CoV-2 infection. Chronic hyperglycemia, as indicated by HbA1c levels, is positively correlated with CTSL concentration and activity in diabetic patients. Acute hyperglycemia induced by a hyperglycemic clamp in healthy individuals increases CTSL activity. In vitro, high glucose, but not high insulin, promotes SARS-CoV-2 infection in wild-type (WT) cells, while CTSL knockout (KO) cells show reduced susceptibility to high glucose-promoted effects. Using lung tissue samples from diabetic and non-diabetic patients, as well as db/db diabetic and control mice, our findings demonstrate that diabetic conditions increase CTSL activity in both humans and mice. Mechanistically, high glucose levels promote CTSL maturation and CTSL translocation from the endoplasmic reticulum (ER) to the lysosome via the ER-Golgi-lysosome axis. This study emphasizes the significance of hyperglycemia-induced cathepsin L maturation in the development of diabetic comorbidities and complications.

Clinical Characteristics of 427 Unvaccinated Chinese Adult Patients with Maintenance Hemodialysis infected with SARS-CoV-2 Omicron subvariant BA.5.2 (preprint)

To analyze the clinical characteristics and outcomes of unvaccinated adult patients on maintenance hemodialysis infected with SARS-CoV-2 Omicron subvariant BA.5.2.The clinical data of 427 maintenance hemodialysis patients infected with SARS-CoV-2 Omicron subvariant BA.5.2 in our hospital were retrospectively collected. The patients were grouped according to the severity of the disease and compared. The clinical outcome and two-month follow-up were analyzed.These results suggest that CRP level, procalcitonin level, and bicarbonate concentration are related to the severity of disease caused by SARS-CoV-2 omicron BA.5.2 infection in unimmunized MHD patients. In addition, the co-bacterial infection may be an important cause of severe illness. Therefore, strengthen the treatment of critically ill patients, and actively and effectively control infection and secondary infection; Effective vaccination is the key to improving clinical outcomes to prevent the conversion of ordinary patients to severe and critical cases. Fever, age, ORF1ab gene value, and arterial oxygen partial pressure may be independent risk factors for disease severity in COVID-19 patients.

Navigating Radiation Therapy During COVID-19 Using YouTube as a Source of Information.

The COVID-19 pandemic brought considerable change to the practice of radiotherapy. In the meantime, patients are increasingly turning to online resources for health information, with YouTube being one of the biggest platforms. However, little is known about what information is being disseminated to cancer patients about radiotherapy in the context of COVID-19. Therefore, this study aims to characterize and assess YouTube videos on radiotherapy during COVID-19. A YouTube search using the terms "Radiation therapy COVID-19", "Radiation therapy coronavirus", "Radiotherapy COVID-19", and "Radiotherapy coronavirus" was completed using a clear-cache web browser. The top 50 videos were collected from each search. After applying pre-determined exclusion criteria, each video was assessed for general parameters, source, and content. Two raters were used to ensure interrater reliability. One hundred five unique videos resulted from the four searches. Ninety-eight per cent were published in the last year. The median video length was 6 min and 54 s, and the median number of views was 570. Most videos were from the USA (58%). The majority of videos were published by a commercial channel (31%), non-profit organization (28%), or healthcare facility (26%). Forty-two per cent of the videos covered a topic related to radiotherapy during the pandemic. Bias was identified in 6% of videos. YouTube information on radiotherapy during COVID-19 is non-specific and can be misleading. The results of this study highlight the need for healthcare providers to proactively address patient information needs and guide them to appropriate sources of information.

Lung cancer and oncolytic virotherapy--enemy's enemy.

Lung cancer is one of the malignant tumors that seriously threaten human health worldwide, while the covid-19 virus has become people's nightmare after the coronavirus pandemic. There are too many similarities between cancer cells and viruses, one of the most significant is that both of them are our enemies. The strategy to take the advantage of the virus to beat cancer cells is called Oncolytic virotherapy. When immunotherapy represented by immune checkpoint inhibitors has made remarkable breakthroughs in the clinical practice of lung cancer, the induction of antitumor immunity from immune cells gradually becomes a rapidly developing and promising strategy of cancer therapy. Oncolytic virotherapy is based on the same mechanisms that selectively kill tumor cells and induce systemic anti-tumor immunity, but still has a long way to go before it becomes a standard treatment for lung cancer. This article provides a comprehensive review of the latest progress in oncolytic virotherapy for lung cancer, including the specific mechanism of oncolytic virus therapy and the main types of oncolytic viruses, and the combination of oncolytic virotherapy and existing standard treatments. It aims to provide new insights and ideas on oncolytic virotherapy for lung cancer.

