Background: Hepatic perivascular epithelioid cell tumor (PEComa) is a rare tumor with malignant potential that is frequently misdiagnosed as hepatocellular carcinoma (HCC), despite requiring distinct treatment approaches. This study retrospectively investigated the imaging characteristics of PEComa and HCC without high-risk factors using conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) to improve preoperative diagnostic accuracy.

Materials and methods: Sixteen patients with pathologically confirmed PEComa and 31 patients with HCC and no known high-risk factors underwent preoperative ultrasound examinations. Imaging features from CUS and CEUS were systematically reviewed and compared. Independent predictive factors of PEComa were identified using multiple logistic regression analysis and diagnostic performance was assessed through receiver operating characteristic curve analysis. Bootstrap validation and optimism correction were applied to assess the stability and generalization performance.

Results: Of the 16 patients in the PEComa group, 11 underwent surgical resection and biopsies were performed in 5. PEComa exhibited distinct CUS imaging features, including a hyperechoic appearance, clear margins, and larger blood vessels around lesions. PEComa was characterized by the absence of necrosis, hyper- or iso-enhancement in the portal phase, isoenhancement in the delayed phase, and prolonged washout time (>180 s) on CEUS. Logistic regression analysis identified hyperechoic appearance, larger blood vessels around lesions, absence of necrosis, and prolonged washout time as independent predictors of PEComa. Integrating CUS and CEUS significantly improved diagnostic accuracy, achieving a sensitivity of 81.25%, a specificity of 96.77%, and an area under the receiver operating characteristic curve of 0.9395. Bootstrap validation and optimism correction confirmed the stability and generalization performance of the combined method.

Conclusion: This preliminary study demonstrated that the integration of CUS and CEUS provides high specificity and accuracy in distinguishing hepatic PEComa from HCC without high-risk factors. The identified imaging features should be considered as initial diagnostic indicators, facilitating accurate preoperative differentiation and supporting appropriate clinical management.

Immune checkpoint inhibitors (ICIs) have achieved remarkable efficacy in treating malignancies but may simultaneously induce immune-related adverse events (irAEs), among which ICI-related digestive system adverse events (ir-DSAEs) occur with relatively high frequency and present severe clinical manifestations. This review systematically examined ir-DSAEs, including clinical presentations, pathogenic mechanisms, risk factors, diagnostic approaches, and therapeutic strategies. It has been reported that ir-DSAEs primarily include colitis, hepatitis, and pancreatitis with underlying mechanisms involving T cell-mediated inflammatory responses, cytokine storm, activation of autoimmune reactions, and alterations in gut microbiota. The diagnosis of ir-DSAEs requires integration of multiple approaches. Standardized therapeutic strategies include treatment regimen adjustments, corticosteroid administration, use of selective immunosuppressants, and comprehensive supportive care. An in-depth understanding of ir-DSAEs has significant clinical implications for enhancing the safety and efficacy of ICI therapy, thereby providing a theoretical foundation for future precise prediction, prevention, and treatment of ir-DSAEs.

Traditional Chinese Medicine (TCM) provides rich pharmacological resources, among which charcoal medicine is a distinctive product of carbonization techniques. Renowned for its anti-inflammatory, hemostatic, and antidiarrheal properties, charcoal medicine has faced developmental limitations because of its unclear pharmacological mechanisms. The emergence of carbon dots (CDs), a nanomaterial with excellent biocompatibility and biochemical versatility, has provided novel perspectives in charcoal medicine. TCM-CDs, derived from TCM precursors such as charcoal medicine, serve as a bridge between traditional practices and modern nanomedicine. Combining high-temperature processing and advanced synthesis enables TCM-CDs to retain therapeutic properties while gaining nanoscale features. These molecules have shown potential in the treatment of neurological disorders, inflammation, and metabolic diseases, and in applications such as biomedical imaging and diagnostics. However, challenges such as incomplete structural characterization, inconsistent synthesis, and limited clinical validation remain. Future research should use advanced analytical methods, artificial intelligence (AI), and standardized protocols to achieve scalable production and quality control. Guided by TCM’s holistic philosophy, multifunctional TCM-CDs have potential to enhance therapeutic effects. By bridging traditional practices and modern nanomedicine, TCM-CDs highlight the modernization of charcoal medicine, and may open avenues for innovation and advancement in TCM research.

Premature ovarian insufficiency (POI) is a complex endocrine disorder characterized by premature depletion of ovarian follicles, and resulting in ovarian failure and decreased fertility. Conventional hormone replacement therapy (HRT) alleviates menopausal symptoms but carries potential risks, such as breast malignancies, and does not restore ovarian endocrine function. As a noninvasive physical therapy, low-intensity pulsed ultrasound (LIPUS) regulates cell proliferation, apoptosis, inflammation, and angiogenesis through mechanical stress, cavitation effects, and microstreaming, thus providing a novel therapeutic avenue for POI. In this review, we systematically analyze recent advances in the application of LIPUS in POI, demonstrating its mechanism of regulating ovarian function. We also analyze the combination of LIPUS with other therapies for POI and discuss prospects for LIPUS-based treatments.

