ObjectiveTo construct and validate a clinical prediction model for inflammatory remission outcomes in rheumatoid arthritis （RA） patients with liver and kidney deficiency syndrome treated with Bushen Zhiwang Decoction （补肾治尪汤， BZD） based on metabolomics. MethodsA prospective cohort study was conducted， enrol-ling 60 RA patients with liver and kidney deficiency syndrome. All patients were treated with BZD and conventional-dose oral conventional synthetic disease-modifying antirheumatic drugs （csDMARDs） for 12 months. Clinical data were collected， and the change in disease activity score in 28 joints （DAS28） after treatment compared with baseline （△DAS28） was used as the primary outcome and grouping criterion. Peripheral blood samples were collected before treatment to analyze plasma metabolites. Differential analysis and least absolute shrinkage and selection operator （LASSO） regression were used to preliminarily screen differential metabolites， followed by machine learning algorithms to further identify a core metabolite combination. Based on the expression levels of the core metabolite combination， a novel metabolite index， namely the metabolomics-based inflammatory remission score （Met-IRS）， was calculated using standar-dized metabolite values， and its clinical applicability was evaluated. A clinical prediction model was constructed by integrating clinical characteristics and Met-IRS， and the model performance was assessed. ResultsAmong the 60 patients， those with △DAS28 ≥ 0.27 were assigned to the high inflammatory remission group， while those with △DAS28 ＜ 0.27 were assigned to the low inflammatory remission group， with 30 cases in each group. Compared to the low inflammatory remission group， the high inflammatory remission group showed a higher frequency of methotrexate use and a lower positive rate of rheumatoid factor （RF） （P＜0.05）. Seven core metabolites were identified as the optimal combination， including mangiferic acid， fatty acid-hydroxy fatty acid ester 40∶6， fatty acid-hydroxy fatty acid ester 18∶0， fatty acid-hydroxy fatty acid ester 36∶1， glucosylceramide， lysophosphatidylcholine 22∶5， and pregnanetriol ketone. The calculated Met-IRS comprehensively reflected the characteristics of differential metabolites and demonstrated clinical applicability. Met-IRS was significantly higher in the high inflammatory remission group than in the low inflammatory remission group， and was positively correlated with high inflammatory remission outcomes （P＜0.05）. Based on the variables Met-IRS， methotrexate use， leflunomide use， and RF positivity， a clinical prediction model for inflammatory remission in RA treatment （Cj-RTRM） was constructed. Model performance evaluation demonstrated that the model had good clinical predictive ability， with an area under the receiver operating characteristic curve （AUC） of 0.880， sensitivity 0.967， specificity 0.700 and Youden's index 0.667. ConclusionThe clinical prediction model Cj-RTRM constructed based on the metabolomics-based inflammatory remission score Met-IRS can effectively predict clinical inflammatory remission outcomes in RA patients treated with BZD and accurately identify the advantageous population for this treatment. This model provides guiding evidence for dynamic inflammation monitoring， targeted management， and identification of populations with advantages in traditional Chinese medicine.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

ObjectiveTo explore the potential mechanism of Xianglian Huazhuo prescription （XLHZ） in treating chronic atrophic gastritis （CAG） by regulating cell cycle and inhibiting proliferation， using bioinformatics technology and animal experiments. MethodsDifferential expressed genes （DEGs） related to CAG were screened using GEO database and GEO2R tool. Weighted gene co-expression network analysis （WGCNA） was employed to search for hub genes of CAG. These hub genes were intersected with cell cycle proliferation based on GeneCards database. Eenrichment analysis of the intersecting genes was performed to obtain signaling pathways and biological processes related to CAG. Protein protein interaction （PPI） analysis of genes was conducted using the Protein Interaction Platform （STRING） database to search the super hub gene （hub 2.0）， and animal experiments were conducted for further validation. Fourteen of 70 male Wistar rats were randomly selected as the normal group， and the remaining 56 rats were prepared by the combined modeling method of "starvation disorder+N-methyl-N-nitro-N-nitrosoguanidine （MNNG） + sodium salicylate". The successfully modeled rats were randomly divided into the model group， XLHZ-H， XLHZ-M， and XLHZ-L groups （36， 18， 9 g·kg^-1， respectively）， and Morodan group （1.4 g·kg^-1）. Each group was given corresponding intervention for 60 days. Hematoxylin-eosin （HE） staining was used to observe the histopathological changes of gastric mucosa in rats. The ultrastructure of gastric mucosal tissue cells was observed by transmission electron microscopy. The relative expression levels of TGF-β₁， Smad2 and Smad3 proteins， S/G₂/M phase marker geminin and proliferation marker MCM2 were detected by Western blot in gastric mucosal tissue， and Spearman correlation analysis was performed. ResultsA total of 15 hub 2.0 genes were identified， including TGF-β₁， suggesting the involvement of the TGF-β₁ signaling pathway in the CAG pathogenesis. Compared with the normal group， the expressions of TGF-β₁， Smad2， geminin and MCM2 proteins in the gastric mucosa tissue of the model group were increased （P<0.05）， and the expression of Smad3 protein was decreased （P<0.05）. Compared with the model group， the expressions of TGF-β₁ and geminin in the gastric mucosa were decreased in the drug groups （P<0.05）. The XLHZ-M group， XLHZ-H group and Morodan group had significantly decreased protein expression of Smad2 and MCM2 （P<0.05）. The protein expression of Smad3 was significantly increased in XLHZ-M， XLHZ-H， and Morodan groups （P<0.05）. Spearman correlation analysis showed that Smad3 was negatively correlated with other indicators， and positively correlated with other indicators （P<0.01）. ConclusionXLHZ may inhibit TGF-β₁/Smads signaling pathway， regulate cell cycle， and inhibit proliferation in the treatment of CAG.

