Corrigendum: Prevalence and outcomes of pancreatic enzymes elevation in patients with COVID-19: a meta-analysis and systematic review.

[This corrects the article DOI: 10.3389/fpubh.2022.865855.].

An Effective Platform for SARS-CoV-2 Prevention by Combining Neutralization and RNAi Technology

At present, the coronavirus disease 2019 (COVID-19) pandemic is a global health crisis. Scientists all over the globe are urgently looking forward to an effective solution to prevent the spread of the epidemic and avoid more casualties at an early date. In this study, we establish an effective platform for the prevention of SARS-CoV-2 by combining the neutralization strategy and RNAi technology. To protect normal cells from infection, the customized cells are constructed to stably express viral antigenic receptor ACE2 on the cell membrane. These modified cells are used as bait for inducing the viral entry. The transcription and replication activities of viral genome are intercepted subsequently by the intracellular shRNAs, which are complementary to the viral gene fragments. A pseudotyped virus reconstructed from the HIV lentivirus is utilized as a virus model, by which we validate the feasibility and effectiveness of our strategy in vitro. Our work establishes an initial model and lays the foundation for future prevention and treatment of various RNA viruses. [ABSTRACT FROM AUTHOR] Copyright of Chinese Journal of Polymer Science (Springer Science & Business Media B.V.) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients.

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

Immune response and homeostasis mechanism following administration of BBIBP-CorV SARS-CoV-2 inactivated vaccine.

The BBIBP-CorV severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inactivated vaccine has been authorized for emergency use and widely distributed. We used single-cell transcriptome sequencing to characterize the dynamics of immune responses to the BBIBP-CorV inactivated vaccine. In addition to the expected induction of humoral immunity, we found that the inactivated vaccine induced multiple, comprehensive immune responses, including significantly increased proportions of CD16+ monocytes and activation of monocyte antigen presentation pathways; T cell activation pathway upregulation in CD8+ T cells, along with increased activation of CD4+ T cells; significant enhancement of cell-cell communications between innate and adaptive immunity; and the induction of regulatory CD4+ T cells and co-inhibitory interactions to maintain immune homeostasis after vaccination. Additionally, comparative analysis revealed higher neutralizing antibody levels, distinct expansion of naive T cells, a shared increased proportion of regulatory CD4+ T cells, and upregulated expression of functional genes in booster dose recipients with a longer interval after the second vaccination. Our research will support a comprehensive understanding of the systemic immune responses elicited by the BBIBP-CorV inactivated vaccine, which will facilitate the formulation of better vaccination strategies and the design of new vaccines.

Analysis and Identification of Bioactive Compounds of Cannabinoids in Silico for Inhibition of SARS-CoV-2 and SARS-CoV.

Despite the approval of multiple vaccinations in different countries, the majority of the world's population remains unvaccinated due to discrepancies in vaccine distribution and limited production capacity. The SARS-CoV-2 RBD-ACE2 complex (receptor binding domain that binds to ACE2) could be a suitable target for the development of a vaccine or an inhibitor. Various natural products have been used against SARS-CoV-2. Here, we docked 42 active cannabinoids to the active site of the SARS-CoV-2 and SARS-CoV complex of RBD-ACE2. To ensure the flexibility and stability of the complex produced after docking, the top three ligand molecules with the best overall binding energies were further analyzed through molecular dynamic simulation (MDS). Then, we used the webserver Swissadme program and binding free energy to calculate and estimate the MMPBSA and ADME characteristics. Our results showed that luteolin, CBGVA, and CBNA were the top three molecules that interact with the SARS-CoV-2 RBD-ACE2 complex, while luteolin, stigmasterol, and CBNA had the strongest contact with that SARS-CoV. Our findings show that luteolin may be a potential inhibitor of infections caused by coronavirus-like pathogens such as COVID-19, although further in vivo and in vitro research is required.