Psychological Capital and Alienation among patients with COVID-19 infection: The mediating role of Social Support (preprint)

Background COVID-19 infection continues all over the world, causing serious physical and psychological impacts to patients. Patients with COVID-19 infection suffer from various negative emotional experiences such as anxiety, depression, mania, and alienation, which seriously affect their normal life and is detrimental to the prognosis. Our study is aimed to investigate the effect of psychological capital on alienation among patients with COVID-19 and the mediating role of social support in this relationship.Methods The data were collected in China by the convenient sampling method. A sample of 259 COVID-19 patients completed the psychological capital, social support and social alienation scale and the structural equation model was adopted to verify the research hypotheses.Results Psychological capital was significantly and negatively related to the COVID-19 patients’ social alienation (p < .01). And social support partially mediated the association between psychological capital and patients’ social alienation (p < .01).Conclusion Psychological capital is critical to predicting COVID-19 patients’ social alienation. Social support plays an intermediary role and explains how psychological capital alleviates the sense of social alienation among patients with COVID-19 infection.

News from Messenger? A Cross-National Comparative Study of News Media's Audience Engagement Strategies via Facebook Messenger Chatbots

As an emerging audience engagement channel for news organizations, news chatbots can interact with and attract audiences in a conversational manner. The present study applies the comparative digital journalism frameworks and examines how society-level factors-such as media systems and information communication technology's development-explain chatbot implementation on social media platforms. We surveyed 365 news organizations across 38 countries or regions and inspected their Facebook Messenger accounts with a mixed-methods approach. We found that less than half of the surveyed news organizations implemented Messenger, and only 67 Messengers were responsive-i.e. able to produce at least one response. We used the walkthrough method to interact with the Messengers with 22 pre-defined search queries on information seeking and navigation related to COVID-19. Then we used qualitative content analysis to examine the contents generated by the Messengers. Some Messengers are out of service or could only provide limited services (e.g. generating templated responses or closed-ended options). The Messengers in different news organizations demonstrated great variations in their capacity to understand the queries and interact with the audiences and reparative strategies to handle search failure. We proposed a three-category typology of news chatbots and offered practical and constructive suggestions for news organizations.

An intranasal vaccine targeting the receptor binding domain of SARS-CoV-2 elicits a protective immune response

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for COVID-19, has caused an ongoing worldwide pandemic. Due to the rapid emergence of variants of concern (VOCs), novel vaccines and vaccination strategies are urgently needed. We developed an intranasal vaccine consisting of the SARS-CoV-2 receptor binding domain (RBD) fused to the antibody Fc fragment (RBD-Fc). RBD-Fc could induce strong humoral immune responses via intranasal vaccination. Notably, this immunogen could efficiently induce IgG and IgA and establish mucosal immunity in the respiratory tract. The induced antibodies could efficiently neutralize wild-type SARS-CoV-2 and currently identified SARS-CoV-2 VOCs, including the Omicron variant. In a mouse model, intranasal immunization could provide complete protection against a lethal SARS-CoV-2 challenge. Unfortunately, the limitation of our study is the small number of animals used in the immune response analysis. Our results suggest that recombinant RBD-Fc delivered via intranasal vaccination has considerable potential as a mucosal vaccine that may reduce the risk of SARS-CoV-2 infection.

