Advances in mRNA nanomedicines for malignant brain tumor therapy

Nowadays, malignant brain tumors are still mostly lethal diseases with poor prognosis and a clinical median survival rate of fewer than 2 years after therapeutic intervention. It is difficult to achieve complete remission of brain tumors due to blood-brain barrier (BBB) and a lack of efficient drug delivery systems to targeted transportation of brain tumor medicines. Nanoparticle delivery systems have shown merits including stability and high carrier capacity for the transportation of different drugs to treat brain tumors. The application of mRNA nanomedicines brings in great promise not only in COVID-19, but also for malignant brain tumor immunotherapy. The appropriate delivery system facilitates mRNA delivery efficiency and enhances the immune response successfully, for optimal treatment outcomes on malignant brain tumors. Herein, we do an updated review on the development of mRNA nanomedicines for malignant brain cancer treatment. We focus on how to design mRNA-loaded nanoparticle-based delivery systems with optimized pharmacokinetics and pharmacodynamics for efficient therapy of brain cancers. In addition, we point out the challenges and solutions for further development of mRNA nanomedicines for brain cancer therapy. We hope this review would stimulate interest among researchers with different backgrounds and expedite the translation from bench to bedside for the mRNA nanomedicines.

A cross-sectional survey of epidemiology workforce performance and its influencing factors during the emergency response to the COVID-19 pandemic in Guangdong, China (preprint)

Background The epidemiology workforce contributes a lot to the response to COVID-19(Corona Virus Disease 2019) pandemic. Here this study focuses on the self-evaluation of the epidemiology workforce’s capacity and their impression of the cases they interviewed during the emergency response of the COVID-19 pandemic.Methods This study was a cross-sectional, anonymous survey conducted in Guangzhou, Shenzhen, Foshan, Dongguan and Zhuhai in Guangdong province. Data collection was performed between December 5, 2020 and December 22, 2020 through convenient sampling. A total of 596 epidemiology workforce participated in this study.Results Role in the team, professional title, gender, perceived social support, enough COVID-19 related training as well as experience were significantly associated with personal skills. 72.8% (429/589) and 86.3% (164/190) of participants reported they had interviewed uncooperative Chinese and foreign COVID-19 patients, respectively.Conclusions Epidemiology workforce needs enough training and experience to perform better in the investigation. Uncooperative patients were a big obstruction during the emergency response of the COVID-19 pandemic. Our results suggest Chinese experience and strategies focusing on the improvement of the public health emergency management system, including establishing Joint Prevention and Control Mechanism, enhancing training and the like.

Warfarin anticoagulation management during the COVID-19 pandemic: The role of internet clinic and machine learning

Background: Patients who received warfarin require constant monitoring by hospital staff. However, social distancing and stay-at-home orders, which were universally adopted strategies to avoid the spread of COVID-19, led to unprecedented challenges. This study aimed to optimize warfarin treatment during the COVID-19 pandemic by determining the role of the Internet clinic and developing a machine learning (ML) model to predict anticoagulation quality. Methods: This retrospective study enrolled patients who received warfarin treatment in the hospital anticoagulation clinic (HAC) and “Internet + Anticoagulation clinic” (IAC) of the Nanjing Drum Tower Hospital between January 2020 and September 2021. The primary outcome was the anticoagulation quality of patients, which was evaluated by both the time in therapeutic range (TTR) and international normalized ratio (INR) variability. Anticoagulation quality and incidence of adverse events were compared between HAC and IAC. Furthermore, five ML algorithms were used to develop the anticoagulation quality prediction model, and the SHAP method was introduced to rank the feature importance. Results: Totally, 241 patients were included, comprising 145 patients in the HAC group and 96 patients in the IAC group. In the HAC group and IAC group, 73.1 and 69.8% (p = 0.576) of patients achieved good anticoagulation quality, with the average TTR being 79.9 ± 20.0% and 80.6 ± 21.1%, respectively. There was no significant difference in the incidence of adverse events between the two groups. Evaluating the five ML models using the test set, the accuracy of the XGBoost model was 0.767, and the area under the receiver operating characteristic curve was 0.808, which showed the best performance. The results of the SHAP method revealed that age, education, hypertension, aspirin, and amiodarone were the top five important features associated with poor anticoagulation quality. Conclusion: The IAC contributed to a novel management method for patients who received warfarin during the COVID-19 pandemic, as effective as HAC and with a low risk of virus transmission. The XGBoost model could accurately select patients at a high risk of poor anticoagulation quality, who could benefit from active intervention.