Miller-Fisher syndrome and Guillain-Barre syndrome overlap syndrome following inactivated COVID-19 vaccine: Case report and scope review.

Miller-Fisher syndrome (MFS) is a rare variant of Guillain-Barré syndrome (GBS) manifesting as the triad of ataxia, areflexia, and ophthalmoplegia. With the extensive 2019 coronavirus disease (COVID-19) immunization program, cases of GBS or MFS following vaccination are increasingly being reported. A 64-y-old Chinese man presented with new-onset paresthesia of the extremities, bilateral abduction limitation, right facial palsy, areflexia of bilateral lower limbs, and left-dominant limb ataxia 12 d after the second dose of inactivated vaccine against COVID-19. Cerebrospinal fluid analysis indicated albumin-cytological dissociation and was positive for anti-GQ1b IgG and anti-GT1b IgG. Nerve conduction studies of limbs showed evidence of axonal neuropathy with reduced sensory amplitudes. Based on the clinical presentations, temporal progression of symptoms, and laboratory findings, the diagnosis of MFS-GBS overlap syndrome was made. The patient was treated with intravenous immunoglobulin and acupuncture and made a complete recovery 54 d after the onset of his initial neurological signs. To the best of our knowledge, we report the first case of MFS-GBS overlap syndrome following the inactivated COVID-19 vaccination. However, a coincidental relationship with this inactivated vaccine cannot be excluded. Although the benefits of COVID-19 vaccination largely outweigh its risk and the prognosis of MFS is generally favorable, a close surveillance of neurological complications post-COVID-19 vaccination is always necessary, considering its potentially disabling and lethal effects on vaccinated populations.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.

BACKGROUND: As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases. METHODS: In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database. RESULTS: CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .

Discovery and characterization of SARS-CoV-2 reactive and neutralizing antibodies from humanized CAMouseHG mice through rapid hybridoma screening and high-throughput single-cell V(D)J sequencing.

The coronavirus disease 2019 pandemic has caused more than 532 million infections and 6.3 million deaths to date. The reactive and neutralizing fully human antibodies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are effective detection tools and therapeutic measures. During SARS-CoV-2 infection, a large number of SARS-CoV-2 reactive and neutralizing antibodies will be produced. Most SARS-CoV-2 reactive and neutralizing fully human antibodies are isolated from human and frequently encoded by convergent heavy-chain variable genes. However, SARS-CoV-2 viruses can mutate rapidly during replication and the resistant variants of neutralizing antibodies easily survive and evade the immune response, especially in the face of such focused antibody responses in humans. Therefore, additional tools are needed to develop different kinds of fully human antibodies to compensate for current deficiency. In this study, we utilized antibody humanized CAMouseHG mice to develop a rapid antibody discovery method and examine the antibody repertoire of SARS-CoV-2 RBD-reactive hybridoma cells derived from CAMouseHG mice by using high-throughput single-cell V(D)J sequencing analysis. CAMouseHG mice were immunized by 28-day rapid immunization method. After electrofusion and semi-solid medium screening on day 12 post-electrofusion, 171 hybridoma clones were generated based on the results of SARS-CoV-2 RBD binding activity assay. A rather obvious preferential usage of IGHV6-1 family was found in these hybridoma clones derived from CAMouseHG mice, which was significantly different from the antibodies found in patients with COVID-19. After further virus neutralization screening and antibody competition assays, we generated a noncompeting two-antibody cocktail, which showed a potent prophylactic protective efficacy against SARS-CoV-2 in cynomolgus macaques. These results indicate that humanized CAMouseHG mice not only provide a valuable platform to obtain fully human reactive and neutralizing antibodies but also have a different antibody repertoire from humans. Thus, humanized CAMouseHG mice can be used as a good complementary tool in discovery of fully human therapeutic and diagnostic antibodies.