Extracellular vesicles (EVs) are membrane-bound nanoparticles secreted by cells and have emerged as promising therapeutic agents for osteoarthritis (OA). These vesicles exhibit high biocompatibility and the intrinsic ability to traverse physiologic barriers, delivering bioactive molecular cargo to recipient cells to exert regulatory effects. To enhance therapeutic efficacy, EVs can be bioengineered to improve biological activity and targeting capacity toward specific cells or tissues. Strategies for EV engineering primarily involve modifications to cargo, membranes, or the pretreatment of parental cells. In recent years advances in EV engineering have led to growing interest in the application of engineered EVs for OA treatment, offering new possibilities for clinical translation. In this review we summarize the fundamental characteristics of EVs and examine the factors limiting the current therapeutic efficacy in OA. We also provide an overview of existing engineering strategies and discuss the therapeutic applications of engineered EVs in OA models. Finally, we outline the remaining challenges and future directions necessary to advance EV-based therapies toward clinical use in OA.

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.

Soft and sustainable wearable bioelectronics are emerging as key platforms for personal health monitoring and digital healthcare. These systems can continuously acquire electrical, mechanical, and biochemical signals during daily life by integrating skin-like soft materials, hydrogel-based interfaces, and environmentally conscious device architectures with wireless communication and data analytics and in some cases, deliver closed-loop interventions. Recent advances have enabled multimodal skin-interfaced patches for chronic disease management, soft cardiovascular and neural interfaces for long-term regulation, and intelligent hydrogel dressings for wound monitoring and therapy. At the same time, concepts of biodegradability, self-healing, and reduced electronic waste are being incorporated to align device lifetimes with therapeutic needs. In this Perspective, these key material and system-level strategies are summarized, representative applications in chronic diseases, cardiovascular and neural regulation, and wound care are highlighted, and the remaining challenges in long-term biocompatibility and stability, data governance and regulation, and the integration of artificial intelligence and miniaturized architectures for future soft bioelectronic systems are discussed.

In recent years, phytochemicals and medicinal plants have increasingly been used to treat autoimmune diseases, such as rheumatoid arthritis (RA). RA, a systemic inflammatory disease, is a chronic condition that affects primarily the joints, which are lined by synovial membranes, and leads to pain, diminished mobility, and joint deterioration. Oxidative stress, synovial hyperplasia, immune cell infiltration, and the production of pro-inflammatory cytokines, such as TNF-α and IL-6, are key factors in RA development. Herbal medicine is an effective alternative to conventional treatments, such as biologics, nonsteroidal anti-inflammatory drugs, and disease-modifying antirheumatic drugs, which are commonly used but can lose effectiveness or cause adverse effects. Phytotherapy therefore provides a promising complementary approach. This review provides an in-depth analysis of the pathophysiology of RA, therapeutic targets, drug resistance, and current therapeutic boundaries, with a focus on the roles of phytochemicals such as lignans, flavonoids, alkaloids, terpenoids, and phenolic compounds. By targeting key pro-inflammatory cytokines such as TNF-α and IL-6, and reformed molecular pathways such as those involving NF-κB, MAPK, and Nrf2/HO-1, these phytochemicals have potent anti-inflammatory and anti-rheumatoid arthritis properties.

Background: Alzheimer’s disease (AD) is a neurodegenerative disorder and the leading cause of dementia worldwide. Microglia, as central nervous system (CNS) resident macrophages, are key to AD pathology. Indeed, microglia aggregation around amyloid-β (Aβ) deposits is an AD hallmark. Triggering receptor expressed on myeloid cells 2 (TREM2) regulates microglial function. TREM2 boosts microglial responses to AD pathologic damage, drives homeostatic activation, and modulates protective pathways. Anti-human TREM2 agonist monoclonal antibody (hT2AB) serves as an alternative TREM2 ligand and has therapeutic potential in TREM2-mutant mouse models. The current study combined single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to clarify hT2AB molecular and cellular mechanisms in improving AD and analyze microglial dynamics in hT2AB-treated groups during AD progression. Key functional subpopulations and core biomarkers were identified through pseudo-time analysis, cell communication analysis, and transcription factors (TFs) with a focus on the differentiation process of microglia towards a therapeutic phenotype, providing a theoretical basis and potential targets for optimizing AD treatment.

Methods: scRNA-seq, spatial transcriptomics, and deconvolution analysis depicted microglia in AD. Differentially expressed genes underwent enrichment analyses. Pseudotemporal analysis demonstrated microglial dynamic differentiation paths during AD progression and post-hT2AB treatment. The CellChat package constructed the cell communication network. Finally, pySCENIC analysis identified key TFs in key subpopulations.

Results: Seven functionally heterogeneous microglial subpopulations were identified with the C2 subpopulation highly expressed in the hT2AB group subpopulation. The proposed temporal sequence analysis revealed two distinct microglial cell differentiation trajectories, both originating from the C6 and C7 subpopulations and extending in different directions starting from the C2 subpopulation. Lineage1-related subpopulations (C7-C6-C4-C2-C1-C5) when combined with pathway activity scoring were confirmed to align with microglial transformation toward protective phenotypes. This study also identified core biomarkers that were highly expressed in the C2 subpopulation (the critical turning subpopulation of two trajectories). In addition, this study combined the spatial transcriptome data of AD mouse brain tissue sections, providing direct evidence for the spatial distribution of key cell subpopulations and pathways.

Conclusion: This study identified the C2 microglial subpopulation as the key effector regulated by hT2AB in AD pathology. hT2AB was confirmed to guide microglia toward protective differentiation, providing cell-level direct evidence for the therapeutic effect. The results deepen our understanding of AD brain microglial heterogeneity and the hT2AB mechanism of action, offering reliable evidence for developing new AD biomarkers and optimizing TREM2-targeted therapies, and is expected to improve AD clinical outcomes.