SARS-CoV-2 infected cells sprout actin-rich filopodia that facilitate viral invasion (preprint)

Emerging COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a great threat to human health and economics. Although SARS-CoV-2 entry mechanism has been explored, little is known about how SARS-CoV-2 regulates the host cell remodeling to facilitate virus invasion process. Here we unveil that SARS-CoV-2 boosts and repurposes filopodia for entry to the target cells. Using SARS-CoV-2 virus-like particle (VLP), real-time live-cell imaging and simulation of active gel model, we reveal that VLP-induced Cdc42 activation leads to the formation of filopodia, which reinforce the viral entry to host cells. By single-particle tracking and sparse deconvolution algorithm, we uncover that VLP particles utilize filopodia to reach the entry site in two patterns, surfing and grabbing, which are more efficient and faster than entry via flat plasma membrane regions. Furthermore, the entry process via filopodia is dependent on the actin cytoskeleton and actin-associated proteins fascin, formin, and Arp2/3. Importantly, either inhibition the actin cross-linking protein fascin or the active level of Cdc42 could significantly hinders both the VLP and the authentic SARS-CoV-2 entry. Together, our results highlight that the spatial-temporal regulation of the actin cytoskeleton by SARS-CoV-2 infection makes filopodia as a highway for virus entry, which emerges as an antiviral target.

Patients with Advanced Pancreatic & Biliary Cancer Appear More Vulnerable to SARS-CoV-2 Omicron Variant: An Observational Study during the COVID-19 Outbreak in Shanghai (preprint)

Background:There is a great controversy about lethal effect of Omicron Variant on vulnerable populations and the measure of full-open or zero community transmission policy. Thus, we designed an observational study to evaluate the outcomes of Omicron-infected patients with pancreatic & biliary cancer (the so-called “King of Cancer”) in order to provide potential evidence for the most appropriate strategy to counter Omicron transmission in Shanghai.Methods: Omicron infected patients with advanced pancreatic & biliary cancer were enrolled from April 15 to May 31, 2022. Four groups were set in this study: Group 1, Omicron-infected cancer patients (N=4); Group 2, non-infected cancer patients (N=4); Group 3, infected non-cancer-afflicted subjects (N=4); Group 4, non-infected non-cancer-afflicted subjects (N=4). On Day 0, 7 and 14 after infection, the blood samples were dynamically collected from all subjects. The primary endpoints were disease severity and survival. Results:By the endpoints in this observational study, Patients No. 2, 3 and 4 died separately at Day 11, 25 and 13 after viral infection, all of whom were patients with advanced cancer, with the death rate up to 75%. Group 1 presented an overall T cell exhaustion status compared with other groups with obviously lower T cell populations and higher B cell% and CD4+T/CD8+T ratio (P<0.05). Time-course cytokine monitoring results showed that IL-1β was significantly decreased in Group 1 (P<0.05) and generally kept at a low level without obvious fluctuation. IL-6 was markedly increased in infected cancer patients (P<0.01), but remained a low level and had no apparent change during the whole infection process in non-cancer-afflicted subjects. Furthermore, several inflammatory parameter indexes indicated a tight association of Omicron infection with disease course and prognosis of Omicron-infected cancer patients.Conclusions:For patients with advanced pancreatic & biliary cancer, the strict & comprehensive control strategy for COVID-19 epidemic in Shanghai provided a guarantee of low infection and death rate. Conclusively, this policy shall be persisted upon the consideration of the welfare of vulnerable populations.

