Mutations Associated With High-Grade irAEs in NSCLC Patients Receiving Immunotherapies.

OBJECTIVES: Compared to low-grade irAEs, high-grade irAEs are more often dose-limiting and can alter the long-term treatment options for a patient. Predicting the incidence of high-grade irAEs would help with treatment selection and therapeutic drug monitoring. MATERIALS AND METHODS: We performed a retrospective study of 430 stage III and IV patients with non-small cell lung cancer (NSCLC) who received an immune checkpoint inhibitor (ICI), either with or without chemotherapy, at a single comprehensive cancer center from 2015 to 2022. The study team retrieved sequencing data and complete clinical information, including detailed irAEs medical records. Fisher's exact test was used to determine the association between mutations and the presence or absence of high-grade irAEs. Patients were analyzed separately based on tumor subtypes and sequencing platforms. RESULTS: High-grade and low-grade irAEs occurred in 15.2% and 46.2% of patients, respectively. Respiratory and gastrointestinal irAEs were the 2 most common irAEs. The distribution of patients with or without irAEs was similar between ICI and ICI+chemotherapy-treated patients. By analyzing the mutation data, we identified 5 genes (MYC, TEK, FANCA, FAM123B, and MET) with mutations that were correlated with an increased risk of high-grade irAEs. For the adenocarcinoma subtype, mutations in TEK, MYC, FGF19, RET, and MET were associated with high-grade irAEs; while for the squamous subtype, ERBB2 mutations were associated with high-grade irAEs. CONCLUSION: This study is the first to demonstrate that specific tumor mutations correlate with the incidence of high-grade irAEs in patients with NSCLC treated with an ICI, providing molecular guidance for treatment selection and drug monitoring.

Bacillus coagulans and Clostridium butyricum synergistically alleviate depression in a chronic unpredictable mild stress mouse model through altering gut microbiota and prefrontal cortex gene expression.

Introduction: The prevalence of major depressive disorder (MDD) has gradually increased and has attracted widespread attention. The aim of this study was to investigate the effect of a probiotic compound consisting of Bacillus coagulans and Clostridium butyricum, on a mouse depression model. Methods: Mice were subjected to chronic unpredictable mild stress (CUMS) and then treated with the probiotics at different concentrations. And mice received behavior test such as forced swimming test and tail suspension test. After that, all mice were sacrificed and the samples were collected for analysis. Moreover, prefrontal cortex (PFC) gene expression and the gut microbiota among different groups were also analyzed. Results: Probiotics improved depressive-like behavior in CUMS mice, as indicated by decreased immobility time (p < 0.05) in the forced swimming test and tail suspension test. probiotics intervention also increased the level of 5-hydroxytryptamine (5-HT) in the prefrontal cortex and decreased the adrenocorticotropic hormone (ACTH) level in serum. In addition, by comparing the PFC gene expression among different groups, we found that the genes upregulated by probiotics were enriched in the PI3K-Akt signaling pathway in the prefrontal cortex. Moreover, we found that downregulated genes in prefrontal cortex of CUMS group such as Sfrp5 and Angpt2, which were correlated with depression, were reversed by the probiotics. Furthermore, the probiotics altered the structure of the gut microbiota, and reversed the reduction of cob(II)yrinate a,c-diamide biosynthesis I pathway in CUMS group. Several species like Bacteroides caecimuris and Parabacteroides distasoni, whose abundance was significantly decreased in the CUMS group but reversed after the probiotics intervention, showed significantly positive correlation with depression associated genes such as Tbxas1 and Cldn2. Discussion: These findings suggested that CUMS-induced depression-like behavior can be alleviated by the probiotics, possibly through alterations in the PFC gene expression and gut microbiota.

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation.

