Impacts of COVID-19 on reproductive health and prenatal genetics

COVID-19 has a dramatic impact on human health, besides respiratory system, reproduction system would be impaired by SARS-CoV-2. For male, the virus has various negative impacts on testes, including overheating and hormone level fluctuation, which have impacts on the spermatogenesis or spermatogonia development. For female, COVID-19 may increase the risk of endocrine and metabolic dysfunction. However, the impact of SARS-CoV-2 on the ovaries is not clear, and further researches are needed to clarify it. Nearly 60% of the pregnant women develop symptoms of infection and more attention should be paid to the increased risk of adverse pregnancy outcomes including preeclampsia, eclampsia, and severe infection. For the newborns of infected pregnant women, vertical transmission of SARS-CoV-2 is still unclear, and further evaluation are required. Meantime, the pregnant women's fear of the potential infection may reduce their access to the prenatal genetic test. In this chapter, we summarize the latest basic and clinical researches on COVID-19 impacts on male, female reproduction, and prenatal genetic test, hoping to provide guidance and advice for people of reproductive age and reproductive healthcare practitioners. © 2023 Elsevier Inc. All rights reserved.

Have students' perceptions of online education changed with the easing of COVID-19 restrictions?

This research examines student preference toward online and on-ground (i.e., face-to-face) course delivery methods in higher education as a result of the easing of COVID-19 pandemic restrictions. Over 130 undergraduate and graduate students enrolled in Computer and Information Systems courses at a university located in the northeastern United States were surveyed from April 2021 to May 2022. The study found that with the easing of COVID-19 restrictions in Spring 2022, students significantly preferred on-ground over online courses in comparison to their preferences when COVID-19 restrictions were still high in 2021. None of the potential influencing factors contributing to the changed preference, including students' perceptions of online course effectiveness, self-skills supporting online learning (e.g., work independently without supervision, prioritization and time management), and the usefulness of classroom interaction in learning, were found to have significant differences from the time when COVID-19 restrictions were high to the present easing of them. © 2023 Issues in Information Systems. All rights reserved.

Rapid, sensitive detection of intact SARS-CoV-2 using DNA nets and a smartphone-linked fluorimeter

We report a single-step, room-temperature, 5-10 minute SARS-CoV-2 saliva self-monitoring method that overcomes the limitations of existing approaches through the use of fluorophore-releasing Designer DNA Nanostructures (DDNs) that bind with the multivalent pattern of spike proteins on the exterior intact virions and an inexpensive smartphone-linked, pocket-size fluorimeter, called a "V-Pod” for its resemblance to an Apple AirPod™ headphone case. We characterize the V-Pod fluorimeter performance and the DDN-based assay to demonstrate a clinically relevant detection limit of 104 virus particles/mL for pseudo-typed WT SARS-CoV-2 and 105 virus particles/mL for real pathogenic variants, including Delta, Omicron, and D614g. © 2023 SPIE.

Addressing Issues of Cross-Linguality in Open-Retrieval Question Answering Systems For Emergent Domains

Open-retrieval question answering systems are generally trained and tested on large datasets in well-established domains. However, low-resource settings such as new and emerging domains would especially benefit from reliable question answering systems. Furthermore, multilingual and cross-lingual resources in emergent domains are scarce, leading to few or no such systems. In this paper, we demonstrate a cross-lingual open-retrieval question answering system for the emergent domain of COVID-19. Our system adopts a corpus of scientific articles to ensure that retrieved documents are reliable. To address the scarcity of cross-lingual training data in emergent domains, we present a method utilizing automatic translation, alignment, and filtering to produce English-to-all datasets. We show that a deep semantic retriever greatly benefits from training on our English-to-all data and significantly outperforms a BM25 baseline in the cross-lingual setting. We illustrate the capabilities of our system with examples and release all code necessary to train and deploy such a system1 © 2023 Association for Computational Linguistics.

