Background: Modification of the gut microbiota has been reported to reduce the incidence of type 1 diabetes mellitus (T1D). We hypothesized that the gut microbiota shifts might also have an effect on cognitive functions in T1D. Herein we used a non-absorbable antibiotic vancomycin to modify the gut microbiota in streptozotocin (STZ)-induced T1D mice and studied the impact of microbial changes on cognitive performances in T1D mice and its potential gut-brain neural mechanism.Results: We found that vancomycin exposure disrupted the gut microbiome, altered host metabolic phenotypes, and facilitated cognitive impairment in T1D mice. Long-term acetate deficiency due to depletion of acetate-producing bacteria resulted in the reduction of synaptophysin (SYP) in the hippocampus as well as learning and memory impairments. Exogenous acetate supplement or fecal microbiota transplant recovered hippocampal SYP level in vancomycin-treated T1D mice, and this effect was attenuated by vagal inhibition or vagotomy.Conclusions: Our results demonstrate the protective role of microbiota metabolite acetate in cognitive functions and suggest long-term acetate deficiency as a risk factor of cognitive decline.

Background: To evaluate the diagnostic value of metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) in immunocompromised patients for the diagnosis of suspected pneumonia in comparison with that of conventional microbiological tests (CMTs). Methods: Sixty-nine immunocompromised patients with suspected pneumonia received both CMTs and mNGS of BALF were analyzed retrospectively. The diagnostic value was compared between CMTs and mNGS, using the clinical composite diagnosis as the reference standard. Results: Sixty patients were diagnosed of pneumonia including fifty-two patients with identified pathogens and eight patients with probable pathogens. Taking the composite reference standard as a gold standard, 42 pathogens were identified by CMTs including nine bacteria, 17 fungi, 8 virus, 6 Mycobacterium Tuberculosis, and two Legionella and 19(45%) of which were detected by BALF culture. As for mNGS, it identified 76 pathogens including 20 bacteria, 31 fungi, 14 virus, 5 Mycobacterium Tuberculosis, four Legionella and two Chlamydia psittaci. The overall detection rate of mNGS for pathogens were higher than that of CMTs. However, a comparable diagnostic accuracy of mNGS and CMTs were found for bacterial and viral infections. mNGS exhibited a higher diagnostic accuracy for fungal detection than CMTs (78% vs. 57%, P < 0.05), which mainly because of the high sensitivity of mNGS in patients with Pneumocystis jirovecii pneumonia (PJP) (100% vs. 28%, P < 0.05). Nineteen patients were identified as pulmonary co-infection, mNGS test showed a higher detection rate and broader spectrum for pathogen detection than that of CMTs in co-infection. Moreover, Pneumocystis jirovecii was the most common pathogen in co-infection and mNGS have identified much more co-pathogens of PJP than CMTs. Conclusions: mNGS of BALF improved the microbial detection rate of pathogens and exhibited remarkable advantages in detecting PJP and identifying co-infection in immunocompromised patients.

Under the background of “innovation and entrepreneurship,” how to scientifically and rationally choose employment or independent entrepreneurship according to their own comprehensive situation is of great significance to the planning and development of their own career and the social adaptation of university personnel training. This study aims to develop an adaptive support vector machine framework, called RF‐CSCA‐SVM, for predicting college students′ entrepreneurial intention in advance; that is, students choose to start a business or find a job after graduation. RF‐CSCA‐SVM combines random forest (RF), support vector machine (SVM), sine cosine algorithm (SCA), and chaotic local search. In this framework, RF is used to select the most important factors; SVM is employed to establish the relationship model between the factors and the students’ decision to choose to start their own business or look for jobs. SCA is used to tune the optimal parameters for SVM. Additionally, chaotic local search is utilized to enhance the search capability of SCA. A total of 300 students were collected to develop the predictive model. To validate the developed method, other four meta‐heuristic based SVM methods were used for comparison in terms of classification accuracy, Matthews Correlation Coefficients (MCC), sensitivity, and specificity. The experimental results demonstrate that the proposed method can be regarded as a promising success with the excellent predictive performance. Promisingly, the established adaptive SVM framework might serve as a new candidate of powerful tools for entrepreneurial intention prediction.

BRAF mutations occur in 2–4% non-small cell lung cancer (NSCLC) patients and can be categorized into three functional classes based on signaling mechanism and kinase activity: RAS-independent kinase-activating V600 monomers (class 1), RAS-independent kinase-activating dimers (class 2) and RAS-dependent kinase-inactivating heterodimers (class 3). The association between functional classes and clinical features in Chinese NSCLC patients remains unexplored. Our multi-center study aimed to survey the BRAF mutation rate and analyze the associated clinical features in this population. Capture-based sequencing data of either plasma or tissue samples obtained from 8405 Chinese stage I–IV NSCLC patients were retrospectively analyzed. BRAF mutations were detected in 238 patients, revealing an overall mutation rate of 2.8%. Among them, 32%, 21% and 13% had BRAF mutant class 1, 2 and 3 respectively. The remaining 34% had other BRAF mutations. V600 (32%) and G469 (13%) were the two most predominant BRAF mutations. Patients with class 2 and 3 mutations were more likely to have concurrent KRAS mutations (P = 0.001). Collectively, BRAF mutations, including non-class 1–3 mutations, were more likely to occur in males (P < 0.01). However, females were more likely to harbor class 1 mutations (P < 0.02). We also compared the overall survival (OS) of first-line chemotherapy-treated advanced-stage patients and revealed comparable OS among the three groups. Our study revealed a 2.8% BRAF mutation rate in Chinese NSCLC patients. Our data also showed a male predominance when all BRAF mutations were considered collectively, and a female predominance for class 1 mutations. Furthermore, BRAF V600E is less likely to have concurrent KRAS mutations comparing to the other two classes.