The experience and inspiration on the prevention and control of coronavirus disease 2019 in the department of radiotherapy

Coronavirus disease 2019 (COVID-19), as a public health emergency, is a serious threat to human health. Cancer patients have a high risk of being infected with COVID-19. As one of important means of cancer treatment, radiotherapy has become an important alternative to surgery during the epidemic of COVID-19. The radiotherapy department of Peking Union Medical College Hospital ensured the smooth development of radiotherapy work on the setup of prevention and control systems for COVID-19 by establishing admission strategies for cancer patients, disinfection, isolation, daily management measures, scientific exploration, and clinical practice. In this paper, the associated strategies are summarized and analyzed, which can provide experience and reference for radiotherapy treatment under public health emergencies.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Human Anti-Ace2 Monoclonal Antibodies as Pan-Sarbecovirus Prophylactic Agents

Background: Human monoclonal antibodies from convalescent individuals that target the SARS-CoV-2 spike protein have been deployed as therapeutics against SARS-CoV-2. However, nearly all of these antibodies have been rendered obsolete by SARS-CoV-2 variants that evolved to resist similar, naturally occurring antibodies. Moreover, Most SARS-CoV-2 specific antibodies are inactive against divergent sarbecoviruses Methods: By immunizing mice that carry human immunoglobulin variable gene segments we generated a suite of fully human monoclonal antibodies that bind the human ACE2 receptor (hACE2) rather than the viral spike protein and were engineered to lack effector functions such as ADCC. Result(s): These ACE2 binding antibodies block infection by all hACE2 binding sarbecoviruses, including emergent SARS-CoV-2 variants, with a potency that of the most potent spike binding therapeutic antibodies. Structural and biochemical analyses revealed that the antibodies target an hACE2 epitope that engages SARS-CoV-2 spike. Importantly, the antibodies do not inhibit hACE2 enzymatic activity, nor do they induce ACE depletion from cell surfaces. The antibodies exhibit favorable pharmacology in human ACE2 knock in mice and provide near complete protection of hACE2 knock-in mice against SARS-CoV-2 infection. Conclusion(s): ACE2 binding antibodies should be useful prophylactic and treatment agents against any current and future SARS-CoV-2 variants, as well as hACE2-binding sarbecoviruses that might emerge as future pandemic threats.

Synthesis and crystal characteristics of nirmatrelvir

Several synthetic routes of nirmatrelvir (the ingredient of a new drug to treat COVID-19 made by Pfizer) have been reported. We focused on a second route to improve the synthetic method of nirmatrelvir with a methodology that included different steps. The first step was an analysis of reaction byproducts using acetonitrile as a solvent of the condensation reaction to improve the inversion rate. Then, we used isobutyl acetate as a crystalline solvent to obtain the key intermediate as a solvate, which was a stable crystal product with high purity. Complementarily, we also used trifluoroacetic anhydride as the primary-amide dehydrating agent, and 2-methyl tetrahydrofuran as the solvent to prepare nirmatrelvir, which led to an overall yield of 48% via four steps and a purity of 99.5% according to high-performance liquid chromatography. We also investigated the crystal form of nirmatrelvir: the single-crystal features and transformation from a crystal form to nirmatrelvir were dependent upon temperature. Our data have great value for study of the synthetic method and crystal stability of nirmatrelvir. © 2023 The Royal Society of Chemistry.

Variations of air pollutant response to COVID-19 lockdown in cities of the Tibetan Plateau