An Effective Platform for SARS-CoV-2 Prevention by Combining Neutralization and RNAi Technology

At present, the coronavirus disease 2019 (COVID-19) pandemic is a global health crisis. Scientists all over the globe are urgently looking forward to an effective solution to prevent the spread of the epidemic and avoid more casualties at an early date. In this study, we establish an effective platform for the prevention of SARS-CoV-2 by combining the neutralization strategy and RNAi technology. To protect normal cells from infection, the customized cells are constructed to stably express viral antigenic receptor ACE2 on the cell membrane. These modified cells are used as bait for inducing the viral entry. The transcription and replication activities of viral genome are intercepted subsequently by the intracellular shRNAs, which are complementary to the viral gene fragments. A pseudotyped virus reconstructed from the HIV lentivirus is utilized as a virus model, by which we validate the feasibility and effectiveness of our strategy in vitro. Our work establishes an initial model and lays the foundation for future prevention and treatment of various RNA viruses. [ FROM AUTHOR] Copyright of Chinese Journal of Polymer Science (Springer Science & Business Media B.V.) is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Release of microplastics and nanoplastics in water from disposable surgical masks after disinfection.

During the COVID-19 pandemic, disposable surgical masks were generally disinfected and reused due to mask shortages. Herein, the role of disinfected masks as a source of microplastics (MPs) and nanoplastics (NPs) was investigated. The amount of MPs and NPs released from masks disinfected by UV ranged from 1054 ± 106 to 2472 ± 70 and from 2.55 ± 0.22 × 109 to 6.72 ± 0.27 × 109 particles/piece, respectively, comparable to that of the undisinfected masks, and the MPs were changed to small-sized particles. The amount of MPs and NPs released after alcohol and steam treatment were respectively lower and higher than those from undisinfected masks, and MPs were shifted to small-sized particles. The amount of MPs and NPs released in water after autoclaving was lower than for undisinfected masks. In all, the amount of fibers released after disinfection decreased greatly, and certain disinfection processes were found to increase the amount of small-sized NPs released from masks into aqueous environments.

Construct and Validate a Predictive Model for Surgical Site Infection after Posterior Lumbar Interbody Fusion Based on Machine Learning Algorithm.

Purpose: Surgical site infection is one of the serious complications after lumbar fusion. Early prediction and timely intervention can reduce the harm to patients. The aims of this study were to construct and validate a machine learning model for predicting surgical site infection after posterior lumbar interbody fusion, to screen out the most important risk factors for surgical site infection, and to explore whether synthetic minority oversampling technique could improve the model performance. Method: This study reviewed 584 patients who underwent posterior lumbar interbody fusion for degenerative lumbar disease at our center from January 2019 to August 2021. Clinical information and laboratory test data were collected from the electronic medical records. The original dataset was divided into training set and validation set in a 1 : 1 ratio. Seven machine learning algorithms were used to develop predictive models; the training set of each model was resampled using synthetic minority oversampling technique. Finally, the model performance was assessed in the validation set. Results: Of the 584 patients, 33 (5.65%) occurred surgical site infection. Stepwise logistic regression showed that preoperative albumin level (OR 0.659, 95% CI 0.563-0.756), diabetes (OR 9.129, 95% CI 3.816-23.126), intraoperative dural tear (OR 8.436, 95% CI 2.729-25.334), and rheumatic disease (OR 8.471, 95% CI 1.743-39.567) were significant predictors associated with surgical site infection. The performance of the AdaBoost Classification Trees model was the best among the seven machine learning models, and synthetic minority oversampling technique improved the performance of all models. Conclusion: The prediction model we constructed based on machine learning and synthetic minority oversampling technique can accurately predict surgical site infection, which is conducive to clinical decision-making and optimization of perioperative management.

Prevalence and Outcomes of Pancreatic Enzymes Elevation in Patients With COVID-19: A Meta-Analysis and Systematic Review.