Spatial Humanities and Geo-computation for Social Sciences:Advances and Applications

Humanities and Social Sciences (HSS) are undergoing the transformation of spatialization and quantification. Geo-computation, with geoinformatics (including RS: Remote Sensing;GIS: Geographical Information System;GNSS: Global Navigation Satellite System), provides effective computational and spatialization methods and tools for HSS. Spatial Humanities and Geo-computation for Social Sciences (SH&GSS) is a field coupling geo-computation, and geoinformatics, with HSS. This special issue accepted a set of contributions highlighting recent advances in methodologies and applications of SH&GSS, which are related to sentiment spatial analysis from social media data, emotional change spatial analysis from news data, spatial analysis of social media related to COVID-19, crime spatiotemporal analysis, “double evaluation” for Land Use/Land Cover (LUCC), Specially Protected Natural Areas (SPNA) analysis, editing behavior analysis of Volunteered Geographic Information (VGI), electricity consumption anomaly detection, First and Last Mile Problem (FLMP) of public transport, and spatial interaction network analysis for crude oil trade network. Based on these related researches, we aim to present an overview of SH&GSS, and propose some future research directions for SH&HSS.

Association of COVID-19 with Diabetes: A Systematic Review and Meta-Analysis (preprint)

Emerging evidence suggests that long COVID-19 may lead to a wide range of post-acute sequelae outcomes, including new onset of diabetes. The aim of this meta-analysis was to estimate the incidence of newly diagnosed diabetes in survivors of coronavirus disease-2019 (COVID-19). Multiple electronic databases (MEDLINE, Scopus, Cochrane Central Register of Controlled Trials and the World Health Organization Global Literature on Coronavirus Disease) and clinical trial registries were searched to June 25, 2022, for studies reporting the association of COVID-19 and diabetes. Two investigators independently assessed studies for inclusion. Risk of bias was assessed using the Newcastle-Ottawa Scale. We estimated the effect of COVID-19 on incident diabetes by random-effects meta-analyses using the generic inverse variance method. We identified 5 eligible studies consisting of 1,130,773 COVID-19 patients and 16,630,187 controls. Median age was 43 years (interquartile range, 1QR: 20–55), and 34.8 % were female. COVID-19 was associated with a 74% higher risk of incident diabetes (risk ratio, 1.74; 95% CI: 1.37; 2.21). The average risk of bias assessment was 7.5. In this systematic review and meta-analysis, COVID-19 was associated with higher risk for developing new onset diabetes among survivors. Active monitoring of glucose dysregulation after recovery from severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) infection is warranted.

Activated interstitial macrophages are a predominant target of viral takeover and focus of inflammation in COVID-19 initiation in human lung (preprint)

Early stages of deadly respiratory diseases such as COVID-19 have been challenging to elucidate due to lack of an experimental system that recapitulates the cellular and structural complexity of the human lung, while allowing precise control over disease initiation and systematic interrogation of molecular events at cellular resolution. Here we show healthy human lung slices cultured ex vivo can be productively infected with SARS-CoV-2, and the cellular tropism of the virus and its distinct and dynamic effects on host cell gene expression can be determined by single cell RNA sequencing and reconstruction of "infection pseudotime" for individual lung cell types. This revealed the prominent SARS-CoV-2 target is a population of activated interstitial macrophages, which as infection proceeds accumulate thousands of viral RNA molecules per cell, comprising up to 60% of the cellular transcriptome and including canonical and novel subgenomic RNAs. During viral takeover, there is cell-autonomous induction of a specific host interferon program and seven chemokines (CCL2, 7, 8, 13, CXCL10) and cytokines (IL6, IL10), distinct from the response of alveolar macrophages in which neither viral takeover nor induction of a substantial inflammatory response occurs. Using a recombinant SARS-CoV-2 Spike pseudotyped lentivirus, we show that entry into purified human lung macrophages depends on Spike but is not blocked by cytochalasin D or by an ACE2-competing monoclonal antibody, indicating a phagocytosis- and ACE2-independent route of entry. These results provide a molecular characterization of the initiation of COVID-19 in human lung tissue, identify activated interstitial macrophages as a prominent site of viral takeover and focus of inflammation, and suggest targeting of these macrophages and their signals as a new therapeutic modality for COVID-19 pneumonia and progression to ARDS. Our approach can be generalized to define the initiation program and evaluate therapeutics for any human lung infection at cellular resolution.

