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To analyze the risk factors for hospital-acquired infections following percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI) and to develop a nomogram prediction model. Clinical data from 324 AMI patients who underwent PCI between July 2021 and June 2023 were retrospectively analyzed. Patients were categorized into an infection group (n = 39) and a non-infection group (n = 285) based on the occurrence of nosocomial infection postoperatively. Optimal cutoff values were determined using receiver operating characteristic (ROC) curve analysis. Independent risk factors for nosocomial infection after PCI were identified through multivariate logistic regression, and a nomogram model was constructed accordingly. The model underwent internal validation via calibration curves, and its predictive performance was assessed using decision curve analysis. No significant differences were observed between the two groups in terms of gender, drinking history, smoking history, hypertension, infarct location, or number of stents implanted (all P  > 0.05). However, the infection group had significantly higher age, higher prevalence of diabetes, greater proportion of New York Heart Association (NYHA) class III/IV, more frequent invasive procedures, and longer hospital stays (all P  < 0.05). ROC analysis identified optimal cutoff values of 60 years for age and 6 days for hospitalization time. Multivariate logistic regression confirmed that age > 60 years, diabetes, NYHA class III/IV, invasive procedures, and hospital stay > 6 days were independent risk factors for nosocomial infection after PCI. The nomogram model demonstrated excellent discrimination, with a C-index of 0.915 (95% CI 0.877–0.953). The calibration curve indicated good agreement between predicted and observed outcomes. The nomogram provided higher net clinical benefit beyond threshold probabilities of 0.24 compared to individual predictors. A nomogram incorporating age, diabetes, cardiac function classification, invasive procedures, and hospitalization time was developed to predict the risk of nosocomial infection in AMI patients after PCI. The model exhibits strong predictive performance and may assist clinicians in identifying high-risk patients for intensified monitoring and preventive strategies. However, as a prognostic tool, it does not directly mitigate infection risk and requires external validation before routine clinical implementation.

Myasthenia gravis (MG) is an autoimmune disease characterized by muscle weakness and abnormal fatigability due to the antibodies against postsynaptic receptors. Despite the individual discrepancy, patients with MG share common muscle weakness, autoimmune dysfunction, and immunosuppressive treatment, which predispose them to infections that can trigger or exacerbate MG. Vaccination, as a mainstay of prophylaxis, is a major management strategy. However, the past years have seen growth in vaccine hesitancy, owing to safety and efficacy concerns. Ironically, vaccines, serving as an essential and effective means of defense, may induce similar immune cross-reactivity to what they are meant to prevent. Herein, we outline the progress in vaccination, review the current status, and postulate the clinical association among MG, vaccination, and immunosuppression. We also address safety and efficacy concerns of vaccination in MG, in relation to COVID-19. Since only a handful of studies have reported vaccination in individuals with MG, we further review the current clinical studies and guidelines in rheumatic diseases. Overall, our reviews offer a reference to guide future vaccine clinical decision-making and improve the management of MG patients.

Diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) are the most lethal brain tumors that primarily occur in pediatric and adult patients, respectively. Both tumors exhibit significant heterogeneity, shaped by distinct genetic/epigenetic drivers, transcriptional programs including RNA splicing, and microenvironmental cues in glioma niches. However, the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. Here, we perform a spatial profiling of DMG and GBM combining short- and long-read spatial transcriptomics, and single-cell transcriptomic datasets. We identify clinically relevant transcriptional programs, RNA isoform diversity, and multi-cellular ecosystems across different glioma niches. We find that while the tumor core enriches for oligodendrocyte precursor-like cells, radial glial stem-like (RG-like) cells are enriched in the neuron-rich invasive niche in both DMG and GBM. Further, we identify niche-specific regulatory programs for RG-like cells, and functionally confirm that FAM20C mediates invasive growth of RG-like cells in a neuron-rich microenvironment in a human neural stem cell derived orthotopic DMG model. Together, our results provide a blueprint for understanding the spatial architecture and niche-specific vulnerabilities of DMG and GBM. The spatial organisation of diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) remains to be investigated. Here, the authors integrate short-read and long-read spatial profiling of DMG and GBM to identify regulatory programs and cellular ecosystems in distinct glioma niches.

