Nuclei Isolation from Ocular Tissues of the Embryonic Chicken for Single-Nucleus Profiling.

The generation of quality data from a single-nucleus profiling experiment requires nuclei to be isolated from tissues in a gentle and efficient manner. Nuclei isolation must be carefully optimized across tissue types to preserve nuclear architecture, prevent nucleic acid degradation, and remove unwanted contaminants. Here, we present an optimized workflow for generating a single-nucleus suspension from ocular tissues of the embryonic chicken that is compatible with various downstream workflows. The described protocol enables the rapid isolation of a high yield of aggregate-free nuclei from the embryonic chicken eye without compromising nucleic acid integrity, and the nuclei suspension is compatible with single-nucleus RNA and ATAC sequencing. We detail several stopping points, either via cryopreservation or fixation, to enhance workflow adaptability. Further, we provide a guide through multiple QC points and demonstrate proof-of-principle using two commercially available kits. Finally, we demonstrate that existing in silico genotyping methods can be adopted to computationally derive biological replicates from a single pool of chicken nuclei, greatly reducing the cost of biological replication and allowing researchers to consider sex as a variable during analysis. Together, this tutorial represents a cost-effective, simple, and effective approach to single-nucleus profiling of embryonic chicken eye tissues and is likely to be easily modified to be compatible with similar tissue types.

Experimental Framework for Assessing Mouse Retinal Regeneration Through Single-Cell RNA-Sequencing.

Retinal degenerative diseases including age-related macular degeneration and glaucoma are estimated to currently affect more than 14 million people in the United States, with an increased prevalence of retinal degenerations in aged individuals. An expanding aged population who are living longer forecasts an increased prevalence and economic burden of visual impairments. Improvements to visual health and treatment paradigms for progressive retinal degenerations slow vision loss. However, current treatments fail to remedy the root cause of visual impairments caused by retinal degenerations-loss of retinal neurons. Stimulation of retinal regeneration from endogenous cellular sources presents an exciting treatment avenue for replacement of lost retinal cells. In multiple species including zebrafish and Xenopus, Müller glial cells maintain a highly efficient regenerative ability to reconstitute lost cells throughout the organism's lifespan, highlighting potential therapeutic avenues for stimulation of retinal regeneration in humans. Here, we describe how the application of single-cell RNA-sequencing (scRNA-seq) has enhanced our understanding of Müller glial cell-derived retinal regeneration, including the characterization of gene regulatory networks that facilitate/inhibit regenerative responses. Additionally, we provide a validated experimental framework for cellular preparation of mouse retinal cells as input into scRNA-seq experiments, including insights into experimental design and analyses of resulting data.

The construction and experimental verification of a 6-LncRNA model based on Lactic acid metabolism in the tumor microenvironment of Wilms tumor.

BACKGROUND: Lactic acid (LA) can promote the malignant progression of tumors through the crosstalk with the tumor microenvironment (TME). However, the function of long non-coding RNAs (lncRNAs) related to LA metabolism in Wilms tumor (WT) remains unclear. METHODS: Gene expression data and clinical data of WT patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Through the ESTIMATE algorithm and Pearson correlation analysis, lncRNAs related to tumor immunity and LA metabolism were screened. Subsequently, Cox regression analysis and Lasso Cox regression analysis were used to construct a model. Furthermore, candidate genes were identified and a competitive endogenous RNA (ceRNA) network was conducted to explore the specific mechanism of characteristic genes. Finally, based on the strong clinical relevance of UNC5B-AS1, its expression and function were experimentally verified. RESULTS: The immune score and stromal score were found to be closely related to the prognosis of WT. Eventually, a prognostic model (TME-LA-LM) consisting of 6 lncRNAs was successfully identified. The model demonstrated favorable predictive ability and accuracy, with significant variation in immune infiltration and drug susceptibility observed between risk groups. Additionally, the study revealed the involvement of 2 candidate genes and 5 microRNAs (miRNAs) in the tumor's development. Notably, UNC5B-AS1 was highly expressed and found to promote the proliferation and migration of tumor cells. CONCLUSION: This study, for the first time, elucidated the prognostic signatures of WT using lncRNAs related to TME and LA metabolism. The fundings of this research offer valuable insights for future studies on immunotherapy, personalized chemotherapy and mechanism research.

