The detection of lymph node (LN) involvement is fundamental for staging colorectal cancer (CRC) and aids in clinical decision-making. Traditionally, determining LN status predominantly relies heavily on histological examination of LN specimens, which can occasionally lead to overtreatment. This study aims to develop a clinical prediction model using machine learning algorithms to assess the risk of mesenteric LN metastasis preoperatively, based on computed tomography images and clinicopathological data from CRC patients. Our findings demonstrate that the predictive model based on XGBoost algorithms exhibited the optimal performance, with area under the curve values consistently stable across training (0.836, 95% confidence interval [CI]: 0.750–0.902) and validation (0.831, 95% CI: 0.688–0.927) cohorts. The model was further elucidated using SHapley Additive Explanation values, which ranked predictors in the XGBoost model by their importance, providing insights into the model&s’s decision-making process. Additionally, the force plot visualizes the contribution of each variable to the prediction for individual samples. The as-obtained model may have the potential to aid in clinical treatment planning, optimize the selection of surgical methods, and guide the decision-making process for adjuvant therapy before surgery.

Platelets play an irreplaceable role in hemostasis and wound healing. However, beyond these classical roles, as the smallest anucleate cells in the blood stream, they are crucial for immune response which have inflammatory functions through specialized receptors and different signaling pathways, influencing both innate and adaptive immune response. Furthermore, many research have proved that platelets significantly contribute to tumor metastasis and are associated with poor prognoses in cancer patients through its coagulability and supporting an immunosuppressive tumor microenvironment. When tumor cells detach from the primary tumor mass and enter the bloodstream, they rapidly initiate the direct activation and adhesion of platelets, forming a protective microenvironment. This environment shields circulating tumor cells (CTCs) from the mechanical shear forces of blood flow and immune surveillance. Here we delve into the interaction between platelets and immunomodulation and explore the multifaceted roles and underlying mechanisms by which platelets influence tumor cell metastasis and tumor growth. Furthermore, we also discussed the diagnostic role of platelets in cancer occurrence and progression, as well as the feasibility and prospects of targeting platelets for antitumor immunotherapy. This review provides a multidimensional perspective and reference for platelet-related cancer treatment strategies and diagnosis.

Next-generation sequencing (NGS) has emerged as a transformative technology in oncology, revolutionizing cancer diagnostics and personalized treatment strategies. By providing comprehensive insights into the genetic landscape of tumors, NGS enables the identification of critical somatic and germline mutations, copy number variations (CNVs), and gene fusions. Over the past decade, advancements in NGS platforms have led to greater accuracy, speed, and cost-effectiveness, making it an integral part of cancer research and clinical diagnostics. Despite its widespread adoption, significant challenges remain, including the need for improved methods to detect minimal residual disease (MRD) and accurately profile tumor heterogeneity. This review explores the evolution of NGS technologies and their pivotal role in cancer biology, from early diagnostics to therapeutic guidance. It delves into the application of NGS in identifying CNVs and gene fusions, monitoring MRD, and the increasing relevance of targeted NGS and spatial genomics. Furthermore, the integration of spatial transcriptomics is highlighted as a frontier in understanding the tumor microenvironment. By addressing these critical aspects, this review provides a comprehensive overview of how NGS is shaping the future of cancer research and treatment, offering a complete overview of potential NGS applications in scientific and clinical oncology.

