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PubMed2025

A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.

Peripheral facial paralysis (PFP) is a common neurological disorder characterized by facial-nerve dysfunction. Identifying therapeutic targets and understanding the molecular and cellular mechanisms underlying PFP are crucial for developing effective treatment strategies. This study combined Mendelian randomization (MR) analysis and single-cell RNA sequencing (scRNA-seq) to explore potential therapeutic candidates and their roles in PFP pathophysiology. The MR analysis included 1925 publicly available plasma protein cis-heritability instruments. Instrumental variables were selected for MR analysis to identify plasma proteins associated with PFP, followed by colocalization analysis to evaluate shared genetic variants between the identified proteins and PFP. After the initial identification of plasma proteins associated with Bell's palsy using MR analysis, a rat model of facial-nerve injury was established to further dissect underlying mechanisms at cellular and molecular levels. Using scRNA-seq technology, we delved deeply into cellular Heterogeneity and dynamic changes in gene expression in the facial-nerve nucleus tissues under both injured and control conditions, thereby achieving a systematic study ranging from macroscopic genetic associations to microscopic cellular functions. Finally, expression patterns were preliminarily validated by performing in vitro immunofluorescence analysis on the facial-nerve nucleus samples of SD rats. The MR analysis results identified 30 plasma proteins significantly associated with PFP, with nine target genes showing differential expression in the scRNA-seq data. Colocalization analysis demonstrated that slit guidance Ligand 2 (SLIT2), semaphorin 4D (SEMA4D), EGF containing fibulin extracellular matrix protein 1 (EFEMP1), and sprouty related EVH1 domain containing 2 (SPRED2) shared causal variants with PFP. SLIT2 was highly expressed in the microglia and inhibitory neurons in the experimental group, whereas SEMA4D showed elevated expression across multiple glial cell types in the same group. In contrast, EFEMP1 and SPRED2 showed distinct expression patterns in fibroblasts and oligodendrocytes. The role of SLIT2 has been previously well-documented in many central nervous system diseases. However, for the first time, this study detected SLIT2 alteration after facial-nerve injury. Altered intercellular signaling, particularly enhanced SLIT2-ROBO signaling between neurons and glial cells, was observed in the PFP group. Pseudotime analysis revealed dynamic SLIT2 expression during microglia and inhibitory neuron differentiation, mirroring changes in ROBO1 expression. Immunofluorescence analysis of rat facial-nerve nucleus samples verified that SLIT2 protein levels were significantly increased in the facial-nerve nuclei of injured samples. In conclusion, despite the fact that this study is primarily founded on animal models and despite notable differences existing between animals and humans in terms of the facial motor nucleus, this study successfully identified SLIT2 as potential therapeutic targets for PFP. The SLIT2-ROBO axis stands out as a particularly promising candidate. SLIT2 may play a role in modulating neuroimmune interactions and promoting nerve repair. These findings provide a foundation for future clinical studies and targeted interventions to enhance recovery from PFP. Future research should focus on human sample validation to enhance clinical translation.

Animals↗

PubMed2026

An integrated single-cell and spatial transcriptomic atlas of thyroid cancer progression identifies prognostic fibroblast subpopulations.

Although well-differentiated thyroid carcinoma (WDTC) is characterized by a robust treatment response, aggressive subtypes, such as anaplastic thyroid carcinoma (ATC), remain highly lethal. To understand thyroid cancer evolution in both children and adults, we analyzed single-cell transcriptomes of 423,733 cells from 81 samples and spatially resolved key tumor and microenvironment populations across 28 tumors with spatial transcriptomics, including rare and unique composite WDTC/ATC tumors and pediatric diffuse sclerosing thyroid carcinomas. Additionally, we identified gene signatures of stromal cell populations in 5 large thyroid cancer bulk RNA-sequencing cohorts. Through this multi-institutional effort, we defined a population of POSTN+ myofibroblast cancer-associated fibroblasts (myCAFs) that are intimately associated with invasive tumor cells and correlate with poor prognosis, lymph node metastasis, and disease progression in thyroid carcinoma. We also revealed a population of inflammatory CAFs that are distant to tumor cells and are found in the inflammatory stromal microenvironment of autoimmune thyroiditis. Together, our study provides spatial profiling of thyroid cancer evolution in samples with mixed WDTC/ATC histopathology and identifies a prognostic myCAF subtype with potential clinical utility in predicting aggressive disease in both children and adults.

