Dynamic chromatin accessibility and transcriptome changes following PDGF-BB treatment of bone-marrow derived mesenchymal stem cells.

BACKGROUND: Mesenchymal stem cells (MSCs) are multipotent stem cells that are under investigation for use in clinical trials because they are capable of self-renewal and differentiating into different cell types under defined conditions. Nonetheless, the therapeutic effects of MSCs have been constrained by low engraftment rates, cell fusion, and cell survival. Various strategies have been explored to improve the therapeutic efficacy of MSCs, with platelet-derived growth factor (PDGF)-BB emerging as a promising candidate. To enhance our comprehension of the impact of PDGF-BB on the gene expression profile and chromosomal accessibility of MSCs, RNA-sequencing and analysis of chromatin accessibility profiles were conducted on three human primary MSCs in culture, both with and without stimulation by PDGF-BB. RESULTS: Integrative analysis of gene expression and chromatin accessibility demonstrated that PDGF-BB treatment modified the chromatin accessibility landscape, marking regions for activation or repression through the AP-1 family transcription factors TEAD, CEBP, and RUNX2. These changes in AP-1 transcription factor expression, in turn, led to cell proliferation and differentiation potential towards osteoblasts, adipocytes, or chondrocytes. The degree of MSC differentiation varies among cells isolated from different donors. The presence of an enrichment of exosome-related genes is also noted among all the differentially expressed genes. CONCLUSIONS: In conclusion, the observed changes in AP-1 transcription factor expression not only induced cellular proliferation and differentiation, but also revealed variations in the degree of MSC differentiation based on donor-specific differences. Moreover, the enrichment of exosome-related genes among differentially expressed genes suggests a potential significant role for PDGF-BB in facilitating intercellular communication.

Identification of GABAergic subpopulations in the lateral hypothalamus for home-driven behaviors in mice.

Home information profoundly influences behavioral states in both humans and animals. However, how "home" is represented in the brain and its role in driving diverse related behaviors remain elusive. Here, we demonstrate that home bedding contains sufficient home information to modulate affective behaviors, including aversion responses, defensive aggression, and mating behaviors. These varied responses to home information are mediated by gama-aminobutyric acid (GABA)ergic neurons in the lateral hypothalamus (LHGABA). Inhibiting LHGABA abolishes, while activating mimics, the effects of home bedding on these behaviors across different contexts. Specifically, projections from LHGABA to the ventral tegmental area (VTA) mediate the relaxation of aversive emotion, while projections to the periaqueductal gray (PAG) initiate defensive concerns. Thus, our data suggest that home information in different contexts converges to activate distinct subgroups of the LHGABA, which, in turn, elicit appropriate affective behaviors in relieving aversion, fighting intruders, or enhancing mating through involving distinct downstream projections.

Anaerobic digestion and biochar/hydrochar enhancement of antibiotic-containing wastewater: Current situation, mechanism and future prospects.

The increasing consumption of antibiotics by humans and animals and their inappropriate disposal have increased antibiotic load in municipal and pharmaceutical industry waste, resulting in severe public health risks worldwide. Anaerobic digestion (AD) is the main force of antibiotic-containing wastewater treatment, and the adaptability of biochar/hydrochar (BC/HC) makes it an attractive addition to AD systems, which aim to promote methane production efficiency. Nevertheless, further studies are needed to better understand the multifaceted function of BC/HC and its role in antibiotic-containing wastewater AD. This review article examines the current status of AD of antibiotic-containing wastewater and the effects of different preparation conditions on the physicochemical properties of BC/HC and AD status. The incorporation of BC/HC into the AD process has several potential benefits, contingent upon the physical and chemical properties of BC/HC. These benefits include mitigation of antibiotic toxicity, establishment of a stable system, enrichment of functional microorganisms and enhancement of direct interspecies electron transfer. The mechanism by which BC/HC enhances the AD of antibiotic-containing wastewater, with focus on microbial enhancement, was analysed. A review of the literature revealed that the challenge of optimization and process improvement must be addressed to enhance efficiency and clarify the mechanism of BC/HC in the AD of antibiotic-containing wastewater. This review aims to provide significant insights and details into the BC/HC-enhanced AD of antibiotic-containing wastewater.

