The inflammatory microenvironment is closely associated with the initiation and progression of osteoarthritis （OA）， specifically manifesting as macrophage activation， dysregulation of inflammatory cytokines， and redox imbalance. Following an overview of the pathological characteristics of the OA inflammatory microenvironment， this paper reviews the research progress on the mechanism of traditional Chinese medicine （TCM） intervening in OA by modulating the inflammatory microenvironment. It has been found that TCM monomers/active ingredients （such as total alkaloids from Strychnos nux-vomica ， quercetin， triptolide， etc.）， herb pairs （e.g. Angelica pubescens - Gentiana macrophylla ， Carthami Flos-Lycopodii Herba）， and TCM formulas （such as Zhuanggu jianxi formula， Duhuo jisheng decoction and Rongjin niantong formula， etc.） can inhibit macrophage activation， reduce the release of proinflammatory cytokines and the generation of reactive oxygen species by inhibiting multiple signaling pathways， including nuclear factor-κB， Wnt/ β -catenin， and mitogen-activated protein kinase， thereby alleviating the articular inflammatory microenvironment， restoring local joint homeostasis， and slowing the progression of OA.

Background: Disorders of the blood-brain barrier (BBB) arising from diabetes mellitus are closely related to diabetic encephalopathy. Previous research has suggested that neuron-glia antigen 2 (NG2)-glia plays a key role in maintaining the integrity of the BBB. However, the mechanism by which NG2-glia regulates the diabetic BBB remains unclear. Methods: Type 2 diabetes mellitus (T2DM) db/db mice and db/m mice were used. Evans-Blue BBB permeability tests and transmission electron microscopy techniques were applied. Tight junction proteins were assessed by immunofluorescence and transmission electron microscopy. NG2-glia number and signaling pathways were evaluated by immunofluorescence. Detection of matrix metalloproteinase-9 (MMP-9) in serum was performed using enzyme-linked immunosorbent assay (ELISA). Results: In T2DM db/db mice, BBB permeability in the hippocampus significantly increased from 16 weeks of age, and the structure of tight junction proteins changed. The number of NG2-glia in the hippocampus of db/db mice increased around microvessels from 12 weeks of age. Concurrently, the expression of MMP-9 increased in the hippocampus with no change in serum. Sixteen- week-old db/db mice showed activation of the Wnt/β-catenin signaling in hippocampal NG2-glia. Treatment with XAV-939 improved structural and functional changes in the hippocampal BBB and reduced MMP-9 secretion by hippocampal NG2-glia in db/db mice. It was also found that the upregulation of β-catenin protein in NG2-glia in the hippocampus of 16-week-old db/db mice was significantly alleviated by treatment with XAV-939. Conclusion The results indicate that NG2-glia can lead to structural and functional disruption of the diabetic BBB by activating Wnt/β-catenin signaling, upregulating MMP-9, and degrading tight junction proteins.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

OBJECTIVE: To observe the clinical effect of acupuncture and moxibustion combined with umbilical therapy on anxiety and depression in patients with neurogenic bladder (NB) after spinal cord injury (SCI). METHODS: Thirty cases of NB after SCI with anxiety and depression were selected and treated with acupuncture and moxibustion combined with umbilical therapy. Acupuncture was applied at Baihui (GV20), Yintang (GV24⁺), Sanyinjiao (SP6), Shenmen (HT7), Hegu (LI4), Taichong (LR3), once a day, continuous treatment for 4 weeks. Ginger moxibustion was applied at the bladder meridian of foot taiyang and governor vessel, once a day, continuous treatment for 4 weeks. In treatment of umbilical therapy, Chaihu (Radix Bupleuri), Yujin (Radix Curcumae), Rougui (Cortex Cinnamomi) were ground and mixed with the same amount of honey, put into the application, and the application was placed on the navel after filling the navel with fine salt, once a day for 4 weeks. Hamilton anxiety scale (HAMA) score, Hamilton depression scale (HAMD) score, urodynamic indexes (maximum urinary flow rate [Qmax], maximum detrusor pressure [Pdet-max], residual urine volume [RUV]), neurogenic bladder symptom score (NBSS), urinary symptom distress scale (USDS) score were compared before and after treatment, and the clinical efficacy was evaluated. RESULTS: After treatment, the scores of HAMA, HAMD, NBSS, USDS and RUVwere lower than those before treatment (P<0.05), and Qmax and Pdet-max were higher than those before treatment (P<0.05). The total effective rate was 93.3 (28/30). CONCLUSION Acupuncture and moxibustion combined with umbilical therapy can effectively relieve anxiety and depression symptoms, improve urination disorders in patients with NB after SCI.
Humans ; Moxibustion ; Male ; Female ; Adult ; Middle Aged ; Acupuncture Therapy ; Spinal Cord Injuries/psychology* ; Depression/etiology* ; Anxiety/etiology* ; Urinary Bladder, Neurogenic/etiology* ; Young Adult ; Aged ; Combined Modality Therapy ; Acupuncture Points