Background: Although coronavirus disease 2019 (COVID-19) is considered to be a disease that mainly involves the respiratory system, an increasing number of studies have reported that COVID-19 patients had pancreatic enzymes (PE) elevation and even pancreatic injury. The study aims to determine the prevalence of PE elevation, and the relationship between elevated PE and prognosis in COVID-19 patients. Methods: A comprehensive literature search was conducted according to the PRISMA guideline in PubMed, Embase, Scopus, Web of Science, and Google Scholar for studies reporting PE elevation in patients with COVID-19 from 1st January 2020 to 24th November 2021. Results: A total of 13 studies (24,353 participants) were included in our review. The pooled prevalence of PE elevation in COVID-19 patients was 24% (18%-31%), the pooled odds ratio (OR) of mortality was 2.5 (1.7-3.6), the pooled OR of ICU admission was 4.4 (2.8-6.8), and the pooled OR of kidney injury, respiratory failure and liver injury were 3.5 (1.6-7.4), 2.0 (0.5-8.7), and 2.3 (1.4-3.9) respectively. In addition, the subgroup analysis revealed that although PE elevated to > 3 × upper normal limit (ULN) was significantly related to the mortality (OR = 4.4, 2.1-9.4), it seemed that mild elevation of PE to 1-3 ULN also had a considerable risk of mortality (OR = 2.3, 1.5-3.5). Conclusions: PE elevation was a common phenomenon in patients with COVID-19, and was associated with poor clinical outcomes. However, due to the limited numbers of included studies, the result of our study still needed to be validated. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=295630, identifier: CRD42021295630.

Acceptance of COVID-19 vaccination and influencing factors among people living with HIV in Guangxi, China: a cross-sectional survey.

BACKGROUND: Vaccination has been proven to be an effective approach against the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to determine the acceptance rate and factors influencing acceptance of COVID-19 vaccination among people living with HIV (PLWH) in Guangxi, China. METHODS: A cross-sectional survey was carried out in five cities in Guangxi, China from May 7 to June 1, 2021. Questionnaires on the acceptance of COVID-19 vaccination and the related factors were conducted among PLWH recruited by simple random sampling. Univariate and multivariate logistic regression analyses were performed to identify factors associated with acceptance of COVID-19 vaccination. RESULTS: Of all valid respondents (n = 903), 72.9% (n = 658) were willing to receive COVID-19 vaccination. Fear of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was the main reason for being willing to receive vaccination (76.0%), while the main reasons for not willing were the concerns about vaccine safety (54.7%) and the vaccination's effect on antiretroviral therapy (ART) (50.6%). The most important factors influencing acceptance were the perception that vaccination is unsafe for HIV-infected people (aOR = 0.082, 95% CI = 0.024-0.282) and the poor efficacy in preventing SARS-CoV-2 infection in HIV-infected people (aOR = 0.093, 95% CI = 0.030-0.287). Other factors associated with acceptance included Zhuang ethnicity (aOR = 1.653, 95% CI = 1.109-2.465), highest education level of middle school, high school or above (aOR = 1.747, 95% CI = 1.170-2.608; aOR = 2.492, 95% CI = 1.326-4.682), and the vaccination having little effect on ART efficacy (aOR = 2.889, 95% CI = 1.378-6.059). CONCLUSIONS: Acceptance rate of the COVID-19 vaccination is relatively low among PLWH compared to the general population in China, although some patients refused vaccination due to concerns about vaccine safety and vaccination affecting ART efficacy. More research is needed to investigate the impact of the COVID-19 vaccines on ART efficacy and the effectiveness in preventing SARS-CoV-2 infection among PLWH.

