Background. Cardiomyopathy encompasses a broad spectrum of diseases affecting myocardial tissue, characterized clinically by abnormalities in cardiac structure, heart failure, and/or arrhythmias. Clinically heterogeneous, major types include dilated cardiomyopathy (DCM), hypertrophic cardiomyopathy (HCM), restrictive cardiomyopathy (RM), ischemic cardiomyopathy (ICM), among which DCM is more prevalent, while ICM exhibits higher incidence and mortality rates. Myocardial injury during cardiomyopathy progression may lead to myocardial fibrosis. Failure to intervene early and inhibit the process of myocardial fibrosis may culminate in heart failure. Cardiac fibroblasts constitute crucial cellular components determining the extent and quality of myocardial fibrosis, with various subpopulations exerting diverse roles in cardiomyopathy progression. Despite this, understanding of the cellular plasticity and transcriptional regulatory networks of cardiac fibroblasts in cardiomyopathy remains limited. Therefore, in this study, we conducted comprehensive single-cell analysis of cardiac fibroblasts in cardiomyopathy to explore differences in cellular plasticity and transcriptional regulatory networks among fibroblast subpopulations, with the aim of providing as many useful references as possible for the diagnosis, prognosis, and treatment of cardiomyopathy. Materials and Methods. Cells with mitochondrial gene expression comprising >20 of total expressed genes were excluded. Differential expression genes (DEGs) and stemness genes within cardiac fibroblast subpopulations were subjected to Gene Ontology (GO) analysis of biological processes (BP) and AUCell analysis. Monocle software was employed to analyze the pseudo-temporal trajectory of cardiac fibroblasts in cardiomyopathy. Additionally, the Python package SCENIC was utilized to assess enrichment of transcription factors and activity of regulators within cardiac fibroblast subpopulations in cardiomyopathy. Results. Following batch effect correction, 179,927 cells were clustered into 32 clusters, designated as T_NK cells, endothelial cells, myeloid cells, fibroblasts, pericytes, SMCs, CMs, proliferating cells, EndoCs, and EPCs. Among them, 8148 fibroblasts were further subdivided into 4 subpopulations, namely C0 THBS4+ Fibroblasts, C1 LINC01133+ Fibroblasts, C2 FGF7+ Fibroblasts, and C3 AGT+Fibroblasts. Results from GO_BP and AUCell analyses suggest that C3 AGT+Fibroblasts may be associated with immune response activation, protein transport, and myocardial contractile function, correlating with disease progression in cardiomyopathy. Transcription factor enrichment analysis indicates that FOS is the most significant TF in C3 AGT+Fibroblasts, also associated with the M1 module, possibly implicated in protein hydrolysis, intracellular DNA replication, and cell proliferation. Moreover, correlation analysis of transcriptional regulatory activity between fibroblast subpopulations reveals a more pronounced heterogeneity within C3 AGT+Fibroblasts in cardiomyopathy. Conclusion. C3 AGT+Fibroblasts exhibit increased sensitivity towards adverse outcomes in cardiomyopathy, such as myocardial fibrosis and impaired cardiac contractile function, compared to other cardiac fibroblast subpopulations. The differential cellular plasticity and transcriptional regulatory activity between C3 AGT+Fibroblasts and other subgroups offer new perspectives for targeting fibroblast subpopulation activity to treat cardiomyopathy. Additionally, stemness genes EPAS1 and MYC, along with the regulator FOS, may play roles in modulating the biological processes of cardiac fibroblasts in cardiomyopathy.