Extracellular Disintegration of Viral Proteins as an Innovative Strategy for Developing Broad-Spectrum Antivirals Against Coronavirus

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has claimed millions of lives and caused innumerable economic losses worldwide. Unfortunately, state-of-the-art treatments still lag behind the continual emergence of new variants. Key to resolving this issue is developing antivirals to deactivate coronaviruses regardless of their structural evolution. Here, we report an innovative antiviral strategy involving extracellular disintegration of viral proteins with hyperanion-grafted enediyne (EDY) molecules. The core EDY generates reactive radical species and causes significant damage to the spike protein of coronavirus, while the hyperanion groups ensure negligible cytotoxicity of the molecules. The EDYs exhibit antiviral activity down to nanomolar concentrations, and the selectivity index of up to 20,000 against four kinds of human coronavirus, including the SARS-CoV-2 Omicron variant, suggesting the high potential of this new strategy in combating the COVID-19 pandemic and a future "disease X."

Statistical correlation coefficients for single-valued neutrosophic sets and their applications in medical diagnosis

The concept of single-valued neutrosophic sets (SVNSs) is considered as an attractive tool for dealing with highly ambiguous and uncertain information. The correlation coefficient of SVNSs acts as an important measure in the single-valued neutrosophic set theory and it has been applied in various fields, such as the pattern recognition, medical diagnosis, decision-making and also clustering analysis. To alleviate the weakness of the existing correlation coefficients, a novel statistical correlation coefficient is put forward to measure the degree of correlation between two SVNSs. This statistical correlation coefficient is developed based on the variance and covariance of SVNSs and its value is between −1 and 1. When solving the multicriteria decision making problems, the criteria show different weight values. To consider the weight information of multiple criteria, the weighted statistical correlation coefficient is developed for SVNSs. Afterwards, two numerical examples are given to show the effectiveness of the proposed statistical correlation coefficient in the pattern recognition, which can accurately classify unknown patterns into known patterns. Finally, the feasibility and practicability of the proposed correlation coefficient formula are illustrated by a practical multiple attribute decision making problem of traditional Chinese medicine diagnosis. The comparative results show that the proposed correlation coefficient formula is rational and effective. © 2023 the Author(s), licensee AIMS Press.

[Estimation of COVID-19 incidence in Shanghai under optimized epidemic prevention and control strategies].

Objective: To quantitatively estimate the incidence of COVID-19 in different backgrounds, including vaccination coverage, non-pharmacological interventions (NPIs) measures, home quarantine willingness and international arrivals, and the demands of healthcare resource in Shanghai in the context of optimized epidemic prevention and control strategies. Methods: Based on the natural history of 2019-nCoV, local vaccination coverage and NPI performance, an age-structured Susceptible-Exposed-Infections-Removed (SEIR) epidemic dynamic model was established for the estimation of the incidence of COVID-19 and demand of hospital beds in Shanghai by using the data on December 1, 2022 as the basis. Results: Based on current vaccination coverage, it is estimated that 180 184 COVID-19 cases would need treatment in hospitals in Shanghai within 100 days. When the booster vaccination coverage reaches an ideal level, the number of the cases needing hospitalization would decrease by 73.20%. School closure or school closure plus workplace closure could reduce the peak demand of regular beds by 24.04% or 37.73%, respectively, compared with the situation without NPI. Increased willingness of home quarantine could reduce the number of daily new cases and delay incidence peak of COVID-19. The number of international arrivals has little impact on the development of the epidemic. Conclusions: According to the epidemiological characteristics of COVID-19 and the actual situation of vaccination in Shanghai, the incidence of COVID-19 and health resource demand might be reduced by increasing vaccination coverage and early implementation of NPI.

Exploration on the construction of the regional center of continuing medical education under the background of normalization of epidemic prevention and control

The COVID-19 epidemic is running at a high level globally, affecting all aspects of society, and medical education is no exception. With the rapid development of medical science, continuing medical education is an important way for medical workers to receive lifelong education. Meanwhile, attending continuing medical education is an inevitable requirement to ensure clinical ability. Under the background of normalization of epidemic prevention and control and the new situation of medical development, the management of continuing medical education in hospitals must follow the current situation and keep pace with the times. Therefore, the Internet support system to continuing education has emerged. This study used PDSA method to explore the construction of the regional center of continuing medical education through Internet under the background of normalization of epidemic prevention and control, aiming to promote the integration of medical education resources under the new situation, expand the learning channels of medical staff, and improve the level of medical education and teaching. © 2022 IEEE.

