An effective method for epidemic suppression by edge removing in complex network

Since the birth of human beings, the spreading of epidemics such as COVID-19 affects our lives heavily and the related studies have become hot topics. All the countries are trying to develop effective prevention and control measures. As a discipline that can simulate the transmission process, complex networks have been applied to epidemic suppression, in which the common approaches are designed to remove the important edges and nodes for controlling the spread of infection. However, the naive removal of nodes and edges in the complex network of the epidemic would be practically infeasible or incur huge costs. With the focus on the effect of epidemic suppression, the existing methods ignore the network connectivity, leading to two serious problems. On the one hand, when we remove nodes, the edges connected to the nodes are also removed, which makes the node is isolated and the connectivity is quickly reduced. On the other hand, although removing edges is less detrimental to network connectivity than removing nodes, existing methods still cause great damage to the network performance in reality. Here, we propose a method to measure edge importance that can protect network connectivity while suppressing epidemic. In the real-world, our method can not only lower the government's spending on epidemic suppression but also persist the economic growth and protect the livelihood of the people to some extent. The proposed method promises to be an effective tool to maintain the functionality of networks while controlling the spread of diseases, for example, diseases spread through contact networks. Copyright © 2023 Liang, Cui and Zhu.

5-alpha reductase inhibitors use in prostatic disease and beyond.

5-alpha reductase inhibitors (5-ARIs) are commonly used and widely available, with benefits observed from their effect on androgen signalling. Their effect relies on the inhibition of the 5-alpha reductase enzyme which aids in the conversion of testosterone to dihydrotestosterone. 5-ARIs have increasing clinical relevance outside of benign prostatic hyperplasia (BPH). Such development requires clinicians to have an updated review to guide clinical practices. This review details the pharmacology and mechanisms of action for 5-ARIs and how this relates to multiple clinical indications. Of note, is the debunked association between finasteride and increased risk of high-grade prostate cancer. Furthermore, adverse effects of 5-ARI use are detailed in this review, with specific mentions to post-finasteride syndrome. In addition to overviews pertaining to BPH and prostate cancer, much attention has also been focused on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The androgen axis may be associated with an increased virulence for SARS-CoV-2 in men, with some reporting a correlation between the severity of illness and androgenic alopecia. Since these observations, the role of antiandrogens, including 5-ARIs, has been explored further in SARS-CoV-2. Increasing understanding of pathological processes involving the androgen axis in which 5-ARIs work, has led to increasing clinical indications for 5-ARIs. Several novel off-label indications have been suggested including its potential role in the pathogenesis of SARS-CoV-2, but to date, these claims have not been substantiated. Previously held truths regarding the role of 5-ARIs and prostate carcinogenesis have been contested, inadvertently leading to the re-exploration of 5-ARIs utility in prostate cancer. With growing evidence into pathological processes involving the androgen axis, 5-ARIs are likely to become increasingly more used. This review serves as a timely update of 5 ARIs pharmacology, current indications and potential future directions.

Academic performance prediction associated with synchronous online interactive learning behaviors based on the machine learning approach

With long-term impact of COVID-19 on education, online interactive live courses have been an effective method to keep learning and teaching from being interrupted, attracting more and more attention due to their synchronous and real-time interaction. However, there is no suitable method for predicting academic performance for students participating in online class. Five machine learning models are employed to predict academic performance of an engineering mechanics course, taking online learning behaviors, comprehensive performance as input and final exam scores (FESs) as output. The analysis shows the gradient boosting regression model achieves the best performance with the highest correlation coefficient (0.7558), and the lowest RMSE (9.3595). Intellectual education score (IES) is the most important factor of comprehensive performance while the number of completed assignment (NOCA), the live viewing rate (LVR) and the replay viewing rate (RVR) of online learning behaviors are the most important factors influencing FESs. Students with higher IES are more likely to achieve better academic performance, and students with lower IES but higher NOCA tend to perform better. Our study can provide effective evidences for teachers to adjust teaching strategies and provide precise assistance for students at risk of academic failure in advance.

Design of Virtual Reality Scenes on Horticultural Therapy Treatment

The prevalence of depression and anxiety disorders has increased dramatically in the last two years due to the global COVID-19 epidemic, which leads to a shortage of traditional mental health care resources. To address these issues, we propose to use the digital, immersive, and private features of virtual reality technology to assist in the treatment of mental illness. We designed and completed a garden scene for virtual reality horticultural therapy based on the basic principles of traditional horticultural therapy. In order to study the effectiveness of the gardening scenario, we recruited 30 subjects to explore the effectiveness of mood regulation. A survey of a PANAS scale was conducted before and after the garden scene, and a user experience scale was presented to the subjects after the experiment. The ANOVA results showed that there were significant differences between anxious, distressed and self-loathing before and after the experiment. This demonstrates that virtual reality horticulture therapy has a mood-improving effect. In future works, we will improve the design of VR gardening scenarios and conduct more in-depth research on virtual reality horticulture therapy. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Potential mechanisms underlying lithium treatment for Alzheimer's disease and COVID-19.