This review summarizes recent advances in the application of graphene oxide (GO) in sports medicine with an emphasis on cartilage repair, skeletal muscle regeneration, ligament and tendon repair, and tendon–bone (enthesis) healing. Owing to the distinctive physicochemical properties and favorable biocompatibility, GO exhibits considerable promise across these indications. We first outline the chemical structure and physical characteristics of GO, then discuss mechanistic roles that underpin the performance of GO in different disease contexts. We further synthesize evidence that GO strengthens biomaterials mechanically and enhances cellular adhesion and lineage commitment, which promotes tenogenic, chondrogenic, and myogenic differentiation, as well as enthesis formation. Despite these advantages, important questions remain regarding the biosafety and long-term in vivo stability of GO. Future work should prioritize rational chemical functionalization and composite design to tailor GO-based materials to specific tissue-repair requirements with the development of next-generation GO scaffolds that better recapitulate the human biomechanical milieu. In parallel, multi-omics interrogation of GO–cell interactions will deepen our mechanistic understanding and guide material optimization. Addressing these key challenges will enable GO to have a larger role in cartilage repair and sports medicine, accelerating progress in the field.

Clinical trials bridge basic research and clinical application, serving as essential steps in drug development. This review examines clinical trial phases (Phase I [safety assessment], Phase II [efficacy evaluation], Phase III [large-scale validation], and Phase IV [post-marketing surveillance]), highlighting the distinct characteristics and interconnections. Major challenges are identified, including ethical compliance, participant recruitment, and ensuring diversity and representativeness in trial populations, while proposing evidence-based mitigation strategies. To address these challenges, innovative technologies, such as artificial intelligence, big data analytics, and digital health tools, are transforming trial design and implementation, enhancing efficiency and data quality. Looking forward, the review explores how emerging therapies, including gene therapy and immunotherapy, are reshaping trial design requirements and emphasizes the growing importance of regulatory harmonization and global collaboration. Clinical trials remain central to advancing innovative drug development and improving patient outcomes.

According to World Health Organization (WHO) reports, parasitic infections substantially affect the world’s population and are responsible for more than 16 million annual deaths in developing countries. Trichomoniasis, giardiasis, cryptosporidiosis, and toxoplasmosis, the most common helminthic infections in humans, are treated with anthelmintics and antibiotics that achieve synergistic effects. The key anthelmintic drug Albendazole (ABZ) has drawbacks of low solubility. Anthelmintics fall under biopharmaceutics classification system (BCS) class II and are therefore administered through conventional approaches and novel nanomedicine techniques to enhance their biopharmaceutical properties and therapeutic efficacy. This review examined the literature on anthelmintics with appreciable benefits. Because the nanomedicine development of ABZ was contemporaneous with its repurposing as an anticancer agent, with or without nanoformulation, this review also addresses the repositioning of ABZ to treat diverse cancers including colon cancer, brain tumors, malignant melanoma, and breast cancer.

Background: Gallbladder and biliary tract cancers (GBTCs) are highly lethal malignancies with a heterogeneous global burden. Most existing epidemiological studies have been regional and descriptive, and have lacked systematic analysis of worldwide spatiotemporal trends, socioeconomic associations, and future projections. Therefore, this study was aimed at comprehensively assessing global GBTCs burden from 1990 to 2021, analyzing its association with socioeconomic development, and projecting trends to 2040.

Methods: Using data from the Global Burden of Disease (GBD) 1990–2021 study, we evaluated global trends in GBTC incidence, mortality, prevalence, and disability adjusted life years (DALYs). Age standardization was applied for comparability. Analytical methods included joinpoint regression for temporal trends, correlation analysis with the Socio-demographic Index (SDI), frontier analysis to benchmark performance, and AIMA modeling to project age-standardized incidence and mortality rates to 2040.

Results: The analysis revealed a dual burden pattern characterized by global declining age-standardized mortality and DALY rates alongside rising absolute case counts attributable to population growth and aging. Age-standardized incidence rates positively correlated with SDI. Males consistently carried a higher burden than females across all metrics. Projections indicated a continuing increase in male age-standardized incidence rates through 2040, whereas female rates were predicted to remain stable.

Conclusions: The global GBTC burden is characterized by a dual challenge of decreasing severity but expanding scale, including sex and socioeconomic gradients. These findings support a need for differentiated public health strategies. High-SDI regions should target metabolic risk factors and survivorship care, whereas low- and moderate-SDI regions require enhanced efforts in early diagnosis and management of traditional risk factors. Tailored, context-specific interventions are essential for effective global cancer control.

Ocular drug delivery systems are essential for treating various eye conditions. Ocular conventional drug delivery techniques, such as eye drops (topical administration), often face challenges, like rapid drainage and low bioavailability. To overcome these challenges, scientists have developed ocular inserts with sustained delivery systems. Biocompatible materials, such as hydrogels, polymers, and biodegradable nanoparticles, have been investigated for insert manufacturing. These materials provide controlled release, improved retention time in the outer surface of the eye, and enhanced penetration of active pharmaceutical ingredients passing through the corneal barrier. Innovations in contact lens technology have made it possible to develop drug-loaded lenses that can deliver drugs in a sustained manner directly to the ocular surface by enhancing drug retention time and therapeutic efficacy. Microneedle-based ocular delivery, a relatively new methodology, has made progress by open-hollow and biodegradable microneedles that permit minimally invasive penetration to the sclera or cornea. Microneedle-based ocular delivery provides high bioavailability with prolonged release of drugs. The introduction of smart polymers, nanotechnology, and 3D printing with these systems has enhanced accuracy, patient comfort, and therapeutic efficacy. Together, these advances represent an evolution from current topical ocular treatment options to long-acting, patient-comfort ocular therapies with high efficacy and accuracy.

