Early autoimmunity and outcome in virus encephalitis: a retrospective study based on tissue-based assay.

To explore the autoimmune response and outcome in the central nervous system (CNS) at the onset of viral infection and correlation between autoantibodies and viruses. METHODS: A retrospective observational study was conducted in 121 patients (2016-2021) with a CNS viral infection confirmed via cerebrospinal fluid (CSF) next-generation sequencing (cohort A). Their clinical information was analysed and CSF samples were screened for autoantibodies against monkey cerebellum by tissue-based assay. In situ hybridisation was used to detect Epstein-Barr virus (EBV) in brain tissue of 8 patients with glial fibrillar acidic protein (GFAP)-IgG and nasopharyngeal carcinoma tissue of 2 patients with GFAP-IgG as control (cohort B). RESULTS: Among cohort A (male:female=79:42; median age: 42 (14-78) years old), 61 (50.4%) participants had detectable autoantibodies in CSF. Compared with other viruses, EBV increased the odds of having GFAP-IgG (OR 18.22, 95% CI 6.54 to 50.77, p<0.001). In cohort B, EBV was found in the brain tissue from two of eight (25.0%) patients with GFAP-IgG. Autoantibody-positive patients had a higher CSF protein level (median: 1126.00 (281.00-5352.00) vs 700.00 (76.70-2899.00), p<0.001), lower CSF chloride level (mean: 119.80±6.24 vs 122.84±5.26, p=0.005), lower ratios of CSF-glucose/serum-glucose (median: 0.50[0.13-0.94] vs 0.60[0.26-1.23], p=0.003), more meningitis (26/61 (42.6%) vs 12/60 (20.0%), p=0.007) and higher follow-up modified Rankin Scale scores (1 (0-6) vs 0 (0-3), p=0.037) compared with antibody-negative patients. A Kaplan-Meier analysis revealed that autoantibody-positive patients experienced significantly worse outcomes (p=0.031). CONCLUSIONS: Autoimmune responses are found at the onset of viral encephalitis. EBV in the CNS increases the risk for autoimmunity to GFAP.

Efficacy of SARS-CoV-2 vaccines and the dose-response relationship with three major antibodies: a systematic review and meta-analysis of randomised controlled trials.

BACKGROUND: The efficacy of SARS-CoV-2 vaccines in preventing severe COVID-19 illness and death is uncertain due to the rarity of data in individual trials. How well the antibody concentrations can predict the efficacy is also uncertain. We aimed to assess the efficacy of these vaccines in preventing SARS-CoV-2 infections of different severities and the dose-response relationship between the antibody concentrations and efficacy. METHODS: We did a systematic review and meta-analysis of randomised controlled trials (RCTs). We searched PubMed, Embase, Scopus, Web of Science, Cochrane Library, WHO, bioRxiv, and medRxiv for papers published between Jan 1, 2020 and Sep 12, 2022. RCTs on the efficacy of SARS-CoV-2 vaccines were eligible. Risk of bias was assessed using the Cochrane tool. A frequentist, random-effects model was used to combine efficacy for common outcomes (ie, symptomatic and asymptomatic infections) and a Bayesian random-effects model was used for rare outcomes (ie, hospital admission, severe infection, and death). Potential sources of heterogeneity were investigated. The dose-response relationships of neutralising, spike-specific IgG and receptor binding domain-specific IgG antibody titres with efficacy in preventing SARS-CoV-2 symptomatic and severe infections were examined by meta-regression. This systematic review is registered with PROSPERO, CRD42021287238. FINDINGS: 28 RCTs (n=286 915 in vaccination groups and n=233 236 in placebo groups; median follow-up 1-6 months after last vaccination) across 32 publications were included in this review. The combined efficacy of full vaccination was 44·5% (95% CI 27·8-57·4) for preventing asymptomatic infections, 76·5% (69·8-81·7) for preventing symptomatic infections, 95·4% (95% credible interval 88·0-98·7) for preventing hospitalisation, 90·8% (85·5-95·1) for preventing severe infection, and 85·8% (68·7-94·6) for preventing death. There was heterogeneity in the efficacy of SARS-CoV-2 vaccines against asymptomatic and symptomatic infections but insufficient evidence to suggest whether the efficacy could differ according to the type of vaccine, age of the vaccinated individual, and between-dose interval (p>0·05 for all). Vaccine efficacy against symptomatic infection waned over time after full vaccination, with an average decrease of 13·6% (95% CI 5·5-22·3; p=0·0007) per month but can be enhanced by a booster. We found a significant non-linear relationship between each type of antibody and efficacy against symptomatic and severe infections (p<0·0001 for all), but there remained considerable heterogeneity in the efficacy, which cannot be explained by antibody concentrations. The risk of bias was low in most studies. INTERPRETATION: The efficacy of SARS-CoV-2 vaccines is higher for preventing severe infection and death than for preventing milder infection. Vaccine efficacy wanes over time but can be enhanced by a booster. Higher antibody titres are associated with higher estimates of efficacy but precise predictions are difficult due to large unexplained heterogeneity. These findings provide an important knowledge base for interpretation and application of future studies on these issues. FUNDING: Shenzhen Science and Technology Programs.

