COVID-19 and neurodegenerative diseases.

OBJECTIVE: The pandemic of Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues, and SARS-CoV-2 variants continue to emerge. In addition to typical fever and respiratory symptoms, many patients with COVID-19 experience a variety of neurological complications. In this review, we analyzed and reviewed the current status and possible mechanisms between COVID-19 and several typical neurodegenerative diseases, particularly Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis, hoping to propose the potential direction of further research and concern. MATERIALS AND METHODS: Electronic literature search of the databases (Medline/PubMed, Web of Science, and Google Scholar). The keywords used were COVID-19, SARS-CoV-2, neurodegenerative disease, Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. The retrieved relevant articles were reviewed and critically analyzed. RESULTS: SARS-CoV-2 is a highly neuroinvasive neurotropic virus that invades cells through angiotensin-converting enzyme 2 (ACE2) receptor-driven pathway. SARS-CoV-2 neuroinvasion, neuroinflammation, and blood-brain barrier (BBB) dysfunction may contribute to the pathogenesis of neurodegenerative diseases. CONCLUSIONS: Some patients with neurodegenerative diseases have already shown more susceptibility to SARS-CoV-2 infection and significantly higher mortality due to the elderly population with underlying diseases. Moreover, SARS-CoV-2 could cause damage to the central nervous system (CNS) that may substantially increase the incidence of neurodegenerative diseases and accelerate the progression of them.

Chest X-ray analysis empowered with deep learning: A systematic review

Chest radiographs are widely used in the medical domain and at present, chest X-radiation particularly plays an important role in the diagnosis of medical conditions such as pneumonia and COVID-19 disease. The recent developments of deep learning techniques led to a promising performance in medical image classification and prediction tasks. With the availability of chest X-ray datasets and emerging trends in data engineering techniques, there is a growth in recent related publications. Recently, there have been only a few survey papers that addressed chest X-ray classification using deep learning techniques. However, they lack the analysis of the trends of recent studies. This systematic review paper explores and provides a comprehensive analysis of the related studies that have used deep learning techniques to analyze chest X-ray images. We present the state-of-the-art deep learning based pneumonia and COVID-19 detection solutions, trends in recent studies, publicly available datasets, guidance to follow a deep learning process, challenges and potential future research directions in this domain. The discoveries and the conclusions of the reviewed work have been organized in a way that researchers and developers working in the same domain can use this work to support them in taking decisions on their research. (c) 2022 Elsevier B.V. All rights reserved.

Study on the Mucosal and Serological Immune Response to the Novel Coronavirus(SARS-CoV- 2) Vaccines

Vaccines that elicit mucosal immune responses against SARS-CoV-2 could potent ially be of exceptional importance in providing first line defence at the site of viral entry. In order to understand the mucosal immune response profiles of SARS-CoV-2 vaccines, we examined both the mucosal and systemic responses of subjects vaccinated by two different vaccination platforms: mRNA (Comirnaty) and inactivated virus (CoronaVac). Nasal epithelial lining fluid (NELF) and peripheral blood samples were collected in subjects who had received two doses of CoronaVac or Comirnaty. We quantified IgA and IgG specific to SARS-CoV-2 S1 protein, neutralisation antibody by ELISA in NELF and plasma samples. Only Comirnaty induced nasal S1-specific IgA and IgG responses, which were evident as early as on 14±2 days after the first dose. The NELF samples of 72% of subjects became IgA+IgG+, while in 62.5% of subjects the samples were neutralising by 7±2 days after the second dose. In 45% of the subjects their NELF remained neutralising 50 days after the booster. In plasma, 91% and 100% Comirnaty subjects possessed S1-specific IgA+IgG+ on 14±2 days after the first dose and 7±2 days after booster, respectively. The plasma collected on 7±2 days after booster was 100% neutralising. The induction of S1-specific antibody by CoronaVac was IgG dominant, and 70% of the subjects possessed specific IgG by 7±2 days after booster and were all neutralising. This study reveals that Comirnaty is able to induce S1-specific IgA and IgG r esponse with neutralising activity in the nasal mucosa in addition to a consistent systemic response.

