ObjectiveTo evaluate the efficacy and safety of Janus kinase （JAK） inhibitors combined with Chinese herbal medicine （CHM） in treating rheumatoid arthritis （RA）. MethodsClinical data from 169 RA patients were retrospectively collected. Among them， 71 cases received JAK inhibitors as the control group， while 98 cases received JAK inhibitors plus CHM as the observation group， both treated for 24 weeks. The rheumatoid factor （RF）， cyclic citic peptide antibody （anti-CCP）， erythrocyte sedimentation rate （ESR）， C-reactive protein （CRP）， and white blood cell count （WBC） were recorded before and after treatment. Databases including CNKI， Wanfang， VIP， PubMed and Web of Science were searched from inception till August 31st， 2025 for randomized controlled trials （RCTs） on the combined use of JAK inhibitors and CHM for RA. The methodological quality of the included studies was evaluated using the risk of bias assessment tool. Meta-analyses were performed for RF， anti-CCP， ESR， CRP， 28-joint disease activity score （DAS28）， overall clinical effective rate， and incidence of adverse events. Sensitivity analysis were also performed. ResultsThe retrospective study demonstrated that after treatment， ESR， CRP， and anti-CCP levels decreased in the observation group， while ESR and CRP levels decreased in the control group （P＜0.05）. Moreover， ESR and RF levels in the observation group were lower than those in the control group （P＜0.05）. A total of 9 RCTs involving 770 patients were included in the meta-analysis. The results indicated that the JAK inhibitors plus CHM group was superior to the JAK inhibitors group in reducing RF （MD=-8.97， 95%CI -15.01 to -2.94， P=0.004）， CRP （MD=-3.34， 95%CI -3.82 to -2.86， P＜0.001）， ESR （MD=-5.33， 95%CI -7.98 to -2.69， P＜0.001）， and DAS28 score （MD=-0.54， 95%CI -0.74 to -0.34， P＜0.001）， as well as in improving the overall clinical effective rate （OR=4.53， 95%CI 2.55 to 8.03， P＜0.001）. No statistically significant differences were observed between groups in anti-CCP levels （SMD=-2.08， 95%CI -4.41 to 0.24， P=0.080） or incidence of adverse events （OR=0.93， 95%CI 0.55 to 1.57， P=0.790）. ConclusionThe combination of JAK inhibitors and CHM demonstrates remarkable efficacy in treating RA， contributing to improved disease activity and reduced inflammatory markers with a favorable safety profile.

The key to the onset and progression of the functional impairments of orthopedic diseases is imba-lance of deficiency and excess， disharmony of movement and stillness， dislocation of sinews and bones， imbalance of rigidity and flexibility， and disharmony of body and spirit. Based on this， the "five views" treatment principle has been proposed for traditional Chinese medicine （TCM） orthopedic rehabilitation， which include the view of balancing deficiency and excess， combining movement and stillness， focusing on both sinews and bones， integrating rigidity and flexibility， and harmonizing body and spirit. Correspondingly， the "five views" collaborative rehabilitation clinical model is established， providing a reference for enhancing the systematization and targeting of TCM orthopedic rehabilitation.

