Apparent Risks of Postural Orthostatic Tachycardia Syndrome Diagnoses After COVID-19 Vaccination and SARS-Cov-2 Infection.

Postural orthostatic tachycardia syndrome (POTS) has been previously described after SARS-CoV-2 infection; however, limited data is available on the relation of POTS with COVID-19 vaccination. Here we show in a cohort of 284,592 COVID-19 vaccinated individuals using a sequence-symmetry analysis, that the odds of POTS are higher 90 days after vaccine exposure than 90 days prior to exposure, and that the odds for POTS are higher than referent conventional primary care diagnoses, but lower than the odds of new POTS diagnosis after SARS-CoV-2 infection. Our results identify a possible association between COVID-19 vaccination and incidence of POTS. Notwithstanding the probable low incidence of POTS after COVID-19 vaccination, particularly when compared to SARS-Cov-2 post-infection odds which were five times higher, our results suggest that further studies, are needed to investigate the incidence and etiology of POTS occurring after COVID-19 vaccination.

Exploring the knowledge, attitudes, behaviors and training needs of obstetric and gynecological nurses regarding COVID-19 during the peak period of the pandemic in middle-risk areas of China: A cross-sectional study.

Background: COVID-19 has become a global pandemic, which necessitates that health workers be capable of protecting themselves and their patients. This article aimed to describe knowledge levels, attitudes, behaviors and training needs regarding COVID-19 among obstetric and gynecological nurses in medium-risk areas during the pandemic. Method: A cross-sectional survey of obstetric and gynecological nurses in medium-risk areas was performed during the peak period of the pandemic in China. The main survey tool was the self-designed COVID-19 Knowledge, Attitude, Behavior and Training Needs Questionnaire. Pearson correlation analysis was conducted to analyze the relationships among knowledge, attitudes, behaviors and training needs. Results: A total of 599 nurses were recruited, of whom 27.7% failed the knowledge part of the questionnaire. Positive correlations were found between knowledge and attitudes (r = 0.100, P = 0.015) and between attitudes and behaviors (r = 0.352, P = 0.000) regarding occupational protection against COVID-19. A total of 88.5% of nurses preferred online training to traditional training, and more than 70% believed that demonstration of and training in operations by their own department were effective ways to learn about how to protect themselves against COVID-19. Conclusion: The higher the level of knowledge about the disease was, the more positive the attitude toward occupational protection, and consequently, the more actively protective behaviors were adopted. Training affected nurses' knowledge of COVID-19 occupational protection and promoted positive attitudes, which further facilitated the effective prevention and control of the disease. Online training with demonstrations are recommended for COVID-19 training of nurses.

The Development of a Counseling Service Questionnaire: Study of Validation and Reliability

The study developed items of a counseling service questionnaire to aid counselors and universities in supporting students ' mental health. The participants of this study were 1,022 Chinese college students from three universities in Thailand. The questionnaire included development items and content validity and reliability testing. The questionnaire contained 17 items covering four aspects: (1) developmental counseling;(2) adaptive counseling;(3) disorder counseling;and (4) intervention in psychological crises. The results showed that the counseling services questionnaire is a valid and reliable instrument that can be used to determine students' mental health.

How mentally healthy we are during the pandemic? Findings from changed travel behavior

Background Many people changed their travel behavior during the coronavirus pandemic with more telecommuting, fewer trip frequencies, and less use of transit and ride-hailing to avoid infection. The lack of outdoor activities may result in social isolation and then trigger anxiety or depressive symptoms. Research objective This study examines the relationship between anxiety and depression, and correlates various sociodemographic, income, job status, health-related factors, and travel behavior changes in six large U.S. cities. Data U.S. Census Household Pulse Survey Phases 3.0 and 3.1 are employed. Method GAD-2 and PHQ-2 are used to screen the scores of anxiety and depression. The synthetic minority oversampling technique is applied to correct sample distribution. The multivariate mixed model is employed to examine relationships. Results (1) Anxiety and depression are positively correlated, and the percentage of high anxiety is greater than the percentage of high depression. (2) The levels of anxiety and depression significantly vary across the six cities. (3) Women, young, singles, and white people have higher levels of anxiety and depression during the pandemic. (4) People who are willing to receive vaccination tend to have higher levels of anxiety and depression. (5) The prevalence of depressive disorders is significantly lower in the high-income group. (6) People who applied for unemployment insurance and experienced expense difficulties are more likely to suffer high levels of anxiety and depression. (7) Travel behavior changes, measured by increased telecommuting, reduced trip frequency, and reduced use of transit and ride-hailing, all suggest positive correlations with anxiety and depression. Conclusions More assistance and attention should be given to women, singles, and low-income households to reduce the prevalence of mental stress in vulnerable groups. Telecommuting can be but need to work with other travel demand management strategies. Travel and outdoor activities should be promoted under the new normal.