Regulatory B (Breg) cells represent a population of suppressor B cells that participate in immunomodulatory processes and inhibition of excessive inflammation. The regulatory function of Breg cells have been demonstrated in mice and human with inflammatory diseases, cancer, after transplantation, and particularly in autoinflammatory disorders. In order to suppress inflammation, Breg cells produce anti-inflammatory mediators, induce death ligand-mediated apoptosis, and regulate many kinds of immune cells such as suppressing the proliferation and differentiation of effector T cell and increasing the number of regulatory T cells. Central nervous system Inflammatory demyelinating diseases (CNS IDDs) are a heterogeneous group of disorders, which occur against the background of an acute or chronic inflammatory process. With the advent of monoclonal antibodies directed against B cells, breakthroughs have been made in the treatment of CNS IDDs. Therefore, the number and function of B cells in IDDs have attracted attention. Meanwhile, increasing number of studies have confirmed that Breg cells play a role in alleviating autoimmune diseases, and treatment with Breg cells has also been proposed as a new therapeutic direction. In this review, we focus on the understanding of the development and function of Breg cells and on the diversification of Breg cells in CNS IDDs.

Here, we introduce Trackplot, a Python package for generating publication-quality visualization by a programmable and interactive web-based approach. Compared to the existing versions of programs generating sashimi plots, Trackplot offers a versatile platform for visually interpreting genomic data from a wide variety of sources, including gene annotation with functional domain mapping, isoform expression, isoform structures identified by scRNA-seq and long-read sequencing, as well as chromatin accessibility and architecture without any preprocessing, and also offers a broad degree of flexibility for formats of output files that satisfy the requirements of major journals. The Trackplot package is an open-source software which is freely available on Bioconda ( https://anaconda.org/bioconda/trackplot ), Docker ( https://hub.docker.com/r/ygidtu/trackplot ), PyPI ( https://pypi.org/project/trackplot/ ) and GitHub ( https://github.com/ygidtu/trackplot ), and a built-in web server for local deployment is also provided.

The proper functioning of diverse biological systems depends on the spatial organization of their cells, a critical factor for biological processes like shaping intricate tissue functions and precisely determining cell fate. Nonetheless, conventional bulk or single-cell RNA sequencing methods were incapable of simultaneously capturing both gene expression profiles and the spatial locations of cells. Hence, a multitude of spatially resolved technologies have emerged, offering a novel dimension for investigating regional gene expression, spatial domains, and interactions between cells. Spatial transcriptomics (ST) is a method that maps gene expression in tissue while preserving spatial information. It can reveal cellular heterogeneity, spatial organization and functional interactions in complex biological systems. ST can also complement and integrate with other omics methods to provide a more comprehensive and holistic view of biological systems at multiple levels of resolution. Since the advent of ST, new methods offering higher throughput and resolution have become available, holding significant potential to expedite fresh insights into comprehending biological complexity. Consequently, a rapid increase in associated research has occurred, using these technologies to unravel the spatial complexity during developmental processes or disease conditions. In this review, we summarize the recent advancement of ST in historical, technical, and application contexts. We compare different types of ST methods based on their principles and workflows, and present the bioinformatics tools for analyzing and integrating ST data with other modalities. We also highlight the applications of ST in various domains of biomedical research, especially development and diseases. Finally, we discuss the current limitations and challenges in the field, and propose the future directions of ST.

In diabetic patients, diabetic retinopathy (DR) is the leading cause of blindness and seriously affects the quality of life. However, current treatment methods of DR are not satisfactory. Advances have been made in understanding abnormal protein interactions and signaling pathways in DR pathology, but little is known about epigenetic regulation. Non-coding RNAs, such as circular RNAs (circRNAs), have been shown to be associated with DR. In this review, we summarized the function of circRNAs and indicated their roles in the pathogenesis of DR, which may provide new therapeutic targets for clinical treatment.