Low-intensity pulsed ultrasound (LIPUS) provides a non-invasive, quantifiable, and deep stimulation method for acupoints, offering a promising alternative to manual acupuncture. This review summarizes evidence indicating the efficacy of LIPUS in regulating internal organ functions via meridian-based mechanisms, demonstrating improvements in gastrointestinal motility, reducing inflammation, and enhancing tissue regeneration. Mechanistically, LIPUS acts through multiple pathways, including neural, immune, and cellular pathways, sharing common ground with acupuncture, while differing in its biomechanical mode of action. Despite encouraging results, variations in treatment parameters and a paucity of large-scale randomized trials limit broader clinical use. By bridging traditional meridian theory with biophysical principles, LIPUS exemplifies a modernized strategy for complementary medicine. Future well-controlled studies are essential to establish standardization and validate therapeutic applicability.

The tumor vasculature, characterized by pathological angiogenesis and structural abnormalities, drives the progression of solid tumors by inducing hypoxia-acidosis microenvironments and therapeutic resistance. Targeting the tumor vasculature has emerged as a critical therapeutic strategy. Although conventional approaches such as anti-angiogenic drugs, vascular disrupting agents, and embolization have shown efficacy, their single-target focus hinders addressing tumor heterogeneity and evolving stage-specific needs. For example, rapid vascular disruption is effective for debulking advanced tumors, whereas vascular normalization enhances early- to mid-stage therapy by improving postoperative chemo-radiotherapy outcomes. Unlike single-mechanism interventions, ultrasound modulates acoustic parameters to achieve diverse effects including angiogenesis suppression, vessel disruption, and vasodilation, thus addressing multi-stage vascular needs. Ultrasound-based monitoring systems provide precise, dynamic vascular assessments to guide intervention strategies. Compared with traditional static imaging ultrasound offers real-time angiogenesis visualization and therapeutic response evaluation, thus enabling treatment optimization. This review synthesizes recent advances in ultrasound-based vascular targeting, emphasizing its dual role in spatiotemporally adaptive therapy and angiogenesis monitoring. We critically examine clinical translation challenges and future directions, highlighting how ultrasound-driven strategies, by bridging mechanistic precision with clinical scalability, might enable personalized, multi-effect therapeutic paradigms in oncology.

Background: Bone marrow mesenchymal stem cell (BMSC) therapy holds great promise for regenerative medicine, but its clinical translation is hindered by the lack of non-invasive, real-time methods to track transplanted cell fate in vivo. Although photoacoustic (PA) imaging offers deep-tissue penetration and high sensitivity, existing cell-labeling strategies relying on endocytosis of contrast agents have drawbacks of prolonged incubation times and variable efficiency, thus potentially compromising cell viability and function.

Methods: To address these limitations, we developed a rapid, bioorthogonal pre-labeling strategy. Azide (N₃) groups were first metabolically engineered onto BMSC surfaces. Subsequently, dibenzocyclooctyne (DBCO)-functionalized gold nanostars (Au-star-DBCO) were conjugated to the cells via a highly efficient, copper-free click reaction, thereby enabling covalent membrane anchoring.

Results: This approach achieved rapid and specific stem cell labeling within 3 h, with an efficiency of 83.1% ± 0.67. The labeling process did not impair BMSC viability or multilineage differentiation potential. The Au-star-DBCO-labeled BMSCs generated strong, concentration-dependent PA signals both in vitro and in a rat subcutaneous model, and enabled dynamic monitoring for at least 72 h post-transplantation. The specificity of the bioorthogonal reaction provided a significantly higher signal-to-noise ratio than passive uptake methods.

Conclusions: We successfully established a biocompatible and efficient platform for stem cell tracking by integrating metabolic glycoengineering, bioorthogonal chemistry, and nanostar-enhanced PA imaging. This strategy overcomes key limitations of traditional endocytosis-based labeling, and offers a rapid, specific, and functional cell-compatible tool for sensitive, longitudinal in vivo monitoring. This platform may advance precise assessment of cell therapies and facilitate their clinical application.

Background: Marker-based motion capture remains the gold standard for deriving lower-limb kinematics and kinetics, but its high cost, lengthy setup time, and large space requirements limit its widespread use. Markerless technologies, such as depth camera systems (e.g., Azure Kinect) and emerging smartphone-based pipelines (e.g., OpenCap), promise laboratory-grade motion capture without markers. However, the effects of their capture data on musculoskeletal multibody dynamics simulation outcomes remain insufficiently understood.

Methods: This study was aimed at developing a single lower-limb musculoskeletal model simultaneously driven by two markerless motion capture inputs (Azure Kinect and OpenCap), and benchmarking the resulting joint angles, ground-reaction forces, and joint contact forces against synchronous Vicon recordings. In gait trials, movements were simultaneously recorded with Azure Kinect, OpenCap, and a Vicon motion capture system. The collected data were processed and used as inputs to construct the musculoskeletal model, which was then combined with a foot-ground contact model to compute lower-limb joint angles, ground reaction forces (GRFs), and joint contact forces.

Results: The OpenCap-based model showed strong agreement with the Vicon-referenced model (ρ > 0.73) in hip flexion-extension (FE), knee FE, and ankle FE, with a root mean square error (RMSE) of 4.04° to 7.66°, Sprague and Geers magnitude error ( M) of −0.25 to −0.10, phase error ( P) of 0.08 to 0.25, and composite error ( C) of 0.16 to 0.39. Additionally, strong correlations (ρ > 0.77) in hip contact force, knee contact force, medial knee contact force, and ankle contact force were observed between OpenCap and Vicon, with an RMSE of 0.26 to 0.90 Body Weight (BW), M of −0.03 to 0.13, P of 0.05 to 0.08, and C of 0.08 to 0.17.

