Current status and continuing medical education need for general practitioners in Tibet, China: a cross-sectional study.

BACKGROUND: The Tibetan area is one of China's minority regions with a shortage of general practice personnel, which requires further training and staffing. This research helps to understand the current condition and demand for general practitioner (GP) training in Tibetan areas and to provide a reference for promoting GP education and training. METHODS: We conducted a cross-sectional survey using stratified sampling targeting 854 GPs in seven cities within the Tibetan Autonomous Region, utilizing an online questionnaire. Achieving a high response rate of 95.1%, 812 GPs provided invaluable insights. Our meticulously developed self-designed questionnaire, available in both Chinese and Tibetan versions, aimed to capture a wide array of data encompassing basic demographics, clinical skills, and specific training needs of GPs in the Tibetan areas. Prior to deployment, the questionnaire underwent rigorous development and refinement processes, including expert consultation and pilot testing, to ensure its content validity and reliability. In our analysis, we employed descriptive statistics to present the characteristics and current training needs of GPs in the Tibetan areas. Additionally, chi-square tests were utilized to examine discrepancies in training needs across various demographic groups, such as age, job positions, and educational backgrounds of the participating GPs. RESULTS: The study was completed by 812 (812/854, 95.1%) GPs, of whom 62.4% (507/812) were female. The top three training needs were hypertension (81.4%, 661/812), pregnancy management (80.7%, 655/812), and treatment of related patient conditions and events (80.5%, 654/812). Further research shows that the training required by GPs of different ages in "puncturing, catheterization, and indwelling gastric tube use" (64.6% vs. 54.8%, p = 9.5 × 10- 6) varies statistically. GPs in various positions have different training needs in "community-based chronic disease prevention and management" (76.6% vs. 63.9%, p = 0.009). The training needs of GPs with different educational backgrounds in "debridement, suturing, and fracture fixation" (65.6% vs. 73.2%, p = 0.027) were also statistically significant. CONCLUSIONS: This study suggests the need for targeted continuing medical education activities and for updating training topics and content. Course developers must consider the needs of GPs, as well as the age, job positions, and educational backgrounds of GPs practicing in the Tibetan Plateau region. TRIAL REGISTRATION: Not applicable.

Knowledge graph analytics platform with LINCS and IDG for Parkinson's disease target illumination.

BACKGROUND: LINCS, "Library of Integrated Network-based Cellular Signatures", and IDG, "Illuminating the Druggable Genome", are both NIH projects and consortia that have generated rich datasets for the study of the molecular basis of human health and disease. LINCS L1000 expression signatures provide unbiased systems/omics experimental evidence. IDG provides compiled and curated knowledge for illumination and prioritization of novel drug target hypotheses. Together, these resources can support a powerful new approach to identifying novel drug targets for complex diseases, such as Parkinson's disease (PD), which continues to inflict severe harm on human health, and resist traditional research approaches. RESULTS: Integrating LINCS and IDG, we built the Knowledge Graph Analytics Platform (KGAP) to support an important use case: identification and prioritization of drug target hypotheses for associated diseases. The KGAP approach includes strong semantics interpretable by domain scientists and a robust, high performance implementation of a graph database and related analytical methods. Illustrating the value of our approach, we investigated results from queries relevant to PD. Approved PD drug indications from IDG's resource DrugCentral were used as starting points for evidence paths exploring chemogenomic space via LINCS expression signatures for associated genes, evaluated as target hypotheses by integration with IDG. The KG-analytic scoring function was validated against a gold standard dataset of genes associated with PD as elucidated, published mechanism-of-action drug targets, also from DrugCentral. IDG's resource TIN-X was used to rank and filter KGAP results for novel PD targets, and one, SYNGR3 (Synaptogyrin-3), was manually investigated further as a case study and plausible new drug target for PD. CONCLUSIONS: The synergy of LINCS and IDG, via KG methods, empowers graph analytics methods for the investigation of the molecular basis of complex diseases, and specifically for identification and prioritization of novel drug targets. The KGAP approach enables downstream applications via integration with resources similarly aligned with modern KG methodology. The generality of the approach indicates that KGAP is applicable to many disease areas, in addition to PD, the focus of this paper.

Multiomics Analysis Reveals Aberrant Metabolism and Immunity Linked Gut Microbiota with Insomnia.