How mentally healthy we are during the pandemic? Findings from changed travel behavior.

Background: Many people changed their travel behavior during the coronavirus pandemic with more telecommuting, fewer trip frequencies, and less use of transit and ride-hailing to avoid infection. The lack of outdoor activities may result in social isolation and then trigger anxiety or depressive symptoms. Research objective: This study examines the relationship between anxiety and depression, and correlates various sociodemographic, income, job status, health-related factors, and travel behavior changes in six large U.S. cities. Data: U.S. Census Household Pulse Survey Phases 3.0 and 3.1 are employed. Method: GAD-2 and PHQ-2 are used to screen the scores of anxiety and depression. The synthetic minority oversampling technique is applied to correct sample distribution. The multivariate mixed model is employed to examine relationships. Results: (1) Anxiety and depression are positively correlated, and the percentage of high anxiety is greater than the percentage of high depression. (2) The levels of anxiety and depression significantly vary across the six cities. (3) Women, young, singles, and white people have higher levels of anxiety and depression during the pandemic. (4) People who are willing to receive vaccination tend to have higher levels of anxiety and depression. (5) The prevalence of depressive disorders is significantly lower in the high-income group. (6) People who applied for unemployment insurance and experienced expense difficulties are more likely to suffer high levels of anxiety and depression. (7) Travel behavior changes, measured by increased telecommuting, reduced trip frequency, and reduced use of transit and ride-hailing, all suggest positive correlations with anxiety and depression. Conclusions: More assistance and attention should be given to women, singles, and low-income households to reduce the prevalence of mental stress in vulnerable groups. Telecommuting can be but need to work with other travel demand management strategies. Travel and outdoor activities should be promoted under the new normal.

Infection with wild-type SARS-CoV-2 elicits broadly neutralizing and protective antibodies against omicron subvariants.

The omicron variants of SARS-CoV-2 have substantial ability to escape infection- and vaccine-elicited antibody immunity. Here, we investigated the extent of such escape in nine convalescent patients infected with the wild-type SARS-CoV-2 during the first wave of the pandemic. Among the total of 476 monoclonal antibodies (mAbs) isolated from peripheral memory B cells, we identified seven mAbs with broad neutralizing activity to all variants tested, including various omicron subvariants. Biochemical and structural analysis indicated the majority of these mAbs bound to the receptor-binding domain, mimicked the receptor ACE2 and were able to accommodate or inadvertently improve recognition of omicron substitutions. Passive delivery of representative antibodies protected K18-hACE2 mice from infection with omicron and beta SARS-CoV-2. A deeper understanding of how the memory B cells that produce these antibodies could be selectively boosted or recalled can augment antibody immunity against SARS-CoV-2 variants.

Hand-powered centrifugal micropipette-tip with distance-based quantification for on-site testing of SARS-CoV-2 virus.

This paper proposed a hand-powered centrifugal micropipette-tip strategy, termed HCM, for all-in-one immunoassay combined with a distance-based readout for portable quantitative detection of SARS-CoV-2. The target SARS-CoV-2 virus antigen triggers the binding of multiple monoclonal antibody-coated red latex nanobeads, forming larger complexes. Following incubation and centrifugation, the formed aggregated complexes settle at the bottom of the tip, while free red nanobeads remain suspended in the solution. The HCM enables sensitive (1 ng/mL) and reliable quantification of SARS-CoV-2 within 25 min. With the advantages of free washing, free fabrication, free instrument, and without the optical device, the proposed low-cost and easy-to-use HCM immunoassay shows great potential for quantitative POC diagnostics for SARS-CoV-2.