Humans↗

PubMed2003

Activation of site-specific DNA integration in human cells by a single chain integration host factor.

The heterodimeric integration host factor (IHF) is a site-specific DNA-binding and DNA-bending protein from Escherichia coli. It plays essential roles in a variety of DNA transactions including recombination, transcription and DNA replication. IHF's ability for concerted binding and bending of DNA is key to its biological function. Here we report the design, characterization and application of a single polypeptide chain IHF, termed scIHF2. In a novel approach for protein engineering, we inserted almost the entire alpha-subunit of IHF into the beta-subunit. DNA binding and DNA bending assays revealed that purified wild-type IHF and scIHF2 behave very similarly. Further, scIHF2 is required for site-specific integrative recombination by phage lambda integrase and for pSC101 replication in a DeltaIHF E.coli host. It also triggers site-specific integrative and excisive recombination in vitro to the same extent as the wild-type protein. We also demonstrate that scIHF2 is stably expressed in HeLa cells, that it is localized primarily in the cell nucleus and that it triggers integrative recombination in mammalian cells by wild-type integrase. Hence, scIHF2 may be used as a novel regulatory cofactor for recombination or other DNA transactions in mammalian cells that require or benefit from sequence-specific high precision DNA bending.

Amino Acid Sequence↗

PubMed2004

Design and fabrication of an integrated cell processor for single embryo cell manipulation.

This paper presents an integrated cell processor for the automatic handling of individual embryo cells. The integrated processor can perform various functions such as cell transport, isolation, orientation, and immobilization. These functions are indispensable and frequently used for the manipulation of single cells, but can only be carried out by a skillful operator. The purpose of this study was the integration and automation of these functions for effective cell manipulation, using a MEMS approach. The isolation of a cell was performed using polypyrrole (PPy) valves in a microchannel into which cells were transported. The orientation of cells was controlled by electrorotation (ER), and the target cell was immobilized by suction from a microhole. All of these functions were seamlessly realized on a single chip. Excellent experimental results with mouse (B6CBA) embryo cells showed that this device could substitute for routine and cumbersome manual work. It is expected that the integrated chip will contribute significantly to faster and more reliable manipulation of cells.

Animals↗

PubMed1972

Integral equation solution for biopotentials of single cells.

A Fredholm integral equation of the second type is developed for the biopotentials of single cells. Two singularities arise in the numerical solution of this integral equation and methods for handling them are presented. The problem of a spherical cell in an applied uniform field is used to illustrate the technique.

Cell Physiological Phenomena↗

PubMed2025

Enhancing and accelerating cell type deconvolution of large-scale spatial transcriptomics slices with dual network model.

MOTIVATION: Cell type deconvolution deciphers spatial distribution of mRNA transcripts at single cell level by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to infer mixture of cell types of spots in slices. Current algorithms are criticized for neglecting connection between scRNA-seq and spatial transcriptomics data, as well as time-consuming, hampering their application to large-scale datasets. RESULTS: In this study, we propose a joint learning nonnegative matrix factorization algorithm for fast cell type deconvolution (aka jMF2D), which integrates scRNA-seq and spatial transcriptomics data with network models. To bridge scRNA-seq and spatial transcriptomics data, jMF2D jointly learns cell type similarity network to enhance quality of signatures of cell types, thereby promoting accuracy and efficiency of deconvolution. Experiments demonstrate that jMF2D outperforms state-of-the-art baselines in terms of accuracy by saving about 90% running time on various datasets generated by different platforms. Furthermore, it can also facilitates the identification of spatial domains and bio-marker genes, providing an efficient and effective model for analyzing spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The software is coded using python, and is free available for academic https://github.com/xkmaxidian/jMF2D.