Cardiac fibrosis is characterized by an elevated amount of extracellular matrix (ECM) within the heart. However, the persistence of cardiac fibrosis ultimately diminishes contractility and precipitates cardiac dysfunction. Circular RNAs (circRNAs) are emerging as important regulators of cardiac fibrosis. Here, we elucidate the functional role of a specific circular RNA CELF1 in cardiac fibrosis and delineate a novel feedback loop mechanism. Functionally, circ-CELF1 was involved in enhancing fibrosis-related markers' expression and promoting the proliferation of cardiac fibroblasts (CFs), thereby exacerbating cardiac fibrosis. Mechanistically, circ-CELF1 reduced the ubiquitination-degradation rate of BRPF3, leading to an elevation of BRPF3 protein levels. Additionally, BRPF3 acted as a modular scaffold for the recruitment of histone acetyltransferase KAT7 to facilitate the induction of H3K14 acetylation within the promoters of the Celf1 gene. Thus, the transcription of Celf1 was dramatically activated, thereby inhibiting the subsequent response of their downstream target gene Smad7 expression to promote cardiac fibrosis. Moreover, Celf1 further promoted Celf1 pre-mRNA transcription and back-splicing, thereby establishing a feedback loop for circ-CELF1 production. Consequently, a novel feedback loop involving CELF1/circ-CELF1/BRPF3/KAT7 was established, suggesting that circ-CELF1 may serve as a potential novel therapeutic target for cardiac fibrosis.

OBJECTIVES: To investigate the mechanism through which pinostrobin (PSB) alleviates dextran sulfate sodium (DSS)-induced colitis in mice. METHODS: C57BL/6 mice were randomized into control group, DSS model group, and PSB intervention (30, 60, and 120 mg/kg) groups. Colitis severity of the mice was assessed by examining body weight changes, disease activity index (DAI), colon length, and histopathology. The expressions of tight junction proteins ZO-1 and claudin-1 in the colon tissues were examined using immunofluorescence staining, and macrophage infiltration and polarization were analyzed with flow cytometry. ELISA and RT-qPCR were used for detecting the expressions of inflammatory factors (TNF‑α and IL-6) and chemokines (CCL₂, CXCL₁₀, and CX₃CL₁) in the colon tissues, and PI3K/AKT phosphorylation levels were analyzed with Western blotting. In cultured Caco-2 and RAW264.7 cells, the effect of PSB on CCL₂-mediated macrophage migration was assessed using Transwell assay. Network pharmacology analysis was performed to predict the key pathways that mediate the therapeutic effect of PSB. RESULTS: In DSS-induced mouse models, PSB at 60 mg/kg optimally alleviated colitis, shown by reduced weight loss and DAI scores and increased colon length. PSB treatment significantly upregulated ZO-1 and claudin-1 expressions in the colon tissues, inhibited colonic macrophage infiltration, and promoted the shift of macrophage polarization from M1 to M2 type. In cultured intestinal epithelial cells, PSB significantly inhibited PI3K/AKT phosphorylation and suppressed chemokine CCL₂ expression. PSB treatment obviously blocked CCL₂-mediated macrophage migration of RAW264.7 cells, which could be reversed by exogenous CCL₂. Network pharmacology analysis and rescue experiments confirmed PI3K/AKT and CCL₂ signaling as the core targets of PSB. CONCLUSIONS PSB alleviates DSS-induced colitis in mice by targeting intestinal epithelial PI3K/AKT signaling, reducing CCL₂ secretion, and blocking macrophage chemotaxis and migration, highlighting the potential of PSB as a novel natural compound for treatment of inflammatory bowel disease.
Animals ; Mice ; Mice, Inbred C57BL ; Phosphatidylinositol 3-Kinases/metabolism* ; Colitis/drug therapy* ; Dextran Sulfate ; Proto-Oncogene Proteins c-akt/metabolism* ; Macrophages ; Chemokine CCL2/metabolism* ; Humans ; Signal Transduction/drug effects* ; Caco-2 Cells ; RAW 264.7 Cells ; Epithelial Cells/drug effects* ; Intestinal Mucosa/metabolism*

Gout significantly impacts both physical health and quality of life,while current pharmacological treatments face notable limitations.TCM non-pharmacological therapies have shown promising potential in the management of gout,offering diverse approaches with favorable efficacy.This article summarized the characteristics,clinical efficacy and mechanisms of different TCM non-pharmacological therapies for treating gout.Recent studies suggest that these therapies may be applied across all clinical stages of gout.During the acute phase,they can rapidly reduce joint inflammation and relieve pain.In the intercritical phase,they help prevent recurrence,decrease the frequency of attacks,and shorten episode duration.In the chronic tophaceous phase,they alleviate persistent symptoms,improve joint function,and support minimally invasive tophi removal.TCM non-pharmacological therapies have their own characteristics and good safety,and can be combined for clinical use,providing TCM treatment strategies for gout.