Integrative Modeling and Analysis of the Interplay Between Epidemic and News Propagation Processes (preprint)

The COVID-19 pandemic has witnessed the role of online social networks (OSNs) in the spread of infectious diseases. The rise in severity of the epidemic augments the need for proper guidelines, but also promotes the propagation of fake news-items. The popularity of a news-item can reshape the public health behaviors and affect the epidemic processes. There is a clear inter-dependency between the epidemic process and the spreading of news-items. This work creates an integrative framework to understand the interplay. We first develop a population-dependent `saturated branching process' to continually track the propagation of trending news-items on OSNs. A two-time scale dynamical system is obtained by integrating the news-propagation model with SIRS epidemic model, to analyze the holistic system. It is observed that a pattern of periodic infections emerges under a linear behavioral influence, which explains the waves of infection and reinfection that we have experienced in the pandemic. We use numerical experiments to corroborate the results and use Twitter and COVID-19 data-sets to recreate the historical infection curve using the integrative model.

Nanopore membrane chip-based isolation method for metabolomic analysis of plasma small extracellular vesicles from COVID-19 survivors.

Multiple studies showed that metabolic disorders play a critical role in respiratory infectious diseases, including COVID-19. Metabolites contained in small extracellular vesicles (sEVs) are different from those in plasma at the acute stage, while the metabolic features of plasma sEVs of COVID-19 survivors remain unknown. Here, we used a nanopore membrane-based microfluidic chip for plasma sEVs separation, termed ExoSEC, and compared the sEVs obtained by UC, REG, and ExoSEC in terms the time, cost, purity, and metabolic features. The results indicated the ExoSEC was much less costly, provided higher purity by particles/proteins ratio, and achieved 205-fold and 2-fold higher sEVs yield, than UC and REG, respectively. Moreover, more metabolites were identified and several signaling pathways were significantly enriched in ExoSEC-sEVs compared to UC-sEVs and REG-sEVs. Furthermore, we detected 306 metabolites in plasma sEVs using ExoSEC from recovered asymptomatic (RA), moderate (RM), and severe/critical COVID-19 (RS) patients without underlying diseases 3 months after discharge. Our study demonstrated that COVID-19 survivors, especially RS, experienced significant metabolic alteration and the dysregulated pathways mainly involved fatty acid biosynthesis, phenylalanine metabolism, etc. Metabolites of the fatty acid biosynthesis pathway bore a significantly negative association with red blood cell counts and hemoglobin, which might be ascribed to hypoxia or respiratory failure in RM and RS but not in RA at the acute stage. Our study confirmed that ExoSEC could provide a practical and economical alternative for high throughput sEVs metabolomic study.

Systematic pan-cancer analysis identifies cGAS as an immunological and prognostic biomarker.