Understanding the Molecular Interface of Cardiovascular Diseases and COVID-19: A Data Science Approach

Recently, mounting evidence documented an increased morbidity and mortality of COVID-19 in individuals with pre-existing cardiovascular diseases (CVDs). To better understand the pathogenesis of COVID-19 and its impact in CVDs, we designed a text-mining analysis project to evaluate the molecular interfaces between COVID-19 and several known CVDs. We assembled our data corpus from publicly accessible databases and applied text mining to COVID-19 symptoms, comorbidities, and human proteins impacted by COVID-19. Our exploration includes a statistical overview of unstructured text datasets with associated biomedical entities where the information extraction was assisted by data indexing and entity search methodologies. Using 333 human COVID-19-interacting proteins as entities and 8 CVDs classified by MeSH as categories, we examined and computed their Context Aware Semantic Analytic Processing (CaseOLAP) scores. Using this dataset, we determined associations of COVID-19 symptoms with a variety of major and minor comorbidities. Then, we further explored proteins at the interface of COVID-19 and 8 categories of CVD, evaluating relationships between the proteins and CVD categories to determine the proteins' significance in each disease. We then performed pathway analyses on those proteins of significance and their presence in each of the CVD categories. For the first time, our cluster analyses determined which COVID-19-interacting proteins are most relevant for each CVD category. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Family satisfaction with ICU communication during the COVID-19 pandemic: a prospective multi-centre Australian study

Introduction: Virtual communication has become common practice during the COVID-19 pandemic due to visitation restriction. We aimed to evaluate overall family satisfaction in intensive care unit (FS-ICU) with virtual communication strategies during the COVID-19 pandemic period. Method(s): In this prospective multi-centre study involving three metropolitan hospitals in Melbourne, Australia, the next of kin (NOK) of all the eligible ICU patients between 07/01/2022 and 10/31/2020 were required to complete an adopted version of FS-ICU 24-Questionnaire. Group comparisons were analysed for family satisfaction scores: ICU/ care (satisfaction with care), FS-ICU/dm (satisfaction with information/ decision-making) and FS-ICU total (overall satisfaction with the ICU) were calculated. The essential predictors that influence family satisfaction were identified using quantitative and qualitative analyses. Result(s): Seventy-three out of the 227 patients' NOK who initially agreed, completed the FS-ICU questionnaire (response rate 32.2%). The mean (SD) FS-ICU/total was 63.9 (30.8). The mean score for satisfaction with FS-ICU/dm was lower than the FS-ICU/care (62.1 [30.30 vs. 65.4 [31.4];p 0.001) (Fig. 1). There was no difference in mean FS-ICU/ total scores between survivors (n = 65;89%) and non-survivors (n = 8, 11%). Higher patient APACHE-III score, female NOK and the patient dying in ICU were independent predictors for FS-ICU/total score while a telephone call at least once a day by an ICU doctor was related to higher family satisfaction for FS-ICU/dm. Conclusion(s): There was low overall family satisfaction with ICU care and virtual communication strategies adopted during the COVID-19 pandemic. Effort should be targeted for improving factors with virtual communication that cause low family satisfaction during the COVID-19 pandemic.