Conclusions: Overall, under the study conditions, the smartphone-based OpenCap preliminarily showed accuracy as a potential alternative to marker-based systems for estimating lower-limb biomechanics. However, given the small sample size and tasks restricted to walking, it is currently primarily suited for research settings or initial screening, rather than high-precision clinical diagnosis. Further studies in larger, more diverse cohorts and validation across dynamic activities are required to confirm and extend its applicability.

Background: In multiple sclerosis (MS), chronic “smoldering” lesions are driven by microglial activation, which promotes demyelination and disease progression. However, microglia exhibit a functional dichotomy by performing both neurotoxic and reparative roles. Precisely modulating these functions remains a major therapeutic challenge, because non-specific approaches can inadvertently impair beneficial microglial functions. Delineating microglial subtypes in chronic MS is therefore essential for targeted therapy.

Methods: Single-cell RNA sequencing, spatial transcriptomics, deconvolution, and pseudotime trajectory mapping were used to characterize cell subtypes. Subsequent investigations encompassed functional annotation, differential gene expression profiling, cell-cell communication pathways, and transcription factor network analysis.

Results: We identified six distinct microglial subtypes with varied functions and focused on the highly disease-relevant C2 microglial subtype. This subtype simultaneously exhibited enhanced phagocytic and pro-inflammatory functions potentially associated with the fatty acid metabolic pathway. Pseudotime trajectory analysis suggested that this subtype is likely to represent a late disease stage. Cell-cell communication analysis revealed interactions between this subtype and both oligodendrocytes and T cells, as further supported by spatial transcriptomics demonstrating co-localization of the C2 microglial subtype with T cells. Finally, transcriptional regulatory network analysis identified an association between the FOSL2 regulon and both the C2 microglial subtype and chronic MS.

Conclusion: Through integrated single-cell sequencing approaches, we identified a C2 microglial subtype in chronic MS that might contribute to disease progression via pro-inflammatory functions. We propose the transcription factor FOSL2 as a promising hypothesis-generating candidate for future studies aimed at modulating microglial differentiation toward a less harmful state. Our findings provide mechanistic insights into the pathology of white matter lesions in chronic MS and suggest novel subtype-specific directions for the development of next-generation disease-modifying therapies.

Background: Inflammatory bowel disease (IBD) and Alzheimer’s disease (AD) are major global health burdens that are rising in prevalence but are typically studied as distinct disorders. This study systematically characterizes the convergent risk architecture between IBD and AD using integrated epidemiological, causal, and molecular approaches.

Methods: Global epidemiology, Mendelian randomization (MR), and in silico transcriptomic cross-validation were integrated. Global Burden of Disease 2021 data from 204 countries (1990–2021) were analyzed. Two-sample MR was conducted using inverse-variance weighted (IVW) as the primary method, with weighted median, MR-Egger, and MR-PRESSO as sensitivity analyses to assess causal effects of genetically proxied lifestyle and socio-environmental factors on IBD and AD. Cross-disease transcriptomic analyses were performed to identify shared pathways.

Results: Parallel increases in IBD and AD burden were observed, with pronounced sociodemographic disparities and a steep rise in AD in aging, high-sociodemographic index (SDI) populations. Higher genetically proxied educational attainment was associated with reduced risk of IBD (odds ratio [OR] = 0.87, 95% confidence interval [CI] = 0.80–0.94) and AD (OR = 0.82, 95% CI = 0.74–0.91). Higher coffee consumption increased IBD (OR = 1.20, 95% CI = 1.09–1.33) and AD risk (OR = 1.19, 95% CI = 1.05–1.35). Higher beef intake had an inverse association with IBD (OR = 0.48, 95% CI = 0.27–0.88) and AD (OR = 0.0012, 95% CI = 0.0006–0.0025). Transcriptomic analyses demonstrated concordant dysregulation of inflammatory and immune pathways, including TNF/NF-κB signaling. Projections indicated a continued escalation of AD burden to 2050.

Conclusions: Convergent epidemiologic, causal, and molecular evidence indicates that IBD and AD share modifiable determinants along the gut–brain axis. These findings highlight opportunities for coordinated prevention strategies targeting chronic inflammatory disease trajectories.

Extracellular vesicles (EVs) are nanoscale membrane structures secreted by cells that contain proteins, nucleic acids, and lipids, and reflect the physiologic state of the parent cells. EVs have a critical role in intercellular communication, signal transduction, and tumorigenesis, influencing tumor progression, metastasis, and remodeling of the tumor microenvironment. Recent advances have highlighted the potential of EVs as natural nanocarriers for cancer therapy that offer advantages, such as biocompatibility, low immunogenicity, and the ability to cross biological barriers. Engineered EVs may overcome many of the limitations of natural EVs, including the low yield, heterogeneity, and limited targeting capabilities. Engineered EVs have shown promise in preclinical studies through genetic engineering, surface modification, and optimized loading strategies in the delivery of therapeutic agents, such as CRISPR/Cas9, mRNA, siRNA, and drugs with enhanced precision and efficacy. EVs loaded with CRISPR/Cas9 plasmids targeting PARP-1 have been shown to induce apoptosis in ovarian cancer cells and increase the sensitivity to cisplatin. Engineered EVs expressing PD-1/PD-L1 blocking antibodies have demonstrated potent anti-tumor immune activity in melanoma models by reactivating exhausted T cells, highlighting the potential for use in cancer immunotherapy. These EVs have been studied in preclinical settings involving targeted therapy, immunotherapy, and combination therapies, such as chemo-photothermal approaches, with the potential to overcoming multidrug resistance and improving treatment outcomes. Despite the promise of EVs, challenges remain in large-scale production, purification, and standardization. Corollary studies are warranted to optimize EV engineering, enhance safety, and evaluate the potential for clinical translation in oncology.