Acute ischemic stroke (AIS) is characterized by high morbidity and mortality, making it crucial to identify the risk factors that influence its occurrence and prognosis. Although individuals with thyroid dysfunction exhibit altered stroke patterns, evidence from observational studies remains inconsistent. Herein, we investigated the influence of thyroid dysfunction on stroke progression and prognosis. We combined Mendelian randomization (MR) and tandem mass tag (TMT)-based quantitative proteomics analysis to study the influence of thyroid dysfunction on AIS. Differentially expression proteins (DEPs) were subsequently identified, functional enrichment analysis was performed, and a protein–protein interaction (PPI) network was constructed. Protein alterations were further validated by western blot. MR analysis revealed a causal association between thyroid disorders and ischemic stroke. DEP analysis identified 38 downregulated proteins and five upregulated proteins. Functional enrichment analysis and PPI network construction highlighted the importance of immune response activation and acute phase pathways, along with the suppression of focal adhesion, regulation of the actin cytoskeleton, and platelet activation pathways. Vasodilator-stimulated phosphoprotein, MYL12B, MYL6, and TPM4 were identified as key DEPs significantly associated with pathological pathways and were verified by western blot. The identification of these key proteins and pathways provides new perspectives for investigating the progression and prognosis of AIS.

Intrauterine adhesion (IUA) is a common endometrial disease caused by injury, leading to reproductive health issues. Current treatments have limited effectiveness, side effects, and high recurrence rates, especially, in severe cases. However, the underlying molecular and cellular mechanisms are largely unknown. Here we performed a comprehensive analysis by profiling integrated single-cell transcriptomes of over 72,000 individual endometrial cells, encompassing samples from both patients with IUA and those with normal endometrium. We identified changes in cell type-specific molecular signatures, including the inflammatory activation in immune cells, extensive damage in epithelial subpopulations, and the deposition of collagen secreted by fibroblasts subpopulations. Our results demonstrated activation of the TREM2⁺ macrophages, which displayed properties of inflammatory regulation. Annexin A1⁺ NK subpopulations exhibited the highest susceptibility among NK subtypes, displaying decreased cellular density and the most pronounced differential gene expression. Furthermore, we identified the matrix metallopeptidase 7 (MMP7⁺) and C-C motif chemokine ligand 5 (CCL5⁺) unciliated epithelial subtype originated from pituitary tumor-transforming gene 1 (PTTG1⁺) unciliated epithelium as the most vulnerable subpopulations to epithelial injury. Collectively, our study offers integrated resources of the cellular microenvironment of IUA, serving as a comprehensive cellular map of the disease in affected individuals. The insights gained from this study are expected to provide valuable resources for future diagnostic and therapeutic approaches.

Long coronavirus disease (COVID) is characterized by persistent symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and has emerged as a significant health concern. As SARS-CoV-2 evolved from the wild-type strain to the Alpha, Beta, Delta, and Omicron variants, there may be a variant-specific influence on long COVID akin to the acute disease. This review aims to summarize our current knowledge of variant-specific influences in long COVID incidence, symptom profile as well as mechanisms of pathogenesis. We highlight that long COVID incidence may be lower with the Omicron variants. The symptom profile of long COVID may also show some dependence on the different variants, with a reduction in cardiopulmonary symptoms with more recent SARS-CoV-2 variants. This heterogeneity of long COVID may also be related to the variant-specific differences in affecting the immune system, viral persistence, and autoimmunity. However, emerging data also suggest that vaccinations may play a big role in shaping the presentation of long COVID. We also highlight ongoing work on long COVID incidence and symptom profiles in populations infected only by the Omicron variants. This will be beneficial toward more useful disease definitions and the development of effective diagnostic and therapeutic strategies.

Acute kidney injury (AKI) is a significant global healthcare burden but lacks specific and effective treatment. Renal tubular cells damage is central to ischemia-reperfusion injury (IRI) induced AKI. It is critical to clarify the initiation mechanisms of renal IRI and develop early intervention targets of AKI. This study used label-free quantification proteomic analysis to identify new targets in AKI-related renal tubular injury and investigate the potential mechanisms. We discovered significant changes in cysteinyl-tRNA synthetase (CARS) in renal tubular cell during IRI. Considering the involvement of CARS in ATP metabolism and the close correlation between ATP and pyroptosis, we further explored pyroptosis phenotype with and without CARS intervention as well as the expression of CARS during pyroptosis activation and inhibition. Our findings suggest that CARS expression decreased over time and is linked to pyroptosis. Modifying CARS affects ATP metabolism and alters the expression of pyroptosis-related proteins during H/R and IRI treatments. Regulating pyroptosis may influence CARS expression during IRI treatment. Overall, CARS is associated with renal tubular damage from ischemia-reperfusion injury, possibly involving pyroptosis, though the regulatory mechanism remains unclear.