Single-Cell Hi-C Analysis Workflow with Pairtools.

Single-cell Hi-C (scHi-C) is a collection of protocols for studying genomic interactions within individual cells. Although data analysis for scHi-C resembles data analysis for bulk Hi-C, the unique challenges of scHi-C, such as high noise and protocol-specific biases, require specialized data processing strategies. In this tutorial chapter, we focus on using pairtools, a suite of tools optimized for scHi-C data, demonstrating its application on a Drosophila snHi-C dataset. While centered on pairtools for snHi-C data, the principles outlined are applicable across scHi-C variants with minor adjustments. This educational chapter aims to guide researchers in using open-source tools for scHi-C analysis, emphasizing critical steps of contact pair extraction, detection of ligation junctions, filtration, and deduplication.

Developmental regulation of dermal adipose tissue by BCL11b.

The distinct anatomic environment in which adipose tissues arise during organogenesis is a principle determinant of their adult expansion capacity. Metabolic disease results from a deficiency in hyperplastic adipose expansion within the dermal/subcutaneous depot; thus, understanding the embryonic origins of dermal adipose is imperative. Using single-cell transcriptomics throughout murine embryogenesis, we characterized cell populations, including Bcl11b + cells, that regulate the development of dermal white adipose tissue (dWAT). We discovered that BCL11b expression modulates the Wnt signaling microenvironment to enable adipogenic differentiation in the dermal compartment. Subcutaneous and visceral adipose arises from a distinct population of Nefl + cells during embryonic organogenesis, whereas Pi16 + /Dpp4 + fibroadipogenic progenitors support obesity-stimulated hypertrophic expansion in the adult. Together, these results highlight the unique regulatory pathways used by anatomically distinct adipose depots, with important implications for human metabolic disease.

Droplet-based single-cell sequencing: Strategies and applications.

Notable advancements in single-cell omics technologies have not only addressed longstanding challenges but also enabled unprecedented studies of cellular heterogeneity with unprecedented resolution and scale. These strides have led to groundbreaking insights into complex biological systems, paving the way for a more profound comprehension of human biology and diseases. The droplet microfluidic technology has become a crucial component in many single-cell sequencing workflows in terms of throughput, cost-effectiveness, and automation. Utilizing a microfluidic chip to encapsulate and profile individual cells within droplets has significantly improved single-cell research. Therefore, this review aims to comprehensively elaborate the droplet microfluidics-assisted omics methods from a single-cell perspective. The strategies for using droplet microfluidics in the realms of genomics, epigenomics, transcriptomics, and proteomics analyses are first introduced. On this basis, the focus then turns to the latest applications of this technology in different sequencing patterns, including mono- and multi-omics. Finally, the challenges and further perspectives of droplet-based single-cell sequencing in both foundational research and commercial applications are discussed.

Unraveling the effects of prenatal anesthesia on neurodevelopment: A review of current evidence and future directions.

Human brain development is a complex, multi-stage, and sensitive process, especially during the fetal stage. Animal studies over the last two decades have highlighted the potential risks of anesthetics to the developing brain, impacting its structure and function. This has raised concerns regarding the safety of anesthesia during pregnancy and its influence on fetal brain development, garnering significant attention from the anesthesiology community. Although preclinical studies predominantly indicate the neurotoxic effects of prenatal anesthesia, these findings cannot be directly extrapolated to humans due to interspecies variations. Clinical research, constrained by ethical and technical hurdles in accessing human prenatal brain tissues, often yields conflicting results compared to preclinical data. The emergence of brain organoids as a cutting-edge research tool shows promise in modeling human brain development. When integrated with single-cell sequencing, these organoids offer insights into potential neurotoxic mechanisms triggered by prenatal anesthesia. Despite several retrospective and cohort studies exploring the clinical impact of anesthesia on brain development, many findings remain inconclusive. As such, this review synthesizes preclinical and clinical evidence on the effects of prenatal anesthesia on fetal brain development and suggests areas for future research advancement.

Gene inactivation of lysyl oxidase in smooth muscle cells reduces atherosclerosis burden and plaque calcification in hyperlipidemic mice.

