Thrombospondin 4 (THBS4; TSP4), a crucial component of the extracellular matrix (ECM), serves as an important regulator of tissue homeostasis and various pathophysiological processes. As a member of the evolutionarily conserved thrombospondin family, THBS4 is a multidomain adhesive glycoprotein characterized by six distinct structural domains that mediate its diverse biological functions. Through dynamic interactions with various ECM components, THBS4 plays pivotal roles in cell adhesion, proliferation, inflammation regulation, and tissue remodeling, establishing it as a key modulator of microenvironmental organization. The transcription and translation of THBS4 gene, as well as the activity of the THBS4 protein, are tightly regulated by multiple signaling pathways and extracellular cues. Positive regulators of THBS4 include transforming growth factor-β (TGF-β), interferon-γ (IFNγ), granulocyte-macrophage colony-stimulating factor (GM-CSF), bone morphogenetic proteins (BMP12/13), and other regulatory factors (such as B4GALNT1, ITGA2/ITGB1, PDGFRβ, etc.), which upregulate THBS4 at the mRNA and/or protein level. Conversely, oxidized low-density lipoprotein (OXLDL) acts as a potent negative regulator of THBS4. This intricate regulatory network ensures precise spatial and temporal control of THBS4 expression in response to diverse physiological and pathological stimuli. Functionally, THBS4 acts as a critical signaling hub, influencing multiple downstream pathways essential for cellular behavior and tissue homeostasis. The best-characterized pathways include: (1) the PI3K/AKT/mTOR axis, which THBS4 modulates through both direct and indirect interactions with integrins and growth factor receptors; (2) Wnt/β-catenin signaling, where THBS4 functions as either an activator or inhibitor depending on the cellular context; (3) the suppression of DBET/TRIM69, contributing to its diverse regulatory roles. These signaling connections position THBS4 as a master regulator of cellular responses to microenvironmental changes. Substantial evidence links aberrant THBS4 expression to a range of pathological conditions, including neoplastic diseases, cardiovascular disorders, fibrotic conditions, neurodegenerative diseases, musculoskeletal disorders, and atopic dermatitis. In cancer biology, THBS4 exhibits context-dependent roles, functioning either as a tumor suppressor or promoter depending on the tumor type and microenvironment. In the cardiovascular system, THBS4 contributes to both adaptive remodeling and maladaptive fibrotic responses. Its involvement in fibrotic diseases arises from its ability to regulate ECM deposition and turnover. The diagnostic and therapeutic potential of THBS4 is particularly promising in oncology and cardiovascular medicine. As a biomarker, THBS4 expression patterns correlate significantly with disease progression and patient outcomes. Therapeutically, targeting THBS4-mediated pathways offers novel opportunities for precision medicine approaches, including anti-fibrotic therapies, modulation of the tumor microenvironment, and enhancement of tissue repair. This comprehensive review systematically explores three key aspects of THBS4 research(1) the fundamental biological functions of THBS4 in ECM organization; (2) its mechanistic involvement in various disease pathologies; (3) its emerging potential as both a diagnostic biomarker and therapeutic target. By integrating recent insights from molecular studies, animal models, and clinical investigations, this review provides a framework for understanding the multifaceted roles of THBS4 in health and disease. The synthesis of current knowledge highlights critical research gaps and future directions for exploring THBS4-targeted interventions across multiple disease contexts. Given its unique position at the intersection of ECM biology and cellular signaling, THBS4 represents a promising frontier for the development of novel diagnostic tools and therapeutic strategies in precision medicine.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Acupotomy therapy demonstrates the definite clinical efficacy on knee osteoarthritis (KOA). After reviewing systematically the mechanism studies on acupotomy for KOA over the past 5 years, It is revealed that acupotomy synergistically intervenes in the pathological progression of KOA through multi-target approaches, such as regulating cartilage homeostasis, restoring skeletal muscle function, alleviating synovial inflammatory responses, remodeling subchondral bone, and neuromodulation. But the current research still limits to single-tissue phenotypic observation, and is insufficiency in the in-depth exploration of multi-tissue synergistic interactions and molecular upstream-downstream regulatory mechanisms. Future studies should focus on the inheritance and innovation of acupotomy theory, and integrating multi-omics analytical technologies, artificial intelligence, and novel biochemical detection methods. The mechanism research targets on the interaction mechanisms among tissues, direct effects of acupotomy, immune-inflammatory regulatory mechanisms, and analgesic mechanisms, so as to comprehensively elucidate the therapeutic mechanism of acupotomy for KOA.