OBJECTIVE To investigate the effects and underlying mechanism of Huangqi granules on hair growth in mice with seborrheic alopecia based on Toll-like receptor 4 （TLR4）/myeloid differentiation primary response protein 88 （MyD88） signaling pathway. METHODS Male mice were randomly divided into control group， model group， inhibitor group （treated with 0.3 mg/kg TLR4 inhibitor TAK-242）， Huangqi granules group （treated with 1.0 g/kg Huangqi g ranules） and Huangqi granules+activator group （treated with 1.0 g/kg Huangqi granules combined with 2.5 mg/kg TLR4 activator lipopolysaccharide）， with 12 mice in each group. Except for the control group， the seborrheic alopecia model of mice in other groups was induced by applying rosin-paraffin mixture on the back and injecting testosterone propionate subcutaneously. After modeling， mice in each group were given intragastric administration and intraperitoneal injection of corresponding drugs or （and） normal saline once a day for 20 consecutive days. The time of skin color transition and hair emergence time were compared among those groups. After the last medication， the length of newly-grown hair， serum levels of immune factors [interferon-γ （IFN-γ）， interleukin-4 （IL-4） ] and sex hormones [testosterone （T）， dihydrotestosterone （DHT） ] ， as well as the levels of hair growth factors [insulin-like growth factor 1 （IGF-1）， vascular endothelial growth factor （VEGF）， transforming growth factor-β 1 （TGF-β 1 ） ] in the dorsal skin tissue were measured in each group. Pathological changes and cell apoptosis of hair follicle tissue were observed， and the protein expressions of TLR4 and MyD88 in the dorsal skin tissue were detected. RESULTS Compared with the control group， hair follicle cells in the model group were irregular in size， disordered in arrangement， and showed a significant reduction in melanin content. The time of skin color transition， hair emergence time， the levels of IFN-γ， T， DHT and TGF-β 1 ， the apoptosis rate of hair follicle cells， as well as the protein expressions of TLR4 and MyD88 in the model group were significantly prolonged/increased/up-regulated， while the length of newly-grown hair， the number of hair follicles， and the levels of IL-4， IGF-1 and VEGF were significantly shortened/reduced/decreased （ P ＜0.05）. Compared with the model group， the morphological structure of hair follicle tissue in the Huangqi granules group and inhibitor group was significantly restored， and the above quantitative indicators were significantly improved （ P ＜0.05）. Moreover， the effects of the two groups were comparable （ P ＞0.05）. The TLR4 activator could significantly reverse the improvement effect of Huangqi granules on the above indicators in mice with seborrheic alopecia （ P ＜0.05）. CONCLUSIONS Huangqi granules can regulate immune function， reduce hair follicle cell apoptosis， and promote hair growth in mice with seborrheic alopecia， which may be related to the inhibition of TLR4/MyD88 signaling pathway activation.

Background/Aims: Cholangiocarcinoma (CCA) is a primary malignant neoplasm with an extremely poor prognosis. While combined chemoradiotherapy has been demonstrated to delay CCA progression to a certain extent, the absence of specific molecular biomarkers or targets significantly hinders the diagnosis and treatment of CCA. Methods: Through cross-analysis of proteomics and ADMA modificationomics, we identified DDX1 overexpressed in CCA with elevated R602-ADMA modifications. HPLC-MS/MS identified PRMT1 as the methyltransferase and USP10 as the deubiquitinating enzyme for DDX1. Immunofluorescence and nuclear-cytoplasmic partitioning experiments confirmed DDX1’s nuclear localization. GO and KEGG analyses clarify the biological functions of DDX1 in response to hypoxia. RNA-seq transcriptomics analyzed key pathways influenced by DDX1. A hydrodynamic in situ CCA mouse model was established to validate the chemopreventive effects of the PRMT1-specific inhibitor GSK715 on CCA development. Results: DDX1 promotes CCA progression both in vivo and in vitro and can be inhibited by GSK715. Mechanistically, PRMT1 mediates ADMA modification at position R602 of DDX1. This modification promotes DDX1 nuclear localization by recruiting USP10 to deubiquitinate DDX1, while simultaneously inhibiting PRMT1 degradation. DDX1 promotes the transcription of PRMT1 and USP10 by binding to the mRNA 3’UTR region, establishing a positive feedback regulatory pathway. This mechanism promotes the occurrence and development of CCA and can serve as a target for the inhibitor GSK715 to suppress CCA progression. Conclusions Our study identified DDX1-R602-ADMA modification as a novel ADMA modification in CCA. It further confirmed its pivotal role in CCA progression. Targeting the USP10-PRMT1-DDX1 axis may represent a significant therapeutic approach for CCA.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Short-chain fatty acids （SCFA） are the main metabolic products generated by the fermentation of dietary fiber by gut microbiota. Studies have shown that SCFA not only play a role in energy metabolism， but also act as important signaling molecules， exhibiting a significant potential in alleviating liver and pancreatic fibrosis. The core mechanism of SCFA mainly involves the regulation of various key signaling pathways by activating G protein-coupled receptors and inhibiting the activity of histone deacetylase， thereby suppressing the activation and proliferation of hepatic stellate cell （HSC） and pancreatic stellate cell （PSC）， which is a key link in fibrosis formation. In addition， SCFA can effectively alleviate tissue inflammation response， improve intestinal barrier function， and regulate gut microbiota balance， thus indirectly preventing the process of fibrosis mediated by the “gut-liver/pancreas axis”. Compared with the research on SCFA in liver fibrosis， studies on their role in pancreatic fibrosis are limited. Given that HSC and PSC are highly homologous， the transcription factors and proteins that have been confirmed in liver fibrosis-related studies are also similarly expressed in PSC， suggesting that they may also influence the activation of PSC. This article systematically summarizes the recent advances in the research on SCFA in alleviating liver and pancreatic fibrosis， in order to provide new perspectives for exploring the mechanism of pancreatic fibrosis and developing related interventional strategies.