Inhibitory effects of ultralow-dose sodium hypochlorite on Microcystis aeruginosa and Chlorella vulgaris: Differences in sensitivity and physiology

Throughout the COVID-19 pandemic, the application of residual free chlorine has been emphasized as an effective disinfectant;however, the discharged residual chlorine is associated with potential ecological risk at concentrations even below 0.1 mg/L. However, the influence of free chlorine at ultralow-doses (far below 0.01 mg/L) on phytoplankton remains unclear. Due to limitations of detection limit and non-linear dissolution, different dilution rates (1/500, 1/1000, 1/5000, 1/10000, and 1/50000 DR) of a NaClO stock solution (1 mg/L) were adopted to represent ultralow-dose NaClO gradients. Two typical microalgae species, cyanobacterium Microcystis aeruginosa and chlorophyta Chlorella vulgaris, were explored under solo- and co-culture conditions to analyze the inhibitory effects of NaClO on microalgae growth and membrane damage. Additionally, the effects of ultralow-dose NaClO on photosynthesis activity, intracellular reactive oxygen species (ROS) production, and esterase activity were investigated, in order to explore physiological changes and sensitivity. With an initial microalgae cell density of approximately 1 × 106 cell/mL, an inhibitory effect on M. aeruginosa was achieved at a NaClO dosage above 1/10000 DR, which was lower than that of C. vulgaris (above 1/5000 DR). The variation in membrane integrity and photosynthetic activity further demonstrated that the sensitivity of M. aeruginosa to NaClO was higher than that of C. vulgaris, both in solo- and co-culture conditions. Moreover, NaClO is able to interfere with photosynthetic activity, ROS levels, and esterase activity. Photosynthetic activity declined gradually in both microalgae species under sensitive NaClO dosage, but esterase activity increased more rapidly in M. aeruginosa, similar to the behavior of ROS in C. vulgaris. These findings of differing NaClO sensitivity and variations in physiological activity between the two microalgae species contribute to a clearer understanding of the potential ecological risk associated with ultralow-dose chlorine, and provide a basis for practical considerations. Graphical Unlabelled Image

Monitoring Spatiotemporal Distribution of the GDP of Major Cities in China during the COVID-19 Pandemic.

Monitoring the fine spatiotemporal distribution of urban GDP is a critical research topic for assessing the impact of the COVID-19 outbreak on economic and social growth. Based on nighttime light (NTL) images and urban land use data, this study constructs a GDP machine learning and linear estimation model. Based on the linear model with better effect, the monthly GDP of 34 cities in China is estimated and the GDP spatialization is realized, and finally the GDP spatiotemporal correction is processed. This study analyzes the fine spatiotemporal distribution of GDP, reveals the spatiotemporal change trend of GDP in China's major cities during the current COVID-19 pandemic, and explores the differences in the economic impact of the COVID-19 pandemic on China's major cities. The result shows: (1) There is a significant linear association between the total value of NTL and the GDP of subindustries, with R2 models generated by the total value of NTL and the GDP of secondary and tertiary industries being 0.83 and 0.93. (2) The impact of the COVID-19 pandemic on the GDP of cities with varied degrees of development and industrial structures obviously varies across time and space. The GDP of economically developed cities such as Beijing and Shanghai are more affected by COVID-19, while the GDP of less developed cities such as Xining and Lanzhou are less affected by COVID-19. The GDP of China's major cities fell significantly in February. As the COVID-19 outbreak was gradually brought under control in March, different cities achieved different levels of GDP recovery. This study establishes a fine spatial and temporal distribution estimation model of urban GDP by industry; it accurately monitors and assesses the spatial and temporal distribution characteristics of urban GDP during the COVID-19 pandemic, reveals the impact mechanism of the COVID-19 pandemic on the economic development of major Chinese cities. Moreover, economically developed cities should pay more attention to the spread of the COVID-19 pandemic. It should do well in pandemic prevention and control in airports and stations with large traffic flow. At the same time, after the COVID-19 pandemic is brought under control, they should speed up the resumption of work and production to achieve economic recovery. This study provides scientific references for COVID-19 pandemic prevention and control measures, as well as for the formulation of urban economic development policies.