Algorithms↗

PubMed2026

Microglial PICALM: A novel genetic driver and therapeutic target in vascular dementia.

BACKGROUND: Vascular dementia (VaD) lacks well-defined genetic mechanisms. Cell-type-specific effects of GWAS loci remain unexplored. METHODS: We integrated single‑cell eQTL data (183 donors, eight cell types) with VaD GWAS (3624 cases, 475,484 controls) using Mendelian randomization and Bayesian colocalization, replicated in an independent cohort (2074 cases, 456,366 controls). Subtype, snRNA‑seq, cell‑cell communication, PheWAS, expression profiling, and drug prediction with BBB permeability assessment were performed. RESULTS: Microglial PICALM was the only robustly replicated signal (OR = 0.8334, p = 5.3 × 10⁻⁴; colocalization PP.H4 > 0.75). The effect was strongest in multiple infarctions dementia (OR = 0.7746). Exploratory snRNA-seq analysis (4 VaD vs. 4 controls; GSE282111) provided supporting evidence for microglial PICALM enrichment and downregulation (p < 0.001). PICALM‑high microglia showed enhanced neurovascular‑ and phagocytosis‑related communication (e.g., SPP1, GAS6, GRN). PheWAS revealed no pleiotropy. In silico drug repurposing prioritised three FDA-approved BBB-penetrant compounds (disopyramide, benzocaine, amantadine) as candidates warranting further mechanistic validation. CONCLUSIONS: Microglial PICALM is identified as a likely genetic determinant of VaD, especially in the multiple infarctions subtype. Upregulating PICALM may be associated with a neuroprotective microglial phenotype, highlighting PICALM as a candidate therapeutic target warranting further experimental validation.

Humans↗

PubMed2000

Amino acid uptake and regulation in multicellular hepatoma spheroids.

BACKGROUND: Cancer cells maintained in monolayer tissue culture are frequently used to study tumor biology and nutrient uptake, but there is a concern that this system may not fully reflect clinical tumor physiology. Because cells grown in a 3-D configuration more closely resemble an in vivo environment, a model was developed and characterized for the growth of SK-Hep human hepatoma cells in suspension as multicellular tumor spheroids (MTS). The measurement of nutrient uptake in such a system has never been established. MATERIALS AND METHODS: SK-Hep cultures were initiated as single cell suspensions and grown as MTS in siliconized spinner flasks. The transport of several individual amino acids (arginine, glutamate, leucine, alpha-(N-methylamino)isobutyric acid (MeAIB), and glutamine (GLN)) was measured in SK-Hep single cell suspensions and MTS (0. 50-0.60 mm diameter) by a radiotracer/rapid filtration technique, as was the regulation of glutamine uptake by phorbol esters. l-[(3)H]GLN uptake was also measured in larger spheroids (0.85-1.5 mm diameter). MTS cellularity was evaluated by histological examination, and single cell integrity after the transport assay was confirmed by scanning electron microscopy (SEM). RESULTS: SK-Hep MTS displayed gradients of cellular morphology and staining, with central necrosis visible at diameters >0.8 mm. Single cell suspensions endured the rapid filtration technique based on functional Na(+)-dependent uptake rates and SEM analysis. Of all amino acids tested, only GLN transport rates were visibly affected by growth format. In small MTS, Na(+)-dependent GLN uptake was diminished by 40%, but was 40-53% higher in MTS >1 mm displaying central necrosis, when compared to single cell suspensions. Likewise, slight parallel changes in glutamine transporter ATB(0) mRNA levels were observed in Northern blot analysis. Finally, phorbol ester-dependent GLN transport down-regulation (by 40-50%), previously established in SK-Hep monolayers, remained operative in all cell formats tested. CONCLUSIONS: The data suggest that the tumor microenvironment differentially impacts the uptake of specific nutrients despite the conservation of key regulatory pathways. This MTS technique may prove useful for further studies on the role of nutrient transport in nascent tumor growth.