Humans ; Acupuncture Therapy ; Osteoarthritis, Knee/genetics* ; Animals

Biomedical big data, characterized by its massive scale, multi-dimensionality, and heterogeneity, offers novel perspectives for disease research, elucidates biological principles, and simultaneously prompts changes in related research methodologies. Biomedical ontology, as a shared formal conceptual system, not only offers standardized terms for multi-source biomedical data but also provides a solid data foundation and framework for biomedical research. In this review, we summarize enrichment analysis and deep learning for biomedical ontology based on its structure and semantic annotation properties, highlighting how technological advancements are enabling the more comprehensive use of ontology information. Enrichment analysis represents an important application of ontology to elucidate the potential biological significance for a particular molecular list. Deep learning, on the other hand, represents an increasingly powerful analytical tool that can be more widely combined with ontology for analysis and prediction. With the continuous evolution of big data technologies, the integration of these technologies with biomedical ontologies is opening up exciting new possibilities for advancing biomedical research.
Deep Learning ; Biological Ontologies ; Humans ; Big Data ; Biomedical Research

OBJECTIVE: To evaluate the clinical efficacy and safety of Yangxue Qingnao Pills (YXQNP) combined with amlodipine in treating patients with grade 1 hypertension. METHODS: This is a multicenter, randomized, double-blind, and placebo-controlled study. Adult patients with grade 1 hypertension of blood deficiency and Gan (Liver)-yang hyperactivity syndrome were randomly divided into the treatment or the control groups at a 1:1 ratio. The treatment group received YXQNP and amlodipine besylate, while the control group received YXQNP's placebo and amlodipine besylate. The treatment duration lasted for 180 days. Outcomes assessed included changes in blood pressure, Chinese medicine (CM) syndrome scores, symptoms and target organ functions before and after treatment in both groups. Additionally, adverse events, such as nausea, vomiting, rash, itching, and diarrhea, were recorded in both groups. RESULTS: A total of 662 subjects were enrolled, of whom 608 (91.8%) completed the trial (306 in the treatment and 302 in the control groups). After 180 days of treatment, the standard deviations and coefficients of variation of systolic and diastolic blood pressure levels were lower in the treatment group compared with the control group. The improvement rates of dizziness, headache, insomnia, and waist soreness were significantly higher in the treatment group compared with the control group (P<0.05). After 30 days of treatment, the overall therapeutic effects on CM clinical syndromes were significantly increased in the treatment group as compared with the control group (P<0.05). After 180 days of treatment, brachial-ankle pulse wave velocity, ankle brachial index and albumin-to-creatinine ratio were improved in both groups, with no statistically significant differences (P>0.05). No serious treatment-related adverse events occurred during the study period. CONCLUSIONS Combination therapy of YXQNP with amlodipine significantly improved symptoms such as dizziness and headache, reduced blood pressure variability, and showed a trend toward lowering urinary microalbumin in hypertensive patients. These findings suggest that this regimen has good clinical efficacy and safety. (Registration No. ChiCTR1900022470).