Distance education quality evaluation based on multigranularity probabilistic linguistic term sets and disappointment theory

Distance education quality evaluation is extremely important in improving the quality of education under COVID-19. As traditional teaching-quality evaluation methods are no longer applicable, it is crucial to construct effective evaluation methods. In the evaluation of distance education quality, decision-makers have different linguistic expression preferences, and the evaluation information may be biased due to an improper grasp of the problem. In addition, the correlation between the criteria of distance education quality evaluation is common, and the results of existing evaluation methods are quite different. In this paper, to compensate for these deficiencies, we utilize the multi-granularity probabilistic linguistic term set (MGPLTS), which can reflect the linguistic expression preference of decision-makers and the importance of linguistic terms, and propose a multi-criteria group decision-making (MCGDM) method. First, the dispersion and concentration degrees are proposed as the theoretical basis for judging the hesitancy of decision-makers’ evaluation information, and the decision-maker weight adjustment model is constructed. To reflect the importance and correlation of criteria, the SWARA method and the CRITIC method are constructed as criteria weight methods. To obtain reliable decision results, decision-makers’ psychological expectations are taken into account, the MULTIMOORA method is improved upon, and a new integration theory is proposed to improve its robustness. Finally, through an example case of distance education quality evaluation and comparison with other methods, the effectiveness, practicability and superiority of this method are verified.

Huaier effects on functional compensation with destructive ribosomal RNA structure after anti-SARS-CoV-2 mRNA vaccination. (preprint)

Although striking effects of vaccination strategy against COVID-19 world-wide, a long-term influence by sequential viral mRNA injections are unknown. We analysed biological alterations by total RNA sequencing in Pfizer-BioNTech vaccinated normal healthy volunteers and cancer patients, with or without adjuvant Huaier therapy. A significant destruction in ribosomal RNA structures was identified, enhanced by serial shots. Unlike the destruction caused by chemotherapy with platinum (II) complex, progressive destruction in 18S ribosome was identified even at 6 months after vaccination. The influence resulted in massive inhibition of translation and transcription, significantly in intra/inter neural signaling transfer and in lipid metabolism, related to ageing process. Huaier compensated these dysfunctions by miRNA-mediated transcriptional control, by typical activation in PI3K/AKT signaling pathway. Gene Ontology analysis revealed spontaneous virion production in number even after 3 months of the first vaccination. Present study indicated that the adjuvant therapy like Huaier compensates accelerated ageing process by mRNA vaccination.

Continuously updated forecasting of SARS-CoV-2 in a regional health system.

OBJECTIVES: To build a model of local hospital utilization resulting from SARS-CoV-2 and to continuously update it with new data. STUDY DESIGN: Retrospective analysis of real performance resulting from a model deployed in a major regional health system. METHODS: Using hospitalization data from the Kaiser Permanente Mid-Atlantic States integrated care system during the period from March 10, 2020, through December 31, 2020, and a custom-developed genetic particle filtering algorithm, we modeled the SARS-CoV-2 outbreak in the mid-Atlantic region. This model produced weekly forecasts of COVID-19-related hospital admissions, which we then compared with actual hospital admissions over the same period. RESULTS: We found that the model was able to accurately capture the data-generating process (weekly mean absolute percentage error, 10.0%-48.8%; Anderson-Darling P value of .97 when comparing percentiles of observed admissions with the uniform distribution) once the effects of social distancing could be accurately measured in mid-April. We also found that our estimates of key parameters, including the reproductive rate, were consistent with consensus literature estimates. CONCLUSIONS: The genetic particle filtering algorithm that we have proposed is effective at modeling hospitalizations due to SARS-CoV-2. The methods used by our model can be reproduced by any major health care system for the purposes of resource planning, staffing, and population care management to create an effective forecasting regimen at scale.

The Association between COVID-19-Related Wellbeing with Materialism and Perceived Threat.

The ongoing coronavirus disease (COVID-19) pandemic has had a profound impact on people's wellbeing. Here, we proposed that an individual characteristic might be associated with wellbeing; that is, materialism. Specifically, we conducted three studies (total N = 3219) to examine whether people with high levels of materialism would experience poorer wellbeing (i.e., anxiety and depression, in the current case). The results showed that materialism was positively associated with depression (Studies 1A, 1B and 2) and anxiety (Study 2). Moreover, such a relationship was mediated by people's perceived threat of COVID-19 (Study 2). These findings were observed in both Chinese and American people. The findings are discussed in terms of their theoretical and practical contributions.