Amino Acid Transport System ASC↗

PubMed1993

Intracellular calcium mobilization by inositol 1,4,5-trisphosphate: intracellular movements and compartmentalization.

Intracellular calcium ion (Ca2+) changes in NIH-3T3 fibroblasts responding to inositol 1,4,5-trisphosphate (IP3) injections have been monitored using high resolution digital imaging of the calcium indicator Fura-2. Ester loaded and microinjected indicator report radically different patterns of Ca2+ change during the IP3 response. These differences arise from intracellular compartmentalization of the ester loaded indicator which can seriously distort reported Ca2+ levels. Prominent among these aberrant responses is a signal in which Ca2+ levels in the cell nucleus appear to exceed those in the rest of the cell, and an apparent slowing of the Ca2+ recovery time-course throughout the cell when temperature is increased. Similar behavior is observed in other cell types. Judicious use of both loading techniques can provide information on Ca2+ movements into organelles that might otherwise escape detection. The Ca2+ rise normally measured in bulk or integrated single cell measurements is a complex mix of cytosol/nucleus and organellar changes. Much, if not all, of the observable organellar change is an accumulation, not release, of Ca2+ following the IP3 injection. The Golgi apparatus is a conspicuous early site for this accumulation, and mitochondria show a large, temperature sensitive uptake that is capable of limiting the maximal Ca2+ change during the response.

3T3 Cells↗

PubMed1998

The first-order giant neurons of the giant fiber system in the squid: electrophysiological and ultrastructural observations.

The giant fiber system controlling mantle contraction used for jet propulsion in squid consists of two sets of three giant neurons organized in tandem. The somata of the 1st- and 2nd-order giant cells are located in the brain, while the perikarya of the 3rd-order giant cells are encountered in the stellate ganglia of the mantle. The somata and dendrites of one fused pair of 1st-order giant cells are thought to receive synaptic input from the eye, statocyst, skin proprioceptors, and supraesophageal lobes. To define the cellular properties for integration of such an extensive synaptic load, especially given its diversity, intracellular recordings and electron microscopic observations were performed on 1st-order giant cells in an isolated head preparation. Spontaneous bursts of action potentials and spikes evoked by extracellular stimulation of the brachial lobe were sensitive to the Na+ channel blocker TTX. Action potentials were also abolished by recording with microelectrodes containing the membrane impermeant, use dependent Na+ channel blocker QX-314. The small action potential amplitude and the abundant synaptic input imply that the spike initiation zone is remotely located from the recording site. The high spontaneous activity in the isolated head preparation, as well as the presence of synaptic junctions resembling inhibitory synapses, suggest; that afferent synapses on 1st-order giant neurons might represent the inhibitory control of the giant fiber system. The characterization of the electroresponsive properties of the 1st-order giant neurons will provide a description of the single cell integrative properties that trigger the rapid jet propulsion necessary for escape behavior in squid.

Action Potentials↗

PubMed2025

Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19.

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 and donor lung tissue with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage. We identify changes in cellular composition across progressive damage, including waves of molecularly distinct macrophages and depletion of epithelial and endothelial populations. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early damage, and fibrosis-related collagens in late damage. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early steps of alveolar damage. These results provide a comprehensive, spatially resolved atlas of alveolar damage progression in COVID-19, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways in severe disease.

COVID-19↗

PubMed2025

scMGCL: accurate and efficient integration representation of single-cell multi-omics data.

