Mental health disparities between physicians and nurses: Analyzing the impact of occupational stress and work environment fitness using random forest algorithm.

BACKGROUND: The impact of occupational stress and work environment fitness on mental health disparities between physicians and nurses are not well understood. This study aims to identify and rank key determinants of mental health in physicians and nurses in China and compare the differences in their impact on mental health between physicians and nurses. METHODS: A large cross-sectional survey with multistage cluster sampling was conducted. The survey included the Self-Rating Anxiety Scale (SAS Scale), the Center for Epidemiologic Studies Depression Scale (CES-D Scale), the Maslach Burnout Inventory-General Survey (MBI-GS) and the Person-Environment (PE) Fit. We applied a principled, machine learning-based variable selection algorithm, using random forests, to identify and rank the determinants of the mental health in physicians and nurses. RESULTS: In our study, we analyzed a sample of 9964 healthcare workers, and 2729 (27 %) were physicians. The prevalence of anxiety and depressive disorders among physicians and nurses was 31.0 % and 53.3 %, 30.8 % and 47.9 %, respectively. Among physicians with anxiety disorder, we observed a higher likelihood of cynicism, emotional exhaustion, reduced personal accomplishment, and poor organization fitness, job fitness, group fitness, and supervisor fitness, in order of importance. When comparing the effects on depressive disorder in physicians, group fitness and supervisor fitness did not have significant impacts. For nurses, emotional exhaustion had a more significant effect on depressive disorder compared to cynicism. Supervisor fitness did not have a significant impact on anxiety disorder in nurses. LIMITATIONS: Cross-sectional design, self-reporting screening scales. CONCLUSIONS: Compared to individual and hospital characteristics, the primary factors influencing mental health disorders are occupational burnout and the compatibility of the work environment. Additionally, the key determinants of depressive and anxiety disorders among doctors and nurses exhibit slight variations. Employing machine learning methods proves beneficial for identifying determinants of mental health disorders among physicians and nurses in China. These findings could help improve policymaking aimed at addressing the mental well-being of healthcare professionals.

Evaluation of an identification method for the SARS-CoV-2 Delta variant based on the amplification-refractory mutation system.

The Delta variant of SARS-CoV-2 dominated the COVID-19 pandemic due to its high viral replication capacity and immune evasion, causing massive outbreaks of cases, hospitalizations, and deaths. Currently, variant identification is performed mainly by sequencing. However, the high requirements for equipment and operators as well as its high cost have limited its application in underdeveloped regions. To achieve an economical and rapid method of variant identification suitable for undeveloped areas, we applied an amplification-refractory mutation system (ARMS) based on PCR for the detection of novel coronavirus variants. The results showed that this method could be finished in 90 min and detect as few as 500 copies/mL and not react with SARS-Coronavirus, influenza A H1N1(2009), and other cross-pathogens or be influenced by fresh human blood, α- interferon, and other interfering substances. In a set of double-blind trials, tests of 262 samples obtained from patients confirmed with Delta variant infection revealed that our method was able to accurately identify the Delta variant with high sensitivity and specificity. In conclusion, the ARMS-PCR method applied in Delta variant identification is rapid, sensitive, specific, economical, and suitable for undeveloped areas. In our future study, ARMS-PCR will be further applied in the identification of other variants, such as Omicron.

Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory.

BACKGROUND: The global COVID-19 pandemic has been widely regarded as a catalyst for adopting internet health care technology (IHT) in China. IHT consists of new health care technologies that are shaping health services and medical consultations. Health care professionals play a substantial role in the adoption of any IHT, but the consequences of doing so can often be challenging, particularly when employee burnout is prevalent. Few studies have explored whether employee burnout influences the adoption intention of IHT in health care professionals. OBJECTIVE: This study aims to explain the determinants influencing the adoption of IHT from the perspective of health care professionals. To do so, the study extends the value-based adoption model (VAM) with consideration for employee burnout as a determining factor. METHODS: A cross-sectional web-based survey using a sample of 12,031 health care professionals selected through multistage cluster sampling from 3 provinces in mainland China was conducted. The hypotheses of our research model were developed based on the VAM and employee burnout theory. Structural equation modeling was then used to test the research hypotheses. RESULTS: The results indicate that perceived usefulness, perceived enjoyment, and perceived complexity positively correlate with perceived value (ß=.131, P=.01; ß=.638, P<.001; ß=.198, P<.001, respectively). Perceived value had a positive direct effect on adoption intention (ß=.725, P<.001), perceived risk negatively correlated with perceived value (ß=-.083, P<.001), and perceived value negatively correlated with employee burnout (ß=-.308, P<.001). In addition, employee burnout was negatively related to adoption intention (ß=-.170, P<.001) and mediated the relationship between perceived value and adoption intention (ß=.052, P<.001). CONCLUSIONS: Perceived value, perceived enjoyment, and employee burnout were the most important determinants of IHT adoption intention by health care professionals. In addition, while employee burnout was negatively related to adoption intention, perceived value inhibited employee burnout. Therefore, this study finds that it is necessary to develop strategies to improve the perceived value and reduce employee burnout, which will benefit the promotion of the adoption intention of IHT in health care professionals. This study supports the use of the VAM and employee burnout in explaining health care professionals' adoption intention regarding IHT.