Experimental evaluation of an artificial anal sphincter based on biomechanical compatibility.

BACKGROUND: The artificial anal sphincter is a device used to treat patients with fecal incontinence who are unable to control their bowel movements on their own. Long-term morphological changes in the tissue surrounding the artificial anal sphincter can cause biomechanical compatibility problems, which seriously affect the clinical application of the artificial anal sphincter. METHODS: In this paper, the superelasticity of shape memory alloys was utilized to design and fabricate a biomechanically compatible constant force clamping artificial anal sphincter. An in vitro simulation system was constructed to verify the effectiveness, safety, and constant force characteristics of the artificial anal sphincter. RESULTS: The experimental results demonstrated that the artificial anal sphincter could be effectively closed with no leakage of the liquid-like intestinal contents, which are most likely to leak. The pressure of the artificial anal sphincter on the intestinal tube gradually increased and eventually became constant during closure, and the pressure value was always less than the intestinal blood supply pressure threshold. CONCLUSIONS: In this paper, we designed an artificial anal sphincter based on biomechanical compatibility and the corresponding in vitro simulation experimental program and preliminarily verified the effectiveness, safety, and constant force characteristics of the artificial anal sphincter.

MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants.

SUMMARY: Massively parallel reporter assay (MPRA) is an important technology for evaluating the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs, and genomic features, totaling 242 818 variants tested more than 30 cell lines and 30 human diseases or traits. MPRAVarDB enables users to query MPRA variants by genomic region, disease and cell line, or any combination of these parameters. Notably, MPRAVarDB offers a suite of pretrained machine-learning models tailored to the specific disease and cell line, facilitating the prediction of regulatory variants. The user-friendly interface allows users to receive query and prediction results with just a few clicks. AVAILABILITY AND IMPLEMENTATION: https://mpravardb.rc.ufl.edu.

Acetylation of PGK1 at lysine 323 promotes glycolysis, cell proliferation, and metastasis in luminal A breast cancer cells.

BACKGROUND: In prior research employing iTRAQ (Isobaric Tags for Relative and Absolute Quantitation) technology, we identified a range of proteins in breast cancer tissues exhibiting high levels of acetylation. Despite this advancement, the specific functions and implications of these acetylated proteins in the context of cancer biology have yet to be elucidated. This study aims to systematically investigate the functional roles of these acetylated proteins with the objective of identifying potential therapeutic targets within breast cancer pathophysiology. METHODS: Acetylated targets were identified through bioinformatics, with their expression and acetylation subsequently confirmed. Proteomic analysis and validation studies identified potential acetyltransferases and deacetylases. We evaluated metabolic functions via assays for catalytic activity, glucose consumption, ATP levels, and lactate production. Cell proliferation and metastasis were assessed through viability, cycle analysis, clonogenic assays, PCNA uptake, wound healing, Transwell assays, and MMP/EMT marker detection. RESULTS: Acetylated proteins in breast cancer were primarily involved in metabolism, significantly impacting glycolysis and the tricarboxylic acid cycle. Notably, PGK1 showed the highest acetylation at lysine 323 and exhibited increased expression and acetylation across breast cancer tissues, particularly in T47D and MCF-7 cells. Notably, 18 varieties acetyltransferases or deacetylases were identified in T47D cells, among which p300 and Sirtuin3 were validated for their interaction with PGK1. Acetylation at 323 K enhanced PGK1's metabolic role by boosting its activity, glucose uptake, ATP production, and lactate output. This modification also promoted cell proliferation, as evidenced by increased viability, S phase ratio, clonality, and PCNA levels. Furthermore, PGK1-323 K acetylation facilitated metastasis, improving wound healing, cell invasion, and upregulating MMP2, MMP9, N-cadherin, and Vimentin while downregulating E-cadherin. CONCLUSION: PGK1-323 K acetylation was significantly elevated in T47D and MCF-7 luminal A breast cancer cells and this acetylation could be regulated by p300 and Sirtuin3. PGK1-323 K acetylation promoted cell glycolysis, proliferation, and metastasis, highlighting novel epigenetic targets for breast cancer therapy.