Aerosolized Ad5-nCoV booster vaccination elicited potent immune response against the SARS-CoV-2 Omicron variant after inactivated COVID-19 vaccine priming (preprint)

The SARS-CoV-2 Omicron variant has become the dominant SARS-CoV-2 variant around the world and exhibits immune escape to current COVID-19 vaccines to some extent due to its numerous spike mutations. Here, we evaluated the immune responses to booster vaccination with intramuscular adenovirus-vectored vaccine (Ad5-nCoV), aerosolized Ad5-nCoV, a recombinant protein subunit vaccine (ZF2001) or homologous inactivated vaccine (CoronaVac) in those who received two doses of inactivated COVID-19 vaccines 6 months prior. We found that the Ad5-nCoV booster induced potent neutralizing activity against the wild-type virus and Omicron variant, while aerosolized Ad5-nCoV generated the greatest neutralizing antibody responses against the Omicron variant at day 28 after booster vaccination, at 14.1-fold that of CoronaVac, 5.6-fold that of ZF2001 and 2.0-fold that of intramuscular Ad5-nCoV. Similarly, the aerosolized Ad5-nCoV booster produced the greatest IFNgamma T-cell response at day 14 after booster vaccination. The IFNgamma T-cell response to aerosolized Ad5-nCoV was 12.8-fold for CoronaVac, 16.5-fold for ZF2001, and 5.0-fold for intramuscular Ad5-nCoV. Aerosolized Ad5-nCoV booster also produced the greatest spike-specific B cell response. Our findings suggest that inactivated vaccine recipients should consider adenovirus-vectored vaccine boosters in China and that aerosolized Ad5-nCoV may provide a more efficient alternative in response to the spread of the Omicron variant.

During the COVID-19 Epidemic: Recommendations for the Admission and Treatment of Patients With Ovarian Cancer.

Background: The coronavirus disease 2019 (COVID-19) had become a health care event endangering humans globally. It takes up a large number of healthcare resources. We studied the impact of COVID-19 on patients with ovarian cancer by comprehensively analyzing their admissions before and after the epidemic, and made reasonable suggestions to improve their current situation. Methods: We randomly divided the enrolled patients into three groups, PreCOVID-19 Group (PCG) (2019.8.20-2020.1.20), COVID-19 Group (CG) (2020.1.21-2020.6.14), and Secondary Outbreak COVID-19 Group (SOCG) (2020.6.15-2020.10.10). One-way ANOVA and chi-square test were used for analysis. Results: The number of patients from other provinces decreased significantly (p < 0.05). The total hospital stay during the epidemic was substantially more extended (p < 0.05). Before the epidemic, our department performed more open surgery while during the epidemic outbreak, we tended to choose laparoscopy (p < 0.01). We took a longer surgery time (P < 0.05). Patients had significantly less post-operative fever during the epidemic (p < 0.001). Conclusion: During the COVID-19 epidemic, no patient was infected with COVID-19, and no patient experienced severe post-operative complications. We recommend maintaining the admissions of patients with ovarian cancer during the epidemic following the rules: 1. The outpatients must complete a nucleic acid test and chest CT in the outpatient clinic; 2. Maintain full daily disinfection of the ward and insist that health care workers disinfect their hands after contact with patients; 3. Increase the use of minimally invasive procedures, including laparoscopy and robotics; 4. Disinfect the ward twice a day with UV light and sodium hypochlorite disinfectant; 5. Patients need to undergo at least three nucleic acid tests before entering the operating room.