Smart hydrogels are attracting considerable interest in the biomedical field, because of their high water content, excellent biocompatibility and biodegradability, and distinctive properties in response to stimuli. Their three-dimensional mesh structure effectively mimics the microenvironment of human tissue, by maintaining moist conditions conducive to wound healing while also serving as a support for active ingredients, thus ensuring their precise and controlled release. Consequently, these materials have excellent potential for use in tissue regeneration. This article first classifies smart hydrogels according to their response mechanisms, specifically systems that respond to temperature, pH, light, and magnetic fields. It then systematically examines potential applications of smart hydrogels in tissue regeneration, according to their ability to dynamically adapt to different tissue microenvironments, particularly the regeneration of skin, bone and cartilage, nerve tissue, and internal organs. Despite their promising potential, smart hydrogels still face several challenges, including imbalances in the rates of tissue degradation and regeneration, insufficient mechanical properties, and relatively limited functionality. Future research should focus on material modification and optimization, AI-assisted design, and interdisciplinary collaboration between medicine and engineering to develop hydrogels’ multifunctional, personalized integration and clinical application, and ultimately enable smarter, more effective solutions for tissue engineering and regenerative medicine.

Pulmonary fibrosis (PF) is a progressive and irreversible interstitial lung disease that is characterized by destruction of alveolar architecture, excessive proliferation of fibroblasts, and aberrant deposition of extracellular matrix (ECM) but the precise pathogenesis has yet to be fully elucidated. Although traditionally regarded as the terminal metabolite of glycolysis, lactate has been reappreciated, especially following the rise of metabolic reprogramming concepts after the Warburg effect, as an important signaling molecule capable of actively regulating diverse cellular functions. Among these cellular functions, the lactate-induced post-translational modification (PTM), known as lactylation, offers a new perspective for understanding the broad biological actions of lactate beyond metabolism. Notably, the pathologic microenvironment of PF is characterized by widespread metabolic reprogramming and lactate accumulation, suggesting that lactate and lactate-mediated lactylation may serve key roles in disease progression by regulating pro-fibrotic gene expression and influencing fibroblast activation and differentiation. Therefore, this review focuses on how lactylation functions as a bridge linking metabolic reprogramming to fibrotic phenotypes in PF and the translational potential as a novel therapeutic target is discussed.

Objective: Latent tuberculosis infection (LTBI) is difficult to diagnose due to the lack of a definitive gold standard. This study aimed to explore plasma metabolic alterations associated with LTBIs using an untargeted metabolomics approach.

Design: In this discovery-phase study, LTBI individuals (QuantiFERON-TB Gold-positive) were recruited from close contacts of tuberculosis patients, while non-LTBI individuals (QuantiFERON-TB Gold-negative) were recruited from prison detainees. Plasma samples were analyzed using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry. Multivariate statistical analysis combined with univariate screening was used to identify differential metabolites, followed by receiver operating characteristic analysis.

Results: A total of 43 metabolites showed significant differences between the LTBI (n = 100) and non-LTBI groups (n = 99). Among the 43 metabolites, leucylleucine, tryptophyl-phenylalanine, lysoPE(18:1(11Z)/0:0), and biliverdin displayed relatively high discriminatory ability in this discovery cohort with area under the curve values ranging from 0.975–0.981. Models combining selected metabolites achieved higher apparent classification performance under internal validation, with some area under the curve values approaching 1.00. However, because feature selection and model evaluation were performed within the same cohort and no external validation was performed, these results may overestimate true diagnostic performance.

Conclusions: This study provides exploratory evidence of plasma metabolic differences between LTBI and non-LTBI individuals and identifies four metabolites of potential interest. However, the two groups were drawn from different source populations, which may introduce selection bias and unmeasured confounding. In addition, all metabolites were identified at Metabolomics Standards Initiative level 2 without confirmation using authentic standards and no targeted validation was performed. Therefore, these findings should be interpreted as preliminary and hypothesis-generating. Independent validation in well-matched cohorts with targeted metabolomic approaches is required before any clinical interpretation.

Background: Insulin resistance (IR) and chronic kidney disease (CKD) are independent risk factors for cardiovascular disease (CVD). The triglyceride-glucose (TyG) index is recognized as a convenient marker for IR, while the estimated glomerular filtration rate based on both creatinine and cystatin C (eGFRcr-cys) is commonly used to evaluate kidney function. Therefore, the TyG:eGFRcr-cys ratio is introduced with the aim of obtaining a more effective predictor for CVD risk.

Method: This prospective cohort analysis included 261,865 UK Biobank participants with available information. Cox proportional hazards models were used to evaluate the associations of TyG, eGFRcr-cys, and the TyG:eGFRcr-cys ratio with incident CVD. Restricted cubic splines for model fitting with three knots placed at the 10^th, 50^th, 90^th percentiles were used to determine the non-linear relationship between the TyG:eGFRcr-cys ratio and CVD. Furthermore, subgroup and sensitivity analyses were performed to illustrate the disparate associations across diverse groups and to reinforce the conclusions drawn, respectively. An independent single-center clinical cohort was assembled from the First Affiliated Hospital of Zhengzhou University for external validation by enrolling consecutive patients between 2018 and 2020 with baseline TyG index and eGFRcr-cys measurements and up to 4 years of follow-up. External validation with major adverse cardiovascular events was further performed as the outcome and observed consistent dose–response associations and robust risk stratification for the TyG:eGFRcr-cys ratio.