Humans ; Amlodipine/adverse effects* ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Hypertension/complications* ; Middle Aged ; Treatment Outcome ; Drug Therapy, Combination ; Adult ; Blood Pressure/drug effects* ; Double-Blind Method ; Aged ; Antihypertensive Agents/adverse effects*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

By summarizing the mass spectrometric fragmentation patterns of oxyphenisatin substances,an analytical method was established for screening of illegally added oxyphenisatin compounds in weight-loss health foods using high performance liquid chromatography-in-source-fragmentation-quadrupole time-of-flight mass spectrometry(HPLC-ISF-QTOF-MS),along with a quantitative method for 11 kinds of oxyphenisatin compounds.Based on the developed screening method,an oxyphenisatin derivative was discovered in the reference standards,which was tentatively identified as 4-(3-(4-hydroxyphenyl)-2-oxoindolin-3-yl)phenyl acetate and confirmed by MS/MS analysis.The results showed that all 11 kinds of oxyphenisatin compounds had correlation coefficients greater than 0.9971,with limits of detection(LODs)ranging from 0.12 to 0.68 μg/L and limits of quantification(LOQ)from 0.21 to 2.29 μg/L.The LODs for 11 kinds of characteristic ions ranged from 0.45 to 9.11 μg/kg.At spiking levels of 25,50 and 100 μg/kg,the recoveries ranged from 78.9%to 117.3%.The instrumental precision,intra-day method precision and inter-day method precision were 0.23%?1.70%,0.7%?2.4%,and 1.1%?3.3%,respectively.The developed targeted and non-targeted detection method demonstrated high sensitivity,strong stability,rapid analysis,and an expanded screening range for oxyphenisatin substances,and provided robust technical support for regulatory authorities in combating illegal adulteration.

Objective To investigate the effect of miR-185-5p-mediated targeted negative regulation of transmembrane 9 superfamily member 1(TM9SF1)on proliferation,migration and autophagy in lung adenocarcinoma cells.Methods The expression of miR-185-5p in lung adenocarcinoma tissues was analyzed using dataset GSE51853 downloaded from the Gene Expression Omnibus(GEO)database.Potential target proteins of miR-185-5p were predicted using online databases(miRTargetLink,miRTarbase,and DIANA-microT-CD),and autophagy-related proteins were obtained from HADb.The intersected results from these four databases was identified,and survival curves of vascular endothelial growth factor A(VEGFA)and TM9SF1 within the overlapping candidates were analyzed using the StarBase database.TM9SF1 3'UTR wild-type(WT)or TM9SF1 3'UTR mutant(MUT)reporter plasmids were separately co-transfected with miR-185-5p control plasmid(CON)or miR-185-5p overexpression plasmid(over-miR-185-5p)into HEK-293T cells.A dual-luciferase reporter gene assay was employed to assess the binding interaction between miR-185-5p and TM9SF1 and quantify the subsequent luciferase activity.Western blotting was used to assess TM9SF1 protein expression levels in A549 cells transfected with over-miR-185-5p.A549 cells were divided into three groups:(1)CON+NC group,co-transfected with miR-185-5p control plasmid and TM9SF1 control plasmid;(2)over-miR-185-5p+NC group,co-transfected with over-miR-185-5p and TM9SF1 control plasmid;(3)over-miR-185-5p+over-TM9SF1 group,co-transfected with both miR-185-5p and TM9SF1 overexpression plasmids.EdU cell proliferation assay,wound healing assay,and Transwell migration assay were performed to validate the effects of miR-185-5p targeted binding to TM9SF1 on proliferation and migration capacities in lung adenocarcinoma.Changes in autophagic flux and mitochondrial membrane potential(MMP)of lung adenocarcinoma cells were detected using stubRFP-sensGFP-LC3 lentivirus and JC-1 assays,respectively.Results In the GSE51853 dataset,miR-185-5p expression level was significantly lower in lung adenocarcinoma tissues compared with normal lung tissues(P<0.01).qRT-PCR analysis revealed that miR-185-5p expression was downregulated in lung adenocarcinoma cell lines NCI-H1299 and A549 compared with normal lung epithelial cells BEAS-2B(P<0.01).Bioinformatics predictions using miRTargetLink,miRTarbase,DIANA-microT-CD,and HADb databases indicated that miR-185-5p could target and regulate the autophagy-related protein TM9SF1.Dual-luciferase reporter assays and Western blotting demonstrated that miR-185-5p directly bound to the 3'UTR region of TM9SF1 mRNA,and overexpression of miR-185-5p significantly reduced the expression of target protein TM9SF1(P<0.05).EdU cell proliferation,wound healing,and Transwell migration assays demonstrated that miR-185-5p overexpression inhibited proliferation and migration capacities of lung adenocarcinoma cells,whereas TM9SF1 overexpression could attenuate this inhibition effect(P<0.05).Results of stubRFP-sensGFP-LC3 for autophagic flux analysis demonstrated that overexpression of miR-185-5p enhanced autophagic flux in A549 cells,whereas co-overexpression of miR-185-5p and TM9SF1 suppressed autophagic flux.JC-1 assays showed a decreased MMP level in A549 cells after miR-185-5p overexpression,with higher MMP level observed when miR-185-5p and TM9SF1 were co-overexpressed.Conclusion miR-185-5p may suppress proliferation,migration,and autophagy capacities in lung adenocarcinoma cells by targeting TM9SF1 through negative regulation.