The COVID-19 Pandemic and Mental Health Concerns on Twitter in the United States

Background During the COVID-19 pandemic, mental health concerns (such as fear and loneliness) have been actively discussed on social media. We aim to examine mental health discussions on Twitter during the COVID-19 pandemic in the US and infer the demographic composition of Twitter users who had mental health concerns. Methods COVID-19-related tweets from March 5th, 2020, to January 31st, 2021, were collected through Twitter streaming API using keywords (i.e., “corona,” “covid19,” and “covid”). By further filtering using keywords (i.e., “depress,” “failure,” and “hopeless”), we extracted mental health-related tweets from the US. Topic modeling using the Latent Dirichlet Allocation model was conducted to monitor users' discussions surrounding mental health concerns. Deep learning algorithms were performed to infer the demographic composition of Twitter users who had mental health concerns during the pandemic. Results We observed a positive correlation between mental health concerns on Twitter and the COVID-19 pandemic in the US. Topic modeling showed that “stay-at-home,” “death poll,” and “politics and policy” were the most popular topics in COVID-19 mental health tweets. Among Twitter users who had mental health concerns during the pandemic, Males, White, and 30-49 age group people were more likely to express mental health concerns. In addition, Twitter users from the east and west coast had more mental health concerns. Conclusions The COVID-19 pandemic has a significant impact on mental health concerns on Twitter in the US. Certain groups of people (such as Males and White) were more likely to have mental health concerns during the COVID-19 pandemic.

Prevalence and Risk Factors of Anxious and Depressive Symptoms in First-trimester Females and Their Partners: a study in the post-pandemic era of COVID-19 in China (preprint)

Background: The pandemic of coronavirus disease 2019 lastingly affects public mental health. Many studies have described symptoms of anxiety and depression in pregnant women during the pandemic. However, limited study focuses on the prevalence and risk factors of mood symptoms among females and their partners during early pregnancy in the post-pandemic era in China, which was the aim of the study and could promote clinical attention and suggest possible directions for intervention. Methods: One hundred and sixty-nine first-trimester couples were enrolled. The Edinburgh Postnatal Depression Scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-Item, Family Assessment Device-General Functioning (FAD-GF), and Quality of Life Enjoyment and Satisfaction Questionnaire, Short Form (Q-LES-Q-SF) were applied. Data were mainly analyzed through the binominal logistic regression analysis. Results: 17.8% and 5.9% of first-trimester females had depressive and anxious symptoms, respectively. Among partners, 12.4% and 9.5% had depressive and anxious symptoms, respectively. In females, higher scores of FAD-GF (OR= 5.461 and 14.759; P< 0.05) and lower scores of Q-LES-Q-SF (OR= 0.830 and 0.715; P< 0.01) were related to the risk of depressive and anxious symptoms. A history of smoking and higher scores of FAD-GF were associated with the risk of depressive and anxious symptoms in partners (OR = 4.906 and 6.885; P< 0.05). Conclusions: This study prompted still prominent mood symptoms in the post-pandemic era. Family functioning, quality of life, or a smoking history increased risks of mood symptoms among early pregnant families, which might facilitate the updating of medical intervention. However, the current study did not further explore interventions based on these findings.

2D Zn‐Porphyrin‐Based Co(II)‐MOF with 2‐Methylimidazole Sitting Axially on the Paddle–Wheel Units: An Efficient Electrochemiluminescence Bioassay for SARS‐CoV‐2

High electrocatalytic activity with tunable luminescence is crucial for the development of electrochemiluminescence (ECL) luminophores. In this study, a porphyrin‐based heterobimetallic 2D metal organic framework (MOF), [(ZnTCPP)Co2(MeIm)] (1), is successfully self‐assembled from the zinc(II) tetrakis(4‐carboxyphenyl)porphine (ZnTCPP) linker and cobalt(II) ions in the presence of 2‐methylimidazole (MeIm) by a facile one‐pot reaction in methanol at room temperature. On the basis of the experimental results and the theoretical calculations, the MOF 1 contains paddle–wheel [Co2(‐CO2)4] secondary building units (SBUs) axially coordinated by a MeIm ligand, which is very beneficial to the electron transfer between the Co(II) ions and oxygen. Combining the photosensitizers ZnTCPP and the electroactive [Co2(‐CO2)4] SBUs, the 2D MOF 1 possesses an excellent ECL performance, and can be used as a novel ECL probe for rapid nonamplified detection of the RdRp gene of SARS‐CoV‐2 with an extremely low limit of detection (≈30 aM). A novel porphyrin‐based heterobimetallic 2D MOF, [(ZnTCPP)Co2(MeIm)] (1) is constructed to act as an excellent electrochemiluminescence probe for rapid nonamplified detection of SARS‐CoV‐2.