Coronavirus Disease 2019 (COVID-19) accidentally appeared in Tibet on August 7, 2022, and broke the 920 consecutive epidemic-free days. The cities in Tibet completely kept lockdown to restrict the public to homes. It provided a valuable opportunity for understanding how variations of urban air pollutants responded to the COVID-19 lockdown in the special highland cities of the third polar. Compared with the global COVID-19 restrictions in 2020, a slightly negative O3 anomaly and greater PM2.5 and NO2 reductions were found. The study showed PM10 (−65%) < NO2 (−53%) < PM2.5 (−52%) < O3 (−15%) < CO (−11%) < SO2 (10%) in the Tibetan Lockdown 2022. The total gaseous oxidant (Ox = NO2 + O3) decreased 18% in the Tibetan Lockdown 2022, but showed a limited change in the Lockdown 2020. Moreover, the diurnal profiles of NO2 and PM10 disappeared and the diurnal profiles of Ox, PM2.5, and PM2.5/CO became weakened. Via the random forest model-based weather normalization technique, we obtained the decoupled meteorological effects 1.3 ± 0.6 times higher than the net emission reduction due to the Tibetan Lockdown 2022. Meanwhile, we found that the deweathered PM2.5 was mainly from residential combustion emissions due to the weak industrialization in Tibet. Here we roughly estimated that vehicle-related sources can contribute about 28% and 29% to PM2.5 and NO2 in urban cities of Tibet respectively. For eco-vulnerability protection and sustainable development in Tibet, more attention should be paid to reducing the more intensive local pollutant emissions from vehicles and residential combustion of urban cities. © 2023 The Royal Society of Chemistry.

Exploration on rationalization of diagnosis and treatment of breast cancer patients combined with COVID-19.

Coronavirus disease 2019 (COVID-19) has become a major global public health event as a new acute respiratory infectious disease. During the COVID-19 pandemic, compared with the healthy population, cancer patients had a higher risk of developing comorbidities of other systems, due to their bad poor immunity and older age. Research showed that breast cancer, as a malignant disease, had the highest disease incidence in female patients. Breast cancer patients with COVID-19 infection often have worse prognosis, and they have to postpone anti-tumor treatment due to COVID-19 infection. At present, the effect of delayed treatment on the survival rate of breast cancer patients is unclear, and whether the treatment plan of these patients should be adjusted is still being studied. Through the systematic review of existing clinical research studies, the guidelines of various societies and the expert consensus, this paper reviews the selection and rationalization of breast cancer treatment options under the COVID-19 epidemic, and discusses the opportunity and approaches of anti-tumor treatment for breast cancer patients infected with COVID-19.Copyright © 2022 Editorial Department of Journal of Shanghai Second Medical University. All rights reserved.

Clinical features of COVID-19 Omicron variant cases in makeshift hospital of national exhibition and convention center (Shanghai)

Objective: To summarize and analyze the epidemiological and clinical characteristics of COVID-19 Omicron variant cases in makeshift hospital, and the influence of age, sex and vaccination status on the disease duration, so as to provide reference for the prevention and control of the COVID-19 epidemic. Methods: The epidemiological and clinical characteristics of COVID-19 cases admitted to makeshift hospital of National Convention and Exhibition Center (Shanghai) from April 9 to May 31, 2022 were retrospectively described and analyzed, and further cohort analysis was conducted to determine the influence of age, sex and vaccination status on the disease duration of COVID-19 cases in the author's branch hospital. Results: Among the 174 466 COVID-19 cases in makeshift hospital, most of them were male, accounting for 59.38%. The infected cases were mainly young and middle-aged people aged 18-59 years old, accounting for 83.50%, followed by 12.30% of the elderly group over 60 years old;the average hospital stay was 7.40 days;the proportion of patients with fever was less than 27.79%;15.37% (26 817/174 466) of the patients complicated with underlying diseases, and the top three were hypertension, diabetes and coronary heart disease. The proportion of people who received COVID-19 vaccine accounted for 79.56% (13 799/17 956), of which the highest proportion of three doses was 44.09%. The disease duration of 17 956 COVID-19 cases in the author's branch of makeshift hospital was 10.18 (7.34, 13.05) days. The disease duration in the elderly group was the longest with 11.34 (8.35, 14.37) days, followed by 11.17 (9.07, 14.33) days in the preschool group, 10.37 (8.14, 13.34) days in the middle-aged group, 10.07 (7.37, 12.37) days in the school-age group, and 9.34 (7.05, 12.16) days in the young group. There was significant difference in the overall distribution of disease duration among the five groups (H=550.479 P < 0.01). The disease duration in each age group basically showed a V-shaped distribution. The disease duration was 10.27 (7.34, 12.57) days in males and 10.10 (7.25, 13.09) days in females, and there was no significant difference (Z=-1.505 P > 0.05). The disease duration of vaccinated patients was 10.24 (7.35, 13.05) days, and that of unvaccinated patients was 9.47 (7.09, 12.47) days. There was significant difference between the two groups (Z=-4.338 P < 0.01). Conclusions: COVID-19 Omicron variant cases have a high proportion of males, mainly young and middle-aged, and the proportion of fever patients is less than 30%. The disease duration is significantly lower than that of the original strain in Wuhan, and shows "V" distribution with each age group. Sex had no effect on the disease duration. COVID-19 vaccination did not have a clinical effect on the disease duration.