BACKGROUND AND AIMS: Lysyl oxidase (LOX) catalyzes the crosslinking of collagen and elastin to maintain tensile strength and structural integrity of the vasculature. Excessive LOX activity increases vascular stiffness and the severity of occlusive diseases. Herein, we investigated the mechanisms by which LOX controls atherogenesis and osteogenic differentiation of vascular smooth muscle cells (SMC) in hyperlipidemic mice. METHODS: Gene inactivation of Lox in SMC was achieved in conditional knockout mice after tamoxifen injections. Atherosclerosis burden and vascular calcification were assessed in hyperlipidemic conditional [Loxf/fMyh11-CreERT2ApoE-/-] and sibling control mice [Loxwt/wtMyh11-CreERT2ApoE-/-]. Mechanistic studies were performed with primary aortic SMC from Lox mutant and wild type mice. RESULTS: Inactivation of Lox in SMCs decreased > 70 % its RNA expression and protein level in the aortic wall and significantly reduced LOX activity without compromising vascular structure and function. Moreover, LOX deficiency protected mice against atherosclerotic burden (13 ± 2 versus 23 ± 1 %, p < 0.01) and plaque calcification (5 ± 0.4 versus 11.8 ± 3 %, p < 0.05) compared to sibling controls. Interestingly, gene inactivation of Lox in SMCs preserved the contractile phenotype of vascular SMC under hyperlipidemic conditions as demonstrated by single-cell RNA sequencing and immunofluorescence. Mechanistically, the absence of LOX in SMC prevented excessive collagen crosslinking and the subsequent activation of the pro-osteogenic FAK/ß-catenin signaling axis. CONCLUSIONS: Lox inactivation in SMC protects mice against atherosclerosis and plaque calcification by reducing SMC modulation and FAK/ß-catenin signaling.

Deciphering single-cell gene expression variability and its role in drug response.

The effectiveness of drug treatments is profoundly influenced by individual responses, which are shaped by gene expression variability, particularly within pharmacogenes. Leveraging single-cell RNA sequencing (scRNA-seq) data, our study explores the extent of expression variability among pharmacogenes in a wide array of cell types across eight different human tissues, shedding light on their impact on drug responses. Our findings broaden the established link between variability in pharmacogene expression and drug efficacy to encompass variability at the cellular level. Moreover, we unveil a promising approach to enhance drug efficacy prediction. This is achieved by leveraging a combination of cross-cell and cross-individual pharmacogene expression variation measurements. Our study opens avenues for more precise forecasting of drug performance, facilitating tailored and more effective treatments in the future.

Elucidating ferroptosis mechanisms in heart failure through transcriptomics, single-cell sequencing, and experimental validation.

BACKGROUND: The mechanisms underlying ferroptosis in heart failure (HF) remain incompletely understood. METHODS: This study analyzed the heart failure dataset from the Gene Expression Omnibus to identify differentially expressed ferroptosis-related genes (DFRGs). Key DFRGs were selected using LASSO regression and SVM-RFE machine learning techniques. Their diagnostic accuracy was evaluated via ROC curve analysis. Single-cell sequencing data, heart failure cell, and mouse models were utilized to validate these key DFRGs. Additionally, potential non-coding RNAs targeting these genes were predicted, and analyses for gene set enrichment, immune cell infiltration, and drug targeting were conducted. RESULTS: A total of 127 DFRGs were identified, with 83 downregulated and 44 upregulated compared to controls. Seven key DFRGs (PTGS2, BECN1, SLC39A14, QSOX1, MLST8, TMSB4X, KDM4A) were identified, showing high diagnostic accuracy (AUC 0.988) in the GSE5406 dataset. GO and KEGG analyses linked these genes to ferroptosis, FoxO signaling, and autophagy pathways. A ceRNA network identified 217 miRNAs and 243 lncRNAs potentially targeting these genes, and 64 drugs were predicted as potential targets. Single-cell sequencing and in vitro experiments revealed differential expression of SLC39A14 and QSOX1, which was further confirmed in vivo. CONCLUSION: This study provides novel insights into the role of ferroptosis in heart failure by identifying and validating DFRGs that exhibit differential expression across various cell types. The differential expression patterns of these genes, particularly SLC39A14 and QSOX1, indicate their potential involvement in the pathophysiological mechanisms contributing to HF. These findings offer new insights for the development of targeted therapies for HF.