A Critical Review on Optimization of Cold-Formed Steel Members for Better Structural and Thermal Performances

The construction and building sectors are currently responsible globally for a significant share of the total energy consumption and energy-related carbon dioxide emissions. The use of Modern Methods of Construction can help reduce this, one example being the use of cold-formed steel (CFS) construction. CFS channel sections have inherent advantages, such as their high strength-to-weight ratio and excellent potential for recycling and reusing. CFS members can be rolled into different cross-sectional shapes and optimizing these shapes can further improve their load-bearing capacities, resulting in a more economical and efficient building solution. Conversely, the high thermal conductivity of steel can lead to thermal bridges, which can significantly reduce the building’s thermal performance and energy efficiency. Hence, it is also essential to consider the thermal energy performance of the CFS structures. This paper reviews the existing studies on the structural optimization of CFS sections and the thermal performance of such CFS structures. In total, over 160 articles were critically reviewed. The methodologies used in the existing literature for optimizing CFS members for both structural and thermal performances have been summarized and presented systematically. Research gaps from the existing body of knowledge have been identified, providing guidelines for future research.

Progress in drug development for treatment of coronavirus disease 2019 (COVID-19)

Since the outbreak of the novel coronavirus (SARS-CoV-2), the number of people infected worldwide has been increasing, and the medical situation is very severe. In emergency situations, the development of innovative drugs and the treatment of new coronavirus pneumonia (COVID-19) new adaptations on the market The development of the certificate has become the only way to find specific therapeutic drugs and the best treatment plan for COVID-19. The mechanism of angiotensin-converting enzyme 2 (ACE2) that mediates the invasion of host cells by SARS-CoV-2 has been discovered and is based on SARS-CoV- 2. Potential therapeutic targets of host and host, mainly including RNA-dependent RNA polymerase, 3CL protease, papain-like protease, Janus kinase, interleukin 6 and immunomodulators, etc. According to the above-mentioned pharmacological mechanism of action, the treatment of marketed drugs Great progress has been made in the development of new indications for COVID-19 and the clinical research and development of innovative drugs, but no specific drugs have been found. Some traditional Chinese medicines in China can block the SARS-CoV-2 replication cycle, regulate the body's immune response, and treat COVID-19. Biopharmaceuticals are currently undergoing phase I clinical studies in the world for the treatment of COVID-19. Biopharmaceuticals are progressing rapidly, accounting for 67%. At present, the research and development of drugs for the treatment of COVID-19 in China is facing severe challenges and biosafety The number of protection laboratories is small, the research on the mechanism of SARS-CoV-2 infection and the body's response mechanism is not in-depth, the resources of non-clinical cells and animal models are scarce, and the professional quantitative pharmacology research platform and professional talent training system are not perfect to treat COVID-19 The informatization of drug clinical trials and sample testing capabilities are in urgent need of improvement. If China can use this to improve its ability to develop new drugs in emergency situations, it will be able to better protect people's health.

Comparison of ARIMA, ES, GRNN and ARIMA–GRNN hybrid models to forecast the second wave of COVID-19 in India and the United States

As acute infectious pneumonia, the coronavirus disease-2019 (COVID-19) has created unique challenges for each nation and region. Both India and the United States (US) have experienced a second outbreak, resulting in a severe disease burden. The study aimed to develop optimal models to predict the daily new cases, in order to help to develop public health strategies. The autoregressive integrated moving average (ARIMA) models, generalised regression neural network (GRNN) models, ARIMA–GRNN hybrid model and exponential smoothing (ES) model were used to fit the daily new cases. The performances were evaluated by minimum mean absolute per cent error (MAPE). The predictive value with ARIMA (3, 1, 3) (1, 1, 1)14 model was closest to the actual value in India, while the ARIMA–GRNN presented a better performance in the US. According to the models, the number of daily new COVID-19 cases in India continued to decrease after 27 May 2021. In conclusion, the ARIMA model presented to be the best-fit model in forecasting daily COVID-19 new cases in India, and the ARIMA–GRNN hybrid model had the best prediction performance in the US. The appropriate model should be selected for different regions in predicting daily new cases. The results can shed light on understanding the trends of the outbreak and giving ideas of the epidemiological stage of these regions.