Deep Venous Thrombosis in Elderly Inpatients with Pneumonia

Background: The occurrence of deep vein thrombosis (DVT) in COVID-19 pneumonia has raised wide concern recently, but few studies have reported the incidence of DVT in other types of pneumonia. We evaluate the prevalence, risk factors and treatment of DVT in the elderly inpatients with pneumonia. Method(s): A cohort of 550 elderly inpatients (>= 75 years old) with pneumonia between 2017 and 2021 were reviewed. They were divided into DVT group and non-DVT groups on the basis of whether pneumonia was combined with new-found DVT. Clinical data were collected retrospectively. Patients with DVT were divided into anticoagulant group and non-anticoagulant groups on the basis of whether they received anticoagulant therapy. Result(s): Ninety-seven patients were included in the DVT group;453 in the non-DVT group. The incidence of DVT was 17.64%. Hospital stays were significantly longer for DVT patients than for non-DVT counterparts (p = 0.005). Coronary heart disease, heart failure, hyperlipidemia, bed rest, and elevated D-dimer were independent risk factors for DVT (p < 0.05). The rate of anticoagulant therapy in DVT group was 63.92% (62/97 cases). Follow-up showed that the continuous anticoagulant treatment rate was 48.39% (30/62 cases) at 3 months and 30.65% (19/62 cases) at 6 months. Conclusion(s): Elderly inpatients with pneumonia are at high risk of DVT. The combination of DVT and pneumonia may lead to prolonged hospitalization. Coronary heart disease, heart failure, hyperlipidemia, bed rest and elevated D-dimer are independent risk factors for DVT in these patients. The rate of regular anticoagulant treatment is low because of the high risk of bleeding.Copyright © 2022, Taiwan Society of Geriatric Emergency & Critical Care Medicine.

Effects of different stirrer modes on the physicochemical properties of vegetables during cooking

The coronavirus disease-19 (COVID-19) pandemic caused dietary changes. Humans reduced social activities to prevent the spread of COVID-19, which led to increasing demand for machines to help cook. This work studies the effect of different stirrer modes on the texture of celery, asparagus, green peppers, and spinach during the cooking process and the functional loss of components in vegetables by measuring the changes in vitamin C, total polyphenols, and total flavonoids. The results showed that colour changes and loss of nutrients in each vegetable varied under different stirrer modes. Stirring was found to be the best mode for cooking all four vegetables. In addition, there was a positive correlation between the a* value and functional components during the cooking process, which means that the colour difference and nutritional loss of vegetables can be modulated together. This study provides theoretical guidance for developing the stirring unit in a cooking machine.

SPR analysis on the interactions between heparin and SARS-CoV-2 spike protein RBDs from different variants

The COVID-19 pandemic has become a major human health concern. The pathogen responsible for COVID-19, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), invades its host through the interaction of its spike (S) protein with a host cell receptor, angiotensin-converting enzyme 2 (ACE2). In addition to ACE2, heparan sulfate (HS) on the surface of host cells also plays a significant role as a co-receptor. In this study, SARS-CoV-2 SP receptor binding domain (RBD) wild type (WT), Delta and Omicron variants were expressed in Expi293F cells and used in the kinetic and structural analysis on their interactions with heparin by Surface plasminogen resonance (SPR). Detailed kinetic and structural analysis of the interactions of SARS-CoV-2 SP RBDs with heparin provides important information for designing anti-SARS-CoV-2 molecules.