Pivotal role of JNK protein in the therapeutic efficacy of parthenolide against breast cancer: Novel and comprehensive evidences from network pharmacology, single-cell RNA sequencing and metabolomics.

This study aimed to evaluate the efficacy and therapeutic mechanism of parthenolide (PTL) in breast cancer (BC) through a comprehensive strategy integrating network pharmacology, single-cell RNA sequencing (scRNA-seq) and metabolomics. In network pharmacology, 70 therapeutic targets were identified, of which 16 core targets were filtered out through seven classical algorithms of Cytohubba plugin. Additionally, the hub module of PPI network was extracted using MCODE plugin. Molecular docking and molecular dynamics simulation showed a potent binding affinity between PTL and JNK, subsequently validated by MST and SPR assays. Further, Mendelian randomization analysis indicated that JNK was causally associated with BC. GO and KEGG enrichment analyses revealed that PTL counteracted BC via promoting ROS generation, inducing apoptosis and suppressing proliferation, which potentially involved the coordinated regulation of MAPK and FoxO1 pathways. Moreover, ssGSEA and scRNA-seq analysis suggested that PTL may act on T cell immune microenvironment of BC. Subsequently, these bioinformatics-based predictions were experimentally validated using in-vitro and in-vivo models. Finally, metabolome profiling unveiled that PTL remodeled the glycine, serine and threonine metabolism as well as biosynthesis of unsaturated fatty acids, and thereby contributed to BC inhibition. From molecular, immune and metabolic perspectives, this study not only provided a unique insight into the mechanistic details of PTL against BC, but also proposed a novel promising therapeutic strategy for BC.

Olfr2-positive macrophages originate from monocytes proliferate in situ and present a pro-inflammatory foamy-like phenotype.

AIMS: Olfactory receptor 2 (Olfr2) has been identified in a minimum of 30% of vascular macrophages, and its depletion was shown to reduce atherosclerosis progression. Mononuclear phagocytes, including monocytes and macrophages within the vessel wall, are major players in atherosclerosis. Single-cell RNA sequencing studies revealed that atherosclerotic artery walls encompass several monocytes and vascular macrophages, defining at least nine distinct subsets potentially serving diverse functions in disease progression. This study investigates the functional phenotype and ontogeny of Olfr2-expressing vascular macrophages in atherosclerosis. METHODS AND RESULTS: Olfr2+ macrophages rapidly increase in Apoe-/- mice's aorta when fed a Western diet (WD). Mass cytometry showed that Olfr2+ cells are clustered within the CD64 high population and enriched for CD11c and Ccr2 markers. Olfr2+ macrophages express many pro-inflammatory cytokines, including Il1b, Il6, Il12, and Il23, and chemokines, including Ccl5, Cx3cl1, Cxcl9, and Ccl22. By extracting differentially expressed genes from bulk RNA sequencing (RNA-seq) of Olfr2+ vs. Olfr2- macrophages, we defined a signature that significantly mapped to single-cell data of plaque myeloid cells, including monocytes, subendothelial MacAir, and Trem2Gpnmb foamy macrophages. By adoptive transfer experiments, we identified that Olfr2 competent monocytes from CD45.1Apoe-/-Olfr2+/+ mice transferred into CD45.2Apoe-/-Olfr2-/- recipient mice fed WD for 12 weeks, accumulate in the atherosclerotic aorta wall already at 72 h, and differentiate in macrophages. Olfr2+ macrophages showed significantly increased BrdU incorporation compared to Olfr2- macrophages. Flow cytometry confirmed that at least 50% of aortic Olfr2+ macrophages are positive for BODIPY staining and have increased expression of both tumour necrosis factor and interleukin 6 compared to Olfr2- macrophages. Gene set enrichment analysis of the Olfr2+ macrophage signature revealed a similar enrichment pattern in human atherosclerotic plaques, particularly within foamy/TREM2hi-Mφ and monocytes. CONCLUSIONS: In summary, we conclude that Olfr2+ macrophages in the aorta originate from monocytes and can accumulate at the early stages of disease progression. These cells can undergo differentiation into MacAir and Trem2Gpnmb foamy macrophages, exhibiting proliferative and pro-inflammatory potentials. This dynamic behaviour positions them as key influencers in shaping the myeloid landscape within the atherosclerotic plaque.