Cancer immunotherapies, developed on the basis of research into tumor escape mechanisms, manipulate the immune system to reactivate an antitumor immune response to recognize and attack cancer cells. Immunotherapy has demonstrated promising and exciting outcomes in the treatment of many cancers, yet not all patients experience favorable responses. The gut microbiota plays a critical role in modulating the host immune system, influencing responses to cancer immunotherapy. Research has increasingly demonstrated that specific microbial communities can increase the efficacy of immune checkpoint inhibitors, although the mechanisms involved remain under investigation. However, a clear gap exists in the understanding of how bacterial therapies can be further optimized for cancer treatment. This review provides an in-depth analysis of current bacterial therapies used in clinical trials as adjuncts to cancer immunotherapy, summarizing common research approaches and technologies utilized to investigate gut microbiota interactions with the immune system. Additionally, advanced strategies for modifying bacteria, including genetic engineering, surface modifications, and the development of bacterial derivatives, are discussed. By synthesizing these findings, this review highlights the potential of microbiota-based therapies to improve immunotherapy outcomes and offers future directions for improving clinical applications.

Vancomycin (VAN)-intermediate Staphylococcus aureus (VISA) is a critical cause of VAN treatment failure worldwide. Multiple genetic changes are reportedly associated with VISA formation, whereas VISA strains often present common phenotypes, such as reduced autolysis and thickened cell wall. However, how mutated genes lead to VISA common phenotypes remains unclear. Here, we show a metabolism regulatory cascade (CcpA-GlmS), whereby mutated two-component systems (TCSs) link to the common phenotypes of VISA. We found that ccpA deletion decreased VAN resistance in VISA strains with diverse genetic backgrounds. Metabolic alteration in VISA was associated with ccpA upregulation, which was directly controlled by TCSs WalKR and GraSR. RNA-sequencing revealed the crucial roles of CcpA in changing the carbon flow and nitrogen flux of VISA to promote VAN resistance. A gate enzyme (GlmS) that drives carbon flow to the cell wall precursor biosynthesis was upregulated in VISA. CcpA directly controlled glmS expression. Blocking CcpA sensitized VISA strains to VAN treatment in vitro and in vivo. Overall, this work uncovers a link between the formation of VISA phenotypes and commonly mutated genes. Inhibition of CcpA-GlmS cascade is a promising strategy to restore the therapeutic efficiency of VAN against VISA infections.

Muscle atrophy, characterized by the loss of muscle mass and function, is a hallmark of sarcopenia and cachexia, frequently associated with aging, malignant tumors, chronic heart failure, and malnutrition. Moreover, it poses significant challenges to human health, leading to increased frailty, reduced quality of life, and heightened mortality risks. Despite extensive research on sarcopenia and cachexia, consensus in their assessment remains elusive, with inconsistent conclusions regarding their molecular mechanisms. Muscle atrophy models are crucial tools for advancing research in this field. Currently, animal models of muscle atrophy used for clinical and basic scientific studies are induced through various methods, including aging, genetic editing, nutritional modification, exercise, chronic wasting diseases, and drug administration. Muscle atrophy models also include in vitro and small organism models. Despite their value, each of these models has certain limitations. This review focuses on the limitations and diverse applications of muscle atrophy models to understand sarcopenia and cachexia, and encourage their rational use in future research, therefore deepening the understanding of underlying pathophysiological mechanisms, and ultimately advancing the exploration of therapeutic strategies for sarcopenia and cachexia.