ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveThe essence of syndrome manifestation recognition in traditional Chinese medicine (TCM) is to infer the body’s latent pathogenesis state from clinical observational information, rather than to perform simple label matching. However, previous studies have largely modeled this task as syndrome pattern classification within a fixed label space, which does not adequately reflect the cognition process of TCM syndrome differentiation centered on pathogenesis reasoning, and is also insufficient to capture the openness, semantic variability, and cross-disease reusability of syndrome manifestation expression. This study aimed to investigate whether introducing pathogenesis reasoning chain-of-thought (PR-CoT) supervision into large language models (LLMs) could improve the quality and cognitive consistency of syndrome manifestation recognition and support cross-disease transfer. MethodsSyndrome manifestation recognition was formulated as a conditional generation task under the framework of clinical observational information (X)→pathogenesis structure (Z)→syndrome pattern output (Y), where Z serves as an explicit intermediate structural variable linking the clinical evidence and syndrome judgment. Within this framework, a PR-CoT-supervised dataset for syndrome manifestation recognition was constructed based on medical case records of spleen-stomach disorders. After preprocessing, information extraction, manual proofreading, and data cleaning, the dataset comprised 4 800 training cases, 400 development cases, and 400 test cases. Each sample was annotated with a structured PR-CoT consisting of three progressive levels: clinical information summarization, comprehensive pathogenesis analysis, and syndrome pattern output. Supervised fine-tuning was conducted on open-source LLMs, with an end-to-end model serving as the baseline. Qwen3-32B was used as the primary experimental model, and Qwen3-14B as the scale comparison model. A progressive multidimensional evaluation framework was further established, comprising a structural parsing level, a semantic similarity level, and an expert blind review level. At the structural parsing level, syndrome pattern expressions were decomposed into structural elements and evaluated using Precision, Recall, F1 score, and Jaccard similarity. At the semantic similarity level, independent LLMs scored the theoretical proximity between predicted and reference syndrome patterns. At the expert blind review level, three TCM experts independently evaluated model outputs on two dimensions: syndrome differentiation consistency and terminology standardization of syndrome patterns. In addition, zero-shot cross-disease transfer evaluation was conducted on gynecological and heart-system disorder test sets. ResultsAt the structural parsing level, PR-CoT supervision did not lead to a stable improvement in the element-wise overlap of syndrome pattern structural components. Compared with the corresponding baselines, neither Qwen3-32B nor Qwen3-14B showed consistent advantages in structural matching metrics after the introduction of PR-CoT supervision. In contrast, at the semantic similarity level, PR-CoT supervision produced stable positive gains across different model scales and evaluation systems. The average semantic score of Qwen3-32B increased from 6.425 8 in the baseline model to 6.585 0 after PR-CoT supervision, and that of Qwen3-14B increased from 5.870 0 to 5.964 2. At the expert blind review level, the overall score of Qwen3-32B (PR-CoT) was 7.026 0±0.107 7, higher than 6.416 3±0.288 9 for its baseline. In zero-shot cross-disease testing, the PR-CoT model still showed advantages in semantic evaluation and expert evaluation on both gynecological and heart-system disorder test sets, indicating a certain degree of transferability. ConclusionThe benefits of PR-CoT supervision are mainly reflected in TCM semantic consistency and clinical plausibility, rather than in improved hard matching of structural elements. These findings support understanding syndrome manifestation recognition as a process of generating and expressing latent pathogenesis structures, rather than as a classification task within a traditional fixed label space. By introducing pathogenesis reasoning as an explicit intermediate structure into the modeling process and combining it with a progressive multidimensional evaluation framework, this study provides a methodological pathway for intelligent TCM syndrome differentiation that integrates theoretical alignment, interpretability, and multi-level evaluation.