Result: Following extensive covariate adjustment, the hazard ratios [HRs] (95% confidence intervals [CIs]) for total CVD across increasing quartiles of the TyG:eGFRcr-cys ratio, with the lowest quartile (Q1) as the reference, were 1.15 (1.10–1.21) for Q2 versus Q1, 1.17 (1.12–1.23) for Q3 versus Q1, and 1.24 (1.18–1.30) for Q4 versus Q1, respectively, for the TyG:eGFRcr-cys ratio. In addition, each standard deviation increase in the TyG:eGFRcr-cys ratio was associated with a higher risk of CVD, coronary heart disease, and stroke, corresponding to estimated increases of 249% [HR, 3.49; 95% CI, 2.94–4.15], 250% [HR, 3.50; 95% CI, 2.92–4.20], and 165% [HR, 2.65; 95% CI, 1.80–3.90], respectively, in the fully adjusted models. The non-linear relationship between the TyG:eGFRcr-cys ratio and CVD ( P-value for the overall model < 0.001 and P-value for the non-linear model < 0.001) indicated that the CVD risk increased as the TyG:eGFRcr-cys ratio increased. Subgroup analysis results suggested that these associations were more pronounced in White individuals and females.

Conclusion: As the TyG:eGFRcr-cys ratio increased, the risk of CVD also increased with a higher likelihood in females and White individuals.

Skeletal healing is constrained by a long-standing paradox. Specifically, analgesia is clinically essential, yet neural signaling is biologically required for effective repair. Recent evidence showed that bone-innervating sensory neurons are temporally plastic rather than functionally fixed. After injury, these neurons transition from an early nociceptive state to a later pro-regenerative secretory program, including trophic factors that are required for periosteal progenitor expansion and successful callus formation. Importantly, this switch is better interpreted as stage-linked than clock-like, broadly tracking the evolution from inflammatory injury signaling toward reparative callus formation with timing varying by skeletal site, age, and injury context. This dynamic framework helps explain why broad neural inhibition can relieve pain, while inadvertently compromising osteogenesis. The translational implication is not to reduce analgesia but to redesign analgesia. Future strategies should decouple nociceptive suppression from the loss of regenerative neural output. Defining therapeutic time windows and modality-specific effects on neurotrophic signaling as well as pain and developing biomarker-guided rescue strategies will be essential for next-generation skeletal management that preserves pain control and biological healing.

Background: Cell death pathways have crucial roles in cancer development, immune responses, and disease progression. With the discovery of 14 distinct types of regulated cell death, there is a critical need for integrated analytical tools that can simultaneously evaluate multiple cell death pathways in transcriptomic data.

Methods: We developed CellDeathAnalysis (v0.4.0), an R package providing a unified framework for analyzing 14 cell death pathways in bulk RNA-seq data. The package introduces two novel algorithms: Crosstalk-Aware Pathway Scoring, which uses gene specificity weighting (inverse document frequency-inspired) and residual debiasing to reduce redundancy from inter-pathway gene overlap; and Cell Death Subtype Classification, which uses consensus clustering on pathway score profiles to identify biologically meaningful patient subtypes. The package integrates curated gene sets from FerrDb, MSigDB, KEGG, and the primary literature, and implements multiple scoring methods (z-score, ssGSEA, GSVA, and AUCell, and the novel crosstalk-aware method), survival analysis, enrichment analysis, and publication-ready visualizations.

Results: By applying CellDeathAnalysis to 2704 The Cancer Genome Atlas (TCGA) samples across four cancer types (BRCA, LUAD, LIHC, and STAD), the crosstalk-aware method reduced inter-pathway correlation (mean reduction = 0.69) compared to z-score scoring. The disulfidptosis score in LUAD exhibited a significant survival association (HR = 2.19, P_adj = 0.037). Consensus clustering identified clinically meaningful subtypes in LIHC ( P = 0.017) and STAD ( P = 0.028).

Conclusions: CellDeathAnalysis provides the first dedicated toolkit for multi-pathway cell death analysis with novel crosstalk-aware scoring and subtype classification capabilities. The package addresses the critical challenge of gene overlap between cell death pathways and enables discovery of clinically meaningful patient subtypes.

Background: Fat mass and obesity-associated protein (FTO), an epitranscriptomic regulator, has been implicated in cancer progression and immune regulation but the therapeutic relevance in pancreatic cancer is unclear.

Methods: TCGA and GTEx transcriptomic datasets were analyzed to evaluate FTO expression and prognostic associations in pancreatic cancer. Candidate FTO-targeting compounds were identified by active learning-assisted virtual screening of > 22 million compounds. The lead candidate, DE19725241, was further assessed by binding pose metadynamics, molecular dynamics simulations in multiple environments, MM/GBSA calculations, and in vitro testing in three pancreatic cancer cell lines and one normal pancreatic epithelial cell line.

Results: FTO was overexpressed in pancreatic tumors and associated with poorer overall survival. DE19725241 showed favorable predicted interactions with FTO, particularly with ARG-96, TYR-108, and GLU-234, and exhibited moderate but selective antiproliferative activity in pancreatic cancer cells.

Conclusions: DE19725241 represents a potential early-stage scaffold for developing FTO-targeted strategies in pancreatic cancer.