Psychosomatic Symptoms and Neuroticism following COVID-19: The Role of Online Aggression toward a Stigmatized Group.

The present study investigated the effect of interpersonal mistreatment on the perpetrators' mental health. We proposed that the threat of COVID-19 will increase people's mental health problems through their on-line aggression toward stigmatized groups accused of spreading the disease and that there might be potential gender differences in such effects. We tested our predictions among a sample of U.S. residents (Study 1) and a large sample of Chinese residents living out of Hubei province (Study 2) during a heightened period of concern about COVID-19, February 2020. Specifically, we measured U.S. residents' on-line aggressive behaviors toward Chinese people (Study 1) and Chinese non-Hubei residents' on-line aggressive behaviors toward Hubei residents (Study 2) as well as their neuroticism (Study 1) and mental health states (Study 2). In line with our predictions, both studies showed that perceived infection of COVID-19 can induce on-line aggression toward stigmatized groups, thereby increasing people's mental health problems. Moreover, the relationship between COVID-19 vulnerability, on-line aggression, and psychosomatic symptoms was more prominent in men than in women. These results offer insights into people's responses toward COVID-19 and add to the understanding of people's mental and physical health during the epidemic stage of contagious diseases.

Theory and reality of antivirals against SARS-CoV-2.

At present, over 180 million people have been infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) worldwide and there have been more than 3.8 million deaths due to the virus. However, specific effective antiviral treatment for this infectious disease is absent. At the beginning of the epidemic, relevant cellular and animal experiments of antiviral treatment for SARS-CoV-2 were conducted based on the prior studies of SARS-CoV and Middle East respiratory syndrome coronavirus. Some antivirals were preliminarily validated to be potentially effective in the clinical settings. But as the epidemic continued and more studies were carried out, the efficacy of these antiviral drugs became controversial. This paper reviews the pharmacology and application of interferon, lopinavir/ritonavir, ribavirin, chloroquine, arbidol, favipiravir, remdesivir, and thymosin α1 in coronavirus disease 2019. The actual effect of these drugs remains controversial. Meanwhile, the efficacy and safety of these drugs for patients with coronavirus disease 2019 still need to be explored.

How Chinese Herbal Medicine Prevents Epidemics: From Ancient Pestilences to COVID-19 Pandemic.

The ongoing coronavirus disease 2019 (COVID-19) pandemic calls for effective control and prevention. Chinese medicine (CM) has developed systematic theories and approaches for infectious disease prevention over 2000 years. Here, we review and analyze Chinese herbal medicines (CHM) used in infectious disease prevention from ancient pestilences to modern epidemics and pandemics to share cumulative preventive medical experience. A total of 829 formulas, including 329 herbs from 189 ancient books, 131 formulas with 152 herbs, and 13 Chinese patent medicines (CPM) from 30 official Chinese prevention programs used in ancient epidemics, SARS, influenza and COVID-19 prevention, were reviewed and analyzed. Preventive CHM mainly has four functions and can be taken orally or applied externally. CHM that kill pathogens (Realgar [Xionghuang], Cyrtomium Fortunei J. Sm[Guanzhong]) were commonly used externally for disinfection in ancient prevention while CHM tonifying Qi (Astragali Radix [Huangq], Glycyrrhizae Radix et Rhizoma [Gancao]) are used for modern prevention. Taking CHM that expel pathogens (Realgar [Xionghuang], Lonicerae Japonicae Flos[Jinyinhua]) and CHM eliminating dampness (Atractylodis Rhizoma [Cangzhu], Pogostemonis Herba[Guanghuoxiang]) have been commonly used from ancient times to COVID-19. Damp toxins are a common characteristic of infectious diseases such as SARS and COVID-19. Thus, taking CHM expelling damp toxins and tonifying Qi are the main methods for SARS and COVID-19 prevention. CHM with different approaches have been widely used in infectious disease prevention from ancient times to the present. Multiple CM prevention methods may provide new perspectives for future pandemics.

A Chemical-Enhanced System for CRISPR-Based Nucleic Acid Detection (preprint)

The CRISPR-based nucleic acid detection systems such as SHERLOCK, DETECTR and HOLMES have shown great potential for point-of-care testing of viral pathogens, especially in the context of COVID-19 pandemic. Here we optimize several key parameters of reaction chemistry and develop a Chemical Enhanced CRISPR Detection system for nucleic acid (termed CECRID). For the Cas12a/Cas13a-based signal detection phase, we determine buffer conditions and substrate range for optimal detection performance. By comparing several chemical additives, we find that addition of L-proline can secure or enhance Cas12a/Cas13a detection capability. For isothermal amplification phase with typical LAMP and RPA methods, inclusion of L-proline can also enhance specific target amplification as determined by CRISPR detection. Using SARS-CoV-2 pseudovirus, we demonstrate CECRID has enhanced detection sensitivity over chemical additive-null method with either fluorescence or lateral flow strip readout. Thus, CECRID provides an improved detection power and system robustness towards practical application of CRISPR-based diagnostics.