DeepLPI: a novel deep learning-based model for protein-ligand interaction prediction for drug repurposing (preprint)

The substantial cost of new drug research and development has consistently posed a huge burden for both pharmaceutical companies and patients. In order to lower the expenditure and development failure rate, repurposing existing and approved drugs by identifying interactions between drug molecules and target proteins based on computational methods have gained growing attention. Here, we propose the DeepLPI, a novel deep learning-based model that mainly consists of ResNet-based 1-dimensional convolutional neural network (1D CNN) and bi-directional long short term memory network (biLSTM), to establish an end-to-end framework for protein-ligand interaction prediction. We first encode the raw drug molecular sequences and target protein sequences into dense vector representations, which go through two ResNet-based 1D CNN modules to derive features, respectively. The extracted feature vectors are concatenated and further fed into the biLSTM network, followed by the MLP module to finally predict protein-ligand interaction. We downloaded the well-known BindingDB and Davis dataset for training and testing our DeepLPI model. We also applied DeepLPI on a COVID-19 dataset for externally evaluating the prediction ability of DeepLPI. To benchmark our model, we compared our DeepLPI with the state-of-the-art methods of DeepCDA and DeepDTA, and observed that our DeepLPI outperformed these methods, suggesting the high accuracy of the DeepLPI towards protein-ligand interaction prediction. The high prediction performance of DeepLPI on the different datasets displayed its high capability of protein-ligand interaction in generalization, demonstrating that the DeepLPI has the potential to pinpoint new drug-target interactions and to find better destinations for proven drugs.

The evolution trend of availability of China's community-based care services and its impact on the cognitive function of elderly people: 2008-2018.

BACKGROUND: To address the challenge of the aging population, community-based care services (CBCS) have been developed rapidly in China as a new way of satisfying the needs of elderly people. Few studies have described the evolution trend of availability of CBCS in rural and urban areas and evaluated their effectiveness. This study aims to show the availability of China's CBCS and further analyze the effect of the CBCS on the cognitive function of elderly people. METHODS: Longitudinal analysis was performed using data from the 2008 to 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS). A total of 23937 observations from 8421 elderly people were included in the study. The Chinese version of the Mini-Mental State Examination (MMSE) was used to assess cognitive function. We aggregated similar CBCS to generate three binary variable categories (daily life support, emotional comfort and entertainment services, medical support and health services) indicating the availability of CBCS (1 = yes, 0 = no). Multilevel growth models were employed to estimate the association between CBCS and cognitive function while adjusting for many demographic and socioeconomic characteristics. RESULTS: The availability of CBCS increased a lot from 2008 to 2018 in China. Although the availability of CBCS in urban areas was higher than that in rural areas in 2008, by 2018 the gap narrowed significantly. Emotional comfort and entertainment services (B = 0.331, 95% CI = 0.090 to 0.572) and medical support and health services (B = 1.041, 95% CI = 0.854 to 1.228) were significantly and positively associated with cognitive function after adjusting for the covariates. CONCLUSION: There was a significant increase in the availability of CBCS from 2008 to 2018 in China. This study sheds light on the positive correlation between CBCS and cognitive function among Chinese elderly individuals. The results suggest that policymakers should pay more attention to the development of CBCS and the equity of the supply of CBCS in urban and rural areas.

Effect of Bacillus licheniformis capsule on the cytokines level and clinical prognosis of COVID-19 patients

Objective: To investigate the drug of Bacillus licheniformis Capsule (BLC) to improve the high levels of cytokines and clinical prognosis in COVID-19 patients, and to provide the clinical evidence for gut microflora therapy in COVID-19.

Infectivity and Antigenicity of SARS-CoV-2 Strains in Portugal (preprint)