Disruption of intracellular Ca2+ homeostasis plays an important role as an upstream pathology in Alzheimer's disease (AD), and correction of Ca2+ dysregulation has been increasingly proposed as a target of future effective disease-modified drugs for treating AD. Calcium dysregulation is also an upstream pathology for the COVID-19 virus SARS-CoV-2 infection and replication, leading to host cell damage. Clinically available drugs that can inhibit the disturbed intracellular Ca2+ homeostasis have been repurposed to treat COVID-19 patients. This narrative review aims at exploring the underlying mechanism by which lithium, a first line drug for the treatment of bipolar disorder, inhibits Ca2+ dysregulation and associated downstream pathology in both AD and COVID-19. It is suggested that lithium can be repurposed to treat AD patients, especially those afflicted with COVID-19.

Using Social Media to Analyze Public Concerns and Policy Responses to COVID-19 in Hong Kong

The outbreak of COVID-19 has caused huge economic and societal disruptions. To fight against the coronavirus, it is critical for policymakers to take swift and effective actions. In this article, we take Hong Kong as a case study, aiming to leverage social media data to support policymakers' policy-making activities in different phases. First, in the agenda setting phase, we facilitate policymakers to identify key issues to be addressed during COVID-19. In particular, we design a novel epidemic awareness index to continuously monitor public discussion hotness of COVID-19 based on large-scale data collected from social media platforms. Then we identify the key issues by analyzing the posts and comments of the extensively discussed topics. Second, in the policy evaluation phase, we enable policymakers to conduct real-time evaluation of anti-epidemic policies. Specifically, we develop an accurate Cantonese sentiment classification model to measure the public satisfaction with anti-epidemic policies and propose a keyphrase extraction technique to further extract public opinions. To the best of our knowledge, this is the first work which conducts a large-scale social media analysis of COVID-19 in Hong Kong. The analytical results reveal some interesting findings: (1) there is a very low correlation between the number of confirmed cases and the public discussion hotness of COVID-19. Themajor public concern in the early stage is the shortage of anti-epidemic items. (2) The top-3 anti-epidemic measures with the greatest public satisfaction are daily press conference on COVID-19 updates, border closure, and social distancing rules.

Factors affecting recurrent positive RT-PCR results in clinically cured COVID-19 patients: a multicenter study

The aim of this study was to evaluate factors affecting the recurrence of positive RT-PCR results. By performing a retrospective analysis, we evaluated the clinical data of recurrent positive coronavirus disease 2019 (COVID-19) patients in multiple medical institutions in Wuhan. We recruited COVID-19 patients who were hospitalized from January 1 to March 10, 2020, in three tertiary hospitals in Wuhan, met the discharge criteria and received at least one additional nucleic acid test before leaving the hospital. According to the RT-PCR results, patients were split into a recurrent positive group (RPos group) and a nonrecurrent positive group (non-RPos group). Clinical characteristics, therapeutic schedules and antibody titers were compared between the two groups. AI-assisted chest high-resolution computed tomography (HRCT) technology was applied to investigate pulmonary inflammatory exudation and compare the extent of lung areas with different densities. This study involved 122 COVID-19 patients. There were no significant differences in age, sex, preexisting diseases, clinical symptoms, clinical classification, course of disease, therapeutic schedules or serum-specific antibodies between the two groups. A higher proportion of patients who showed pulmonary inflammatory exudation on HRCT scans were recurrent positive at the time of discharge than other patients (81.6% vs 13.7%, P < 0.01). In addition, the degree of pulmonary fibrosis was higher in the RPos group than in the non-RPos group (P < 0.05). Subpleural exudation at the peripheral edge of the lung and extensive pulmonary fibrosis at the time of discharge represent risk factors for the recurrence of COVID-19.

An Efficient Algorithm for Clarification of Rumors with Limited Costs in Social Networks

Nowadays, the information about COVID-19 is spreading widely on social networks while rumors about it are also propagating quickly. When users receive two opposing opinions, they are more likely to accept the information with greater impact. Therefore, there is an urgent need to clarify rumors. Given the cost Ctotal, the rumor clarifying problem aims to find a seed set with at most k users such that the total number of the users influenced by positive information can be maximized. In this paper, we propose a Cost-Randomized Greedy algorithm called CRG to solve the rumor clarifying problem. It runs in O((n-r)mC{total}), where n, m and r are the number of nodes, edges and the initial rumor nodes, respectively. Extensive contrast experiments on online networks show that our algorithm is much more efficient than the state-of-The art methods. © 2020 IEEE.