Myocardial infarction (MI) is a life-threatening coronary artery-related pathology characterized by sudden cardiac death, often leading to cardiac fibrosis and heart failure (HF). Despite advances in emergency care and treatment measures such as percutaneous coronary intervention (PCI), the mortality rate due to HF following MI remains high, making it the leading cause of death in MI patients. While cardiac fibroblasts are known to be closely associated with the adverse outcomes of cardiac fibrosis and HF post-MI, the cellular landscape of fibroblasts after MI and their role in myocardial fibrosis and HF progression has not been fully explored. Our study identified a key, highly proliferative fibroblast subpopulation, named C1 Postn + Fibroblasts, which showed high myocardial fibrosis scores. C1 Postn + Fibroblasts were primarily located at the early stage of the pseudo-time trajectory and exhibited high stemness. These cells interact with EndoCs, ECs, and macrophages through the Cxcl12-Ackr3, Ptn-Ncl, and Mdk-Lrp1 signaling pathways, thereby influencing myocardial fibrosis progression. Additionally, Tead1 and Hdac2 were found to be key and highly active transcription factors in this subpopulation. In vitro experiments showed that knocking down Postn significantly decreased the activity of cardiac fibroblasts, inhibited their migration and adhesion capabilities, and induced apoptosis. This subpopulation may be more sensitive to post-MI adverse events, while other subpopulations may exhibit more inhibited responses. Stemness genes Ctnnb1 and Hifla, as well as oxidative phosphorylation and glutathione metabolism pathways, should be closely monitored in efforts to prevent myocardial fibrosis post-MI. The Cxcl12-Ackr3, Ptn-Ncl, and Mdk-Lrp1 pathways may represent potential routes to disrupt the key interactions between C1 Postn + Fibroblasts and EndoCs, ECs, and macrophages. Tead1 and Hdac2 may be potential targets for inhibiting myocardial fibrosis and preventing adverse outcomes of MI after further experimental verification. The gene Postn, expressed in C1 Postn + Fibroblasts, may contribute to the inhibition of abnormal fibroblast activation post-MI. These findings open new perspectives for the prevention and treatment of myocardial fibrosis after MI and the prevention of its progression to HF.

Background: Colorectal cancer (CRC) is a heterogeneous illness influenced by intricate tumor-immune interactions and characterized by a dismal prognosis. Macrophage-mediated immunological signaling facilitates tumor proliferation and may associate inflammation in the tumor microenvironment (TME) of CRC with negative outcomes. Notwithstanding therapeutic advancements, resistance to treatment remains a significant obstacle. scRNA-seq offers comprehensive insights into the immune signaling network and immunological dynamics inside the CRC’s TME.Methods: We integrated scRNA-seq data from GEO with extensive RNA-seq data from TCGA to elucidate immunological signaling and dynamic cellular variation in the TME of CRC. The analyses encompassed quality control via Seurat, InferCNV, Monocle, CellChat, and SCENIC, differential gene expression, inference of copy number variation (CNV), pseudo time trajectories, and intercellular communication. Prognostic modeling was conducted using Cox regression and LASSO. Immune infiltration and drug sensitivity were evaluated by CIBERSORT, ESTIMATE, xCell, TIDE, and pRRophetic. Functional validation encompassed siRNA knockdown, qRT-PCR, Western blot analysis, and cellular assessment in CRC cell lines.Results: We discovered four categories of tumor cells exhibiting variations in cell cycle, stemness, and differentiation. The MKI67⁺ subpopulation exhibited a heightened dynamic cell state and engaged with macrophages via the MIF-(CD74+CD44) axis to facilitate immunological signaling. HMGA1 is a crucial transcription factor in this fraction, and its knockdown impedes CRC cell proliferation, motility, and invasion. The cancer model utilizing the MKI67⁺ TCs subpopulation (MTRS) successfully classified patient survival and linked with immune infiltration patterns and medication responses. Enrichment analysis revealed tumor-promoting and immunological signaling networks. Correlation scores suggest that this subpopulation may be linked to inflammation and immunosuppression inside the TME.Conclusion: Our research indicates that the C2 MKI67⁺ TCs subpopulation is a key driver of immune signal transduction in CRC TME, which may induce inflammatory responses through interaction with macrophages, thereby leading to adverse consequences such as cardiac dysfunction. HMGA1 represents a viable target for immunotherapy, and our cancer model derived from this subpopulation offers prognostic significance and direction for immunotherapeutic treatments.