Expression and biological significance of topoisomerase II α (TOP2A) in oral squamous cell carcinoma.

BACKGROUND: Topoisomerase II α(TOP2A) is usually highly expressed in rapidly proliferating cells, and its expression is regulated by cell cycle. The relationship between TOP2A and oral squamous cell carcinoma (OSCC) needs further study. METHODS: TOP2A immunoreactivity was analyzed using immunohistochemical (IHC) staining analysis in specimens from 20 OSCC patients. Based on the high-throughput sequencing and gene microarray database, the expression of TOP2A mRNA in OSCC was calculated and its ability to identify OSCC tissues was evaluated by diagnostic analysis. CRISPR screen was used to select the genes necessary for OSCC cell growth, and the gene set was analyzed for function enrichment. Single-cell RNA sequencing analysis was conducted to evaluate the expression level of TOP2A mRNA in OSCC cells. RESULTS: Compared with normal oral tissues, the expression of TOP2A protein was up-regulated in OSCC tissues. A total of 1240 OSCC and 428 non-OSCC oral tissue samples were included based on high-throughput dataset retrieval, and it was confirmed that TOP2A mRNA was highly expressed in OSCC tissues [SMD = 1.51 (95% CI 0.94-2.07), sROC AUC = 0.96 (95% CI 0.94-0.98)]. As an essential gene for OSCC cell growth, single-cell RNA sequencing data also confirmed that TOP2A mRNA expression was up-regulated in OSCC cells. CONCLUSION: The up-regulation of TOP2A may play a pivotal role in OSCC.

Identification of neutrophil extracellular trap-related biomarkers in non-alcoholic fatty liver disease through machine learning and single-cell analysis.

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes.

High infiltration of immune cells with lower immune activity mediated the heterogeneity of gastric adenocarcinoma and promoted metastasis.

Background: Gastric adenocarcinoma (GA) is a heterogeneous malignancy with high invasion and metastasis. We aimed to explore the metastatic characteristics of GA using single-cell RNA-sequencing (scRNA-seq) analysis. Methods: The scRNA-seq dataset was downloaded from the GEO database and the "Seurat" package was used to perform the scRNA-seq analysis. The CellMarker2.0 database provided gene markers. Subsequently, differentially expressed genes (DEGs) were identified using the FindMarkers function and subjected to enrichment analysis with the "ClusterProlifer". "GseaVis" package was used for visualizing the gene levels. Finally, the SCENIC analysis was performed for identifying key regulons. The expression level and functionality of the key genes were verified by quantitative real-time PCR (qRT-PCR), wound healing and transwell assays. Results: A total of 7697 cells were divided into 8 cell subsets, in which the Cytotoxic NK/T cells, Myeloid cells and Myofibroblasts had higher proportion in the metastatic tissues. Further screening of DEGs and enrichment analysis revealed that in the metastatic tissues, NK cells, monocytes and inflammatory fibroblasts with low immune levels contributed to GA metastasis. In addition, this study identified a series of key immune-related regulons that mediated the lower immune activity of immune cells. Further in vitro experiment verified that CXCL8 was a key factor mediating the proliferation and migration of GA cells. Conclusion: The scRNA-seq analysis showed that high infiltration of immune cells with lower immune activity mediated heterogeneity to contribute to GA metastasis.

Mitochondrial Dysfunction and Disulfidptosis Co-regulate Neuronal cell in Neuropathic Pain Based on Bioinformatics Analysis.

Neuropathic pain (NP) affects approximately 6.9-10% of the world's population and necessitates the development of novel treatments. Mitochondria are essential in the regulation of cell death. Neuroimmune mechanisms are implicated in various forms of cell death associated with NP. However, the specific involvement of mitochondrial dysfunction and disulfidptosis in NP remains uncertain. Further research is required to gain a better understanding of their combined contribution. Our comprehensive study employs a variety of bioinformatic analysis methods, including differential gene analysis, weighted gene co-expression network analysis, machine learning, functional enrichment analysis, immune infiltration, sub-cluster analysis, single-cell dimensionality reduction and cell-cell communication to gain insight into the molecular mechanisms behind these processes. Our study rationally defines a list of key gene sets for mitochondrial dysfunction and disulfidptosis. 6 hub mitochondrial genes and 3 disulfidptosis-related genes (DRGs) were found to be associated with NP. The key genes were predominantly expressed in neurons and were lowly expressed in the NP group compared to SHAM. In addition, our macrophages used the APP (Amyloid precursor protein)-CD74 (MHC class II invariant chain) pathway to interact with neurons. These results suggest that NP is interconnected with the mechanistic processes of mitochondrial dysfunction and disulfidptosis, which may contribute to clinically targeted therapies.