Studies have confirmed that insomnia is related to gut microbiota. Previous research suggests that immunity and metabolism are also associated with insomnia. However, to our knowledge, the integration of these factors has not been investigated in insomnia. Here, we explored the correlations across gut microbiota, serum metabolism, and inflammatory factors in insomnia. Our results showed that the composition and structure of gut microbiota and metabolism in insomnia patients were different from healthy controls. Compared to healthy controls, the relative abundances of Lactobacillus, Streptococcus, and Lactobacillus crispatus were significantly increased in insomniacs. There were five metabolic pathways in insomniacs (glycerophospholipid metabolism; glutathione metabolism; nitrogen metabolism; alanine, aspartate, and glutamate metabolism; aminoacyl-tRNA biosynthesis) significantly different between the two groups. Moreover, we found that IL-1ß levels were significantly higher in insomnia patients while TNF-α was significantly reduced. We further identified that the changes in the level of IL-1ß and TNF-α were associated with some specific bacteria and metabolites, such as Prevotella amnii, Prevotella buccalis, Prevotella timonensis, and Prevotella colorans. Mediation analysis further determined that the immune factors and metabolites could mediate the relationship between gut microbes and insomnia. IMPORTANCE Our study indicated that systematic inflammation and metabolites might be a pathway linking the gut microbiome with insomnia. These findings provide new insights and a better understanding of gut microbiota's role in insomnia as well as potential novel microbiome-related etiologies for insomnia.

Molecular characterization and antibiotic resistance of Acinetobacter baumannii in cerebrospinal fluid and blood.

The increasing prevalence of carbapenem-resistant Acinetobacter baumannii (CRAB) caused nosocomial infections generate significant comorbidity and can cause death among patients. Current treatment options are limited. These infections pose great difficulties for infection control and clinical treatment. To identify the antimicrobial resistance, carbapenemases and genetic relatedness of Acinetobacter baumannii isolates from cerebrospinal fluid (CSF) and blood, a total of 50 nonrepetitive CSF isolates and 44 blood isolates were collected. The resistance phenotypes were determined, and polymerase chain reaction (PCR) was performed to examine the mechanisms of carbapenem resistance. Finally, multilocus sequence typing (MLST) was conducted to determine the genetic relatedness of these isolates. It was observed that 88 of the 94 collected isolates were resistant to imipenem or meropenem. Among them, the blaOXA-23 gene was the most prevalent carbapenemase gene, with an observed detection rate of 91.5% (86/94), followed by the blaOXA-24 gene with a 2.1% detection rate (2/94). Among all carbapenem-resistant Acinetobacter baumannii (CRAB) observations, isolates with the blaOXA-23 gene were resistant to both imipenem and meropenem. Interestingly, isolates positive for the blaOXA-24 gene but negative for the blaOXA-23 gene showed an imipenem-sensitive but meropenem-resistant phenotype. The MLST analysis identified 21 different sequence types (STs), with ST195, ST540 and ST208 most frequently detected (25.5%, 12.8% and 11.7%, respectively). 80 of the 94 isolates (85.1%) were clustered into CC92 which showed a carbapenem resistance phenotype (except AB13). Five novel STs were detected, and most of them belong to CRAB. In conclusion, these findings provide additional observations and epidemiological data of CSF and blood A. baumannii strains, which may improve future infection-control measures and aid in potential clinical treatments in hospitals and other clinical settings.

Gut microbiota and diabetes: From correlation to causality and mechanism.

In this review, we summarize the recent microbiome studies related to diabetes disease and discuss the key findings that show the early emerging potential causal roles for diabetes. On a global scale, diabetes causes a significant negative impact to the health status of human populations. This review covers type 1 diabetes and type 2 diabetes. We examine promising studies which lead to a better understanding of the potential mechanism of microbiota in diabetes diseases. It appears that the human oral and gut microbiota are deeply interdigitated with diabetes. It is that simple. Recent studies of the human microbiome are capturing the attention of scientists and healthcare practitioners worldwide by focusing on the interplay of gut microbiome and diabetes. These studies focus on the role and the potential impact of intestinal microflora in diabetes. We paint a clear picture of how strongly microbes are linked and associated, both positively and negatively, with the fundamental and essential parts of diabetes in humans. The microflora seems to have an endless capacity to impact and transform diabetes. We conclude that there is clear and growing evidence of a close relationship between the microbiota and diabetes and this is worthy of future investments and research efforts.