Global prediction for monkeypox epidemic (preprint)

The monkeypox epidemic has now spread all over the world and has become an epidemic of widespread concern in the international community. Before the emergence of targeted vaccines and specific drugs, it is necessary to numerically simulate and predict the epidemic. In order to better understand and grasp its transmission situation, and put forward some countermeasures accordingly, we predicted and simulated monkeypox transmission and vaccination scenarios using models developed for COVID-19 predictions. The results suggest the monkeypox epidemic will spread to almost all countries in the world by the end of 2022 based on modified SEIR model prediction. The total number of people infected with monkeypox will reach 100,000. The top five countries will be the United States, Brazil, Germany, France and Britain with more than 28000, 20000, 4000, 4500 and 4000 cases respectively. If 30% of the population is vaccinated, the number of infected people will drop by 35%.

Investigation of coronavirus and hepatitis E virus in rodents in Dali City, Yunnan Province

An investigation of coronavirus (CoV) and hepatitis E virus (HEV) in rodents was performed to understand CoV and HEV infection of rodents in Dali City, Yunnan Province. Rodent samples were obtained in the four towns of Dali city through traps from August 2020 to August 2021. A total of 76 rodents belonging to six species and five genera were captured: Rattus tanezumi, Rattus norvegicus, Apodemus chevrieri, Eothenomys miletus, Niviventer fulvescens, and Mus Pahari. Detection of CoV and HEV was performed by nested-PCR. The infection rate of CoV was 40.74% (11/27) and 2.38% (1/42) in R. norvegicus and R. tanezumi, respectively. The infection rate of HEV was 14.81% (4/27) and 2.38% (1/42) in R. norvegicus and R. tanezumi, respectively. Co-infection with CoV and HEV was detected in two R. norvegicus, with a co-infection rate of 7.41% (2/27). A Basic Local Alignment Search Tool (BLAST) search was performed on partial RNA-dependent RNA polymerase (RdRp) sequences of CoV and HEV. Eleven strains from R. norvegicus were a-CoV, and matched best to strain KY370050 from Rattus losea (Fujian, China), with 99.73% to 99.74% nucleotide (nt) sequency identity. One strain was ss-CoV from R. tanezumi, which displayed 98.21% nt sequence identity with strain MT820632 from Bandicota indica (Yunnan, China). Five strains from R. norvegicus were all HEV-C, and showed 95.87% to 96.21% sequence similarity to strain MN450853 from a patient in Hong Kong, China. In conclusion, CoV and HEV infections are present in rodents in Dali City. Because the host animals of the two viruses are closely related to humans, surveillance and investigations of related viruses should be strengthened.

Are female-specific cancers long-term sequelae of COVID-19? Evidence from a large-scale genome-wide cross-trait analysis (preprint)

ABSTRACT Background Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers due to the restricted length of observational time, nor the shared genetic influences underlying these conditions. Methods Leveraging summary statistics from the hitherto largest genome-wide association studies conducted in each trait, we performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture and the putative genetic associations between COVID-19 with three main female-specific cancers: breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC). Three phenotypes were selected to represent COVID-19 susceptibility (SARS-CoV-2 infection) and severity (COVID-19 hospitalization, COVID-19 critical illness). Results For COVID-19 susceptibility, we found no evidence of a genetic correlation with any of the female-specific cancers. For COVID-19 severity, we identified a significant genome-wide genetic correlation with EC for both hospitalization ( r g =0.19, P =0.01) and critical illness ( r g =0.29, P =3.00×10 −4 ). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (OR IVW =1.09, 95%CI=1.01-1.18, P =0.04) and critical illness (OR IVW =1.06, 95%CI=1.00-1.11, P =0.04) with EC risk, none withstanding multiple correction. No reverse association was found. Cross-trait meta-analysis identified multiple pleiotropic SNPs between COVID-19 and female-specific cancers, including 20 for BC, 15 for EOC, and 5 for EC. Transcriptome-wide association studies revealed shared genes, mostly enriched in the hematologic, cardiovascular, and nervous systems. Conclusions Our genetic analysis highlights an intrinsic link underlying female-specific cancers and COVID-19 - while COVID-19 is not likely to elevate the immediate risk of the examined female-specific cancers, it appears to share mechanistic pathways with these conditions. These findings may provide implications for future therapeutic strategies and public health actions.