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes novel coronavirus disease 2019 (COVID-19), which is characterized by pneumonia, cytokine storms, and lymphopenia. Due to immunosuppression, cancer patients may be more susceptible to SARS-CoV-2 and have more serious complications. According to recent research, cyclic GMP-AMP synthase (cGAS) could be a potential SARS-CoV-2 sensor. However, at present, no studies have been conducted on cGAS gene alterations in pan-cancer. This study aimed to discover therapeutic implications for COVID-19-infected tumor patients by performing a comprehensive analysis of cGAS in malignant tumors. Methods: cGAS expression matrices were obtained from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases, which were used to evaluate cGAS expression in various tumors, its prognostic value, and its relationship to the immune microenvironment, microsatellite instability (MSI), immune neoantigens, gene mutations, immune checkpoints, MSI, tumor mutational burden (TMB), mismatch repair (MMR) genes, and DNA methyltransferases (DNMT). We also used the cBioPortal, Human Protein Atlas (HPA), and GeneMANIA databases to explore the types of changes, gene networks and immunofluorescence localization, and protein expression of these genes. Results: Compared to normal tissues, cGAS was highly expressed in 13 types of cancer (e.g., lung cancer) and lowly expressed in other cancers (e.g., pancreatic cancer). cGAS expression was associated with prognosis in nine cancers, such as renal clear cell carcinoma (P<0.05). Furthermore, deep deletion was the most common type of cGAS genomic mutation. DNMT, immune infiltration levels, TMB, MSI, MMR genes, neoantigens, and immune checkpoints were all correlated with cGAS expression. Moreover, we used the GSE30589 dataset to investigate the post-SARS-CoV infection changes in cGAS expression in vitro. Finally, mithramycin, MI219, AFP464, aminoflavone, kahalide F, AT13387, doxorubicin, and other drugs increased the sensitivity of cGAS expression. According to the evidence presented above, cGAS may become an important target for cancer therapy. Conclusions: This study discovered that SARS-CoV-2-infected cancer patients might experience changes in their tumor environment as a result of cGAS, making patients with tumors expressing high cGAS more susceptible to COVID-19 and possibly a worsening prognosis. Furthermore, cGAS may be a novel biomarker for diagnosing and treating COVID-19-infected tumor patients.

Knowledge Adaptive Multi-Way Matching Network for Biomedical Named Entity Recognition via Machine Reading Comprehension.

Rapid and effective utilization of biomedical literature is paramount to combat diseases like COVID19. Biomedical named entity recognition (BioNER) is a fundamental task in text mining that can help physicians accelerate knowledge discovery to curb the spread of the COVID-19 epidemic. Recent approaches have shown that casting entity extraction as the machine reading comprehension task can significantly improve model performance. However, two major drawbacks impede higher success in identifying entities (1) ignoring the use of domain knowledge to capture the context beyond sentences and (2) lacking the ability to deeper understand the intent of questions. In this paper, to remedy this, we introduce and explore external domain knowledge which cannot be implicitly learned in text sequence. Previous works have focused more on text sequence and explored little of the domain knowledge. To better incorporate domain knowledge, a multi-way matching reader mechanism is devised to model representations of interaction between sequence, question and knowledge retrieved from Unified Medical Language System (UMLS). Benefiting from these, our model can better understand the intent of questions in complex contexts. Experimental results indicate that incorporating domain knowledge can help to obtain competitive results across 10 BioNER datasets, achieving absolute improvement of up to 2.02% in the f1 score.

Higher SARS-CoV-2 shedding in exhaled aerosol probably contributed to the enhanced transmissibility of Omicron BA.5 subvariant.

The global pandemic of the BA.5 subvariant had moved from prediction to reality. In this study, we compared SARS-CoV-2 aerosol emissions from patients with BA.2 or BA.5 subvariant infection. First, patients with BA.2 subvariant infection had higher upper respiratory viral loads than patients with BA.5 subvariant infection. However, the average breath emission rate (BER) of patients with BA.5 subvariant infection, which represented the concentration of exhaled SARS-CoV-2 aerosols, was nearly 40 times higher than that of patients with BA.2 subvariant. Second, aerosols exhaled by patients with BA.5 subvariant infection exhibited SARS-CoV-2 RNA detection positive rate than patients with BA.1 or BA.2 subvariant infection. Meanwhile, for BA.5 subvariant infection, patients that exhaled infectious SARS-CoV-2 aerosols accounted for 14.8% of all patients. Third, since the onset of COVID-19, the SARS-CoV-2 RNA detection signals of throat swabs showed a gradual decline trend, although the decline process was accompanied by fluctuations. Overall, the monitoring of infectious SARS-CoV-2 aerosols may provide the data support for the transmissibility evaluation of the Omicron BA.5 subvariant. This article is protected by copyright. All rights reserved.

The Impact of Urban Facilities on Crime during the Pre- and Pandemic Periods: A Practical Study in Beijing.