The multimorbidity of rheumatoid arthritis （RA） and periodontitis （PD） has drawn increasing attention， as both conditions are characterized by chronic inflammation， immune dysregulation， and progressive bone destruction. Modern research confirms that PD is a significant risk factor for RA development， and their coexistence mutually exacerbates disease progression. However， traditional Chinese medicine （TCM） currently lacks a systematic theoretical explanation for this complex multimorbid relationship. This study， based on the TCM theory of abnormal collateral， thoroughly examines the intrinsic connection between RA and PD multimorbidity， proposing "abnormal collateral as the pivot， with accumulated toxins eroding bone" as the core TCM pathogenesis. The research elucidates PD as the "origin of abnormal collateral"， where its pathogens act as toxic factors that invade the joints through collaterals， triggering RA via mechanisms such as molecular mimicry. The dynamic pathological progression of RA-PD multimorbidity can be described as follows： the displacement of Ying and Wei at the microscopic level manifests as immune hyperactivation， leading to collateral malnutrition； heat-toxins traversing collaterals induce collateral hyperactivity， resulting in pathological angiogenesis； ultimately， toxin accumulation at the pivotal abnormal collateral site erodes bone， activating the receptor activator of nuclear factor kappa-B ligand （RANKL）-receptor activator of nuclear factor kappa-B （RANK） signaling pathway-driven osteoclast differentiation. This theoretical framework innovatively integrates modern findings in oral microbiology， immune-inflammation， and bone metabolism， offering a holistic and dynamic perspective to understand the complexity of multimorbidity. Given the limited efficacy of current periodontal treatments for RA and the scarcity of reported TCM compound interventions for multimorbidity， the abnormal collateral theory proposes a systematic intervention strategy centered on "governing diseases through collaterals and regulating collaterals with herbs"， along with TCM therapeutic principles such as "unblocking， clearing， and nourishing collaterals". Potential herbal treatments for multimorbidity are also highlighted. Future research should focus on refining TCM syndrome patterns in multimorbid patients and leveraging omics technologies for deeper exploration， thereby providing a theoretical foundation and research direction for TCM in addressing complex multimorbid conditions.

The multimorbidity of rheumatoid arthritis （RA） and periodontitis （PD） has drawn increasing attention， as both conditions are characterized by chronic inflammation， immune dysregulation， and progressive bone destruction. Modern research confirms that PD is a significant risk factor for RA development， and their coexistence mutually exacerbates disease progression. However， traditional Chinese medicine （TCM） currently lacks a systematic theoretical explanation for this complex multimorbid relationship. This study， based on the TCM theory of abnormal collateral， thoroughly examines the intrinsic connection between RA and PD multimorbidity， proposing "abnormal collateral as the pivot， with accumulated toxins eroding bone" as the core TCM pathogenesis. The research elucidates PD as the "origin of abnormal collateral"， where its pathogens act as toxic factors that invade the joints through collaterals， triggering RA via mechanisms such as molecular mimicry. The dynamic pathological progression of RA-PD multimorbidity can be described as follows： the displacement of Ying and Wei at the microscopic level manifests as immune hyperactivation， leading to collateral malnutrition； heat-toxins traversing collaterals induce collateral hyperactivity， resulting in pathological angiogenesis； ultimately， toxin accumulation at the pivotal abnormal collateral site erodes bone， activating the receptor activator of nuclear factor kappa-B ligand （RANKL）-receptor activator of nuclear factor kappa-B （RANK） signaling pathway-driven osteoclast differentiation. This theoretical framework innovatively integrates modern findings in oral microbiology， immune-inflammation， and bone metabolism， offering a holistic and dynamic perspective to understand the complexity of multimorbidity. Given the limited efficacy of current periodontal treatments for RA and the scarcity of reported TCM compound interventions for multimorbidity， the abnormal collateral theory proposes a systematic intervention strategy centered on "governing diseases through collaterals and regulating collaterals with herbs"， along with TCM therapeutic principles such as "unblocking， clearing， and nourishing collaterals". Potential herbal treatments for multimorbidity are also highlighted. Future research should focus on refining TCM syndrome patterns in multimorbid patients and leveraging omics technologies for deeper exploration， thereby providing a theoretical foundation and research direction for TCM in addressing complex multimorbid conditions.