A Large-Scale Clinical Validation Study Using nCapp Cloud Plus Terminal by Frontline Doctors for the Rapid Diagnosis of COVID-19 and COVID-19 pneumonia in China

Background The outbreak of coronavirus disease 2019 (COVID-19) has become a global pandemic acute infectious disease, especially with the features of possible asymptomatic carriers and high contagiousness. Currently, it is difficult to quickly identify asymptomatic cases or COVID-19 patients with pneumonia due to limited access to reverse transcription-polymerase chain reaction (RT-PCR) nucleic acid tests and CT scans. Goal This study aimed to develop a scientific and rigorous clinical diagnostic tool for the rapid prediction of COVID-19 cases based on a COVID-19 clinical case database in China, and to assist doctors to efficiently and precisely diagnose asymptomatic COVID-19 patients and cases who had a false-negative RT-PCR test result. Methods With online consent, and the approval of the ethics committee of Zhongshan Hospital Fudan University (NCT04275947, B2020-032R) to ensure that patient privacy is protected, clinical information has been uploaded in real-time through the New Coronavirus Intelligent Auto-diagnostic Assistant Application of cloud plus terminal (nCapp) by doctors from different cities (Wuhan, Shanghai, Harbin, Dalian, Wuxi, Qingdao, Rizhao, and Bengbu) during the COVID-19 outbreak in China. By quality control and data anonymization on the platform, a total of 3,249 cases from COVID-19 high-risk groups were collected. The effects of different diagnostic factors were ranked based on the results from a single factor analysis, with 0.05 as the significance level for factor inclusion and 0.1 as the significance level for factor exclusion. Independent variables were selected by the step-forward multivariate logistic regression analysis to obtain the probability model. Findings We applied the statistical method of a multivariate regression model to the training dataset (1,624 cases) and developed a prediction model for COVID-19 with 9 clinical indicators that are accessible. The area under the receiver operating characteristic (ROC) curve (AUC) for the model was 0.88 (95% CI: 0.86, 0.89) in the training dataset and 0.84 (95% CI: 0.82, 0.86) in the validation dataset (1,625 cases). Discussion With the assistance of nCapp, a mobile-based diagnostic tool developed from a large database that we collected from COVID-19 high-risk groups in China, frontline doctors can rapidly identify asymptomatic patients and avoid misdiagnoses of cases with false-negative RT-PCR results.

COVID-19 Effects on Arbitrage Trading in the Energy Market

This paper investigates the effects of coronavirus disease 2019 (COVID-19) on the performance of arbitrage trading in the energy market using daily data covering the period between 1 January 2015 and 5 December 2021. The investigation was achieved by utilizing a parametric pairs-trading model, where pairs of energy-related securities, including futures, stocks and ETFs traded in the United States, are formed. The empirical results suggest that the out-of-sample performances of pair trading declined sharply in the face of COVID-19. Dividing the whole data sample into two sub-samples, we found that the strategy performed well before COVID-19 but yielded poor results in the pandemic era. The analysis presented in this paper could serve as a benchmark for arbitrage-based trading models in the energy market during the pandemic.

The SARS-CoV-2 S1 Spike Protein Promotes MAPK and NF-kB Activation and Inflammatory Cytokine Production In Human Lung and Intestinal Epithelial Cells (preprint)

The Coronavirus disease 2019 (COVID-19) pandemic began in Jan. 2020 in Wuhan, China with a new coronavirus designated SARS-CoV-2. The principle cause of death from COVID-19 disease quickly emerged as Acute Respiratory Distress Syndrome (ARDS). A key ARDS pathogenic mechanism is the “Cytokine Storm”. This is a dramatic increase in the blood of inflammatory cytokines. In the last 2 years of the pandemic new pathology has emerged in COVID-19 survivors in which a variety of long-term symptoms emerge. This condition is called “Long COVID”. The spike protein on the surface of the virus (target for the new mRNA/DNA vaccines) is composed of joined S1-S2 subunits. Upon S1 bind-ing to the human ACE2 receptor on cells, the S1 subunit is cleaved and the S2 subunit me-diates entry of the virus. The S1 protein is then released into the blood, which might be one of the pivotal triggers for initiation and/or perpetuation of the cytokine storm. In this study, we tested the hypothesis that the spike S1 protein may activate inflammatory sig-naling and cytokine production independent of the virus. Our data support a potential role for spike S1 activation of inflammatory signaling and cytokine production in human lung and intestinal epithelial cells in culture. These data support a potential role for the SARS-CoV-2 spike S1 protein in COVID-19 pathogenesis.