ObjectiveProtein-protein interactions (PPIs) are fundamental to the execution of biological functions within living cells. However, traditional biochemical methods, such as co-immunoprecipitation (Co-IP), often fail to capture transient, weak, or membrane-associated interactions due to the stringent detergent requirements for cell lysis. Proximity labeling (PL) has emerged in recent years as a transformative technology for mapping the proteomes of specific subcellular compartments and identifying dynamic interactomes in situ. Golgi protein 73 (GP73, also known as GOLPH2), a resident type II Golgi transmembrane protein, is a well-recognized clinical biomarker for liver diseases, including hepatocellular carcinoma (HCC). Despite its clinical significance, the comprehensive physiological and pathological functions of GP73 remain partially understood. This study aims to establish an APEX2-mediated proximity labeling system specifically targeting GP73 to map its interactome in a living cellular environment, thereby providing new insights into its molecular roles and regulatory mechanisms. MethodsTo achieve spatial specificity, we first constructed a stable cell line expressing a fusion protein consisting of GP73 and the engineered soybean peroxidase APEX2. The localization of the GP73-APEX2 fusion protein was validated to ensure it correctly targeted the Golgi apparatus. The proximity labeling reaction was initiated by incubating the cells with biotin-phenol (BP) for 30 min, followed by a brief (1 min) treatment with1 mmol/L hydrogen peroxide (H₂O₂). This catalytic reaction converts BP into highly reactive, short-lived biotin-phenoxyl radicals that covalently attach to endogenous proteins within a small labeling radius of the GP73-APEX2 enzyme. Subsequently, the cells were quenched, and biotinylated proteins were enriched using high-affinity streptavidin-coated magnetic beads. The captured “neighbor” proteins were subjected to on-bead digestion and analyzed via liquid chromatography-tandem mass spectrometry (LC-MS/MS) for high-throughput identification. Rigorous bioinformatics analysis, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and protein-protein interaction network mapping, was performed to interpret the biological significance of the identified candidates. ResultsOur results demonstrate the successful establishment of a robust and sensitive APEX2-based proximity labeling system for GP73. We identified a total of 95 high-confidence interacting proteins that were significantly enriched in the GP73 proximity proteome compared to control groups. Bioinformatics analysis revealed that these interactors were predominantly associated with biological processes such as vesicular transport, protein localization, and, most notably, molecular functions related to “ribosome binding” and “translation regulation”. This suggested an unexpected role for the Golgi-resident GP73 in the cellular translation machinery. To validate these findings, we performed targeted biochemical assays which confirmed a direct interaction between GP73 and the subunits of the eukaryotic translation initiation factor 3 (eIF3) complex, specifically EIF3G and EIF3I. Furthermore, functional validation using the surface sensing of translation (SUnSET) assay—a non-radioactive method to monitor protein synthesis—revealed that the overexpression of GP73 significantly promoted global protein translation levels in the cell, whereas its depletion or inhibition resulted in reduced translation efficiency. ConclusionThis study successfully utilized APEX2-mediated proximity labeling to provide the first systematic map of GP73 interactome in living cells. Our findings uncover a novel, unconventional function of GP73 as a regulator of cellular protein translation, likely mediated through its interaction with the eIF3 complex. This discovery significantly broadens our understanding of the biological roles of GP73 beyond its traditional function in the Golgi apparatus and suggests that it may act as a bridge between Golgi-related trafficking and the protein synthesis machinery. Furthermore, the technical framework established in this study provides a valuable template for investigating other complex organelle-associated protein networks and resolving transient macromolecular interactions in various physiological and pathological contexts.