ObjectiveTo evaluate the anti-inflammatory activity of the novel magnolol ester derivative YW and to investigate its effects on chondrocyte senescence and preliminary mechanisms. MethodsMagnolol and p-methylbenzoic acid were used as raw materials to synthesize the magnolol ester derivative YW （Molecular Formula： C₂₆H₂₄O₃， Molecular Weight： 384.17， HPLC Purity >96%） via DCC/DMAP-catalyzed esterification. Cytotoxicity was assessed using the CCK-8 assay. A lipopolysaccharide （LPS）-induced RAW264.7 macrophage activation model and an interleukin-1β （IL-1β）-induced rat primary chondrocyte model were established. The release and mRNA expression of inflammatory factors including nitric oxide （NO）， IL-1β， tumor necrosis factor-alpha （TNF-α）， and IL-6 were detected by enzyme-linked immunosorbent assay （ELISA）， Griess reagent method， and quantitative real-time PCR （RT-qPCR）. The expression of senescence markers such as inducible nitric oxide synthase （iNOS）， pro-interleukin-1β （pro-IL-1β）， lysine acetyltransferase 7 （KAT7）， cyclin-dependent kinase inhibitor 1A （p21）， and cyclin-dependent kinase inhibitor 2A （p16）， as well as proteins related to chondrocyte extracellular matrix synthesis and catabolism， were analyzed by Western blot （WB）. Molecular docking was performed using Discovery Studio 2019 to validate target binding. ResultsYW exhibited no significant cytotoxicity at concentrations ≤20 μmol/L. YW concentration-dependently inhibited LPS-induced macrophage inflammatory cytokine release， significantly downregulated iNOS， Pro-IL-1β protein， and inflammatory cytokine mRNA expression （P<0.01）. YW stably bound to KAT7 protein （binding energy： -94.2 kcal/mol）； YW downregulated KAT7 and aging marker protein expression in naturally aged and IL-1β-induced chondrocyte models （P<0.01）； YW regulated chondrocyte matrix synthesis and catabolic protein expression in IL-1β-induced chondrocytes （P<0.01）. ConclusionYW inhibits macrophage activation and inflammatory cytokine release while downregulating KAT7 and senescence marker protein expression in chondrocytes， thereby blocking chondrocyte senescence.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Narcotic plants are strictly regulated worldwide due to their ability to extract drug alkaloids and drug precursor components. Besides the three traditional core species, cannabis, opium poppy, and coca, the misuse of psychoactive plants with addictive properties has become increasingly prevalent globally in recent years, and the establishment of accurate identification methods for such plants has become an urgent need in the field of narcotics control. Within existing identification frameworks, the conventional morphological and chemical analysis methods, despite their long-term application, have demonstrated considerable limitations. In contrast, DNA-based molecular identification techniques have achieved significant advancement in recent years due to their high specificity and stability. This review comprehensively examines current DNA-based identification approaches for narcotic plants through three key dimensions: DNA molecular marker technology, DNA barcoding technology, and emerging molecular biological techniques, and elaborates on the principles, technical characteristics, application scenarios, and research progress of each technology, providing some reference for the scientific selection of DNA identification strategies for narcotic plants in different specific scenarios.