Improving the treatment pathway in small cell lung cancer

Introduction: Extensive stage small cell lung cancer (ES-SCLC) is the most aggressive form of lung cancer, and delays in treatment result in worse outcomes. The National Lung Cancer Audit1 guidelines advise 70% of patients should receive systemic treatment and 80% within 14 days of pathological diagnosis. We aimed to assess compliance with these recommendations and improve the treatment pathway for patients with ES-SCLC in East London. Method(s): To establish baseline metrics, we reviewed compliance with these guidelines in all patients diagnosed with ES-SCLC in 2019 (pre-COVID pandemic). Two interventions were made: i) admission of all newly diagnosed patients for urgent chemotherapy to improve time to treatment and ii) all newly diagnosed ES-SCLC patients across our network of five hospitals were requested to be reviewed by or transferred under a lung oncologist to improve treatment rates. We re-evaluated data from all ES-SCLC patients diagnosed in 2022 using the same pre-intervention criteria. Result(s): 31 patients in 2019 and 17 patients in 2022 were included. There was no significant difference in baseline characteristics including (median) age (68 vs 70, p=0.64), co-morbidities (1 vs 1, p=0.12), and performance status (1 vs 1, p=0.86) between cohorts. There was a significant decrease in the median [range] time to treatment (13 [4-80] days vs 4 [1-31] days, p=0.03] and an increase in the proportion of patients reviewed by a lung oncologist (74% to 100%, p=0.04). There was also an increase in the proportion of patients receiving treatment (61% vs 77%). [Figure presented] Conclusion(s): Our data suggest that these interventions may improve the proportion of patients receiving treatment and the time to treatment. Larger local audits and correlation with national data is required to evaluate the impact these interventions have on outcomes. Reference: [1] RCP National Lung Cancer Audit Annual Report. 2022. Disclosure: No significant relationships.Copyright © 2023 Elsevier B.V.

FRD: Few-shot rumor detection for the novel coronavirus pneumonia epidemic

With the full arrival of the digital era, fueled by both information technology and business marketing, rumors are produced and spread endlessly on social networks. During the recent novel coronavirus pneumonia epidemic, online rumors have continued to flourish. Most existing studies on traditional rumor detection rely on a large number of features in practical applications. However, the current severe epidemic scenarios have limited rumor information features, and it remains a challenging problem to detect epidemic rumors with high accuracy using only limited information. As a result, we propose a novel Few-shot Rumor Detection model (FRD) for the novel coronavirus pneumonia, which is combined with meta-learning to be able to accurately identify rumors as soon as possible in crises. Specifically, we started by using the BERT+BiLSTM combination for rumor text feature extraction and representation to generate the historical rumor sample-wise vector and epidemic rumor sample-wise vector;secondly, the prototypical network was introduced to summarize the historical rumor data, and the feature vectors of samples belonging to the same category were averaged to obtain the prototype representation of historical rumor category;finally, we utilize the modified cosine similarity measure function to calculate the distance between the class-wise vector of historical rumor text and the sample-wise vector of epidemic rumor, and complete the rumor detection according to the nearest neighbor method. Our experimental results on English datasets show that the FRD rumor detection model proposed in this paper is superior to other baseline algorithms in terms of accuracy, precision, recall and macro F1 value. From the comparison of experimental results, the FRD model can effectively improve conventional rumor detection methods, and better realize the early detection of sudden epidemic rumors. © 2022 IEEE.

The Application of Equivalent Method for Cost Accounting and Performance Management in Community Healthcare Institutions

Background During the promotion of category-based management for community healthcare institutions （class 1 institutions obtain the financial security，and class 2 institutions implement a performance management system），how to appropriately determine the security level and scientifically evaluate the performance is a difficulty to tackle for health administrative departments. Objective To assess the operational efficiency of community healthcare institutions with the data envelopment analysis（DEA） using the information of costs of these institutions calculated using the equivalent method，then attempt to develop an input and management model of integrating cost accounting and performance management for these institutions，providing a theoretical basis for accurate and scientific input of various resources into the community through cost measurement with equivalent method，and a data basis for performance assessment in communities with different characteristics through efficiency evaluation. Methods The real data（financial status and staffing） of 14 community healthcare institutions during 2019 to 2020 were collected from their financial reports，hospital information system，maternal and child healthcare information system，chronic disease management information system，as well as focus group interviews. The equivalent method was used to calculate the total costs of medical services and public health services. The super-efficiency DEA was used to evaluate and analyze the operational efficiency of the 14 sample institutions. Results （1）The average cost of one equivalent service（a general medical outpatient service lasting for 15 minutes was defined as one standard service equivalent unit） was 67.64 yuan in 2019 and 69.80 yuan in 2020 for the 14 institutions. The average cost of one equivalent essential medical service was higher than that of one equivalent public health service in both 2019（167.14 yuan vs 18.86 yuan） and 2020（215.43 yuan vs 19.78 yuan）. The institutions demonstrated significant differences in the average cost of one equivalent essential medical service and the average cost of one equivalent public health service. （2）Each institution had its own peculiar characteristics. For example，S1 institution mainly provided essential medical services，and had higher total equivalent essential medical services and efficiency than other institutions，while S9 institution focused on providing public health services，and had the highest efficiency in delivering public health services. （3）In 2020，the 14 institutions provided 134 800 equivalent COVID-19-related services，with a cost of 1.037 8 million yuan. （4）In 2019 and 2020，only two institutions were relatively overall efficient，and ≥ 50.0% institutions were pure technically efficient. The institutions with overall operational inefficiency were mainly caused by scale inefficiency primarily due to increasing returns to scale. Conclusion The equivalent method provides a relatively unified "scale" to standardize the service efficiency of different types of community healthcare institutions，provides support for health administrative departments implementing category-based compensation for the institutions，benefiting the featured and high-level development of community healthcare institutions. Either institutions delivering essential medical services or those delivering public health services，mainly present increasing returns to scale，suggesting that the efficiency of these institutions can be improved by increasing the human/financial/material input into the institutions and providing precise compensation for them. © 2023 Chinese General Practice. All rights reserved.