Study of Marine Natural Products as Anti-SARS-CoV-2 Agents Using Molecular Modeling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created a global pandemic. Viral entry into host cells is mediated by spike glycoprotein (SGP) interactions with angiotensin-converting enzyme 2 (ACE2) and heparan sulfate glycosaminoglycans on the cell surface. Carbohydrate small molecules were found to bind to the receptor binding domain (RBD) of SGP, which also interacts with ACE2, forming a ternary complex. Moreover, glycans isolated from sea cucumber and red alga species exhibited anti-SARS-CoV-2 activities, presumably by blocking viral entry mediated through SGP-heparan sulfate interactions. Here we report a collection of computational studies conducted as part of a collaborative effort to investigate the effects of marine natural products (NPs) on the wild-type and N501Y mutant SGP RBD. Starting from an X-ray crystal structure of the RBD-ACE2 complex, a model of SGP RBD was built. To investigate the static and dynamic behavior of RBD-NP interactions, blind and site-targeted molecular docking using diverse docking programs (Glide, AutoDock Vina or ClusPro) was carried out, followed by extensive molecular dynamics simulations with two force fields (CHARMM36 or Glycam06) and binding free energy calculations. Predicted conformations of the NPs varied considerably when modeled in water or in complex with RBD. Five NP binding sites on the RBD were studied. NP binding specificities towards SARS-CoV-2 variants were explained and important RBD residues were identified. Statistical analyses of the stability of various protein-NP complexes during molecular dynamics simulations helped to differentiate pseudo-vs. real-binding sites. Our results provide significant insights into the importance of extensive molecular dynamics calculations in order to move beyond the limitations of molecular docking.

An approach combining bioinformatics and machine learning to identify eight autophagy-related biomarkers and construct molecular mechanisms underlying COVID-19 and major depressive disorders.

OBJECTIVE: A lack of objective biomarkers is preventing the screening and diagnosis of COVID-19 combined with major depression disorder (COVID-19-MDD). The purpose of this study was to identify diagnostic biomarkers and gene regulatory mechanisms associated with autophagy; a crucial process significantly involved in the pathogenesis of COVID-19-MDD. MATERIALS AND METHODS: In this study, differentially expressed genes (DEGs) were screened using GSE98793 from the GEO2R analysis (GEO) database, and intersected with the COVID-19-related gene (CRGs) and autophagy-related genes (ARGs) to obtain common genes involved in. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these common genes were performed. Subsequently, the transcription factor (TF)-gene regulatory network and comorbidity network were constructed. In addition, 10 drug candidates were screened using the DSigDB database. To identify diagnostic markers, we used LASSO regression. RESULTS: In total, 13 common genes were screened, which were primarily enriched in lysosomes, endoplasmic reticulum membranes, and other endomembrane systems also associated with autophagy. Additionally, these genes were involved in neurological cell signaling and have a functional role in pathways related to vascular endothelial growth factor, tyrosine kinase, autophagy, inflammation, immunity, and carcinogenesis. Tumors and psychiatric disorders were the most highly linked diseases to COVID-19. Finally, ten drug candidates and eight diagnostic markers (STX17, NRG1, RRAGD, XPO1, HERC1, HSP90AB1, EPHB2, and S1PR3) were screened. CONCLUSIONS: This is the first study to screen eight diagnostic markers and construct a gene regulatory network for COVID-19-MDD from the perspective of autophagy. The findings of our study provide novel insights into the diagnosis and treatment of COVID-19-MDD.

Robust Cough Feature Extraction and Classification Method for COVID-19 Cough Detection Based on Vocalization Characteristics

A fast, efficient and accurate detection method of COVID-19 remains a critical challenge. Many cough-based COVID-19 detection researches have shown competitive results through artificial intelligence. However, the lack of analysis on vocalization characteristics of cough sounds limits the further improvement of detection performance. In this paper, we propose two novel acoustic features of cough sounds and a convolutional neural network structure for COVID-19 detection. First, a time-frequency differential feature is proposed to characterize dynamic information of cough sounds in time and frequency domain. Then, an energy ratio feature is proposed to calculate the energy difference caused by the phonation characteristics in different cough phases. Finally, a convolutional neural network with two parallel branches which is pre-trained on a large amount of unlabeled cough data is proposed for classification. Experiment results show that our proposed method achieves state-of-the-art performance on Coswara dataset for COVID-19 detection. The results on an external clinical dataset Virufy also show the better generalization ability of our proposed method. Copyright © 2022 ISCA.