Convergence analysis of sparse TSK fuzzy systems based on spectral Dai-Yuan conjugate gradient and application to high-dimensional feature selection.

Dealing with high-dimensional problems has always been a key and challenging issue in the field of fuzzy systems. Traditional Takagi-Sugeno-Kang (TSK) fuzzy systems face the challenges of the curse of dimensionality and computational complexity when applied to high-dimensional data. To overcome these challenges, this paper proposes a novel approach for optimizing TSK fuzzy systems by integrating the spectral Dai-Yuan conjugate gradient (SDYCG) algorithm and the smoothing group L0 regularization technique. This method aims to address the challenges faced by TSK fuzzy systems in handling high-dimensional problems. The smoothing group L0 regularization technique is employed to introduce sparsity, select relevant features, and improve the generalization ability of the model. The SDYCG algorithm effectively accelerates convergence and enhances the learning performance of the network. Furthermore, we prove the weak convergence and strong convergence of the new algorithm under the strong Wolfe criterion, which means that the gradient norm of the error function with respect to the weight vector converges to zero, and the weight sequence approaches a fixed point.

Single-nucleus chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry.

Single-nucleus analysis allows robust cell-type classification and helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Here, using samples from 92 women of several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells, and macrophages. In addition to the known cell identity genes FOXA1 (luminal hormone sensing), EHF and ELF5 (LASP), TP63 and KRT14 (basal-myoepithelial), epithelial subtypes displayed several uncharacterized markers and inferred gene regulatory networks. By integrating breast epithelial cell gene expression signatures with spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.

Occurrence of microplastics in the headwaters of Yellow River on the Tibetan Plateau: Source analysis and ecological risk assessment.

The widespread occurrence of Microplastics (MPs) has aroused increasing concerns. However, the fate of MPs in remote areas remains poorly understood. Here, the spatial distribution, potential sources, and environmental risks of MPs were analyzed in the headstream of the Yellow River on the eastern Tibetan Plateau. The average MP abundances are (464.3 ± 200.9) items /m3 and (63.6 ± 34.7) items /kg in the water and sediment, respectively, with both majority polymer is polypropylene (PP) (water: 28.7 %; sediment: 25.2 %). The structural equation modeling and conditional fragmentation model were used in this study to analyze the source and impact factors of riverine MPs. According to the models, MPs were influenced by water quality parameters and anthropogenic activities. Furthermore, the source analysis through MP characteristics and statistical analysis showed that the main sources of MPs include domestic sewage, plastic waste disposal, and the use of agricultural plastic film. Moreover, the differences in MP sources along the river were distinguished by the conditional fragmentation model. The potential ecological risks of MPs were evaluated, resulting in relatively medium-to-low levels. Our findings will serve as important references for improving the understanding of the plateau environmental impacts of MP distribution in the headwaters of large rivers.

The Loss of PPARγ Expression and Signaling Is a Key Feature of Cutaneous Actinic Disease and Squamous Cell Carcinoma: Association with Tumor Stromal Inflammation.

Given the importance of peroxisome proliferator-activated receptor (PPAR)-gamma in epidermal inflammation and carcinogenesis, we analyzed the transcriptomic changes observed in epidermal PPARγ-deficient mice (Pparg-/-epi). A gene set enrichment analysis revealed a close association with epithelial malignancy, inflammatory cell chemotaxis, and cell survival. Single-cell sequencing of Pparg-/-epi mice verified changes to the stromal compartment, including increased inflammatory cell infiltrates, particularly neutrophils, and an increase in fibroblasts expressing myofibroblast marker genes. A comparison of transcriptomic data from Pparg-/-epi and publicly available human and/or mouse actinic keratoses (AKs) and cutaneous squamous cell carcinomas (SCCs) revealed a strong correlation between the datasets. Importantly, PPAR signaling was the top common inhibited canonical pathway in AKs and SCCs. Both AKs and SCCs also had significantly reduced PPARG expression and PPARγ activity z-scores. Smaller reductions in PPARA expression and PPARα activity and increased PPARD expression but reduced PPARδ activation were also observed. Reduced PPAR activity was also associated with reduced PPARα/RXRα activity, while LPS/IL1-mediated inhibition of RXR activity was significantly activated in the tumor datasets. Notably, these changes were not observed in normal sun-exposed skin relative to non-exposed skin. Finally, Ppara and Pparg were heavily expressed in sebocytes, while Ppard was highly expressed in myofibroblasts, suggesting that PPARδ has a role in myofibroblast differentiation. In conclusion, these data provide strong evidence that PPARγ and possibly PPARα represent key tumor suppressors by acting as master inhibitors of the inflammatory changes found in AKs and SCCs.