The SARS-CoV-2 virus has had a major impact on global human health. During the spread of SARS-CoV-2, weakened host immunity and the use of vaccines with low efficacy may result in the development of more virulent strains or strains with resistance to existing vaccines and antibodies. The prevalence of SARS-CoV-2 mutant strains differs among regions, and this variation may affect the effectiveness of vaccines. In this study, an epidemiological investigation of SARS-CoV-2 in Portugal was performed, and the VSV-ΔG-G* pseudovirus system was used to construct 12 S protein epidemic mutants, D614G, A222V+D614G, B.1.1.7, S477N+D614G, P1162R+D614G+A222V, D839Y+D614G, L176F+D614G, B.1.1.7+L216F, B.1.1.7+M740V, B.1.258, B.1.258+L1063F, and B.1.258+N751Y.The mutant pseudoviruses were used to infect four susceptible cell lines (i.e., Huh7, hACE2-293T, Vero, and LLC-MK2) and 14 cell lines overexpressing ACE2 from different species. Mutant strains did not show increased infectivity or cross-species transmission. Neutralization activity was evaluated using the newly constructed pseudoviruses, mouse serum, and 11 monoclonal antibodies. The neutralizing activity in immunized mouse serum was not significantly reduced for the mutant strains. Additionally, mutant strains in Portugal showed escape from 9 of 11 monoclonal antibodies. Neutralization resistance was mainly caused by the S477N, N439K, and N501Y mutations in the Spike receptor binding domain. These findings emphasize the importance of SARS-CoV-2 mutation tracking in different regions for epidemic prevention and control.

Clinical Features of Imported Chinese COVID-19 Patients Following Chinese Inactivated Vaccines Injection Abroad (preprint)

Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination has been demonstrated as an effective way to reduce the risk of coronavirus disease 2019 (COVID-19), and only a few vaccinees suffered from SARS-CoV-2 infection. However, limited data concerning the clinical features of these vaccinees infected with SARS-CoV-2 can be identified. Methods We retrospectively collected and analyzed epidemiological and clinical characteristics data of the imported COVID-19 cases who received Chinese inactivated vaccines abroad. Data were extracted from electronic medical records from a designated hospital in the Shaanxi Province of China between March 22 and May 17, 2021. Results Totally, 46 confirmed SARS-CoV-2 infection patients were enrolled. The mean age was 40.5 years (range 20-61), 41 (89.1%) are male. Eighteen (39.1%) patients were from Pakistan. Fourteen (30.4%) patients had at least one comorbidity. Forty (87.0%) and 6 cases were fully vaccinated and partly vaccinated. The time interval between vaccination and infection was 88 days (IQR, 33-123), 31 (67.4%) and 15 (32.6%) were asymptomatic and symptomatic cases, respectively. Fever (3/46, 6.5%) was the most common symptom; however, none had a body temperature higher than 38.0℃, and no severe case was observed. Notably, the rate of SARS-CoV-2 shedding discontinuation at 7 days after hospitalization in asymptomatic cases was higher than symptomatic one (93.5% vs 40%, P < 0.0001). Conclusions Individuals who received Chinese inactivated vaccines abroad remain have the probability to be infected with SARS-CoV-2, but all the vaccinees infected with SARS-CoV-2 were asymptomatic or had mild symptoms with favorable clinical outcomes.

Infectivity and antigenicity of SARS-CoV-2 B.1.617 variants (preprint)

SARS-CoV-2 has caused the COVID-19 pandemic. Recently, B.1.617 variants have been transmitted rapidly in India. The transmissibility, pathogenicity, and neutralization characteristics of these variants have received considerable interest. In this study, 22 pseudotyped viruses were constructed for B.1.617 variants and their corresponding single amino acid mutations. B.1.617 variants did not exhibit significant enhanced infectivity in human cells, but mutations T478K and E484Q in the receptor binding domain led to enhanced infectivity in mouse ACE2-overexpressing cells. Furin activities were slightly increased against B.1.617 variants and cell–cell fusion after infection of B.1.617 variants was enhanced. Furthermore, B.1.617 variants escaped neutralization by several mAbs, mainly because of mutations L452R, T478K, and E484Q in the receptor binding domain. The neutralization activities of sera from convalescent patients, inactivated vaccine-immunized volunteers, adenovirus vaccine-immunized volunteers, and SARS-CoV-2 immunized animals against pseudotyped B.1.617 variants were reduced by approximately twofold, compared with the D614G variant.