The measures in the fight against COVID-19 have reshaped the functions of urban facilities, which might cause the associated crimes to vary with the occurrence of the pandemic. This paper aimed to study this phenomenon by conducting quantitative research. By treating the area under the jurisdiction of the police station (AJPS) as spatial units, the residential burglary and non-motor vehicle theft that occurred during the first-level response to the public health emergencies (pandemic) period in 2020 and the corresponding temporal window (pre-pandemic) in 2019 were collected and a practical study to Beijing was made. The impact of urban facilities on crimes during both periods was analyzed independently by using negative binomial regression (NBR) and geographical weight regression (GWR). The findings demonstrated that during the pandemic period, a reduction in the count and spatial concentration of both property crimes were observed, and the impact of facilities on crime changed. Some facilities lost their impact on crime during the pandemic period, while other facilities played a significant role in generating crime. Additionally, the variables that always kept a stable significant impact on crime during the pre- and pandemic periods demonstrated a heterogeneous impact in space and experienced some variations across the periods. The study proved that the strategies in the fight against COVID-19 changed the impact of urban facilities on crime occurrence, which deeply reshaped the crime patterns.

Chinese expert consensus on intestinal microecology and management of digestive tract complications related to tumor treatment (version 2022).

The human gut microbiota represents a complex ecosystem that is composed of bacteria, fungi, viruses, and archaea. It affects many physiological functions including metabolism, inflammation, and the immune response. The gut microbiota also plays a role in preventing infection. Chemotherapy disrupts an organism's microbiome, increasing the risk of microbial invasive infection; therefore, restoring the gut microbiota composition is one potential strategy to reduce this risk. The gut microbiome can develop colonization resistance, in which pathogenic bacteria and other competing microorganisms are destroyed through attacks on bacterial cell walls by bacteriocins, antimicrobial peptides, and other proteins produced by symbiotic bacteria. There is also a direct way. For example, Escherichia coli colonized in the human body competes with pathogenic Escherichia coli 0157 for proline, which shows that symbiotic bacteria compete with pathogens for resources and niches, thus improving the host's ability to resist pathogenic bacteria. Increased attention has been given to the impact of microecological changes in the digestive tract on tumor treatment. After 2019, the global pandemic of novel coronavirus disease 2019 (COVID-19), the development of novel tumor-targeting drugs, immune checkpoint inhibitors, and the increased prevalence of antimicrobial resistance have posed serious challenges and threats to public health. Currently, it is becoming increasingly important to manage the adverse effects and complications after chemotherapy. Gastrointestinal reactions are a common clinical presentation in patients with solid and hematologic tumors after chemotherapy, which increases the treatment risks of patients and affects treatment efficacy and prognosis. Gastrointestinal symptoms after chemotherapy range from nausea, vomiting, and anorexia to severe oral and intestinal mucositis, abdominal pain, diarrhea, and constipation, which are often closely associated with the dose and toxicity of chemotherapeutic drugs. It is particularly important to profile the gastrointestinal microecological flora and monitor the impact of antibiotics in older patients, low immune function, neutropenia, and bone marrow suppression, especially in complex clinical situations involving special pathogenic microbial infections (such as clostridioides difficile, multidrug-resistant Escherichia coli, carbapenem-resistant bacteria, and norovirus).

Lymphocyte-C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission.

In this study, we aimed to explore whether lymphocyte-C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Merging microfluidics with luminescence immunoassays for urgent point-of-care diagnostics of COVID-19.

The Coronavirus disease 2019 (COVID-19) outbreak has urged the establishment of a global-wide rapid diagnostic system. Current widely-used tests for COVID-19 include nucleic acid assays, immunoassays, and radiological imaging. Immunoassays play an irreplaceable role in rapidly diagnosing COVID-19 and monitoring the patients for the assessment of their severity, risks of the immune storm, and prediction of treatment outcomes. Despite of the enormous needs for immunoassays, the widespread use of traditional immunoassay platforms is still limited by high cost and low automation, which are currently not suitable for point-of-care tests (POCTs). Microfluidic chips with the features of low consumption, high throughput, and integration, provide the potential to enable immunoassays for POCTs, especially in remote areas. Meanwhile, luminescence detection can be merged with immunoassays on microfluidic platforms for their good performance in quantification, sensitivity, and specificity. This review introduces both homogenous and heterogenous luminescence immunoassays with various microfluidic platforms. We also summarize the strengths and weaknesses of the categorized methods, highlighting their recent typical progress. Additionally, different microfluidic platforms are described for comparison. The latest advances in combining luminescence immunoassays with microfluidic platforms for POCTs of COVID-19 are further explained with antigens, antibodies, and related cytokines. Finally, challenges and future perspectives were discussed.