Single-nucleus multiome analysis of human cerebellum in Alzheimer's disease-related dementia.

Although human cerebellum is known to be neuropathologically impaired in Alzheimer's disease (AD) and AD-related dementias (ADRD), the cell type-specific transcriptional and epigenomic changes that contribute to this pathology are not well understood. Here, we report single-nucleus multiome (snRNA-seq and snATAC-seq) analysis of 103,861 nuclei isolated from cerebellum from 9 human cases of AD/ADRD and 8 controls, and with frontal cortex of 6 AD donors for additional comparison. Using peak-to-gene linkage analysis, we identified 431,834 significant linkages between gene expression and cell subtype-specific chromatin accessibility regions enriched for candidate cis-regulatory elements (cCREs). These cCREs were associated with AD/ADRD-specific transcriptomic changes and disease-related gene regulatory networks, especially for RAR Related Orphan Receptor A (RORA) and E74 Like ETS Transcription Factor 1 (ELF1) in cerebellar Purkinje cells and granule cells, respectively. Trajectory analysis of granule cell populations further identified disease-relevant transcription factors, such as RORA, and their regulatory targets. Finally, we prioritized two likely causal genes, including Seizure Related 6 Homolog Like 2 (SEZ6L2) in Purkinje cells and KAT8 Regulatory NSL Complex Subunit 1 (KANSL1) in granule cells, through integrative analysis of cCREs derived from snATAC-seq, genome-wide AD/ADRD loci, and Hi-C looping data. This first cell subtype-specific regulatory landscape in the human cerebellum identified here offer novel genomic and epigenomic insights into the neuropathology and pathobiology of AD/ADRD and other neurological disorders if broadly applied.

Sequential action-induced invariant representation for reinforcement learning.

How to accurately learn task-relevant state representations from high-dimensional observations with visual distractions is a realistic and challenging problem in visual reinforcement learning. Recently, unsupervised representation learning methods based on bisimulation metrics, contrast, prediction, and reconstruction have shown the ability for task-relevant information extraction. However, due to the lack of appropriate mechanisms for the extraction of task information in the prediction, contrast, and reconstruction-related approaches and the limitations of bisimulation-related methods in domains with sparse rewards, it is still difficult for these methods to be effectively extended to environments with distractions. To alleviate these problems, in the paper, the action sequences, which contain task-intensive signals, are incorporated into representation learning. Specifically, we propose a Sequential Action-induced invariant Representation (SAR) method, which decouples the controlled part (i.e., task-relevant information) and the uncontrolled part (i.e., task-irrelevant information) in noisy observations through sequential actions, thereby extracting effective representations related to decision tasks. To achieve it, the characteristic function of the action sequence's probability distribution is modeled to specifically optimize the state encoder. We conduct extensive experiments on the distracting DeepMind Control suite while achieving the best performance over strong baselines. We also demonstrate the effectiveness of our method at disregarding task-irrelevant information by applying SAR to real-world CARLA-based autonomous driving with natural distractions. Finally, we provide the analysis results of generalization drawn from the generalization decay and t-SNE visualization. Code and demo videos are available at https://github.com/DMU-XMU/SAR.git.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder.

