ObjectiveTo address the challenges of unstructured classical Chinese expressions， nested entity relationships， and limited annotated data in famous traditional Chinese medicine（TCM） case records， this study proposes a joint relation extraction framework that integrates data augmentation and entity mapping， aiming to support the construction of TCM diagnostic knowledge graphs and clinical pattern mining. MethodsWe developed an annotation structure for entities and their relationships in TCM case texts and applied a data augmentation strategy by incorporating multiple ancient texts to expand the relation extraction dataset. A cascade binary tagging framework for relation triple extraction（CasRel） model for TCM semantics was designed， integrating a pre-trained bidirectional encoder representations from transformers（BERT） layer for classical TCM texts to enhance semantic representation， and using a head entity-relation-tail entity mapping mechanism to address entity nesting and relation overlapping issues. ResultsExperimental results showed that the CasRel model， combining data augmentation and entity mapping， outperformed the pipeline-based Bert-Radical-Lexicon（BRL）-bidirectional long short-term memory（BiLSTM）-Attention model. The overall precision， recall， and F₁-score across 12 relation types reached 65.73%， 64.03%， and 64.87%， which represent improvements of 14.26%， 7.98%， and 11.21% compared to the BRL-BiLSTM-Attention model， respectively. Notably， the F₁-score for tongue syndrome relations increased by 22.68%（69.32%）， and the prescription-syndrome relations performed the best with the F₁-score of 70.10%. ConclusionThe proposed framework significantly improves the semantic representation and complex dependencies in TCM texts， offering a reusable technical framework for structured mining of TCM case records. The constructed knowledge graph can support clinical syndrome differentiation， prescription optimization， and drug compatibility， providing a methodological reference for TCM artificial intelligence research.

OBJECTIVE To investigate the mechanism by which Shenfukang capsule （SFK） ameliorates renal interstitial fibrosis （RIF） by regulating macrophage-fibroblast crosstalk via the signal transducer and activator of transcription 3 （STAT3）/Yes-associated protein （YAP） pathway. METHODS RAW264.7 macrophages were induced to polarize with transforming growth factor-β 1 （TGF-β 1 ）. Subsequently， a non-contact co-culture system of macrophages with renal fibroblasts NRK-49F， as well as a non-contact co-culture system of macrophages with YAP-knockdown renal fibroblasts， were established. Cells were treated with low， medium， and high concentrations （4， 8， 16 μg/mL） of SFK， as well as a STAT3 inhibitor （STAT3-I，1.64 μg/mL） and losartan potassium tablets （positive control， 0.28 μg/mL）， for 48 h. After intervention， the protein and mRNA expression levels of CD86， CD163， and STAT3 in macrophages， as well as CD86， F4/80， and STAT3 mRNA， were detected. In co-cultured renal fibroblasts， the protein and mRNA expression levels of α -smooth muscle actin （ α -SMA）， Vimentin， collagen type Ⅰ （Col-Ⅰ）， matrix metalloproteinase-1 （MMP-1）， and YAP were detected. In co-cultured YAP-knockdown renal fibroblasts， the protein and mRNA expression levels of α -SMA， Vimentin， and MMP-1 were also detected. RESULTS Following TGF-β 1 induction， the protein expression levels of CD86， CD163， and STAT3， as well as the mRNA expression levels of CD86， F4/80， and STAT3 in macrophages were significantly increased （ P ＜0.05）. The conditioned medium from polarized macrophages activated renal fibroblasts， as evidenced by significantly increased protein and mRNA expression levels of α -SMA， Vimentin， Col-Ⅰ， and YAP， and significantly decreased protein and mRNA expression levels of MMP-1 in renal fibroblasts （ P ＜0.05）. Treatment with SFK and STAT3-I reversed the changes in the above indicators， with the medium concentration SFK group showing stronge r effects on some indicators than the low and high concentration groups. In the non-contact co-culture experiment of macrophages and YAP-knockdown renal fibroblasts， there were no statistically significant differences in the protein and mRNA expression of α-SMA， Vimentin， and MMP-1 among the groups. CONCLUSIONS SFK can inhibit macrophage-renal fibroblast crosstalk by blocking the STAT3/YAP pathway， thereby delaying the progression of RIF.

ObjectiveTo explore the clinical safety of Feilike Mixture （FLK） in the real world. MethodsThe safety of all children who received FLK from 29 institutions in 12 provinces between January 21，2021 and December 25，2021 was evaluated through prospective centralized surveillance and a nested case control study. ResultsA total of 3 035 juveniles were included. There were 29 research centers involved，which are distributed across 12 provinces，including one traditional Chinese medicine （TCM） hospital and 28 general hospitals. The average age among the juveniles was （4.77±3.56） years old，and the average weight was （21.81±12.97） kg. Among them，119 cases （3.92%） of juveniles had a history of allergies. Acute bronchitis was the main diagnosis for juveniles，with 1 656 cases （54.46%）. FLK was first used in 2 016 cases （66.43%），and 142 juvenile patients had special dosages，accounting for 4.68%. Among them，92 adverse drug reactions （ADRs） occurred，including 73 cases of gastrointestinal system disorders，10 cases of metabolic and nutritional disorders，eight cases of skin and subcutaneous tissue diseases，two cases of vascular and lymphatic disorders，and one case of systemic diseases and various reactions at the administration site. The manifestations of ADRs were mainly diarrhea，stool discoloration，and vomiting，and no serious ADRs occurred. The results of multi-factor analysis indicated that special dosages （the use of FLK）［odds ratio （OR） of 2.642， 95% confidence interval （CI） of 1.105-6.323］，combined administration： spleen aminopeptide （OR of 4.978， 95%CI of 1.200-20.655），and reason for combined administration： anti-infection （OR of 1.814， 95%CI of 1.071-3.075） were the risk factors for ADRs caused by FLK. Conclusion92 ADRs occurred among 3 035 juveniles using FLK. The incidence of ADRs caused by FLK was 3.03%，and the severity was mainly mild or moderate. Generally，the prognosis was favorable after symptomatic treatment such as drug withdrawal or dosage reduction，suggesting that FLK has good clinical safety.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