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

Preclinical characterization of amubarvimab and romlusevimab, a pair of non-competing neutralizing monoclonal antibody cocktail, against SARS-CoV-2

Monoclonal antibodies (mAbs) targeting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have demonstrated clinical efficacy in preventing or treating coronavirus disease 2019 (COVID-19), resulting in the emergency use authorization (EUA) for several SARS-CoV-2 targeting mAb by regulatory authority. However, the continuous virus evolution requires diverse mAb options to combat variants. Here we describe two fully human mAbs, amubarvimab (BRII-196) and romlusevimab (BRII-198) that bind to non-competing epitopes on the receptor binding domain (RBD) of spike protein and effectively neutralize SARS-CoV-2 variants. A YTE modification was introduced to the fragment crystallizable (Fc) region of both mAbs to prolong serum half-life and reduce effector function. The amubarvimab and romlusevimab combination retained activity against most mutations associated with reduced susceptibility to previously authorized mAbs and against variants containing amino acid substitutions in their epitope regions. Consistently, the combination of amubarvimab and romlusevimab effectively neutralized a wide range of viruses including most variants of concern and interest in vitro. In a Syrian golden hamster model of SARS-CoV-2 infection, animals receiving combination of amubarvimab and romlusevimab either pre- or post-infection demonstrated less weight loss, significantly decreased viral load in the lungs, and reduced lung pathology compared to controls. These preclinical findings support their development as an antibody cocktail therapeutic option against COVID-19 in the clinic.

Comparison of demographic features and laboratory parameters between COVID-19 deceased patients and surviving severe and critically ill cases.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been far more devastating than expected, showing no signs of slowing down at present. Heilongjiang Province is the most northeastern province of China, and has cold weather for nearly half a year and an annual temperature difference of more than 60ºC, which increases the underlying morbidity associated with pulmonary diseases, and thus leads to lung dysfunction. The demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province, China with such climatic characteristics are still not clearly illustrated. AIM: To illustrate the demographic features and laboratory parameters of COVID-19 deceased patients in Heilongjiang Province by comparing with those of surviving severe and critically ill cases. METHODS: COVID-19 deceased patients from different hospitals in Heilongjiang Province were included in this retrospective study and compared their characteristics with those of surviving severe and critically ill cases in the COVID-19 treatment center of the First Affiliated Hospital of Harbin Medical University. The surviving patients were divided into severe group and critically ill group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (the seventh edition). Demographic data were collected and recorded upon admission. Laboratory parameters were obtained from the medical records, and then compared among the groups. RESULTS: Twelve COVID-19 deceased patients, 27 severe cases and 26 critically ill cases were enrolled in this retrospective study. No differences in age, gender, and number of comorbidities between groups were found. Neutrophil percentage (NEUT%), platelet (PLT), C-reactive protein (CRP), creatine kinase isoenzyme (CK-MB), serum troponin I (TNI) and brain natriuretic peptides (BNP) showed significant differences among the groups (P = 0.020, P = 0.001, P < 0.001, P = 0.001, P < 0.001, P < 0.001, respectively). The increase of CRP, D-dimer and NEUT% levels, as well as the decrease of lymphocyte count (LYMPH) and PLT counts, showed significant correlation with death of COVID-19 patients (P = 0.023, P = 0.008, P = 0.045, P = 0.020, P = 0.015, respectively). CONCLUSION: Compared with surviving severe and critically ill cases, no special demographic features of COVID-19 deceased patients were observed, while some laboratory parameters including NEUT%, PLT, CRP, CK-MB, TNI and BNP showed significant differences. COVID-19 deceased patients had higher CRP, D-dimer and NEUT% levels and lower LYMPH and PLT counts.