Alcohol use disorder (AUD) is likely associated with complex transcriptional alterations in addiction-relevant brain regions. We characterize AUD-associated differences in cell type-specific gene expression and chromatin accessibility in the caudate nucleus by conducting a single-nucleus RNA-seq assay and a single-nucleus RNA-seq + ATAC-seq (multiome) assay on caudate tissue from 143 human postmortem brains (74 with AUD). We identified 17 cell types. AUD was associated with a higher proportion of microglia in an activated state and more astrocytes in a reactive state. There was widespread evidence for differentially expressed genes across cell types with the most identified in oligodendrocytes and astrocytes, including genes involved in immune response and synaptic regulation, many of which appeared to be regulated in part by JUND and OLIG2. Microglia-astrocyte communication via interleukin-1 beta, and microglia-astrocyte-oligodendrocyte interaction via transforming growth factor beta 1 were increased in individuals with AUD. Expression quantitative trait loci analysis revealed potential driver genes of AUD, including ADAL, that may protect against AUD in medium spiny neurons and interneurons. This work provides a thorough profile of the effects of AUD in the human brain and identifies several promising genes for further study.

Targeting Ovarian Cancer Stem Cells by Dual Inhibition of the Long Noncoding RNA HOTAIR and Lysine Methyltransferase EZH2.

Persistence of cancer stem cells (CSCs) is believed to contribute to resistance to platinum-based chemotherapy and disease relapse in ovarian cancer, the fifth leading cause of cancer-related death among US women. HOXC transcript antisense RNA (HOTAIR) is a long noncoding RNA (lncRNA) overexpressed in high-grade serous ovarian cancer and linked to chemoresistance. However, HOTAIR impacts chromatin dynamics in ovarian CSCs and how this oncogenic lncRNA contributes to drug resistant disease are incompletely understood. Here we generated HOTAIR knock-out (KO) high-grade serous ovarian cancer cell lines using paired CRISPR guide RNA design to investigate the function of HOTAIR. We show loss of HOTAIR function re-sensitized ovarian cancer cells to platinum treatment and decreased the population of ovarian CSCs. Furthermore, HOTAIR KO inhibited development of stemness-related phenotypes, including spheroid formation ability, as well as expression of key stemness-associated genes ALDH1A1, NOTCH3, SOX9, and PROM1. HOTAIR KO altered both the cellular transcriptome and chromatin accessibility landscape of multiple oncogenic-associated genes and pathways, including the NF-kB pathway. HOTAIR functions as an oncogene by recruiting enhancer of zeste 2 (EZH2) to catalyze H3K27 tri-methylation to suppress downstream tumor suppressor genes, and it was of interest to inhibit both HOTAIR and EZH2. In vivo, combining a HOTAIR inhibitor with an EZH2 inhibitor and platinum chemotherapy decreased tumor formation and increased survival. These results suggest a key role for HOTAIR in ovarian CSCs and malignant potential. Targeting HOTAIR in combination with epigenetic therapies may represents therapeutic strategy to ameliorate ovarian cancer progression and resistance to platinum-based chemotherapy.

Metaproteomics-informed stoichiometric modeling reveals the responses of wetland microbial communities to oxygen and sulfate exposure.

Climate changes significantly impact greenhouse gas emissions from wetland soil. Specifically, wetland soil may be exposed to oxygen (O2) during droughts, or to sulfate (SO42-) as a result of sea level rise. How these stressors - separately and together - impact microbial food webs driving carbon cycling in the wetlands is still not understood. To investigate this, we integrated geochemical analysis, proteogenomics, and stoichiometric modeling to characterize the impact of elevated SO42- and O2 levels on microbial methane (CH4) and carbon dioxide (CO2) emissions. The results uncovered the adaptive responses of this community to changes in SO42- and O2 availability and identified altered microbial guilds and metabolic processes driving CH4 and CO2 emissions. Elevated SO42- reduced CH4 emissions, with hydrogenotrophic methanogenesis more suppressed than acetoclastic. Elevated O2 shifted the greenhouse gas emissions from CH4 to CO2. The metabolic effects of combined SO42- and O2 exposures on CH4 and CO2 emissions were similar to those of O2 exposure alone. The reduction in CH4 emission by increased SO42- and O2 was much greater than the concomitant increase in CO2 emission. Thus, greater SO42- and O2 exposure in wetlands is expected to reduce the aggregate warming effect of CH4 and CO2. Metaproteomics and stoichiometric modeling revealed a unique subnetwork involving carbon metabolism that converts lactate and SO42- to produce acetate, H2S, and CO2 when SO42- is elevated under oxic conditions. This study provides greater quantitative resolution of key metabolic processes necessary for the prediction of CH4 and CO2 emissions from wetlands under future climate scenarios.