A Reversible Watermarking System for Medical Color Images: Balancing Capacity, Imperceptibility, and Robustness

The authenticity and integrity of medical images in telemedicine has to be protected. Robust reversible watermarking (RRW) algorithms provide copyright protection and the original images can be recovered at the receiver’s end. However, the existing algorithms have limitations in their ability to balance the tradeoff among robustness, imperceptibility, and embedded capacity. Some of them are even not completely reversible. Besides, most medical image watermarking algorithms are not designed for color images. To improve their performance in protecting medical color image information, we propose a novel RRW scheme based on the discrete wavelet transform (DWT). First, the DWT provides a robust solution. Second, the modification of the wavelet domain coefficient guarantees the changes of integer values in the spatial domain and ensures the reversibility of the watermarking scheme. Third, the embedding scheme makes full use of the characteristics of the original image and watermarking. This reduces the modification of the original image and ensures better imperceptibility. Lastly, the selection of the Zernike moments order for geometric correction is optimized to predict attack parameters more accurately by using less information. This enhances the robustness of the proposed scheme against geometric attacks such as rotation and scaling. The proposed scheme is robust against common and geometric attacks and has a high embedding capacity without obvious distortion of the image. The paper contributes towards improving the security of medical images in remote healthcare.

Impact of Home Confinement Due to COVID-19 Pandemic on Mental Health in Young Children: A Natural Experiment (preprint)

Background: The outbreak of coronavirus disease in 2019 (COVID-19) has had an enormous impact on people’s health, and profoundly changed our lives and society. However, the impact of pandemic-related home confinement on children’s life and their mental health remains unknown. We took advantage of a natural experiment due to the onset of COVID-19 and examined this issue in two consecutive cohorts. Methods: This study compared mental health, family environment and lifestyles of two representative cohorts of young children in Shanghai, China. Both prospective cohorts recruited children at entry to kindergarten. Surveys were conducted at both entry and graduation of kindergarten using the same assessment instruments. Children in the non-exposed cohort experienced a normal period of kindergarten study and graduated in June, 2019; those in the exposed cohort were under confinement for five months and graduated in June, 2020. Findings: Compared with the non-exposed cohort, the exposed cohort had a significant increased percentage of children classified as “at-risk for mental health problems”, with an adjusted absolute risk difference of 3·1% (95% CI, 1·9% to 4·4%) for total difficulties as measured by the Strength and Difficulty Questionnaire. The effect of pandemic related confinement on mental health was larger in children with lower parental education. The exposed cohort had longer media time, sleep duration and a less favorable home environment. Interpretation: The pandemic related confinement negatively affected children's mental health and home environment. Strategies and actions are urgently needed to improve parenting skills and mitigate the negative impact by strengthening the family environment.Funding Statement: National Natural Science Foundation of China, Shanghai Committee of Science and Technology, Shanghai Municipal Health Commission, Shanghai Education CommitteeDeclaration of Interests: We declare no competing interests.Ethics Approval Statement: The study was approved by the Institutional Review Board of the Shanghai Children’s Medical Center, the Shanghai Jiao Tong University School of Medicine (SCMCIRB-K2016022-01)

Comparison of 10 emerging SARS-CoV-2 Variants: infectivity, animal tropism, and antibody neutralization (preprint)

Ten emerging SARS-CoV-2 variants—B.1.1.298, B.1.1.7, B.1.351, P.1, P.2, B.1.429, B.1.525, B.1.526-1, B.1.526-2, B.1.1.318—and seven corresponding single amino acid mutations in the receptor-binding domain were examined using SARS-CoV-2 pseudovirus. The results indicate that the current SARS-CoV-2 variants do not increase infectivity among humans. The K417N/T, N501Y, or E484K-carrying variants exhibited increased abilities to infect to mouse ACE2-overexpressing cells. The activities of Furin, TMPRSS2, and cathepsin L were increased against most of the variants. RBD amino acid mutations comprising K417T/N, L452R, Y453F, S477N, E484K, and N501Y caused significant immune escape from 11 of 13 monoclonal antibodies. However, the resistance to neutralization by convalescent serum or vaccines was mainly caused by the E484K mutation, while the neutralization of E484K-carrying variants was decreased by 1.1–6.2-fold. The convalescent serum from B.1.1.7- and B.1.351-infected patients neutralized the variants themselves better than other SARS-CoV-2 variants.