ObjectiveTo investigate the mechanism by which Xiebai San regulates respiratory tract and intestinal mucosal immunity in rats with allergic asthma. MethodsForty male SD rats were randomly divided into four groups based on body weight: control group, model group, positive control group, and Xiebai San group. The model group, positive control group, and Xiebai San group were sensitized with ovalbumin to establish a rat model of allergic asthma. From day 21 (the aerosol challenge phase), each group received daily gavage interventions simultaneously: the positive control group was administered dexamethasone (0.068 mg/kg), the Xiebai San group received Xiebai San solution (2 g/mL, 11.3 mL/kg), while the control and model groups were given an equal volume of normal saline, once daily for 14 consecutive days. After euthanasia, lung and intestinal tissues were collected. Hematoxylin and eosin staining was used to observe histopathological changes. Transmission electron microscopy was employed to examine tissue ultrastructure. Immunohistochemistry was applied to detect the positive reaction areas of phosphatidyl-inositol 3-kinase (PI3K) and protein kinase B (Akt) proteins. Total protein and total RNA were extracted from lung and intestinal tissues, then the protein and mRNA expression levels of PI3K and Akt genes were detected by Western blotting and real-time quantitative PCR, respectively. ResultsHistopathological results showed alveolar emphysema accompanied by inflammatory cell infiltration, and intestinal mucosal injury with inflammatory cell infiltration in the model group as compared with the control group; the cellular structure of lung tissues was disrupted in the model group, with reduced organelles, while the ultrastructural lesions in the intestine were relatively mild. Compared with the model group, Xiebai San group exhibited milder pathological changes in lung tissues, with occasional alveolar wall damage and a small amount of inflammatory cell infiltration; the intestinal mucosal structure was improved, glands were arranged regularly, and pathological changes such as tissue loosening and inflammatory infiltration were alleviated; the cellular structure of lung tissues was relatively intact with reduced severity of lesions, and no ultrastructural pathological changes were observed in intestinal tissues. Immunohistochemistry and Western blotting results showed that compared with the control group, the specific positive reaction areas of PI3K and Akt in lung and intestinal tissues were significantly increased in the model group (all P<0.001); meanwhile, the protein expression levels of PI3K and Akt were significantly upregulated (all P<0.05). Compared with the model group, the positive area of Akt protein in lung tissue was significantly reduced in the Xiebai San group (P<0.001), and the positive area of PI3K in intestinal tissue was also significantly decreased (P<0.000 1). Additionally, the protein expression levels of PI3K and Akt in lung and intestinal tissues were significantly downregulated (all P<0.01). Real-time quantitative PCR results showed that compared with the control group, the mRNA expression levels of PI3K and Akt genes in lung and intestinal tissues were significantly elevated in the model group (all P<0.05). Compared with the model group, the mRNA expression levels of PI3K and Akt genes in lung and intestinal tissues were significantly reduced in the Xiebai San group (all P<0.05). ConclusionXiebai San exerts protective effects on rats with allergic asthma by inhibiting the expression of key nucleic acids and proteins in the PI3K-Akt signaling pathway in lung and intestinal tissues, improving the morphological structure of lung tissue, and maintaining intestinal mucosal integrity, and regulating intestinal mucosal immune function.

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.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Objective: To explore the potential application of PAK4-PROTAC targeted degradation drug (PpD) in renal cancer immunotherapy. Methods: TIMER 2.0 and TISIDB databases were used to analyze the relationship among PAK4 expression, tumor purity and abundance of immune cell infiltration in renal tumor microenvironment (TEM).Renal cancer cell lines OS-RC-2, 786-O and ACHN were treated with 0, 125 and 250 nmol/L PpD, and the effects of Jurkat cell co-culture on the results were investigated.The cell apoptosis was detected with flow cytometry, and the expression of programmed cell death 1 ligand 1 (PD-L1) in renal cancer cells was detected with immunoblotting. Results: The high expression of PAK4 was positively related to immune purity, and inhibited the abundance of immune killer cells in TEM, such as CD8 T cells, CD4 T cells, natural killer cells and dendritic cells.With 250 nmol/L PpD treatment, there were 21.02% apoptotic cells in OS-RC-2, 29.67% apoptotic cells in 786-O, and 15.39% apoptotic cells in ACHN, respectively.However, with the same concentration of 250 nmol/L PpD treatment, cell apoptotic rate was sharply increased to 70.13% in OS-RC-2/Jurkat, 70.68% in 780-O/Jurkat, and 60.27% in ACHN/Jurkat co-culture models, respectively. Conclusion: PpD can promote apoptosis of renal cancer cells by reducing the expression of PAK4 protein, and enhance the killing effects of immune cells on tumor cells.

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.