Analysis on Ethical Principles of Vaccine Use in COVID-19

COVID-19 poses a major threat to safety and health of human life. Vaccination has become an important means to resist and prevent COVID-19. Under the background of limited global supply of COVID-19 vaccine and its initial application, it is extremely necessary to discuss its ethical principles. Based on the bioethics theory and in accordance with relevant laws and regulations on vaccine use in China, this paper put forward the ethical principles of COVID-19 vaccine use, including safety principle, respect principle, fairness and justice principle, optimization principle and humanitarianism principle, which provided reference for scientifically formulating COVID-19 vaccination strategy and forming a group immune barrier to effectively control the epidemic situation in COVID-19. © 2022, Editorial department of Chinese Medical Ethics. All rights reserved.

Mechanistic Insights into a Rare Mutation in Nacad as a Possible Cause of Covid Orchitis

Objective: Aiming to uncover causal mechanisms of COVID-19 sequela outside of pulmonary symptomology, a recent study from our group identified a variant of the NACAD protein (120bp coding sequence deletion) associated with COVID-19 orchitis, a risk factor for male infertility. Interestingly, these patients had decreased ACE2 serum levels. NACAD is proposed to prevent inappropriate targeting of non-secreted peptides to the endoplasmic reticulum. We hypothesized that a defect in NACAD function/processing will decrease ACE2 serum levels by disrupting extracellular transport and endoplasmic reticulum interaction. We explored whether intracellular levels of ACE levels were altered and if cell membrane protein deposition was increased, which may result in more severe effects to SARS-CoV-2 infection. Material(s) and Method(s): We obtained testis biopsies from men undergoing sperm retrieval for infertility. After siRNA NACAD knockdown, we analyzed total ACE2 expression using Western blot and qPCR as well as immunofluorescence/H&E staining for co-localization (with NACAD). Membrane-anchored ACE2 (mACE2) levels were quantified using immunostaining and flowcytometry while secreted ACE2 (sACE2) was analyzed by ELISA and Western blot. Result(s): NACAD and ACE2 co-localize in both the Leydig and germ cells. When NACAD is knocked down, primary testes cells show 80% decreased mRNA and 50% total protein levels of ACE2. The secreted ACE2 was also reduced by nearly 50%. However, when we specifically measured the level of mACE2 on the cell surface, we found that the knockdown of NACAD did not lead to reduction. Conclusion(s): NACAD likely specifically affects the level of sACE2, which is speculated to act as a protection factor by retaining the virus in serum and reducing cellular entry. While the exact reason for the differential effects of NACAD on mACE2 and sACE2 remain unclear, our data is consistent to other studies, which found a reduction of total ACE2 expression and sACE2 in patients is coupled with worse outcomes in COVID-19. We hope that establishing a relationship between NACAD and ACE2 expression will prove useful not only to elucidate why some men with COVID develop orchitis but, ultimately, why some men develop multiorgan failure with COVID infection whereas most do not. Impact Statement: We expect that men with a history of orchitis and an increased level of ACE2 receptors will present with a higher and prolonged risk of impaired semen parameters. By identifying the impact of COVID-19 infection on male fertility, we can determine whether recommendations are warranted for sperm cryopreservation for men at high risk of contracting the infection, such as healthcare workers. Copyright © 2022

Emergency management in university students during coronavirus disease 2019 epidemics: West China urgent recommendation.

During the coronavirus disease 2019 (COVID-19) epidemics, universities take responsibility for the health of their students and epidemic control. Our urgent recommendation focuses on four key questions of emergency management in universities following rigorous evidence-based approaches and provides timely suggestions to university managers, academic faculties and student affairs managers. We recommend universities during the COVID-19 epidemics should: 1) suspend offline lectures;2) provide proper health education on the disease;3) encourage face masks, however oppose using N95 masks on the campus;4) encourage hand hygiene and provide sanitizing products on the campus. Copyright © 2020 West China University of Medical Science. All rights reserved.