Prevalent Gene Regulatory Network (GRN) construction methods rely on generalized correlation analysis. However, in biological systems, regulation is essentially a causal relationship that cannot be adequately captured solely through correlation. Therefore, it is more reasonable to infer GRNs from a causal perspective. Existing causal discovery algorithms typically rely on Directed Acyclic Graphs (DAGs) to model causal relationships, but it often requires traversing the entire network, which result in computational demands skyrocketing as the number of nodes grows and make causal discovery algorithms only suitable for small networks with one or two hundred nodes or fewer. In this study, we propose the SLIVER (cauSaL dIscovery Via dimEnsionality Reduction) algorithm which integrates causal structural equation model and graph decomposition. SLIVER introduces a set of factor nodes, serving as abstractions of different functional modules to integrate the regulatory relationships between genes based on their respective functions or pathways, thus reducing the GRN to the product of two low-dimensional matrices. Subsequently, we employ the structural causal model (SCM) to learn the GRN within the gene node space, enforce the DAG constraint in the low-dimensional space, and guide each factor to aggregate various functions through cosine similarity. We evaluate the performance of the SLIVER algorithm on 12 real single cell transcriptomic datasets, and demonstrate it outperforms other 12 widely used methods both in GRN inference performance and computational resource usage. The analysis of the gene information integrated by factor nodes also demonstrate the biological explanation of factor nodes in GRNs. We apply it to scRNA-seq of Type 2 diabetes mellitus to capture the transcriptional regulatory structural changes of ß cells under high insulin demand.

TFTG: A comprehensive database for human transcription factors and their targets.

Transcription factors (TFs) are major contributors to gene transcription, especially in controlling cell-specific gene expression and disease occurrence and development. Uncovering the relationship between TFs and their target genes is critical to understanding the mechanism of action of TFs. With the development of high-throughput sequencing techniques, a large amount of TF-related data has accumulated, which can be used to identify their target genes. In this study, we developed TFTG (Transcription Factor and Target Genes) database (http://tf.liclab.net/TFTG), which aimed to provide a large number of available human TF-target gene resources by multiple strategies, besides performing a comprehensive functional and epigenetic annotations and regulatory analyses of TFs. We identified extensive available TF-target genes by collecting and processing TF-associated ChIP-seq datasets, perturbation RNA-seq datasets and motifs. We also obtained experimentally confirmed relationships between TF and target genes from available resources. Overall, the target genes of TFs were obtained through integrating the relevant data of various TFs as well as fourteen identification strategies. Meanwhile, TFTG was embedded with user-friendly search, analysis, browsing, downloading and visualization functions. TFTG is designed to be a convenient resource for exploring human TF-target gene regulations, which will be useful for most users in the TF and gene expression regulation research.

Oxidized sodium alginate hydrogel-mouse nerve growth factor sustained release system promotes repair of peripheral nerve injury.

In recent years, mouse nerve growth factor (mNGF) has emerged as an important biological regulator to repair peripheral nerve injury, but its systemic application is restricted by low efficiency and large dosage requirement. These limitations prompted us to search for biomaterials that can be locally loaded. Oxidized sodium alginate hydrogel (OSA) exhibits good biocompatibility and physicochemical properties, and can be loaded with drugs to construct a sustained-release system that can act locally on nerve injury. Here, we constructed a sustained-release system of OSA-mouse nerve growth factor (mNGF), and investigated the loading and release of the drug through Fourier transform infrared spectroscopy and drug release curves. In vitro and in vivo experiments showed that OSA-mNGF significantly promoted the biological activities of RSC-96 cells and facilitated the recovery from sciatic nerve crush injury in rats. This observation may be attributed to the additive effect of OSA on promoting Schwann cell biological activities or its synergistic effect of cross-activating phosphoinositide 3-kinase (PI3K) through extracellular signal regulated kinase (ERK) signaling. Although the specific mechanism of OSA action needs to be explored in the future, the current results provide a valuable preliminary research basis for the clinical application of the OSA-mNGF sustained-release system for nerve repair.

In situ monitoring of toxic effects of algal toxin on cells by a novel microfluidic flow cytometry instrument.