Pan-Cancer Single-Cell Analysis Revealing the Heterogeneity of Cancer-Associated Fibroblasts in Skin Tumors.

BACKGROUND: Cancer-Associated Fibroblasts (CAFs) constitute a heterogeneous group of cells critical for the remodeling of the tumor microenvironment (TME). Given their significant impact on tumor progression, particularly in skin cancers, a deeper understanding of their characteristics and functions is essential. METHODS: This study employed a single-cell transcriptomic analysis to explore the diversity of CAFs within three major types of skin cancer: basal cell carcinoma, melanoma, and head and neck squamous cell carcinoma. We applied analytical techniques, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), pseudotime tracking, metabolic profiling, and stemness assessment to delineate and define the functional attributes of identified CAF subgroups. RESULTS: Our analysis successfully delineated nine distinct CAF subgroups across the studied tumor types. Of particular interest, we identified a novel CAF subtype, designated as C0, exclusive to basal cell carcinoma. This subtype exhibits phenotypic traits associated with invasive and destructive capabilities, significantly correlating with the progression of basal cell carcinoma. The identification of this subgroup provides new insights into the role of CAFs in cancer biology and opens avenues for targeted therapeutic strategies. CONCLUSION: A pan-cancer analysis was performed on three cancers, BCC, MA, and HNSCC, focusing on tumor fibroblasts in TME. Unsupervised clustering categorized CAF into nine subpopulations, among which the C0 subpopulation had a strong correspondence with BCC-CAF and an invasive- destructive-related phenotype.

Dynamic Roles and Expanding Diversity of Adipose Tissue Macrophages in Obesity.

Adipose tissue macrophages (ATMs) are key regulators of adipose tissue (AT) inflammation and insulin resistance in obesity, and the traditional M1/M2 characterization of ATMs is inadequate for capturing their diversity in obese conditions. Single-cell transcriptomic profiling has revealed heterogeneity among ATMs that goes beyond the old paradigm and identified new subsets with unique functions. Furthermore, explorations of their developmental origins suggest that multiple differentiation pathways contribute to ATM variety. These advances raise questions about how to define ATM functions, how they are regulated, and how they orchestrate changes in AT. This review provides an overview of the current understanding of ATMs and their updated categorization in both mice and humans during obesity. Additionally, diverse ATM functions and contributions in the context of obesity are discussed. Finally, potential strategies for targeting ATM functions as therapeutic interventions for obesity-induced metabolic diseases are addressed.

Identification of Key Genes in Fetal Gut Development at Single-Cell Level by Exploiting Machine Learning Techniques.

The study of fetal gut development is critical due to its substantial influence on immediate neonatal and long-term adult health. Current research largely focuses on microbiome colonization, gut immunity, and barrier function, alongside the impact of external factors on these phenomena. Limited research has been dedicated to the categorization of developing fetal gut cells. Our study aimed to enhance our understanding of fetal gut development by employing advanced machine-learning techniques on single-cell sequencing data. This dataset consisted of 62,849 samples, each characterized by 33,694 distinct gene features. Four feature ranking algorithms were utilized to sort features according to their significance, resulting in four feature lists. Then, these lists were fed into an incremental feature selection method to extract essential genes, classification rules, and build efficient classifiers. Several important genes were recognized by multiple feature ranking algorithms, such as FGG, MDK, RBP1, RBP2, IGFBP7, and SPON2. These features were key in differentiating specific developing intestinal cells, including epithelial, immune, mesenchymal, and vasculature cells of the colon, duo jejunum, and ileum cells. The classification rules showed special gene expression patterns on some intestinal cell types and the efficient classifiers can be useful tools for identifying intestinal cells.