[Objective]To explore and analyze the development of acupuncture and moxibustion based on the evolution of acupuncture needle materials.[Methods]By reviewing ancient literature,combining archaeological facts,and referring to the exploration process of modern and contemporary new needles,the evolution of needle materials and their clinical application history were systematically reviewed according to material classification.[Results]With the development of metal smelting technology and the gradual deepening of people's understanding of diseases,needles have evolved from needle stones and early non-metallic needles to metal needles such as bronze needles,gold and silver needles,iron needles,and steel needles,and then to modern stainless steel needles and various new types of needles such as electric needles,laser needles,magnetic needles,ultrasonic needles,nano needles,etc.Needles have undergone changes in shape,material and usage.The continuous improvement of acupuncture equipment has expanded the therapeutic scope of acupuncture and moxibustion and is more suitable for clinical.Under the background of modern medicine,the combination of medicine and industry has promoted the scientization,standardization and internationalization of acupuncture and moxibustion.[Conclusion]The development of needle materials has centered on improving clinical efficacy,enriching the variety of acupuncture techniques and expanding the scope of acupuncture applications;grounded in progressively sophisticated metallurgical technologies and increasingly refined theoretical system of acupuncture,which drives the advancement of the acupuncture discipline.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

Objective:To explore the effectiveness of robotic implant technology in the postgraduate education of implant dentistry.Methods:The teaching method that combines of theory and model manipulation was used to teach 20 postgraduate students. After completing the theoretical course of implant dentistry, all students performed free hand, digital template, and dental implant robot implant surgery on the simulation jaw models. At the end of the course, an error analysis of the three and a feedback questionnaire distributed to the students were conducted in order to assess the effectiveness of the dental implant robot.Results:Compared to the freehand [2.45(1.1) mm,2.80(0.88) mm,4.95°(2.68°)] and digital template group [1.25(0.68) mm,2.00(0.90) mm, 3.35°(1.60°)], the dental robot implant group had smaller values for implant platform deviation, apical deviation and angular deviation [0.29(0.08) mm,0.26(0.20) mm,0.72°(0.13°)], and the difference was statistically significant ( P<0.001). The results of the questionnaire showed that dental implant robot helps to ensure the accuracy and safety of the implanting process and stimulates students′ interest in learning. Conclusions:At postgraduate level, the safety and accuracy of the implantation process was effectively improved and good teaching result achieved by introducing dental implant robot into the process of dental implant training.

Objective To investigate the expression of regional cerebral oxygen saturation(rSO2)in preterm infants with brain injury(BIPI)and its relationship with amplitude-integrated electroencephalogram(aEEG)parameters and neurodevelopment.Methods Retrospectively,116 cases of BIPI(Bilateral Intra-ventricular Perforation)born in the hospital between February 2022 and February 2023 were selected as the study subjects.According to the Expert Consensus on the Diagnosis and Prevention of Premature Infant Brain Injury,these cases were categorized into mild,moderate,and severe groups,with 59,35,and 22 cases,respectively.The study compared the general characteristics of premature infants with different brain injury levels.Regression analysis was conducted to identify the factors affecting brain injury in premature infants,and correlation analyses were performed on aEEG scores,rSO2,and GMS scores.ROC curve analysis was used to evaluate the value of combining brain oxygen saturation monitoring with aEEG in predicting abnormal whole-body motor quality assessment.Results On the 3rd and 7th days after birth,severe brain-injured premature infants had significantly lower rSO2 and aEEG scores compared to those with mild and moderate brain injuries(P<0.05).At 7 days,these infants also had lower scores for graph continuity,sleep-wake cycles,lower boundary amplitude,bandwidth,total score,rSO2,gestational age,and birth weight,and a higher proportion of abnormal developmental outcomes(PR+CS)(P<0.05).Multivariate logistic regression analysis revealed that the 3-day aEEG total score(OR=0.448,95％CI:0.094～0.890),7-day aEEG total score(OR=0.384,95％CI:0.058～0.726),3-day rSO2(OR=0.574,95％CI:0.398～0.750),and 7-day rSO2(OR=0.431,95％CI:0.115～0.777)were all protective factors for brain injury in premature infants,P<0.05.Correlation analysis showed that brain oxygen saturation was negatively correlated with aEEG scores and overall motor quality.The prediction value for abnormal overall motor quality using 7-day rSO2,aEEG,and the combination of 7-day rSO2 and 7-day aEEG scores was as follows:the positive predictive value for rSO2 was 86.46％,the negative predictive value was 96.85％,the sensitivity was 92.31％,the specificity was 92.21％,and the cut-off value was 0.845;The positive predictive value(PPV)of aEEG was 78.26％,the negative predictive value(NPV)was 96.86％,the sensitivity was 89.74％,and the specificity was 92.21％,with a cut-off value of 0.820.The positive predictive value(PPV)of 7-day rSO2 combined with 7-day aEEG score was 89.04％,the NPV was 96.88％,the sensitivity was 94.90％,and the specificity was 93.51％,with a cut-off value of 0.884,P<0.05.ROC curve analysis showed that the AUC of 7-day rSO2+7-day aEEG score was 0.895,De-long test P<0.005,indicating high predictive value for overall exercise quality.Conclusion Combined with rSO2 and EEG,the prediction of overall motor quality is better,which may have clinical value for excluding high-risk children.