Development and validity of computerized neuropsychological assessment devices for screening mild cognitive impairment: Ensemble of models with feature space heterogeneity and retrieval practice effect.

OBJECTIVE: This study aimed to develop and validate computerized neuropsychological assessment devices for screening patients with mild cognitive impairment (MCI). METHODS: We conducted this study in three phases. Phase I involved the development of a conceptual framework of Memory Guard (MG) based on the principles of the cognitive design system (CDS). Phase II involved three steps of feature engineering: item development, filter, and wrapper. Based on the initial items, the number of items in each dimension was determined through analytic hierarchy process. We constructed an initial set with a total of 198 items with three levels of difficulty. Next, we performed feature selection through comprehensive reliability and validity tests, which resulted in the best item bank of 38 test items. The features for modeling were obtained from the best item bank (option scores, reading time scores and total time scores), demographic variables and their MoCA groups. Regarding the heterogeneity of the feature space, we combined the AdaBoost with the Naive Bayes classification algorithm as the decision model of MG. For the screening tool to be used repeatedly, the retrieval practice effect was considered in the design. Phase III involved the validation of measuring instruments. The features incorporated into the modeling process were optimized based on the classification accuracy and area under curve. We also verified the classification effect of the other three classification models with MG. RESULTS: After three steps of feature engineering, a total of 6 dimensions of cognitive areas were included in MG: orientation, memory, attention, calculation, recall, and language & executive function. 38 features were included in the model (17 features of option score, 20 features of time score, and 1 demographic feature). A total of 333 individuals from two communities in Shanghai and Henan province were included in the measuring instrument verification process. Women accounted for 68.2% of the sample. The median age was 63. 15.3% of the participants had bachelor's degrees or above and 111 participants lived in urban areas (33.3%). The results showed that MG had an accuracy of 93.75% and AUC of 0.923, with a sensitivity of 91.67% and a specificity of 95.45%. Compared to the other three classification models, MG that combined the AdaBoost with the Naive Bayes classification algorithm was the most accurate classifier. CONCLUSIONS: MG was proved to be reliable and valid in early screening for patients with MCI. MG that integrated heterogeneous features such as demography, option scores, and time scores had a better predictive performance for screening MCI.

SARS-CoV-2 detection using quantum dot fluorescence immunochromatography combined with isothermal amplification and CRISPR/Cas13a.

The development of reliable, sensitive, and fast devices for the diagnosis of COVID-19 is of great importance in the pandemic of the new coronavirus. Here, we proposed a new principle of analysis based on a combination of reverse transcription and isothermal amplification of a fragment of the gene encoding the S protein of the SARS-CoV-2 and the CRISPR/Cas13a reaction for cleavage of the specific probe. As a result, the destroyed probe cannot be detected on an immunochromatographic strip using quantum fluorescent dots. Besides, the results can be obtained by an available and inexpensive portable device. By detecting SARS-CoV-2 negative (n = 25) and positive (n = 62) clinical samples including throat swabs, sputum and anal swabs, the assay showed good sensitivity and specificity of the method and could be completed within 1 h without complicated operation and expensive equipment. These superiorities showed its potential for fast point-of-care screening of SARS-CoV-2 during the outbreak, especially in remote and underdeveloped areas with limited equipment and resources.

Fingolimod Potentiates the Antifungal Activity of Amphotericin B.

Candida albicans (C. albicans) is an opportunistic human fungal pathogen that can cause severe infection in clinic. Its incidence and mortality rate has been increasing rapidly. Amphotericin B (AMB), the clinical golden standard antifungal agent, has severe side effects that limit its clinical application. Thus, lowering the concentration and increasing the efficacy of AMB in a combinatorial antifungal therapy have been pursued by both industry and academia. Here we identify that fingolimod (FTY720), an immunomodulatory drug used for oral treatment of relapsing-remitting multiple sclerosis, can potentiate the efficacy of AMB against C. albicans growth synergistically. Furthermore, we observe an antifungal efficacy of FTY720 in combination with AMB against diverse fungal pathogens. Intriguingly, cells treated with both drugs are hypersensitive to endothelial endocytosis and macrophage killing. This is later found to be due to the hyperaccumulation of reactive oxygen species and the corresponding increase in activities of superoxide dismutase and catalase in the cells that received combinatorial treatment. Therefore, the combination of AMB and FTY720 provides a promising antifungal strategy.

Dengue Specific Immunoglobulin A Antibody is Present in Urine and Associated with Disease Severity.