Hepatitis B virus (HBV) damages liver cells through abnormal immune responses. Mitochondrial metabolism is necessary for effector functions of white blood cells (WBCs). The aim was to investigate the altered counts and mitochondrial mass (MM) of WBCs by two novel indicators of mitochondrial mass, MM and percentage of low mitochondrial membrane potential, MMPlow%, due to chronic HBV infection. The counts of lymphocytes, neutrophils and monocytes in the HBV infection group were in decline, especially for lymphocyte (p = 0.034) and monocyte counts (p = 0.003). The degraded MM (p = 0.003) and MMPlow% (p = 0.002) of lymphocytes and MM (p = 0.005) of monocytes suggested mitochondrial dysfunction of WBCs. HBV DNA within WBCs showed an extensive effect on mitochondria metabolic potential of lymphocytes, neutrophils and monocytes indicated by MM; hepatitis B e antigen was associated with instant mitochondrial energy supply indicated by MMPlow% of neutrophils; hepatitis B surface antigen, antiviral therapy by nucleos(t)ide analogues and prolonged infection were also vital factors contributing to WBC alterations. Moreover, degraded neutrophils and monocytes could be used to monitor immune responses reflecting chronic liver fibrosis and inflammatory damage. In conclusion, MM combined with cell counts of WBCs could profoundly reflect WBC alterations for monitoring chronic HBV infection. Moreover, HBV DNA within WBCs may be a vital factor in injuring mitochondria metabolic potential.

Background Sex chromosomes have arisen independently in a wide variety of species, yet they share common characteristics, including the presence of suppressed recombination surrounding sex determination loci. Mammalian sex chromosomes contain multiple palindromic repeats across the non-recombining region that show sequence conservation through gene conversion and contain genes that are crucial for sexual reproduction. In plants, it is not clear if palindromic repeats play a role in maintaining sequence conservation in the absence of homologous recombination. Results Here we present the first evidence of large palindromic structures in a plant sex chromosome, based on a highly contiguous assembly of the W chromosome of the dioecious shrub Salix purpurea . The W chromosome has an expanded number of genes due to transpositions from autosomes. It also contains two consecutive palindromes that span a region of 200 kb, with conspicuous 20-kb stretches of highly conserved sequences among the four arms that show evidence of gene conversion. Four genes in the palindrome are homologous to genes in the sex determination regions of the closely related genus Populus , which is located on a different chromosome. These genes show distinct, floral-biased expression patterns compared to paralogous copies on autosomes. Conclusion The presence of palindromes in sex chromosomes of mammals and plants highlights the intrinsic importance of these features in adaptive evolution in the absence of recombination. Convergent evolution is driving both the independent establishment of sex chromosomes as well as their fine-scale sequence structure.

The proteomic analysis of seminal plasma (SP) is a powerful tool for screening and identifying potential novel biomarkers of male infertility. However, the proteomic composition of seminal extracellular (SE) vesicles in varicocele (VC) is still poorly characterized. The main objective of the present study was to compare the proteome of SEs between infertile men with VC and fertile men without VC and to reveal differentially expressed SEs proteins (DESEPs) that can serve as potential novel biomarkers of VC‐associated infertility. SEs were isolated and purified from SP, and SEs proteins were extracted and labeled with TMT and analyzed by high‐resolution LC‐MS/MS. A total of 1457 proteins were quantitatively identified in these SEs samples. Of these proteins, 175 DESEPs (76 upregulated and 99 downregulated) were identified. Bioinformatics analysis indicated that the molecular functions and biological processes of these DESEPs were involved in metabolism, cell growth and/or maintenance, energy pathways, transport, and cell activation. Among these DESEPs of interest, PGK2 and LGALS3BP were validated by Western blotting. The expression level of the SEs LGALS3BP was also determined by ELISA. A significant positive association was observed between the concentration of SEs LGALS3BP and clinical characteristics. Moreover, receiver operating characteristic (ROC) curve analysis showed that SEs LGALS3BP had better predictive efficacy than seminal LGALS3BP as a potential diagnostic biomarker of VC‐associated infertility. Differences in the SEs protein profiles indicate that DESEPs may serve as potential biomarkers for VC‐associated infertility.