Characteristics of PM2.5 concentration and water-soluble ions in the typical town of southern Gansu

In order to study the pollution levels of PM2.5 and water-soluble inorganic ions（WSIIs）in the towns of southern Gansu, PM2.5 samples were collected quarterly in Cheng County of Gansu from April 2019 to February 2020. Their characteristics of variation were analyzed, and the sources were apportioned using correlation and principal component analysis. The results showed that the mean annual mass concentration of PM2.5 was（57.2±26.9）μg·m-3 in Cheng County of Gansu Province. The seasonal variation of PM2.5 concentration was represented by winter>spring>autumn>summer during the sampling period, and the concentrations in winter were about 1.9 times than that in summer. The annually good air quality rate was 81%, of which 100% in summer. The ranking of WSII concentrations was SO42->NO3->Na+>NH4+>Ca2+>K+>Cl->Mg2+.SNA is the highest water-soluble ions, accounting for 70.1% of the concentration of eight main water-soluble ions. The mean ratio of ρ（NO3-）/ρ（SO42-）was 0.6, indicating that fixed sources such as industrial and agricultural production and fossil fuel combustion emissions, was the major source for particulate pollution. During the 2019 coronavirus epidemic, control measures had a significant impact on the concentration of PM2.5 and SNA in water-soluble ions, and the mean concentration of PM2.5 was reduced by 44.2%. Source apportionment showed that WSIIs in PM2.5 were mainly from fossil fuel combustion, biomass combustion, secondary formation and road construction dust, etc. © 2022 Science Press. All rights reserved.

<span contenteditable="false" data-cke-magic-line="1" style="width: 695px;height: 0px;padding: 0px;margin: 0px;display: block;z-index: 9999;color: rgb(255,255,255);font-size: 0px;line-height: 0px;position: absolute;border-top: 1px dashed rgb(255,0,0);user-select: none;left:-2px;top: 64.2px;"><span style="color:#ffffff"> </span><span style="color:#ffffff"> </span><span style="color:#ffffff">?</span></span>Estimating daily ground-level NO2 concentrations over China based on TROPOMI observations and machine learning approach

Nitrogen dioxide (NO2) is an important target for monitoring atmospheric quality. Deriving ground-level NO2 concentrations with much finer resolution, it requires high-resolution satellite tropospheric NO2 column as input and a reliable estimation algorithm. This paper aims to estimate the daily ground-level NO2 concentrations over China based on machine learning models and the TROPOMI NO2 data with high spatial resolution. In this study, four tree-based algorithm machine learning models, decision trees (DT), gradient boost decision tree (GBDT), random forest (RF) and extra-trees (ET), were used to estimate ground-level NO2 concentrations. In addition to considering many influencing factors of the ground-level NO2 concentrations, we especially introduced simplified temporal and spatial information into the estimation models. The results show that the extra-trees with spatial and temporal information (ST-ET) model has great performance in estimating ground-level NO2 concentrations with a cross-validation R-2 of 0.81 and RMSE of 3.45 mu g/m(3) in test datasets. The estimated results for 2019 based on the ST-ET model achieves a satisfactory accuracy with a cross-validation R-2 of 0.86 compared with the other models. Through time-space analysis and comparison, it was found that the estimated high-resolution results were consistent with the ground observed NO2 concentrations. Using data from January 2020 to test the prediction power of the models, the results indicate that the ST-ET model has a good performance in predicting ground-level NO2 concentrations. Taking four ground-level NO2 concentrations hotspots as examples, the estimated ground-level NO2 concentrations and ground-based observation data during the coronavirus disease (COVID-19) pandemic were lower compared with the same period in 2019. The findings offer a solid solution for accurately and efficiently estimating ground-level NO2 concentrations by using satellite observations, and provide useful information for improving our understanding of the regional atmospheric environment.