ObjectiveCerebral ischemic injury triggers a complex pathological cascade characterized by excessive reactive oxygen species (ROS) accumulation, persistent oxidative stress, and sustained neuroinflammation in the injured brain microenvironment. These events collectively drive mitochondrial dysfunction, microglial overactivation, pro-inflammatory cytokine release, and progressive neuronal apoptosis, ultimately leading to severe and irreversible neurological deficits. However, conventional therapeutic strategies face critical limitations, including poor blood-brain barrier penetration, insufficient local drug concentration, uncontrolled drug release, and off-target systemic side effects. To address this pathological process, we rationally designed and fabricated an injectable ROS-responsive hydrogel loaded with polydopamine nanoparticles (PDA NPs) for spatiotemporally controlled antioxidation, anti-inflammation, and neuroprotection in the ischemic injury microenvironment. The present study aimed to systematically characterize the physicochemical properties, ROS-responsive drug release behavior, biocompatibility, and neuroprotective efficacy of this composite hydrogel system in vitro. MethodsPDA NPs were fabricated via oxidative self-polymerization. The ROS-responsive hydrogel was cross-linked using N1-(4-boronobenzyl)-N3-(4-boronophenyl)-N1,N1,N3,N3-tetramethylpropane-1, 3-diaminium (TSPBA) and polyvinyl alcohol (PVA). Morphology, particle size, Zeta potential, and structure of PDA NPs were characterized by dynamic light scattering (DLS), Zeta potential analysis, scanning electron microscopy (SEM), and transmission electron microscopy (TEM). Microstructure, rheological properties, shear-thinning behavior, and ROS-triggered release profiles of the hydrogel were examined by SEM and rheometry. Biocompatibility was evaluated using HT22 mouse hippocampal neurons with CCK-8 and live/dead staining. An oxygen-glucose deprivation/reoxygenation (OGD/R) model was established to simulate ischemic injury in vitro. ROS levels and neuronal apoptosis were detected by DHE staining and TUNEL assay. Microglial polarization and pro-inflammatory cytokine expression were analyzed using immunofluorescence and RT-qPCR in BV-2 microglia. Transwell co-culture was used to verify the indirect neuroprotection mediated by modulated microglia. ResultsCharacterization results confirmed that the as-prepared PDA NPs were monodispersed spherical nanoparticles with uniform diameter and negative surface potential, demonstrating favorable dispersibility and robust ROS-scavenging activity. The TSPBA-PVA hydrogel exhibited a highly porous interconnected network, suitable mechanical strength, and obvious shear-thinning behavior, supporting its application as an injectable implant. More importantly, the hydrogel displayed typical ROS-responsive degradation and on-demand PDA NP release in a ROS-concentration-dependent manner. In vitro cellular experiments demonstrated that the PDA NP-loaded hydrogel possessed excellent biocompatibility with HT22 cells. In the OGD/R model, the hydrogel significantly reduced intracellular ROS accumulation and markedly suppressed neuronal apoptosis. Furthermore, the composite hydrogel effectively redirected BV-2 microglia from the pro-inflammatory M1 toward the anti-inflammatory M2 phenotypes, downregulated the expression of pro-inflammatory cytokines including TNF-α, IL-1β, and IL-6, and reduced inflammatory damage. Transwell co-culture assays further validated that M2-polarized microglia mediated by the hydrogel significantly enhanced the survival of OGD/R-injured HT22 neurons and attenuated apoptosis. ConclusionIn this study, we successfully developed a novel injectable ROS-responsive hydrogel loaded with PDA NPs for synergistic antioxidative and anti-inflammatory neuroprotection. This intelligent hydrogel system enables ROS-triggered on-demand release of PDA NPs, efficiently scavenges excessive ROS, inhibits oxidative stress injury, modulates microglial polarization, and suppresses neuroinflammation, thereby exerting robust neuroprotective effects in vitro. This biomaterial platform provides a promising strategy for the targeted and controlled delivery of bioactive nanomaterials in the central nervous system diseases and establishes a solid experimental foundation for the development of in situ injectable therapies for ischemic brain injury.