Objective:To explore and model risk factors in patients with major adverse cardiovascular events (MACEs) after acute type A aortic dissection (ATAAD), and to develop and validate a personalized machine learning model to assess risk factors and predict MACEs in these patients.Methods:Clinical data of patients who attended Beijing Anzhen Hospital and underwent surgical treatment for ATAAD from January 2018 to October 2022 were retrospectively analyzed. Using MACEs as the endpoint, 70% of these patients were randomly divided into the training set and the remaining 30% into the validation set. LASSO regression was applied to explore key clinical variables in the training set. The optimal predictive model was selected from nine machine learning algorithms based on area under the curve. And Shapley Additive explanations was used to elucidate the predictive model. Results:Of the 481 patients included in this study, 135 (35.6%) patients experienced an endpoint event. By combining the results of the training and validation sets, when assessing the validity of the single model with the highest predictive accuracy for the outcome, it was shown that the logistic model (0.774, 95% CI: 0.717-0.830) was the most effective in the combined effect and had a high model accuracy (0.743, 95% CI: 0.720-0.766). According to the results of the LASSO, the factors most associated with postoperative MACEs were history of cerebrovascular disease, coronary artery involvement, shock status on admission to the operating room, FDP, PLT, CPB, ascending aortic clamping, and age. Conclusion:In this study, nine machine learning models were developed to predict the occurrence of postoperative MACEs in patients with acute type A aortic dissection. The logistic model performed significantly better compared to other algorithms. Our study successfully predicted postoperative MACES and identified the factors most associated with MACEs.

Objective:To develop a risk prediction model for moderate to severe orthodontic-induced inflammatory root resorption (OIIRR) of maxillary incisors based on cone beam CT (CBCT) radiomics features and clinical characteristics of the orthodontic patients.Methods:Clinical and CBCT data from 101 orthodontic patients treated by the same attending orthodontist in the Department of Orthodontics, Stomatology Hospital of Tianjin Medical University from January 2019 to January 2024 were retrospectively collected. The sample included 42 class Ⅰ patients, 52 class Ⅱ patients and 7 class Ⅲ patients [age: (19.7±6.3) years], and a total of 394 maxillary incisors were analyzed. Potential influencing factors for moderate to severe OIIRR (root volume resorption rate≥10%) were collected from the patients′ CBCT and medical records, including initial age, gender, treatment duration, Angle′s classification, extraction or not, type of orthodontic appliance (fixed or clear aligner), changes in root inclination, root movement distance and direction, pre-treatment cephalometric measurements, pre-treatment root-bone relationship, pre-treatment root length, and pre-treatment radiomics features of the teeth. Univariate analysis was initially performed to screen for factors influencing moderate to severe OIIRR. Subsequently, least absolute shrinkage and selection operator (LASSO) regression, best subset regression, and random forest were used for feature selection to construct the OIIRR risk prediction model. The discrimination, calibration, and net benefit of the three risk prediction models were evaluated, and the optimal model was displayed using a nomogram.Results:LASSO regression identified clinical features including initial age (LASSO coefficient 0.052), treatment duration (LASSO coefficient 0.024), pre-treatment root length (LASSO coefficient -0.023), and vertical root movement distance (LASSO coefficient -0.029). Initial age and treatment duration were positively correlated with the severity of OIIRR, while root length and vertical root movement distance were negatively correlated. A total of 14 radiomics features were identified, including 2 original image features and 12 wavelet features. Best subset regression identified vertical root movement distance as the clinical feature and 7 radiomics features, including 1 original image feature and 6 wavelet features. The random forest model identified 8 wavelet features as important predictors, and all of which were radiomics features. Model performance evaluation showed that the random forest model had the highest discrimination, calibration, and net benefit, making it the optimal model, with radiomics features being the most important predictors.Conclusions:Based on the data from this study, radiomics features were identified as the most important predictors by the optimal model for OIIRR risk prediction. Predicting the occurrence of moderate to severe OIIRR before orthodontic treatment held potential clinical application value.