Full recovery of elective orthopedic surgery in the age of COVID-19: an 8-month retrospective cohort study.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has led to dramatic disruptions to orthopedic services. The purpose of this study is to quantify the reinstatement of elective orthopedic surgeries of our institution in Shanghai, China, and share our first-hand experiences of how this region is managing the post-outbreak period. METHODS: The number of patients receiving elective orthopedic surgeries was analyzed in the timeframe of 8 months since the start of the pandemic (from January 20 to September 16) and compared with the patients receiving the same treatment during the same period in 2019. And a detailed workflow for handling patients about to receive elective surgeries in the COVID-19 post-outbreak period was described. RESULTS: The number of the selective surgeries in the first 3 months only accounted for 31.72% of the same period in 2019 (p = 0.0031), and the ratio reached 97.47% when it came to the last 5 months (p > 0.9999). The selective surgeries even surpassed the pre-epidemic level in months 7 and 8. And the difference of the surgeries was not significant in the whole eight observed months between 2019 and 2020 (p = 0.1526). No health care providers or hospitalized patients in orthopedic departments in Shanghai have been infected nosocomially. CONCLUSIONS: Elective orthopedic surgeries have been fully recovered from the COVID-19 pandemic in our institution, and the new normalcy established during the post-outbreak period helped this region co-exist with the impact of the virus well. TRIAL REGISTRATION: Retrospectively registered, registration number: ChiCTR2000039711 , date of registration: November 6, 2020.

Dominate others, hurt self: Social dominance orientation predicts depression during the COVID-19 pandemic.

The ongoing coronavirus pandemic threatens physical and psychological health. We examined whether social dominance orientation (SDO), a preference for inequality among social groups, contributes to mental health during the pandemic. In particular, we predicted that people high in SDO would experience higher levels of depression than others low in SDO. Our results (N = 2008) showed that SDO was positively associated with depression. In addition, participants' perceived lifestyle changes moderated the association between SDO and depression. We also discuss the theoretical and practical implications of the current work.

SARS-CoV-2 Proteome Microarray for Mapping COVID-19 Antibody Interactions at Amino Acid Resolution.

Comprehensive profiling of humoral antibody response to severe acute respiratory syndrome (SARS) coronavirus-2 (CoV-2) proteins is essential in understanding the host immunity and in developing diagnostic tests and vaccines. To address this concern, we developed a SARS-CoV-2 proteome peptide microarray to analyze antibody interactions at the amino acid resolution. With the array, we demonstrate the feasibility of employing SARS-CoV-1 antibodies to detect the SARS-CoV-2 nucleocapsid phosphoprotein. The first landscape of B-cell epitopes for SARS-CoV-2 IgM and IgG antibodies in the serum of 10 coronavirus disease of 2019 (COVID-19) patients with early infection is also constructed. With array data and structural analysis, a peptide epitope for neutralizing antibodies within the SARS-CoV-2 spike receptor-binding domain's interaction interface with the angiotensin-converting enzyme 2 receptor was predicted. All the results demonstrate the utility of our microarray as a platform to determine the changes of antibody responses in COVID-19 patients and animal models as well as to identify potential targets for diagnosis and treatment.

A Computational Framework of Host-Based Drug Repositioning for Broad-Spectrum Antivirals against RNA Viruses (preprint)

RNA viruses are responsible for many types of zoonotic diseases that post great challenges for public health system. Effective therapeutics against these viral infections remains limited. Here we deployed a computational framework for host-based drug repositioning to predict potential antiviral drug candidates from 2352 approved drugs and 1062 natural compounds embedded in Traditional Chinese Medicine herbs. By systematically interrogating public genetic screening data, we comprehensively catalogued human-specific host dependency genes that are indispensable for the successful viral infection corresponding to 10 families and 29 species of RNA viruses. In addition, we utilized these host dependency genes as potential drug targets, and interrogated extensive drug-target interactions through multiple ways such as database retrieval, literature mining and de novo prediction using artificial intelligence-based algorithms. Repurposed drugs or natural compounds were proposed for combating many viral pathogens such as coronaviruses (e.g., SARS-CoV-2), flaviviruses (e.g., Zika virus) and influenza viruses. This study helps to prioritize promising drug candidates for further therapeutic evaluation against these viral-related diseases.