MOTIVATION: Single-cell multi-omics data integration is essential for understanding cellular states and disease mechanisms, yet integrating heterogeneous data modalities remains a challenge. We present scMGCL, a graph contrastive learning framework for robust integration of single-cell ATAC-seq and RNA-seq data. Our approach leverages self-supervised learning on cell-cell similarity graphs, in which each modality's graph structure serves as an augmentation for the other. This cross-modality contrastive paradigm enables the learning of biologically meaningful, shared representations while preserving modality-specific features. RESULTS: Benchmarking against state-of-the-art methods demonstrates that scMGCL outperforms others in cell-type clustering, label transfer accuracy, and preservation of marker-gene correlations. Additionally, scMGCL significantly improves computational efficiency, reducing runtime and memory usage. The method's effectiveness is further validated through extensive analyses of cell-type similarity and functional consistency, providing a powerful tool for multi-omics data exploration. AVAILABILITY AND IMPLEMENTATION: Code and datasets are released at https://github.com/zlCreator/scMGCL.

Single-Cell Analysis↗

PubMed2026

SCMO: a deep learning model integrating the single-cell resolution TME ecosystem and multi-omics for survival prediction in CRC patients.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of global cancer mortality, highlighting the need for precise survival prediction to guide clinical decisions. Although tissue-level multi-omics is widely utilized for survival prediction, its limited resolution cannot capture tumor heterogeneity. Single-cell RNA sequencing (scRNA-seq) enables dissection of the tumor microenvironment (TME) at cellular resolution, supporting personalized prognostic assessment. METHODS: We collected 213 CRC scRNA-seq samples and established a CRC-specific TME atlas comprising 339,060 cells. Using this atlas as a reference, we deconvolved bulk RNA-seq data from TCGA-CRC cohort with the EcoTyper algorithm to reconstruct TME features. Clinical, genomic, and transcriptomic data were obtained from the Xena platform; microbial data were sourced from the BIC database. We integrated TME and multi-omics features through a self-normalizing neural network to construct a deep learning model (single-cell resolution TME ecosystem with multi-omics data [SCMO]) for survival prediction. To enhance interpretability, we utilized the Integrated Gradients algorithm and spatial transcriptomic data to analyze multi-omics and TME features. We performed anticancer drug screening with tumor necrosis factor receptor-associated protein 1 (TRAP1), a critical feature according to the Integrated Gradients algorithm, as a potential target. RESULTS: We identified 13 survival-related TME features from the CRC-specific atlas: 12 cell states and one multi-cellular ecosystem. SCMO, which combined TME and multi-omics features, improved survival prediction and outperformed existing methods, achieving a concordance index of 0.762. The SCMO demonstrated robust performance for long-term predictions, achieving areas under the curve (AUCs) of 0.752, 0.772, and 0.869 for 1-, 3-, and 5-year predictions in the training set, with corresponding test set AUCs of 0.639, 0.756, and 0.772. TME features from the SCMO model revealed that ecosystem density increased with CRC malignancy. Multi-omics features included TRAP1 as a potential drug target. Drug screening identified saikosaponin A as a novel TRAP1 inhibitor, and its anticancer activity was validated in vitro. We developed SCMO-Lite, a simplified model incorporating 12 high-attribution-weight multi-omics features, which demonstrated robust risk stratification. CONCLUSIONS: SCMO combines analytical precision with biological interpretability, offering novel insights for oncology survival prediction.

Humans↗

PubMed2026

Integration of single-cell transcriptomics and genomic mutation analysis identifies an immunotherapy-resistant tumor subcluster and validates ARNTL2 as a malignant driver in lung adenocarcinoma.