Early antiviral therapy of abidol combined with lopinavir/ritonavir and recombinant interferon alpha-2b for patients with COVID-19 in Zhejiang: A multicenter prospective study.

Objective: To compare the efficacy of the combination of abidol, lopinavir/ritonavir plus recombinant interferon alpha-2b (rIFNalpha-2b) and the combination of lopinavir/ritonavir plus rIFNalpha-2b for patients with COVID-19 in Zhejiang province. Method(s): A multicenter prospective study was carried out to compare the efficacy of triple combination antiviral therapy and dual combination antiviral therapy in 15 medical institutions of Zhejiang province during January 22 to February 16, 2020. All patients were treated with rIFNalpha-2b (5 million U, 2 times/d) aerosol inhalation, in addition 196 patients were treated with abidol (200 mg, 3 times/d) + lopinavir/ritonavir (2 tablets, 1 time/12 h) (triple combination group) and 41 patients were treated with lopinavir/ritonavir (2 tablets, 1 time/12 h) (dual combination group). The patients who received triple combination antiviral therapy were further divided into three subgroups: <48 h, 3-5 d and >5 d according the time from the symptom onset to medication starting. The therapeutic efficacy was compared between triple combination group and dual combination group, and compared among 3 subgroups of patients receiving triple combination antiviral therapy. SPSS 17.0 software was used to analyze the data. Result(s): The virus nucleic acid-negative conversion time in respiratory tract specimens was (12.2+/-4.7) d in the triple combination group, which was shorter than that in the dual combination group [(15.0+/-5.0) d] (t=6.159, P<0.01). The length of hospital stay in the triple combination group [12.0 (9.0, 17.0) d] was also shorter than that in the dual combination group [15.0 (10.0, 18.0) d] (H=2.073, P<0.05). Compared with the antiviral treatment which was started within after the symptom onset of in the triple combination group, the time from the symptom onset to the viral negative conversion was 13.0 (10.0, 17.0), 17.0 (13.0, 22.0) and 21.0 (18.0, 24.0) d in subgroups of 48 h, 3-5 d and >5 d, respectively (Z=32.983, P<0.01), while the time from antiviral therapy to viral negative conversion was (11.8+/-3.9), (13.5+/-5.1) and (11.2+/-4.3) d, respectively(Z=6.722, P<0.05). Conclusion(s): The triple combination antiviral therapy of abidol, lopinavir/litonavir and rIFNalpha-2b shows shorter viral shedding time and shorter hospitalization time, compared with the dual combination antiviral therapy;and the earlier starting triple combination antiviral therapy will result in better antiviral efficacy.Copyright © 2020 by the Chinese Medical Association.