Thirst and water intake are regulated by the organum vasculosum of the lamina terminalis (OVLT) and subfornical organ (SFO), located around the anteroventral third ventricle, which plays a critical role in sensing dynamic changes in sodium and water balance in body fluids. Meanwhile, neural circuits involved in thirst regulation and intracellular mechanisms underlying the osmosensitive function of OVLT and SFO are reviewed. Having specific Na_x channels in the glial cells and other channels (such as TRPV1 and TRPV4), the OVLT and SFO detect the increased Na⁺ concentration or hyperosmolality to orchestrate osmotic stimuli to the insular and cingulate cortex to evoke thirst. Meanwhile, the osmotic stimuli are relayed to the supraoptic nucleus (SON) and paraventricular nucleus of the hypothalamus (PVN) via direct neural projections or the median preoptic nucleus (MnPO) to promote the secretion of vasopressin which plays a vital role in the regulation of body fluid homeostasis. Importantly, the vital role of OVLT in sleep-arousal regulation is discussed, where vasopressin is proposed as the mediator in the regulation when OVLT senses osmotic stimuli.

Cardiac cell death and myocardial fibrosis after ischemia-reperfusion (I/R) injury are the primary causes of impaired cardiac function. Despite advances in therapies targeting ischemia, fibrosis, and angiogenesis, the early molecular and cellular mechanisms driving I/R injury remain poorly defined, particularly regarding interactions between specific cardiomyocyte (CM) subtypes and stromal cells. Extensive signaling interactions have been demonstrated between myocardial cells and fibroblasts during injury repair and remodeling, but the dynamic characteristics and molecular pathways involved in early I/R stages remain to be fully elucidated. Herein, we used single-cell transcriptomics to identify a key subtype of CMs, termed C0 Atcayos ⁺ CMs, that are activated in I/R. Components of the Bmp6–(Bmpr1a+Bmpr2) and Fgf1–Fgfr1 signaling axes were highly expressed and mediated interactions between the C0 Atcayos ⁺ CM subtype and fibroblasts. These pathways are known to promote angiogenesis and regulate endothelial homeostasis, and to be crucial in inhibiting myocardial fibrosis. Ligand-receptor interaction network visualization suggested that communication between C0 Atcayos ⁺ CMs and fibroblasts might be a critical link in the transition from myocardial cell death to fibrosis after I/R. Targeting these signaling axes might therefore offer new strategies to impede fibrosis progression and improve cardiac function after I/R. This research provides a potential reference for inhibiting the progression of diseases such as myocardial fibrosis after I/R.

Background: Chronic kidney disease (CKD) is a globally prevalent and highly lethal condition, often accompanied by dilated cardiomyopathy (DCM), which increases the risk of cardiac complications. Early detection of DCM in CKD patients remains challenging, despite established research demonstrating the relationship between CKD and cardiac abnormalities.Methods: We retrieved expression matrices for DCM (GSE57338, GSE29819) and CKD (GSE104954) from GEO and a DCM scRNA-seq dataset (GSE145154). These were analyzed for differential gene expression and WGCNA. KEGG and GO analyses were performed on shared differentially expressed genes in DCM and CKD. Potential drugs for DCM were identified using CMAP. Machine learning methods LASSO, SVM-RFE, and RF were used to find biomarkers and develop a diagnostic nomogram for CKD-associated DCM, validated with external datasets. Single-gene GSEA was conducted to understand model gene mechanisms in CKD-associated DCM. Immune cell infiltration was analyzed with CIBERSORT, and single-cell sequencing examined model gene distribution and expression in the heart.Results: Our examination of the expression matrix datasets associated with DCM and CKD revealed 115 key model genes that are shared by the two disorders as well as 47 genes that are differently expressed. These 47 differentially expressed genes were primarily linked to immune regulation and inflammation, according to enrichment analysis. CMAP analysis suggested withaferin-a, droxinostat, fluorometholone, and others as potential DCM treatments. Machine learning identified MNS1 and HERC6 as significant CKD-associated DCM biomarkers. A diagnostic nomogram using these genes was developed, showing strong discriminative power and clinical utility. MNS1 and HERC6 are implicated in metabolism, inflammation, immunity, and heart function. Immune cell infiltration analysis indicated dysregulation in DCM, with MNS1 and HERC6 correlating with immune cells. Single-cell sequencing showed MNS1 and HERC6 expression in endothelial cells and fibroblasts, respectively.Conclusion: We identified MNS1 and HERC6 as biomarkers and developed a new diagnostic nomogram based on them for the timely diagnosis of CKD patients presenting with DCM complications. This study’s findings offer novel insights into potential diagnostic methods and therapeutic strategies regarding the coexistence of CKD and DCM.