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.

Kynurenine pathway (KP) is a major catabolic route of tryptophan, generating a series of bioactive metabolites including kynurenine, kynurenic acid (KA), quinolinic acid, and 3-hydroxykynurenine. Beyond its fundamental role in amino acid metabolism, KP exerts critical regulatory functions in neurodevelopment, synaptic plasticity, and immune modulation. Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental condition with onset in early childhood, characterized by persistent deficits in social communication and restricted, repetitive behaviors. Despite extensive research, the etiological mechanisms underlying ASD remain highly complex and incompletely understood, involving genetic, environmental, and immunological factors. Emerging clinical evidence has consistently revealed a significant imbalance in KP metabolites in individuals with ASD, often accompanied by altered ratios of neuroprotective versus neurotoxic byproducts. However, the primary drivers of this metabolic dysregulation and its causative contribution to ASD pathogenesis are not yet fully elucidated. In this review, we systematically review the enzymatic steps of KP and the principal physiological functions of its major metabolites, with particular emphasis on their dual roles in neuroprotection and neurotoxicity. We then analyze the potential pathogenic mechanisms through which KP dysfunction may contribute to ASD, focusing on two interconnected etiological dimensions. First, KP imbalance can promote oxidative stress, which in turn triggers chronic inflammatory responses via microglial activation and release of pro-inflammatory cytokines, thereby disrupting neuronal homeostasis. Second, aberrant KP metabolism affects neurotransmitter systems, particularly glutamatergic and dopaminergic signaling, leading to impaired neural circuit development and synaptic pruning. By integrating current findings on the KP-ASD association, this review offers a comprehensive etiological framework and a clinically relevant paradigm. Furthermore, we highlight that specific KP metabolites, such as the KA/quinolinic acid ratio, hold promise as peripheral biomarkers for early diagnosis and disease stratification. Finally, we discuss the therapeutic potential of targeting KP enzymes or receptors for personalized intervention strategies, while acknowledging the challenges in translating these findings into clinical practice.

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.

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.

In June 2018,sows at a pig farm in Jiamusi,Heilongjiang Province,suffered a large num-ber of miscarriages,and subsequently weaned piglets at the farm began to show persistent high fe-ver symptoms at around 35 days of age,with some pigs having a fever of more than 41.5 ℃.In or-der to determine the cause of this outbreak,63 clinical samples from this farm were tested.The re-sults showed that 60 out of 63 samples were positive for the porcine reproductive and respiratory syndrome virus(PRRSV)antigen.Subsequently,PRRSV antigen-positive plasmid was transfected into African green monkey embryonic kidney cells(Marc-145),and after three generations of blind transmission,indirect immunofluorescence assay(IFA)was performed.The results showed that one PRRSV strain,named HLJ38,was successfully isolated.Then the whole genome of HLJ38 strain was sequenced and then analyzed in detail by bioinformatics software.Sequence analysis showed that there were three deletions of 131 amino acids(323-433 aa,483 aa and 504-522 aa)in the derived sequence of Nsp2 gene of HLJ38 strain,which was consistent with the molecular ge-netic marker of NADC30 PRRSV.The phylogenetic tree analysis showed that HLJ38 and NADC30 PRRSV in GenBank belong to lineage 1 subgroup,and the nucleotide homology of HLJ38 and NADC30 PRRSV in GenBank was only 85.2％and 84.6％.Recombinant analysis showed that HLJ38 was a recombinant NADC30-like PRRSV,and the recombinant gene fragments were de-rived from multiple strains,among which the fragment of 1-201 nt was provided by VR2332 strain and fragment of 6 641-8 061 nt derived from the HP-PRRSV strain.In summary,the re-sults showed that the outbreak in this pig farm may be caused by the recombination of PRRSV strains among different lineages,and the recombinant circulating strains not only have certain pathogenicity but also suggest that the existing commercial vaccines provide limited cross-protec-tion against them.Recombination between different lineages increases the genetic diversity of PRRSV and aggravates the difficulty of prevention and control of PRRS in pig farms.Therefore,it is necessary to continuously monitor the epidemic dynamics of PRRSV in pig farms and take effec-tive measures in time to curb the spread of PRRS.

Objective:To understand the prevalence of hearing loss among individuals aged 60 and above undergoing physical examinations and to explore the feasibility of using pure tone audiometry (PTA) for hearing screening in the elderly population, as well as to establish screening criteria suitable for our country.Methods:The study was a cross-sectional study, a total of 1 066 elderly individuals (619 males and 447 females; Age range: 60-90 years old, with an average of 66.5 years old) who underwent physical examinations at the Peking Union Medical College Hospital physical examination center from February to December 2023, were screened using PTA and the Chinese version Hearing Handicap Inventory for the Elderly Screening (CHHIE-S). Different screening criteria were applied to calculate the proportion of individuals who did not pass the PTA screening in the elderly population. The consistency between these results and the screening outcomes of the CHHIE-S scale was analyzed to explore reasonable screening standards. We performed statistical analysis using SPSS 27.0.Results:It was found that 18.39% of the elderly population had moderate or severe hearing loss. The positive rate determined by the detection of pure tones at a fixed dB level was significantly higher than that based on the average hearing threshold across 0.5, 1, 2, and 4 kHz frequencies (4-frequency pure-tone average, 4fPTA), and the difference was statistically significant ( χ2=136.56, P<0.001). The criterion of 4fPTA>35 dB HL in the better ear showed the highest consistency with the criterion of CHHIE-S>8, with a Kappa value of 0.554 ( P<0.001), and this criterion resulted in a positive rate of 15.57% (166/1 066). Conclusions:Conducting hearing screening based on PTA among the elderly population undergoing physical examinations is an effective and feasible approach. Given the subjective perceptions of the elderly population being screened, a 4fPTA greater than 35 dB HL in both ears might be a reasonable criterion.

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.