Social determinants of health, prenatal maternal stress, and earlier birth during the COVID-19 pandemic

During the COVID-19 pandemic, pregnant women, especially those from socioeconomically disadvantaged and marginalized groups, experienced unprecedented stress. Prenatal stress and social determinants of health (SDoH) such as lower education and lack of a relationship partner are known to contribute to earlier birth. However, whether SDoH and stress independently contribute or whether the harmful impact of SDoH is mediated by stress is unknown. Moreover, the contributions of these factors has not been investigated in the context of a communal health crisis such as the COVID-19 pandemic. To examine these processes, we used a longitudinal cohort of 2473 women pregnant during the COVID-19 pandemic who reported a live birth. We compared structural equation models predicting gestational age at birth from SDoH (race/ethnicity, education, financial security, health insurance, relationship status, and lifetime abuse) and from prenatal maternal stress related and unrelated to the COVID-19 pandemic. Results indicate that the association of SDoH with earlier birth was partially mediated by prenatal stress. These findings help uncover mechanisms explaining health disparities in the U.S. and highlight the need to address both SDoH and the stress that these factors produce in under-resourced and marginalized communities. © 2023 John Wiley & Sons Ltd.

Epidemiological characteristics and disease spectrum analysis of outpatients in the dermatology department of a hospital in Wuhan during the COVID-19 epidemic.

Objective: To investigate epidemiological characteristics of outpatients and disease spectrum in the dermatology department during the COVID-19 epidemic Methods: A retrospective comparison of outpatient visits, gender, age and disease types in the dermatology department of Wuhan No.1 Hospital was performed between COVID-19 epidemic period (from 23th January 2020 to 15th April 2020) and the same period in 2019. Enumeration data were analyzed by Pearson's chi-square test. Result(s): During the COVID-19 epidemic, the number of outpatient visits to the dermatology department of the hospital decreased markedly, and the average daily number of outpatient visits (236 visits/day) was only 8.81% of that during the same period in 2019 (2 678 visits/day) ;the ratio of male to female patients was reversed from 1:1.37 in 2019 to 1.16:1 in 2020;the proportions of patients aged 0-6, 7-12, 13-17 and 18-45 years significantly decreased compared with those in 2019 (all P < 0.001), and the proportions of patients aged 46-69 and > 69 years significantly increased (both P < 0.001). During the COVID-19 epidemic, there were 171 types of skin diseases in the dermatology outpatient department, and the number of disease categories decreased compared with that during the same period in 2019 (442 types) ;the number of patient visits for allergic skin diseases, erythematous papulosquamous skin diseases, viral infectious skin diseases and bacterial infectious skin diseases significantly increased compared with that during the same period in 2019 (all P < 0.001), while the number of patient visits for sebaceous and sweat gland disorders, pigmented skin diseases and physical skin diseases significantly decreased (all P < 0.001). Conclusion(s): Compared with the same period in 2019, the number of outpatient visits, patient sex ratio, age distribution and disease types in the dermatology department have undergone marked changes during the COVID-19 epidemic, and this study provides a reference for healthcare workers in dermatology department to respond to various epidemics and natural disasters in the future.Copyright © 2021 by the Chinese Medical Association.

Practical exploration of online teaching of animal product processing

Online teaching has become an important part of higher education due to the continuous effects of the global COVID-19. In this paper, the online teaching of Animal Product Processing was designed and implemented from three aspects of optimization of online teaching content, organization of teaching process and implementation of online assessment. According to the analysis of the questionnaire survey and the final evaluation results, the online teaching of Animal Product Processing is well received by the students and has achieved good teaching results, providing a useful reference for colleges and universities to carry out in-depth online teaching of Animal Product Processing.

Cross-lingual transfer learning for COVID-19 outbreak alignment

The spread of COVID-19 has become a significant and troubling aspect of society in 2020. With millions of cases reported across countries, new outbreaks have occurred and followed patterns of previously affected areas. Many disease detection models do not incorporate the wealth of social media data that can be utilized for modeling and predicting its spread. It is useful to ask, can we utilize this knowledge in one country to model the outbreak in another? To answer this, we propose the task of cross-lingual transfer learning for epidemiological alignment. Utilizing both macro and micro text features, we train on Italy's early COVID-19 outbreak through Twitter and transfer to several other countries. Our experiments show strong results with up to 0.85 Spearman correlation in cross-country predictions. © ACL 2020.All right reserved.