Algal toxins produced by microalgae, such as domoic acid (DA)1, have toxic effects on humans. However, toxicity tests using mice only yield lethal doses of algal toxins without providing insights into the mechanism of action on cells. In this study, a fast segmentation of microfluidic flow cytometry cell images based on the bidirectional background subtraction (BBS)2 method was developed to get the visual evidence of apoptosis in both bright-field and fluorescence images. This approach enables mapping of changes in cell morphology and activity under algal toxins, allowing for fast (within 60 s) and automated biological detection. By combining microfluidics with flow cytometry, the intricate cellular-level reaction process can be observed in micro samples of 293 T cells and mouse spleen cells, offering potential for future in vitro experiments.

SCInter: A comprehensive single-cell transcriptome integration database for human and mouse.

Single-cell RNA sequencing (scRNA-seq), which profiles gene expression at the cellular level, has effectively explored cell heterogeneity and reconstructed developmental trajectories. With the increasing research on diseases and biological processes, scRNA-seq datasets are accumulating rapidly, highlighting the urgent need for collecting and processing these data to support comprehensive and effective annotation and analysis. Here, we have developed a comprehensive Single-Cell transcriptome integration database for human and mouse (SCInter, https://bio.liclab.net/SCInter/index.php), which aims to provide a manually curated database that supports the provision of gene expression profiles across various cell types at the sample level. The current version of SCInter includes 115 integrated datasets and 1016 samples, covering nearly 150 tissues/cell lines. It contains 8016,646 cell markers in 457 identified cell types. SCInter enabled comprehensive analysis of cataloged single-cell data encompassing quality control (QC), clustering, cell markers, multi-method cell type automatic annotation, predicting cell differentiation trajectories and so on. At the same time, SCInter provided a user-friendly interface to query, browse, analyze and visualize each integrated dataset and single cell sample, along with comprehensive QC reports and processing results. It will facilitate the identification of cell type in different cell subpopulations and explore developmental trajectories, enhancing the study of cell heterogeneity in the fields of immunology and oncology.

Encapsulation of CsPb2Br5 in TiO2 Microcrystals to Enhance Environmental Stability.

All-inorganic lead halide perovskite has emerged as an attractive semiconducting material due to its unique optoelectronic properties. However, its poor environmental stability restricts its broad application. Here, a simple method for the fabrication of CsPb2Br5/TiO2 is investigated. The introduction of p-aminobenzoic acid, which has two functional groups, is critical for the capping of amorphous TiO2 on CsPb2Br5. After calcination at 300 °C, amorphous TiO2 crystallizes into the anatase phase. The CsPb2Br5/TiO2 NCs show high long-term stability in water and enhanced stability against ultraviolet radiation and heat treatment, owing to the chemical stability of TiO2. More importantly, photo-electrochemical characterizations indicate that the formation of TiO2 shells can increase the charge separation efficiency. Hence, CsPb2Br5/TiO2 exhibits improved photoelectric activity owing to the electrical conductivity of the TiO2 in water. This study provides a new route for the fabrication of optoelectronic devices and photocatalysts based on perovskite NCs in the aqueous phase. Furthermore, the present results demonstrate that CsPb2Br5/TiO2 NCs has considerable potential to be used as a photoelectric material in optical sensing and monitoring.

Characteristics of the Gut Microbiota in Young Adults with Autism Spectrum Disorder.

BACKGROUND: Although the characteristics of the gut microbiota of children with autism spectrum disorder (ASD) have been well studied, those of young adults with ASD have seldom been reported. METHODS: Using 16S rRNA gene sequencing, we characterized the gut microbiota of 19 young adults with ASD and compared them with that of 19 healthy adults. A random forest prediction model was used to distinguish between the two groups at the genus level. RESULTS: The abundance levels of one phylum, seven families, and 18 genera in adults with ASD were significantly different from those of controls. The genus Phascolarctobacterium was significantly enriched in adults with ASD, which might elicit ASD-like behavior through production of propionate. In addition, a random forest model identified 15 genera that could distinguish adults with ASD from healthy controls with areas under the receiver operating curve of 92.86%, and ten of them were biomarkers identified by LEfSe. CONCLUSIONS: Our results identified specific gut bacteria associated with ASD, and the successful application of certain genera in the prediction model further supports the association between gut microbiota and ASD.