Mental health and psychosocial problems among laboratory technicians in response to the COVID-19 pandemic in Hebei, China.

Objective: During the coronavirus disease 2019 (COVID-19) pandemic, an increased mental burden has been widely reported among medical health workers such as physicians and nurses. However, data on laboratory technicians exposed to COVID-19 have rarely been published. The aim of this study was to assess the magnitude of psychological symptoms among laboratory technicians and analyze potential risk factors associated with these symptoms. Methods: A cross-sectional online survey was performed via the Wenjuanxing platform (a professional online questionnaire platform) (https://www.wjx.cn/mobile/statnew.aspx) to investigate the mental health of laboratory technicians during the COVID-19 pandemic in Hebei, China from October 4, 2021, to November 3, 2021. The online questionnaire included demographic and occupational characteristics data of responders, and the Symptom Check List-90-Revised (SCL90-R)was used to quantify the magnitude of psychological symptoms among laboratory technicians. Participants' demographic and occupational characteristics were analyzed using descriptive statistical analyses. Chi-square tests were applied to compare the severity of each symptom between two or more groups. A binary logistic regression model was developed to identify the predictors of laboratory technicians' mental health in response to the COVID-19 pandemic, and outcomes are presented as odds ratios and 95% confidence interval. Statistical analysis was performed using SPSS version 21 (SPSS, New Orchard Road, Armonk, New York, USA). Results: A total of 3081 valid questionnaires were collected. Of these 3081 participants, 338 (11.0%) reported a total SCL90-R score >160, which indicated positive psychological symptoms. Among the 338 participants who reported psychological problems, most of them were mild symptoms. Several factors associated with mental health problems in laboratory technicians during COVID-19 were found, which include a history of physical and/or psychological problems (all 10 symptoms p < 0.001), more than 10 years of work experience (depression symptoms: OR = 2.350, p = 0.024; anxiety symptoms: OR = 2.642, p = 0.038), frontline work (depression symptoms: OR = 1.761, p = 0.001; anxiety symptoms: OR = 2.619, p < 0.001; hostility symptoms: OR = 1.913, p = 0.001), participant in more than 3 times large-scale SARS-CoV-2 screenings and more than 36 h per week in SARS-CoV-2 nucleic acid testing. Conclusion: A portion of laboratory technicians reported experiencing varying levels of psychological burden. During the COVID-19 pandemic, multiple interventions should be developed and implemented to address existing psychosocial challenges and promote the mental health of laboratory technicians.

Single-cell transcriptome profiling of the immune space-time landscape reveals dendritic cell regulatory program in polymicrobial sepsis.

Rationale: Evident immunosuppression has been commonly seen among septic patients, and it is demonstrated to be a major driver of morbidity. Nevertheless, a comprehensive view of the host immune response to sepsis is lacking as the majority of studies on immunosuppression have focused on a specific type of immune cells. Methods: We applied multi-compartment, single-cell RNA sequencing (scRNA-seq) to dissect heterogeneity within immune cell subsets during sepsis progression on cecal ligation and puncture (CLP) mouse model. Flow cytometry and multiplex immunofluorescence tissue staining were adopted to identify the presence of 'mature DCs enriched in immunoregulatory molecules' (mregDC) upon septic challenge. To explore the function of mregDC, sorted mregDC were co-cultured with naïve CD4+ T cells. Intracellular signaling pathways that drove mregDC program were determined by integrating scRNA-seq and bulk-seq data, combined with inhibitory experiments. Results: ScRNA-seq analysis revealed that sepsis induction was associated with substantial alterations and heterogeneity of canonical immune cell types, including T, B, natural killer (NK), and myeloid cells, across three immune-relevant tissue sites. We found a unique subcluster of conventional dendritic cells (cDCs) that was characterized by specific expression of maturation- and migration-related genes, along with upregulation of immunoregulatory molecules, corresponding to the previously described 'mregDCs' in cancer. Flow cytometry and in stiu immunofluorescence staining confirmed the presence of sepsis-induced mregDC at protein level. Functional experiments showed that sepsis-induced mregDCs potently activated naive CD4+ T cells, while promoted CD4+ T cell conversion to regulatory T cells. Further observations indicated that the mregDC program was initiated via TNFRSF-NF-κB- and IFNGR2-JAK-STAT3-dependent pathways within 24 h of septic challenge. Additionally, we confirmed the detection of mregDC in human sepsis using publicly available data from a recently published single-cell study of COVID-19 patients. Conclusions: Our study generates a comprehensive single-cell immune landscape for polymicrobial sepsis, in which we identify the significant alterations and heterogeneity in immune cell subsets that take place during sepsis. Moreover, we find a conserved and potentially targetable immunoregulatory program within DCs that associates with hyperinflammation and organ dysfunction early following sepsis induction.