Objective To construct and compare logistic regression and decision tree models for predicting systemic inflammatory response syndrome (SIRS) in patients with type B aortic dissection (TBAD) after interventional surgery. Methods A retrospective analysis was conducted on clinical data of TBAD patients at Peking University Shenzhen Hospital from 2020 to 2024. The patients were divided into a SIRS group and a non SIRS group based on whether SIRS occurred within 24 hours after surgery. Multivariate logistic regression was used to analyze the influencing factors of SIRS occurrence in TBAD intervention patients, and a decision tree model was constructed using SPSS Modeler to compare the predictive performance of the two models. Results A total of 742 patients with TBAD were included, including 579 males and 163 females, aged 27-97 (58.85±10.79) years. Within 24 hours after intervention, a total of 506 patients developed SIRS, with an incidence rate of 68.19%. Logistic regression analysis showed that the extensive involvement of the dissection, the surgical time≥2 hours, PET coated stents implanted, serum creatinine, white blood cell count, C-reactive protein, monocyte (MONO), neutrophil count levels elevated, estimated glomerular filtration rate and decreased albumin levels were independent risk factors for SIRS (P<0.05). The decision tree model selected a total of 10 explanatory variables and 6 layers with 37 nodes, among which MONO was the most important predictor. The area under the decision tree model curve was 0.829 [95%CI (0.800, 0.856)], which was better than the logistic regression model's 0.690 [95%CI (0.655, 0.723)], and the difference was statistically significant (P<0.001). Conclusion The incidence of SIRS after TBAD intervention is high, and the decision tree model has better predictive performance than logistic regression. It can identify high-risk patients with higher accuracy and provide a practical tool for early clinical intervention.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Diabetic retinopathy(DR),as one of the most common microvascular complications in patients with diabe-tes mellitus(DM),has a complex and multifaceted etiology that involves multiple factors.The unique characterization of DR in genomics,epigenomics,transcriptomics,proteomics,and metabolomics has opened new avenues for the exploration and development of novel therapeutic strategies for this disease.However,the inherent limitation of single-omics approa-ches is that they can only analyze the biological and molecular mechanisms underlying the disease from a single dimension,which makes it difficult to comprehensively capture the complex nature of DR.With the rapid advancement of high-throughput sequencing technology,multi-omics joint analysis combines the advantages of different histological techniques and can explore the pathogenesis of DR from multiple dimensions and levels.This paper aims to comprehensively review the latest progress of multi-omics technologies in revealing the pathogenesis of DR and its complex molecular mechanisms and thoroughly explore the new opportunities,current challenges,and future development prospects of multi-omics tech-nologies for DR research.

In recent years, targeted PET imaging of chemokine CXC subfamily receptor 4 (CXCR4) has become a prominent area of research, offering considerable potential for precise diagnosis, tracking disease progression noninvasively, guiding therapeutic strategies, and monitoring treatment responses. This article reviews recent achievements in noninvasive molecular imaging techniques targeting CXCR4 expression, with a particular focus on the pathophysiological mechanisms underlying CXCR4 and the clinical utility of the molecular probe 68Ga-pentixafor PET for diagnosis and treatment. Furthermore, the paper discusses the clinical translation of CXCR4 molecular imaging and highlights prospective research directions.

In order to understand the infection status of Escherichia coli(E.coli)in different popu-lations of chickens,E.coli was isolated and identified from 1-day-old chickens,dead embryos,clini-cal dead chickens from 3 hatcheries and 9 broiler farms in Yantai area,and 1 950 samples from e-liminated breeder chickens;the homology of the isolated strains was analyzed by pulsed field gel e-lectrophoresis;virulence genes and serotypes were identified by PCR;pathogenicity was determined by challenge chicken embryos.Drug resistance of the strain was determined by drug sensitivity test.Results showed that a total of 116 strains of E.coli were isolated,of which 97 strains were successfully classified into 66 band types,15 virulence genes and 5 serotype were detected by PCR,and 56,32 and 28 strains were divided into high,medium and low pathogenic strains by chicken embryo challenge test.Results indicated that E.coli from clinically dead chickens and eliminated breeder chickens had higher pathogenicity and drug resistance.This study provides a reference ba-sis for the prevention and control of colibacillosis in chicken farms.