This study investigates whether compounds in Salvia miltiorrhiza Bunge can bind to the Toll like receptor 4/myeloid differentiation protein 2 (TLR4/MD2) protein complex and exhibit anti-inflammatory activity. Virtual screening of reported chemical components of Salvia miltiorrhiza Bunge against TLR4/MD2 was conducted in this study. The selected compound, neoprzewaquinone A (Neo A), was tested for its impact on the binding of lipopolysaccharide (LPS) to receptors on the cell membrane, its affinity for the protein, its influence on the dimerization of TLR4 and MD2 in LPS-induced cells, and its effects on the phosphorylation of nuclear factor-κB (NF-κB) p65 protein and the secretion of inflammatory cytokines in cells. Results indicate that Neo A in Salvia miltiorrhiza Bunge exhibited the highest virtual binding affinity with TLR4/MD2, with a value of -12.8 kcal·mol^-1. Neo A significantly inhibited the binding of LPS to receptors on the cell membrane (P < 0.01). Moreover, Neo A demonstrated affinity for rhTLR4/MD2, rhTLR4, and rhMD2, with K_D values of 267, 534, and 228 nmol·L^-1, respectively. Amino acid residues like TYR131 and PHE121 in TLR4/MD2 might play a role in the alkyl and π-alkyl hydrophobic interactions with Neo A. Neo A also significantly inhibited the dimerization of TLR4 and MD2 in LPS-mediated cells (P < 0.01) and markedly suppressed the phosphorylation of NF-κBp65 protein (P < 0.05). Furthermore, Neo A significantly or markedly inhibited the secretion of nitric oxide (NO), tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) in LPS-induced cells (P < 0.05, P < 0.01). In conclusion, Neo A exerts its anti-inflammatory effects by binding TLR4/MD2 then disrupting the binding of LPS to TLR4/MD2. It may serve as a TLR4/MD2 inhibitor with the potential to treat inflammation-related diseases targeting TLR4/MD2.

Based on the species-specific peptides of Pheretima and its common counterfeit (Metaphire magna), an identification method was established using ultra-high performance liquid chromatography tandem triple quadrupole mass spectrometry (UHPLC-MS/MS) for quality evaluation of Pheretima and its preparations. Separation was performed on a CORTECS T3 C18 column with 0.1% formic acid and acetonitrile as the mobile phases. Mass spectrometry with multiple reaction monitoring (MRM) using ESI⁺ mode was used to simultaneously monitor three ion pairs. The results indicated that the method was specific and could distinguish Guang Dilong, Hu Dilong, and M. magna, which were consistent with those of DNA barcode identification. The adulteration test showed that the LOD of peptide M was 1 μg·g^-1. Peptide M could be detected when 1% M. magna was added to Guang Dilong, indicating the high sensitivity of the method. Fifty-four batches of commercially available samples contained 35% Guang Dilong, 35% Hu Dilong, and 15% M. magna. No ions were detected in 15% of the samples, and DNA barcode identification revealed that they were mainly from Amynthas, with similar appearance to Hu Dilong. The analysis results of the formulation showed that no peptide ions were detected in 3 batches of Xiaohuoluo pills (3/6) and M. magna were detected in 2 batches of Shenjindan capsules (2/4). The developed method in the study has good specificity, sensitivity, and feasibility, and could be used for quality control of Pheretima and its related preparations. It is of great significance for improving quality standards and regulating the medicinal market of Pheretima.