Advanced Genetic Methodologies in Tracking Evolution and Spread of SARS-CoV-2.

A newly emerged coronavirus, SARS-CoV-2, caused severe pneumonia outbreaks in China in December 2019 and has since spread to various countries around the world. Here, we describe genetic methods to trace the evolution route and probe the transmission dynamics of this virus.

Evaluation of Antibody Response to SARS-CoV-2 mRNA-1273 Vaccination in Patients With Cancer in Florida.

Importance: Patients with cancer experience high rates of morbidity and mortality after SARS-CoV-2 infection. Immune response to mRNA-1273 vaccination across multiple cancer types and treatments remains to be established. Objective: To quantitate antibody responses after mRNA-1273 vaccination among patients with solid tumors and hematologic cancer and to assess clinical and treatment factors associated with vaccine response. Design, Setting, and Participants: This cohort study included patients with cancer who were aged 18 years or older, spoke English or Spanish, had received their first mRNA-1273 dose between January 12 and 25, 2021, and agreed to blood tests before and after vaccination. Exposures: Receipt of 1 and 2 mRNA-1273 SARS-CoV-2 vaccine doses. Main Outcomes and Measures: Seroconversion after each vaccine dose and IgG levels against SARS-CoV-2 spike protein obtained immediately before the first and second vaccine doses and 57 days (plus or minus 14 days) after the first vaccine dose. Cancer diagnoses and treatments were ascertained by medical record review. Serostatus was assessed via enzyme-linked immunosorbent assay. Paired t tests were applied to examine days 1, 29, and 57 SARS-CoV-2 antibody levels. Binding antibody IgG geometric mean titers were calculated based on log10-transformed values. Results: The 515 participants were a mean (SD) age of 64.5 (11.4) years; 262 (50.9%) were women; and 32 (6.2%) were Hispanic individuals and 479 (93.0%) White individuals; race and ethnicity data on 4 (0.7%) participants were missing. Seropositivity after vaccine dose 2 was 90.3% (465; 95% CI, 87.4%-92.7%) among patients with cancer, was significantly lower among patients with hematologic cancer (84.7% [255]; 95% CI, 80.1%-88.6%) vs solid tumors (98.1% [210]; 95% CI, 95.3%-99.5%), and was lowest among patients with lymphoid cancer (70.0% [77]; 95% CI, 60.5%-78.4%). Patients receiving a vaccination within 6 months after anti-CD20 monoclonal antibody treatment had a significantly lower seroconversion (6.3% [1]; 95% CI, 0.2%-30.2%) compared with those treated 6 to 24 months earlier (53.3% [8]; 95% CI, 26.6%-78.7%) or those who never received anti-CD20 treatment (94.2% [456]; 95% CI, 91.7%-96.1%). Low antibody levels after vaccination were observed among patients treated with anti-CD20 within 6 months before vaccination (GM, 15.5 AU/mL; 95% CI, 9.8-24.5 AU/mL), patients treated with small molecules (GM, 646.7 AU/mL; 95% CI, 441.9-946.5 AU/mL), and patients with low lymphocyte (GM, 547.4 AU/mL; 95% CI, 375.5-797.7 AU/mL) and IgG (GM, 494.7 AU/mL; 95% CI, 304.9-802.7 AU/mL) levels. Conclusions and Relevance: This cohort study found that the mRNA-1273 SARS-CoV-2 vaccine induced variable antibody responses that differed by cancer diagnosis and treatment received. These findings suggest that patients with hematologic cancer and those who are receiving immunosuppressive treatments may need additional vaccination doses.

Early Fever Is Associated With Clinical Outcomes in Patients With Coronavirus Disease.

