Comprehensive analysis of the gut microbiome and post-translational modifications elucidates the route involved in microbiota-host interactions.

The gut microbiome interacts with the host to maintain body homeostasis, with gut microbial dysbiosis implicated in many diseases. However, the underlying mechanisms of gut microbe regulation of host behavior and brain functions remain unclear. This study aimed to elucidate the influence of gut microbiota on brain functions via post-translational modification mechanisms in the presence or absence of bacteria without any stimulation. We conducted succinylome analysis of hippocampal proteins in germ-free (GF) and specific pathogen-free (SPF) mice and metagenomic analysis of feces from SPF mice. These results were integrated with previously reported hippocampal acetylome and phosphorylome data from the same batch of mice. Subsequent bioinformatics analyses revealed 584 succinylation sites on 455 proteins, including 54 up-regulated succinylation sites on 91 proteins and 99 down-regulated sites on 51 proteins in the GF mice compared to the SPF mice. We constructed a panoramic map of gut microbiota-regulated succinylation, acetylation, and phosphorylation, and identified cross-talk and relative independence between the different types of post-translational modifications in modulating complicated intracellular pathways. Pearson correlation analysis indicated that 13 taxa, predominantly belonging to the Bacteroidetes phylum, were correlated with the biological functions of post-translational modifications. Positive correlations between these taxa and succinylation and negative correlations between these taxa and acetylation were identified in the modulation of intracellular pathways. This study highlights the hippocampal physiological changes induced by the absence of gut microbiota, and proteomic quantification of succinylation, phosphorylation, and acetylation, contributing to our understanding of the role of the gut microbiome in brain function and behavioral phenotypes.

MRI radiomic features-based machine learning approach to classify ischemic stroke onset time.

PURPOSE: We aimed to investigate the ability of MRI radiomics features-based machine learning (ML) models to classify the time since stroke onset (TSS), which could aid in stroke assessment and treatment options. METHODS: This study involved 84 patients with acute ischemic stroke due to anterior circulation artery occlusion (51 in the training cohort and 33 in the independent test cohort). Region of infarct segmentation was manually outlined by 3D-slicer software. Image processing including registration, normalization and radiomics features calculation were done in R (version 3.6.1). A total of 4312 radiomic features from each image sequence were captured and used in six ML models to estimate stroke onset time for binary classification (≤ 4.5 h). Receiver-operating characteristic curve (ROC) and other parameters were calculated to evaluate the performance of the models in both training and test cohorts. RESULTS: Twelve radiomics and six clinic features were selected to construct the ML models for TSS classification. The deep learning model-based DWI/ADC radiomic features performed the best for binary TSS classification in the independent test cohort, with an AUC of 0.754, accuracy of 0.788, sensitivity of 0.952, specificity of 0.500, positive predictive value of 0.769, and negative predictive value of 0.857, respectively. Furthermore, adding clinical information did not improve the performance of the DWI/ADC-based deep learning model. The TSS prediction models can be visited at: http://123.57.65.199:3838/deeptss/ . CONCLUSIONS: A unique deep learning model based on DWI/ADC radiomic features was constructed for TSS classification, which could aid in decision making for thrombolysis in patients with unknown stroke onset.

The Pathogenesis of Aspergillus fumigatus, Host Defense Mechanisms, and the Development of AFMP4 Antigen as a Vaccine.

Aspergillus fumigatus is one of the ubiquitous fungi with airborne conidia, which accounts for most aspergillosis cases. In immunocompetent hosts, the inhaled conidia are rapidly eliminated. However, immunocompromised or immunodeficient hosts are particularly vulnerable to most Aspergillus infections and invasive aspergillosis (IA), with mortality from 50% to 95%. Despite the improvement of antifungal drugs over the last few decades, the therapeutic effect for IA patients is still limited and does not provide significant survival benefits. The drawbacks of antifungal drugs such as side effects, antifungal drug resistance, and the high cost of antifungal drugs highlight the importance of finding novel therapeutic and preventive approaches to fight against IA. In this article, we systemically addressed the pathogenic mechanisms, defense mechanisms against A. fumigatus, the immune response, molecular aspects of host evasion, and vaccines' current development against aspergillosis, particularly those based on AFMP4 protein, which might be a promising antigen for the development of anti-A. fumigatus vaccines.

A three serum miRNA panel as diagnostic biomarkers of radiotherapy-related metastasis in non-small cell lung cancer.

Serum microRNAs (miRNAs) have been implicated as noninvasive biomarkers for lung cancer diagnosis. However, there are no sensitive and specific biomarkers for the detection of radiotherapy-related non-small cell lung cancer (NSCLC) metastasis. The present study aimed to investigate the role of three serum miRNAs, namely miRNA (miR)-130a, miR-25 and miR-191*, in diagnosing NSCLC, and their biological functions in radiation-mediated development of metastatic properties in A549 cells. To determine this, serum samples were collected from 84 patients with NSCLC and 42 age- and sex-matched healthy controls. Differential expression of serum miRNAs was analyzed by quantitative PCR. Significant associations between miRNA expression and overall survival of patients with NSCLC were identified using the Cox proportional regression model. A receiver operating characteristic curve was generated to evaluate diagnostic accuracy. The functions of miR-130a, miR-25 and miR-191* in lung cancer cells were studied by transfecting A549 cells with miRNA mimics and inhibitors. The results of the present study demonstrated that the expression levels of miR-130a, miR-25 and miR-191* in the serum of patients with NSCLC were increased compared with those in healthy controls, and these increases were associated with advanced age (≥60 years), radiotherapy, histological type (squamous carcinoma), low survival rate and low median survival time. Additionally, irradiation induced the upregulation of miR-130a, miR-25 and miR-191* expression in A549 cells in vitro and in a xenograft mouse model. Irradiation also promoted the invasiveness of A549 cells in vitro and metastasis in vivo. In conclusion, miR-130a, miR-25 and miR-191* may be potential biomarkers for the diagnosis of patients with NSCLC and may serve oncogenic roles in radiation-mediated metastasis of NSCLC.