In silico generation and augmentation of regulatory variants from massively parallel reporter assay using conditional variational autoencoder.

Predicting the functional consequences of genetic variants in non-coding regions is a challenging problem. Massively parallel reporter assays (MPRAs), which are an in vitro high-throughput method, can simultaneously test thousands of variants by evaluating the existence of allele specific regulatory activity. Nevertheless, the identified labelled variants by MPRAs, which shows differential allelic regulatory effects on the gene expression are usually limited to the scale of hundreds, limiting their potential to be used as the training set for achieving a robust genome-wide prediction. To address the limitation, we propose a deep generative model, MpraVAE, to in silico generate and augment the training sample size of labelled variants. By benchmarking on several MPRA datasets, we demonstrate that MpraVAE significantly improves the prediction performance for MPRA regulatory variants compared to the baseline method, conventional data augmentation approaches as well as existing variant scoring methods. Taking autoimmune diseases as one example, we apply MpraVAE to perform a genome-wide prediction of regulatory variants and find that predicted regulatory variants are more enriched than background variants in enhancers, active histone marks, open chromatin regions in immune-related cell types, and chromatin states associated with promoter, enhancer activity and binding sites of cMyC and Pol II that regulate gene expression. Importantly, predicted regulatory variants are found to link immune-related genes by leveraging chromatin loop and accessible chromatin, demonstrating the importance of MpraVAE in genetic and gene discovery for complex traits.

Genome-wide meta-analyses of cross substance use disorders in European, African, and Latino ancestry populations.

Genetic risks for substance use disorders (SUDs) are due to both SUD-specific and SUD-shared genes. We performed the largest multivariate analyses to date to search for SUD-shared genes using samples of European (EA), African (AA), and Latino (LA) ancestries. By focusing on variants having cross-SUD and cross-ancestry concordant effects, we identified 45 loci. Through gene-based analyses, gene mapping, and gene prioritization, we identified 250 SUD-shared genes. These genes are highly expressed in amygdala, cortex, hippocampus, hypothalamus, and thalamus, primarily in neuronal cells. Cross-SUD concordant variants explained ~ 50% of the heritability of each SUD in EA. The top 5% individuals having the highest polygenic scores were approximately twice as likely to have SUDs as others in EA and LA. Polygenic scores had higher predictability in females than in males in EA. Using real-world data, we identified five drugs targeting identified SUD-shared genes that may be repurposed to treat SUDs.

TRIM59 deficiency promotes M1 macrophage activation and inhibits colorectal cancer through the STAT1 signaling pathway.

Tumor-associated macrophages play a crucial role in the tumor microenvironment. Tripartite motif 59 (TRIM59), a member of the tripartite motif (TRIM) family, is known to be associated with immunological diseases and macrophage activation. The functional and molecular mechanisms by which TRIM59 affects the occurrence and development of colorectal cancer (CRC) through macrophages are still not well understood. To address this, we generated macrophage-specific TRIM59 conditional knockout mice and utilized these mice to establish colitis-associated cancer and MC38 transplanted CRC models for further investigation. We found that the deficiency of TRIM59 in macrophages inhibited colorectal tumorigenesis in mice. This tumor-suppressive effect was achieved by promoting the activation of M1 macrophages via STAT1 signaling pathway. Further mechanistic studies revealed that TRIM59 could regulate macrophage polarization by ubiquitinating and degrading STAT1. These findings provide evidence that TRIM59 deficiency promotes M1 macrophage activation and inhibits CRC through the STAT1 signaling pathway, suggesting that the TRIM59/STAT1 signaling pathway may be a promising target for CRC.

The correlation between serum calcium levels and prognosis in patients with severe acute osteomyelitis.