Analysis on the causes of PM2.5 pollution in Nanning City in February 2020

During the novel coronavirus (COVID-19) lock down from 31st January to 2nd February, a regional atmospheric PM2.5 pollution episode had arosed concerns of society in Guangxi. Based on Nanning as an sampling site, Monitor for Aerosols and Gases in Ambient Air (MARGA), particulate LiDAR, surface meteorological and environmental data, satellite remote sensing data and modeled HYSPLIT4 trajectory were used to analyze the cause of PM2.5 pollution. According to the air quality sub-index, the observation durations were classified as the superior period, the fine period and the polluted period. The results indicated that K+ and Cl- concentrations closely related to biomass burning (BB) increased significantly during the polluted period. The average concentrations of K+ and Cl- in polluted period were 3.6 and 17.0 times higher than those corresponding figures of the superior period. The total concentration of eight water-soluble ions accounted for about 30% of PM2.5 in all three periods. The total concentration of three secondary water-soluble ions accounted for 83.33%~89.18% of the total concentration of eight ions. The high proportion of secondary inorganic components was related to the secondary transformation promoted by BB. The variation trends of proportion and levels of secondary water-soluble ions were not consistent, which was not only attributed to the emission characteristics of straw combustion, but also related to the formation mechanism and main influencing factors of different secondary inorganic ions. Straw burning spots were centralized around Nanning city during the fine period. The accumulation of direct emissions of particulate and gaseous pollutants caused by open burning of straw during the fine period under decreased boundary layer height, increased humidity and low wind speed were the main causes for atmospheric PM2.5 pollution in Nanning. During the polluted period, there was no obvious vertical transmission process of particulate matter in Nanning. The near ground was mainly affected by the southward airflow from the Beibu Gulf of Guangxi and Guangdong coastal, which indicated the regional pollution transmissions were insignificant. © 2021, Science Press. All right reserved.

Dantrolene repurposed to treat sepsis or septic shock and COVID-19 patients.

OBJECTIVE: Disruption of intracellular Ca2+ homeostasis via excessive and pathological Ca2+ release from the endoplasmic reticulum (ER) and/or sarcoplasmic reticulum (SR) through ryanodine receptor (RyRs) Ca2+ channels play a critical role in the pathology of systemic inflammatory response syndrome (SIRS) and associated multiple organ dysfunction syndrome (MODS) in sepsis or septic shock. Dantrolene, a potent inhibitor of RyRs, is expected to ameliorate SIRS and MODS and decrease mortality in sepsis or septic shock patients. This review summarized the potential mechanisms of therapeutic effects of dantrolene in sepsis or septic shock at molecular, cell, and organ levels and provided suggestions and strategies for future clinical studies.

Could dantrolene be explored as a repurposed drug to treat COVID-19 patients by restoring intracellular calcium homeostasis?

Dantrolene, an FDA approved drug to treat malignant hyperthermia and muscle spasm, has been demonstrated to inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mediated toxicity of host cells. Ryanodine receptor overactivation and associated disruption of intracellular Ca2+ homeostasis play important roles in SARS-CoV-2 infection and replication of host cells. Dantrolene, as an inhibitor of RyRs, is expected to ameliorate these detrimental effects of SARS-CoV-2 in host cells. Additionally, dantrolene has also been shown to inhibit multiple cell or organ damage induced by hypoxia/ischemia, mitochondria damage, oxidative stresses, inflammation, impairment of autophagy and apoptosis, etc., which are often the causes of severity and mortality of COVID-19 patients. We have repurposed that dantrolene has a high potential at treating COVID-19 patients and reducing its morbidity and mortality.

Scoping review: hotspots for COVID-19 urological research: what is being published and from where?

PURPOSE: Contemporary, original research should be utilised to inform guidelines in urology relating to the COVID-19 pandemic. This comprehensive review aimed to: identify all up-to-date original publications relating to urology and COVID-19, characterise where publications were from, and outline what topics were investigated. METHODS: This review utilised a search strategy that assessed five electronic databases, additional grey literature, and global trial registries. All current published, in-press, and pre-print manuscripts were included. Eligible studies were required to be original research articles of any study design, reporting on COVID-19 or urology, in any of study population, intervention, comparison, or outcomes. Included studies were reported in a narrative synthesis format. Data were summarised according to primary reported outcome topic. A world heatmap was generated to represent where included studies originated from. RESULTS: Of the 6617 search results, 48 studies met final inclusion criteria, including 8 pre-prints and 7 ongoing studies from online registries. These studies originated from ten countries according to first author affiliation. Most studies originated from China (n = 13), followed by Italy (n = 12) and USA (n = 11). Topics of the study included pathophysiological, administrative, and clinical fields: translational (n = 14), COVID-19-related outcomes (n = 5), urology training (n = 4), telemedicine (n = 7), equipment and safety (n = 2), urology in general (n = 4), uro-oncology (n = 3), urolithiasis (n = 1), and kidney transplantation (n = 8). CONCLUSION: This review has outlined available original research relevant to COVID-19 and urology from the international community. This summary may serve as a guide for future research priorities in this area.