Fever is one of the typical symptoms of coronavirus disease (COVID-19). We aimed to investigate the association between early fever (EF) and clinical outcomes in COVID-19 patients. A total of 1,014 COVID-19 patients at the Leishenshan Hospital were enrolled and classified into the EF and non-EF groups based on whether they had fever within 5 days of symptom onset. Risk factors for clinical outcomes in patients with different levels of disease severity were analyzed using multivariable analyses. Time from symptom onset to symptom alleviation, CT image improvement, and discharge were longer for patients with moderate and severe disease in the EF group than in the non-EF group. Multivariable analysis showed that sex, EF, eosinophil number, C-reactive protein, and IL-6 levels were positively correlated with the time from symptom onset to hospital discharge in moderate cases. The EF patients showed no significant differences in the development of acute respiratory distress syndrome, compared with the non-EF patients. The Kaplan-Meier curve showed no obvious differences in survival between the EF and non-EF patients. However, EF patients with increased temperature showed markedly lower survival than the non-EF patients with increased temperature. EF had no significant impact on the survival of critically ill patients, while an increase in temperature was identified as an independent risk factor. EF appears to be a predictor of longer recovery time in moderate/severe COVID-19 infections. However, its value in predicting mortality needs to be considered for critically ill patients with EF showing increasing temperature.

Post-COVID-19 Epidemic: Allostatic Load among Medical and Nonmedical Workers in China.

BACKGROUND: As the fight against the COVID-19 epidemic continues, medical workers may have allostatic load. OBJECTIVE: During the reopening of society, medical and nonmedical workers were compared in terms of allostatic load. METHODS: An online study was performed; 3,590 Chinese subjects were analyzed. Socio-demographic variables, allostatic load, stress, abnormal illness behavior, global well-being, mental status, and social support were assessed. RESULTS: There was no difference in allostatic load in medical workers compared to nonmedical workers (15.8 vs. 17.8%; p = 0.22). Multivariate conditional logistic regression revealed that anxiety (OR = 1.24; 95% CI 1.18-1.31; p < 0.01), depression (OR = 1.23; 95% CI 1.17-1.29; p < 0.01), somatization (OR = 1.20; 95% CI 1.14-1.25; p < 0.01), hostility (OR = 1.24; 95% CI 1.18-1.30; p < 0.01), and abnormal illness behavior (OR = 1.49; 95% CI 1.34-1.66; p < 0.01) were positively associated with allostatic load, while objective support (OR = 0.84; 95% CI 0.78-0.89; p < 0.01), subjective support (OR = 0.84; 95% CI 0.80-0.88; p < 0.01), utilization of support (OR = 0.80; 95% CI 0.72-0.88; p < 0.01), social support (OR = 0.90; 95% CI 0.87-0.93; p < 0.01), and global well-being (OR = 0.30; 95% CI 0.22-0.41; p < 0.01) were negatively associated. CONCLUSIONS: In the post-COVID-19 epidemic time, medical and nonmedical workers had similar allostatic load. Psychological distress and abnormal illness behavior were risk factors for it, while social support could relieve it.

Genetic cluster analysis of SARS-CoV-2 and the identification of those responsible for the major outbreaks in various countries.

A newly emerged coronavirus, SARS-CoV-2, caused severe pneumonia outbreaks in China in December 2019 and has since spread to various countries around the world. To trace the evolution route and probe the transmission dynamics of this virus, we performed phylodynamic analysis of 247 high quality genomic sequences available in the GISAID platform as of 5 March 2020. Among them, four genetic clusters, defined as super-spreaders (SSs), could be identified and were found to be responsible for the major outbreaks that subsequently occurred in various countries. SS1 was widely disseminated in Asia and the US, and mainly responsible for outbreaks in the states of Washington and California as well as South Korea, whereas SS4 contributed to the pandemic in Europe. Using the signature mutations of each SS as markers, we further analysed 1539 genome sequences reported after 29 February 2020 and found that 90% of these genomes belonged to SSs, with SS4 being the most dominant. The relative degree of contribution of each SS to the pandemic in different continents was also depicted. Identification of these super-spreaders greatly facilitates development of new strategies to control the transmission of SARS-CoV-2.