Skin wound healing, especially in chronic non-healing conditions, such as diabetic foot ulcers and infected wounds, remains a formidable clinical challenge due to the complex pathophysiologic mechanisms and prolonged repair processes. Hydrogels have emerged as ideal wound dressing platforms because of the high water content, excellent moisture-retention capacity, superior biocompatibility, and structural similarity to the extracellular matrix. In recent years bioactive polysaccharides derived from Traditional Chinese Medicine (TCM), including Bletilla striata polysaccharide (BSP), Astragalus polysaccharide (APS), and Dendrobium officinale polysaccharide (DOP), have attracted increasing attention for the construction of functional wound-healing hydrogels. This growing interest is driven by the intrinsic multifunctional bioactivities, such as anti-inflammatory, antioxidant, immunomodulatory, pro-angiogenic, and hemostatic effects, which position bioactive polysaccharides as promising “all-in-one” therapeutic biomaterials. This review systematically summarizes recent advances in TCM polysaccharide-based functional hydrogels for skin wound healing applications. We highlight design and fabrication strategies, encompassing physical and chemical crosslinking approaches for constructing diverse network architectures, as well as functionalization strategies that incorporate bioactive components or leverage advanced manufacturing techniques to achieve tailored properties. Furthermore, we comprehensively discuss the therapeutic performance of these hydrogels in various in vitro and in vivo wound models with particular emphasis on the underlying mechanisms of action, such as modulation of macrophage polarization, scavenging of reactive oxygen species, enhancement of angiogenesis, acceleration of cell proliferation and migration, and regulation of extracellular matrix remodeling. Finally, existing challenges and future research perspectives are critically analyzed. Overall, functional hydrogels based on bioactive TCM polysaccharides that integrate traditional medical wisdom with modern biomedical engineering represent a highly promising platform for the development of next-generation, effective, and intelligent wound repair materials.

Background and objective: Preterm birth complications are among leading causes of mortality in neonates and children under 5 years of age worldwide. The association between prenatal vitamin D supplementation and risk of preterm birth is controversial based on randomized controlled trials (RCTs). We aimed to determine the effect of vitamin D supplementation during pregnancy on preterm birth and maternal and neonatal secondary outcomes, and to ascertain whether the effects of vitamin D supplementation on preterm birth differed by baseline 25(OH)D status, supplementation dose, and timing of initiation.

Data sources: PubMed, Web of Science, Medline, Cochrane Library, and Embase were searched from inception to April 2023 with no language restrictions.

Study selection: RCTs comparing vitamin D supplementation with placebo, no treatment, or standard low-dose vitamin D (≤ 600 IU/day) in pregnant women were included. The primary outcome was preterm birth (<37 weeks’ gestation) and secondary outcomes included maternal adverse events and neonatal anthropometric indicators.

Results: Thirty-eight RCTs involving 17,392 pregnant women were included. Nineteen RCTs involving 7959 pregnant women reported preterm birth. Vitamin D supplementation was associated with a borderline increase in preterm birth risk in the primary analysis (RR, 1.13; 95% CI, 1.01–1.26; P = 0.04; I² = 0%) but this association was modest and largely driven by one large RCT among women living with HIV. An increased preterm birth signal was noted among participants with a baseline 25(OH)D ≥ 30 nmol/L (OR, 1.25; 95% CI, 1.05–1.48) in exploratory subgroup analyses presented as ORs and this signal was entirely derived from the same HIV trial. No significant subgroup associations were detected in the < 30 nmol/L subgroup or by supplementation dose or initiation timing. No significant effects were noted for maternal or neonatal secondary outcomes.

Limitations: The main study limitations included incomplete reporting of preterm births across trials, reliance on the risk signal on a single population-specific risk signal, dichotomization of baseline 25(OH)D status, and lack of individual participant data for refined subgroup analyses.

Conclusions: Current evidence does not support universal vitamin D supplementation to prevent preterm birth. A possible increased risk of preterm birth among participants with a baseline 25(OH)D ≥ 30 nmol/L should be interpreted cautiously because this finding was driven by a single trial in HIV-positive pregnant women and should not be generalized to healthy pregnant women. Further large-scale RCTs and individual participant data meta-analyses are warranted to clarify whether baseline vitamin D status modifies effects of vitamin D supplementation.

Background: Accurate localization of anatomical landmarks is crucial for clinical diagnosis and treatment assessment. However, existing convolutional neural network (CNN)-based methods may result in global spatial information loss and consequent localization failures in the presence of complex anatomical structures or parenchymal abnormalities. Therefore, a method capable of modeling global context while preserving local information is needed.

Methods: Leveraging the Transformer’s ability to capture long-range dependencies, we propose a novel landmark localization framework, Res-SwinFusion, which integrates a Swin Transformer and a classical CNN backbone in parallel. To effectively merge their complementary features, we designed a feature interactive aggregation module that fuses semantic representations from both branches. Additionally, we introduced a discrimination feature guidance module to provide pixel-level cues and disambiguate landmark locations. We further analyzed the effects of various Gaussian heatmap settings on convergence.

Results: Res-SwinFusion achieved strong performance across three anatomical landmark localization datasets. The mean radial errors were 1.04 mm and 1.37 mm on two public cephalogram test sets, 0.63 mm on a public hand X-ray dataset, and 1.44 mm on an internal pelvic X-ray dataset. Ablation studies indicated that Transformer-based global modeling, feature interactive aggregation, and discrimination feature guidance each contributed to improved localization accuracy.

Conclusion: The proposed Res-SwinFusion framework offers a solution for anatomical landmark localization with enhanced robustness and precision by combining global contextual modeling and local feature preservation. Code is publicly available at https://github.com/JZK00/Res-SwinFusion.