Objective: To explore the relationship between serum calcium levels and the prognosis of severe acute osteomyelitis, and to assess the effectiveness of calcium levels in prognostic evaluation. Methods: Relevant patient records of individuals diagnosed with severe acute osteomyelitis were obtained for this retrospective study from the Medical Information Mart for Intensive Care (MIMIC-IV). The study aimed to assess the impact of different indicators on prognosis by utilizing COX regression analysis. To enhance prognostic prediction for critically ill patients, a nomogram was developed. The discriminatory capacity of the nomogram was evaluated using the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve, in addition to the calibration curve. Result: The study analyzed a total of 1,133 cases of severe acute osteomyelitis, divided into the survivor group (1,025 cases) and the non-survivor group (108 cases). Significant differences were observed between the two groups in terms of age, hypertension, sepsis, renal injury, and various laboratory indicators, including WBC, PLT, Ca2+, CRP, hemoglobin, albumin, and creatinine (P<0.05). However, no significant differences were found in race, gender, marital status, detection of wound microbiota, blood sugar, lactate, and ALP levels. A multivariate COX proportional hazards model was constructed using age, hypertension, sepsis, Ca2+, creatinine, albumin, and hemoglobin as variables. The results revealed that hypertension and sepsis had a significant impact on survival time (HR=0.514, 95% CI 0.339-0.779, P=0.002; HR=1.696, 95% CI 1.056-2.723, P=0.029). Age, hemoglobin, Ca2+, albumin, and creatinine also showed significant effects on survival time (P<0.05). However, no statistically significant impact on survival time was observed for the other variables (P>0.05). To predict the survival time, a nomogram was developed using the aforementioned indicators and achieved an AUC of 0.841. The accuracy of the nomogram was further confirmed by the ROC curve and calibration curve. Conclusion: According to the findings, this study establishes that a reduction in serum calcium levels serves as a distinct and standalone predictor of mortality among individuals diagnosed with severe acute osteomyelitis during their stay in the Intensive Care Unit (ICU) within a span of two years.

Dynamic Single Cell Transcriptomics Defines Kidney FGF23/KL Bioactivity and Novel Segment-Specific Inflammatory Targets.

FGF23 via its coreceptor αKlotho (KL) provides critical control of phosphate metabolism, which is altered in rare and very common syndromes, however the spatial-temporal mechanisms dictating renal FGF23 functions remain poorly understood. Thus, developing approaches to modify specific FGF23-dictated pathways has proven problematic. Herein, wild type mice were injected with rFGF23 for 1, 4 and 12h and renal FGF23 bioactivity was determined at single cell resolution. Computational analysis identified distinct epithelial, endothelial, stromal, and immune cell clusters, with differential expressional analysis uniquely tracking FGF23 bioactivity at each time point. FGF23 actions were sex independent but critically relied upon constitutive KL expression mapped within proximal tubule (S1-S3) and distal tubule (DCT/CNT) cell sub-populations. Temporal KL-dependent FGF23 responses drove unique and transient cellular identities, including genes in key MAPK- and vitamin D-metabolic pathways via early- (AP-1-related) and late-phase (EIF2 signaling) transcriptional regulons. Combining ATACseq/RNAseq data from a cell line stably expressing KL with the in vivo scRNAseq pinpointed genomic accessibility changes in MAPK-dependent genes, including the identification of FGF23-dependent EGR1 distal enhancers. Finally, we isolated unexpected crosstalk between FGF23-mediated MAPK signaling and pro-inflammatory TNF receptor activation via NF-κB, which blocked FGF23 bioactivity in vitro and in vivo . Collectively, our findings have uncovered novel pathways at the single cell level that likely influence FGF23-dependent disease mechanisms. Translational statement: Inflammation and elevated FGF23 in chronic kidney disease (CKD) are both associated with poor patient outcomes and mortality. However, the links between these manifestations and the effects of inflammation on FGF23-mediated mineral metabolism within specific nephron segments remain unclear. Herein, we isolated an inflammatory pathway driven by TNF/NF-κB associated with regulating FGF23 bioactivity. The findings from this study could be important in designing future therapeutic approaches for chronic mineral diseases, including potential combination therapies or early intervention strategies. We also suggest that further studies could explore these pathways at the single cell level in CKD models, as well as test translation of our findings to interactions of chronic inflammation and elevated FGF23 in human CKD kidney datasets.