The kinetics of dengue virus (DENV)-specific IgA antibody in urine and the potential correlation with disease severity remain elusive. In this study, 262 serial urine samples from 78 laboratory-confirmed patients were assayed by a commercial immunoglobulin A (IgA) kit against DENV. All cases were classified into dengue fever (DF) and severe dengue (SD) according to the 2009 WHO/TDR guideline. The total positive rate of IgA in urine was 59%. DENV-specific IgA was detected in urine from day 2 to day 13 after the onset of illness in DF patients; While for SD patients, anti-DENV IgA could be detected till day 14. The positive rate of IgA in patients with secondary infection was higher than that in patients with primary infection. Importantly, during 4-7 days after the onset of illness, the IgA positive rate of SD patients was significantly higher than that of DF patients. Especially, the intensity of IgA signal in SD patients was obviously stronger than that in DF patient at the recovery stage. Overall, our results suggested that the existence of DENV-specific IgA antibodies in urine might be a warning sign for the severity of disease and its measurement might provide valuable guidance for proper patient management.

A novel reporter system for neutralizing and enhancing antibody assay against dengue virus.

BACKGROUND: Dengue virus (DENV) still poses a global public health threat, and no vaccine or antiviral therapy is currently available. Antibody plays distinct roles in controlling DENV infections. Neutralizing antibody is protective against DENV infection, whereas sub-neutralizing concentration of antibody can increase DENV infection, termed antibody-dependent enhancement (ADE). Plaque-based assay represents the most widely accepted method measuring neutralizing or enhancing antibodies. RESULTS: In this study, a novel reporter virus-based system was developed for measuring neutralization and ADE activity. A stable Renilla luciferase reporter DENV (Luc-DENV) that can produce robust luciferase signals in BHK-21 and K562 cells were used to establish the assay and validated against traditional plaque-based assay. Luciferase value analysis using various known DENV-specific monoclonal antibodies showed good repeatability and a well linear correlation with conventional plaque-based assays. The newly developed assay was finally validated with clinical samples from infected animals and individuals. CONCLUSIONS: This reporter virus-based assay for neutralizing and enhancing antibody evaluation is rapid, lower cost, and high throughput, and will be helpful for laboratory detection and epidemiological investigation for DENV antibodies.

Identification and characterization of a linearized B-cell epitope on the pr protein of dengue virus.

The four serotypes of dengue virus (DENV) represent one of the major mosquito-borne pathogens globally; so far no vaccine or specific antiviral is available. During virion maturation, the pr protein is cleaved from its precursor form the prM protein on the surface of immature DENV by host protease. Recent findings have demonstrated that the pr protein not only played critical roles in virion assembly and maturation, but was also involved in antibody-dependent enhancement of DENV infection. However, the B-cell epitopes on the pr protein of DENV have not been well characterized. In this study, a set of 11 partially overlapping peptides spanning the entire pr protein of DENV-2 were fused with glutathione S-transferase and expressed in Escherichia coli. ELISA screening with murine hyperimmune antiserum against immature DENV identified the P8 peptide (57KQNEPEDIDCWCNST7¹) in the pr protein as the major immunodominant epitope. Fine mapping by truncated protein assays confirmed the 8-e peptide 57KQNEPEDI64 was the smallest unit capable of antibody binding. Importantly, the 8-e epitope reacted with sera from dengue fever patients. Site-directed mutagenesis revealed the asparagine residue at position 59 was important for epitope recognition. The 8-e epitope coincided well with the B-cell epitopes predicted by Immune Epitope Database analysis, and 3D structural modelling mapped the 8-e peptide on the surface of prM-E heterodimers. Overall, our findings characterized a linearized B-cell epitope on the pr protein of DENV, which will help to understand the life cycle of DENV and pathogenesis of dengue infections in human.

Complete genome sequence of dengue virus serotype 2 Cosmopolitan genotype strain in Guangdong, China.

Here we report the complete genome sequence of a dengue virus serotype 2 (DENV-2) strain, GZ40, isolated in Guangdong, China, in 2010. A phylogenetic analysis classified GZ40 into the Cosmopolitan genotype, while previous Chinese DENV-2 isolates belong to the Asian I genotype. The reemergence of the Cosmopolitan genotype of DENV-2 in China deserves further investigation.

A single nucleotide mutation in NS2A of Japanese encephalitis-live vaccine virus (SA14-14-2) ablates NS1' formation and contributes to attenuation.

Japanese encephalitis (JE) remains the leading cause of viral encephalitis in the Asia-Pacific region, and the live vaccine SA14-14-2 is currently recommended by WHO and widely used in Asian countries with a good safety and efficacy profile. In this study, we demonstrated that SA14-14-2 failed to produce NS1', the larger NS1-related protein, compared with its parental strain SA14 in various cells. Sequence analysis and secondary structure prediction identified a single silent mutation G66A in the NS2A-coding region of SA14-14-2 destabilized the conserved pseudoknot structure, which was associated with a -1 ribosomal frame shift event. Using reverse genetic technology and animal study, we provided solid evidence that this single silent mutation G66A in the NS2A gene abolished the production of NS1' in vitro and reduced neurovirulence and neuroinvasiveness in mice. These findings provide critical information in understanding the molecular mechanism of JE vaccine attenuation and is critical for JE vaccine quality control.