An Evaluation of the Quality of Answers to Academic Questions Relating to COVID-19 on Academic Social Q&A Platforms

Academic social network sites have become an important channel by which scholars obtain academic information. In the context of the COVID-19 pandemic, the use of academic social question and answer (Q&A) online platforms is a fast and efficient means of gathering information needed to solve research problems relating to the study of COVID-19. The question then is how to provide scholars with high-quality answers. Therefore, this research focuses on studying the characteristics of high-quality answers to COVID-19 questions on academic social Q&A platforms in terms of the answer content. By analyzing 6791 answers to 349 questions about COVID-19 on ResearchGate Q&A, high-quality academic answers on this topic should be rich in content, contain more negative emotions, be fluent in the use of language, and propose conjectures or hypotheses. This research helps to improve the provision of satisfactory academic information services for scholars during public health emergencies.

How Situational Cognition, Communication Behaviour and Public Trust of NPOs Affect Individual Donation Intention: The Case of Anti-COVID-19 in China

By investigating the relationship between information dissemination behaviour, public trust in NPOs and individual donation, this study seeks to expand our knowledge of individuals' donation behaviour in NPOs' charitable crowdfunding. Through an online quantitative study nationwide from April to July in 2020, we find that the public's situational cognition has a great impact on their information dissemination behaviour, and the public's trust in NPOs plays a moderating role in the interaction between information dissemination and donation behaviour. For academia, this study helps to better understand the individuals' decision-making behind donation. Our model can help researchers understand individuals' philanthropic behavior by providing empirical explanations for the relationship between information dissemination behaviour, public trust in NPOs and individuals' donation behavior. For practitioners, the research suggests appropriate design, launch, and operation strategies to facilitate individuals' donation behavior in the future.

Spatiotemporal Distribution and Ecological Risk Assessment of Plastic Additives in Taihu Lake

To reveal the spatiotemporal distribution and risks of plastic additives in Taihu Lake during the COVID-19 pandemic, the occurrences of typical bisphenols, phthalate esters, and benzotriazoles in the surface water of Taihu Lake were investigated. The plastic additives in 19 sites in Taihu Lake were monitored in four seasons, and their potential ecological risks were evaluated. Diethylphthalate (DEP), dimethoxyethyl phthalate (DMEP), benzyl butyl phthalate (BBP), bisphenol A (BPA), and 2-(2H-benzotriazol-2-yl)-4, 6-di-tert-pentylphenol (UV-328) were detected, with detection rates of 100%, 97%, 58%, 98%, and 7%, respectively. During the COVID-19 pandemic, the sharply increasing usage of plastic products did not result in a significant increase in the plastic additives pollution in Taihu Lake. Conversely, the pollution of plastic additives showed a decreasing trend due to reduced human activities. There were significant seasonal differences in the concentrations of plastic additives in Taihu Lake. The average concentrations of plastic additives in spring and summer were 104.7 and 100.3 ng•L-1, respectively, which were higher than those in autumn (30.7 ng•L-1) and winter (29.9 ng•L-1). The plastic additive pollution also showed some differences in spatial distribution. The concentrations of plastic additives near the southwest coast of Taihu Lake were higher than those in other monitoring sites. The presence of plastic additives in Taihu Lake showed low risks to algae with the proportion of 30%. The risks in autumn and winter were higher than those in spring and summer. BPA and UV-328 may have been the main risk factors, which should be of concern. © 2022, Science Press. All right reserved.

The Lothian Diary Project: sociolinguistic methods during the COVID-19 lockdown

The Lothian Diary Project is an interdisciplinary effort to collect self-recorded audio or video diaries of people's experiences of COVID-19 in and around Edinburgh, Scotland. In this paper we describe how the project emerged from a desire to support community members. The diaries have been disseminated through public events, a website, an oral history project, and engagement with policymakers. The data collection method encouraged the participation of people with disabilities, racialized individuals, immigrants, and low-proficiency English/Scots speakers, all of whom are more likely to be negatively affected by COVID-19. This is of interest to sociolinguists, given that these groups have been under-represented in previous studies of linguistic variation in Edinburgh. We detail our programme of partnering with local charities to help ensure that digitally disadvantaged groups and their caregivers are represented. Accompanying survey and demographic data means that this self-recorded speech can be used to complement existing Edinburgh speech corpora. Additional sociolinguistic goals include a narrative analysis and a stylistic analysis, to characterize how different people engage creatively with the act of creating a COVID-19 diary, especially as compared to vlogs and other video diaries.