BACKGROUND: Immunotherapy resistance in lung adenocarcinoma (LUAD) remains a critical clinical challenge, and the mechanisms underlying resistance-associated intratumoral heterogeneity are poorly characterized. METHODS: We performed single-cell RNA sequencing of LUAD patients receiving neoadjuvant immunotherapy (responders vs. non-responders), integrating inferCNV, GSVA, and differential expression analyses. Cluster-specific genes were validated across seven independent cohorts (TCGA-LUAD, GSE13213, GSE26939, GSE29016, GSE30219, GSE31210, GSE42127). A multi-algorithm machine learning framework was used to construct a prognostic model, and the immune microenvironment was characterized using TCIA scoring, seven infiltration algorithms, and ESTIMATE. ARNTL2 function was assessed by CCK-8 and Transwell assays in A549 and H1299 cells. RESULTS: Non-responders showed significant enrichment of epithelial cells, depletion of cytotoxic T/NK cells, and elevated copy number variation burden versus responders (p < 0.0001). A resistance-enriched malignant subcluster (Cluster 2) exhibited hyperproliferative and metabolic reprogramming signatures with upregulated KRT17, S100A2, and CST6, which showed tumor-specific overexpression, adverse prognostic value, and genomic amplification across cohorts. CoxBoost combined with survivalSVM achieved optimal predictive performance (C-index = 0.686), yielding robust risk stratification (HR: 2.54-10.51, all p < 0.05). Low-risk patients showed greater immune infiltration and higher TCIA immunophenoscores. ARNTL2 was an independent prognostic factor (HR: 2.07-4.64) strongly correlated with risk score (r = 0.69), and its knockdown suppressed proliferation and invasion in both LUAD cell lines (all p < 0.05). CONCLUSION: This study identifies a resistance-associated malignant subcluster in LUAD, constructs a validated CoxBoost + survivalSVM prognostic model with robust immune stratification, and establishes ARNTL2 as a core oncogenic driver and therapeutic target.

ARNTL2↗

PubMed2026

Integrated bulk and single-cell RNA sequencing reveals a prognostic neuro-mimicry signature in papillary thyroid carcinoma.

BACKGROUND: Cancer cells can acquire neuron-like characteristics ("neural mimicry") to promote progression. However, the role of specific ion channel genes in Papillary Thyroid Carcinoma (PTC) and their clinical significance remains unclear. METHODS: We included transcriptomic data from 521 PTC patients in the TCGA cohort. A neuron-specific gene set was used to screen for potential targets. We constructed a prognostic model using LASSO logistic regression. To verify the cellular origin of the signature, we performed single-cell RNA sequencing (scRNA-seq) analysis on the GSE184362 dataset. RESULTS: We established an 8-gene signature involving KCNN4, KCNN1, KCNT2, SNAP25, KCNK16, GABRG1, GABRG2, and GABRB2. The model demonstrated good predictive performance for lymph node metastasis, with an AUC of 0.721 (95% CI 0.677-0.765). Single-cell analysis of seven integrated tumor samples (N = 65,744 cells) confirmed that GABRB2 was specifically enriched in malignant thyrocytes (EPCAM+/KRT18+) at 200-fold higher detection rates than immune cells (20.0% vs. 0.1%, P ≈ 0), supporting tumor-intrinsic neural mimicry. High-risk patients showed immunosuppressive features with altered immune cell infiltration patterns. CONCLUSION: This study identifies a malignant cell-intrinsic signature for predicting PTC prognosis. Validated by single-cell data, our findings suggest that targeting ion channels may represent a potential therapeutic strategy for modulating neuro-immune interactions in thyroid cancer, pending experimental validation.

GABRB2↗

PubMed2006

Contraction study of a single cardiac muscle cell in a microfluidic chip.