Objective:To observe the effect of moxibustion on angiogenesis-related indicators in knee joint synovial tissue of adjuvant arthritis model rats,and to explore the mechanism of moxibustion in inhibiting vascular endothelial growth factor(VEGF)expression in synovial tissue and further limiting the activation of Rho family proteins Rac1 and Cdc42,thereby inhibiting angiogenesis during rheumatoid arthritis(RA)treatment.Methods:Forty-eight male Sprague-Dawley rats were equally divided into a normal group,a model group,a moxibustion group,and a moxibustion+VEGF agonist group according to the random principle.The complete Freund's adjuvant method was used for modeling.On the 12th day after modeling,the moxibustion group and the moxibustion+VEGF agonist group were subjected to suspended moxibustion at bilateral Zusanli(ST36),Guanyuan(CV4),and Ashi points for 20 min each time,once a day,for a total of 15 times.The moxibustion+VEGF agonist group received VEGF agonist(tirofiban hydrochloride hydrate)injection in the knee joint cavity at the same time.Hematoxylin-eosin staining was used to evaluate the pathological changes of rat synovial tissue in each group.Immunohistochemistry was used to observe the CD31 expression level in rat synovial tissue.Western blotting was used to detect the levels of VEGF,Rac1,and Cdc42 protein in rat synovial tissue,and polymerase chain reaction(PCR)was used to detect the VEGF mRNA expression.Results:Compared to the normal group,the expression levels of CD31 protein and VEGF mRNA and protein in rat synovial tissue in the model group increased significantly(P<0.01),and the expression levels of phospho-Rac1 and phospho-Cdc42 proteins also increased significantly(P<0.01).After moxibustion intervention,the expression levels of CD31 protein and VEGF mRNA and protein in the moxibustion group were significantly lower than those in the model group(P<0.01),while the differences in each indicator between the moxibustion+VEGF agonist group and the model group were not statistically significant(P>0.05).Compared to the moxibustion group,the expression levels of CD31 protein,VEGF mRNA and protein,phospho-Cdc42,and phospho-Rac1 in the moxibustion+VEGF agonist group increased significantly(P<0.01).Conclusion:Moxibustion improved synovial inflammation in RA by inhibiting angiogenesis.The mechanism may be to regulate angiogenesis-related VEGF,restrict the activation of Rac1 and Cdc42,and inhibit pseudopodia formation in vascular endothelial cells,thereby reducing angiogenesis.

Nitrofurazone(NFZ)is an antibiotic that is used as a veterinary drug in aquaculture.NFZ abuse can lead to a series of environmental and health issues,making it crucial to establish a rapid and highly sensitive method for NFZ detection.In this study,platinum nanoparticle(PtNPs)-loaded zeolitic imidazolate framework(ZIF-8)was used as a precursor,and PtNPs functionalized nitrogen doped porous carbon(NC)was obtained through pyrolysis.Pt@NC was combined with multi-walled carbon nanotubes(MWCNTs)and cast onto a glassy carbon electrode(GCE)surface to construct an electroch-emical sensor.Electrochemical tests revealed that Pt@NC/WCNT/GCE exhibited an electrochemical active area of 0.066 cm2 and a heterogeneous electron transfer rate constant(k0)of 2.03×10-3 cm/s,which were higher than other materials.Compared with the electrodes modified by other materials,the NFZ generated the highest peak current of irreversible reduction peak on the Pt@NC/WCNT/GCE electrode.In comparison with Pt@ZIF-8/WCNT/GCE,after pyrolysis and carbonization treatment,the reduction current of NFZ increased by 2.19 times,and the reduction peak potential shifted positively by 19 mV simultaneously.When compared with NC/WCNT/GCE,the PtNPs in the composite material enhanced the NFZ current by 4.25 times.Additionally,the experimental conditions for detecting NFZ using the sensor were optimized,including the carbonization temperature of Pt@ZIF-8,ratio of Pt@NC to CNT,loading amount of the modified material,and electrolyte pH.Under the optimized conditions,the sensor demonstrated a linear detection range for NFZ of 0.20-240 μmol/L,a sensitivity of 9.995 μA/((μmol/L)?cm2)and a limit of detection(LOD)of 0.06 μmol/L.The sensor exhibited excellent anti-interference capability,good reproducibility,and stability,with spiked recoveries for NFZ in water samples ranging from 94.6%to 105.6%.This study provided a novel electrochemical sensing approach for NFZ detection.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

As the first defense of respiratory system,airway epi-thelial cells(AECs)play an important role in separating the re-spiratory internal and external environment.They are essential for the natural immune function.Small airway lesions are an im-portant early pathology of chronic obstructive pulmonary disease(COPD),when AECs are exposed to harmful particles or gases for a long time,the epithelial barrier is damaged,and the signa-ling pathways which involved in differentiation,repair,and in-flammatory are disordered,resulting in epithelial cell cycle stag-nation and accelerated aging.A number of studies have sugges-ted that AECs of COPD patients express high levels of aging markers,suggesting that senescence of AECs is closely related to COPD.This review discusses the potential mechanisms of AECs senescence in COPD,the impact of AECs senescence on the de-velopment and severity of the disease,and highlights potential targets for modulating cellular senescence in airway epithelium as a therapeutic approach in COPD.

Objective: Negative symptoms in schizophrenia indicate a poor prognosis. However, the mechanisms underlying the development of negative symptoms remain unclear. This study investigated the relationship between negative symptoms in schizophrenia and frontal alpha asymmetry (FAA). Methods: The study used a 32-channel electroencephalography to acquire alpha power in 4 target-paired sites in each patient. Regional alpha asymmetry was calculated based on the alpha power using EEGLAB Frontal Alpha Asymmetry Toolbox. Results: Sixty schizophrenia patients with predominant negative symptoms (PNS), 72 stabilized schizophrenia (SS) patients, and 73 healthy control (HC) participants were enrolled in this study. No significant differences were observed in FAA between the PNS and SS groups, although both groups exhibited reduced P3-P4 alpha asymmetry compared to HCs. A positive correlation was found between F7-F8 alpha asymmetry and illness duration. Additionally, a predictive model based on P3-P4 alpha asymmetry scores was able to differentiate schizophrenia patients from HCs, achieving a sensitivity of 71.2% and a specificity of 72.6%. Conclusion This study highlighted that parietal alpha asymmetry could serve as a valuable diagnostic tool for schizophrenia.

BACKGROUND: A growing body of research is exploring the role of antioxidant and anti-inflammatory dietary supplements in the treatment of osteoarthritis, highlighting an increasing emphasis on non-pharmacological interventions. Although more patients are turning to supplements to manage osteoarthritis, their actual effectiveness remains uncertain. OBJECTIVE: This study aims to provide a comprehensive evaluation of the available evidence concerning the efficacy of various dietary supplements in osteoarthritis treatment. SEARCH STRATEGY: We searched PubMed, Embase, Cochrane Library and Web of Science for studies on the use of various dietary supplements in the treatment of osteoarthritis from the creation of each database until Jan 20, 2025. INCLUSION CRITERIA: (1) Research object: osteoarthritis. (2) Intervention measures: patients in the treatment group received dietary supplements, while the control group received placebos. (3) Research type: randomized controlled trials (RCTs). DATA EXTRACTION AND ANALYSIS: Two researchers independently examined the literature and retrieved data based on predefined criteria. The information gathered included the first author, year of publication, sample size, participant demographics, length of the follow-up period, intervention and control measures, and inclusion indications. RCTs comparing dietary supplements to placebo with the pain and function subscales of the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) among patients with osteoarthritis were included. The optimal dietary supplement was identified based on the total ranking by summing the surface under the cumulative ranking curve (SUCRA) of these two scores. Furthermore, the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) was used to confirm the quality of the evidence. RESULTS: Overall, 23 studies covering 21 dietary supplements and involving 2455 participants met the inclusion criteria. In the WOMAC pain score, the SUCRA of passion fruit peel extract was 91% (mean difference [MD]: -9.2; 95% confidence interval [CI]: [-16.0, -2.3]), followed by methylsulfonylmethane (89%), undenatured type II collagen (87%), collagen (84%), and Lanconone (82%). The SUCRA (99%) of passion fruit peel extract (MD: -41.0; 95% CI: [-66.0, -16.0]) ranked first in terms of the WOMAC function score, followed by Lanconone (95%), collagen (86%), ParActin (84%), and Lactobacillus casei strain Shirota (83%). The top three total rankings are passion fruit peel extract (95.0%), Lanconone (88.5%), and collagen (85.0%). However, the GRADE revealed low evidence quality. CONCLUSION Passion fruit peel extract was the best supplement for improving WOMAC pain and function scores in patients with osteoarthritis, followed by Lanconone and collagen. However, further large-scale, well designed RCTs are required to substantiate these promising findings. Please cite this article as: Chen CS, Wen L, Yang F, Deng YC, Ji JH, Chen RJ, Chen Z, Chen G, Gu JY. Effects of dietary supplements on patients with osteoarthritis: A systematic review and network meta-analysis. J Integr Med. 2025; 23(4): 357-369.
Humans ; Dietary Supplements ; Osteoarthritis/drug therapy* ; Randomized Controlled Trials as Topic