This chapter introduces a microfluidic method to study the contraction of a single cardiac muscle cell (cardiomyocyte). This method integrates single-cell selection, cell retention, dye loading, chemical stimulation, and fluorescence measurement for intracellular calcium on one microfluidic chip. Before single-cell experiments, the bonded chip was modified in order to make the channel deep enough to accommodate a large, single cardiomyocyte. After the modification, a single heart muscle cell could be selected and retained at a cell retention structure. Fluo-4 AM was loaded in the cell for the measurement of intracellular calcium ion concentration in the cell. Subsequently, caffeine was introduced into the chamber to induce the contraction of the cardiomyocyte. During contraction, fluorescence measurement was used to monitor the intracellular calcium level,and an optical imaging system was used to monitor the shape to confirm the contraction. The resting [Ca2+]i of cardiomyocyte was determined and was consistent with the value of approx 100 nM in the literature.

Aniline Compounds↗

PubMed2026

Integrative analysis of single-cell sequencing identifies CD8+ TIM3+ CD101+ T cell-associated genes as prognostic biomarkers in breast cancer.

BACKGROUND: Breast cancer is a prevalent and deadly malignancy that significantly impacts women's quality of life and imposes financial burdens. Despite therapeutic advancements, tumour heterogeneity and frequent relapses remain major challenges. Accordingly, this study aimed to characterize immune features associated with CD8+ TIM3+ CD101+ T cells and develop a prognostic signature for breast cancer. METHODS: This study integrated single-cell and bulk transcriptomic datasets to characterize CD8+ TIM3+ CD101+ T cell (CCT)-related immune features and construct a prognostic signature in breast cancer. Single-cell RNA-seq data were sourced from the Gene Expression Omnibus (GEO) repository, and bulk transcriptomic data were from The Cancer Genome Atlas (TCGA) and GEO databases. Analytical methods included pseudo-time trajectory reconstruction (Monocle2), intercellular signalling analysis (CellChat), functional enrichment (ClusterProfiler), and immune profiling (ssGSEA). Prognostic modeling was conducted using least absolute shrinkage and selection operator (LASSO) Cox regression, with validation via Kaplan-Meier and time-dependent receiver operating characteristic (ROC) analyses. RESULTS: Single-cell analysis identified 17 clusters spanning seven cell types, including T cells, myeloid cells, and epithelial cells. T-cell sub-clustering revealed four subtypes. Pseudotime analysis suggested a potential state-transition relationship between CD8+ CD101- TIM3+ and CD8+ CD101+ TIM3+ T-cell states. A total of 121 differentially expressed genes were enriched in vital biological processes. An 11-gene prognostic model showed strong predictive power across cohorts. Single-cell T-cell reclustering identified a CD8+ CD101+ TIM3+ T-cell subpopulation, which was primarily characterized by the expression of markers such as CD101 and HAVCR2/TIM3. CONCLUSIONS: This study maps cellular heterogeneity and molecular networks in breast cancer, offering insights for targeted therapy and improved prognosis.

Breast invasive carcinoma↗

PubMed1991

Synaptic background activity influences spatiotemporal integration in single pyramidal cells.

The standard one-dimensional Rall cable model assumes that the electrotonic structure of neurons does not change in response to synaptic input. This model is used in a great number of both theoretical and anatomical-physiological structure-function studies. In particular, the membrane time constant, tau m, the somatic input resistance, Rin, and the electrotonic length are used to characterize single cells. However, these studies do not take into account that neurons are embedded in a network of spontaneously active cells. Synapses from these cells will contribute significantly to the membrane conductance, especially if recent evidence of very high specific membrane resistance, Rm = 100 k omega.cm2, is taken into account. We numerically simulated the electrical behavior of an anatomically reconstructed layer V cortical pyramidal cell receiving input from 4000 excitatory and 1000 inhibitory cells firing spontaneously at 0-7 Hz. We found that, over this range of synaptic background activity, tau m and Rin change by a factor of 10 (80-7 msec, 110-14 M omega) and the electrotonic length of the cell changes by a factor of 3. We show that this significantly changes the response of the cell to temporal desynchronized versus temporal synchronized synaptic input distributed throughout the neuron. Thus, the global activity of the network can control how individual cells perform spatial and temporal integration.

Action Potentials↗