ObjectiveTo explore the potential mechanism of action of the combination of Sanguisorbae Radix-Sophorae Flos （DH） in the treatment of ulcerative colitis （UC） using network pharmacology methods and molecular docking technology. MethodsNetwork pharmacology analysis was utilized to predict the potential targets of DH for the treatment of UC. The therapeutic effects were experimentally validated by inducing a UC model in mice with 3% dextran sulfate sodium （DSS）. The experimental groups were the normal group， the model group， the salazosulfapyridine group （100 mg·kg^-1）， and the low， medium， and high dose groups of DH （1.2， 2.4， and 4.8 g·kg^-1）. The efficacy of the treatment was assessed through the general condition of the mice， histopathological examination， and the expression levels of inflammatory markers in the colon. The effect of DH on angiogenesis was explored by messenger RNA （mRNA） detection of colonic angiogenesis-related mediators， vascular endothelial growth factor （VEGF） immunohistochemistry， microvessel density （MVD） detection， and transmission electron microscopy. The phosphatidylinositol-3-kinase （PI3K）-protein kinase B （Akt） signaling pathway proteins were quantitatively analyzed through Western blot to assess whether the suppression of pathological angiogenesis by DH is associated with this pathway. ResultsNetwork pharmacological analysis yielded 112 potential core therapeutic targets for the treatment of UC with DH， of which the core targets were tumor protein 53 （TP53）， JUN， interleukin （IL）-6， Akt1， and tumor necrosis factor （TNF）. Compared with the normal group， mice in the model group showed significant weight loss， colon shortening， and high DAI score， increased expression of inflammatory factors IL-6， IL-1β， and TNF-α， as well as increased mRNA expression levels of angiogenesis-related mediators VEGF， vascular cell adhesion molecule 1 （VCAM1）， angiotensin 1 （Ang1）， matrix metalloproteinase （MMP）-1， MMP-2， and MMP-9. The positive expression of CD31 and VEGF in colonic tissue increased， and the protein expression of the PI3K/Akt pathway was increased （P<0.05）. The endothelial cells of the colonic mucosa and the colonic vasculature were severely damaged. Compared with the model group， mice in the DH groups had significantly reduced weight loss and colon shortening， lower DAI scores， and a significant decrease in mRNA expression of inflammatory factors and angiogenesis-related mediators. In addition， there was decreased positive expression of CD31 and VEGF in colonic tissue and decreased protein expression of the PI3K/Akt pathway （P<0.05）. ConclusionNetwork pharmacology， molecular docking， and experimental validation are applied to explore the mechanism of action of DH in the treatment of UC， and it is found that DH is able to improve the symptoms of colitis and inhibit the pathological angiogenesis in UC mice. Its action might be related to affecting the PI3K/Akt pathway.

Loss-of-function variants of low-density lipoprotein receptor-related protein 5 (LRP5) can lead to reduced bone formation, culminating in diminished bone mass. Our previous study reported transcription factor osterix (SP7)‍-binding sites on the LRP5 promoter and its pivotal role in upregulating LRP5 expression during implant osseointegration. However, the potential role of SP7 in ameliorating LRP5-dependent osteoporosis remained unknown. In this study, we used mice with a conditional knockout (cKO) of LRP5 in mature osteoblasts, which presented decreased osteogenesis. The in vitro experimental results showed that SP7 could promote LRP5 expression, thereby upregulating the osteogenic markers such as alkaline phosphatase (ALP), Runt-related transcription factor 2 (Runx2), and β‍-catenin (P<0.05). For the in vivo experiment, the SP7 overexpression virus was injected into a bone defect model of LRP5 cKO mice, resulting in increased bone mineral density (BMD) (P<0.001) and volumetric density (bone volume (BV)/total volume (TV)) (P<0.001), and decreased trabecular separation (Tb.‍Sp) (P<0.05). These data suggested that SP7 could ameliorate bone defect healing in LRP5 cKO mice. Our study provides new insights into potential therapeutic opportunities for ameliorating LRP5-dependent osteoporosis.
Animals ; Low Density Lipoprotein Receptor-Related Protein-5/metabolism* ; Osteoporosis/genetics* ; Mice ; Mice, Knockout ; Sp7 Transcription Factor/physiology* ; Osteogenesis ; Bone Density ; Osteoblasts/metabolism* ; Core Binding Factor Alpha 1 Subunit/metabolism* ; Mice, Inbred C57BL ; beta Catenin/metabolism*

Objective To investigate the association between serum magnesium levels,serum phosphorus concentrations,vascular calcification,and cardiovascular disease mortality in maintenance hemodialysis patients.Methods This study enrolled 200 hemodialysis patients admitted to Nanjing Drum Tower Hospital from May 2020 to May 2022 as subjects,with an additional 200 healthy individuals from the same period selected as a control group.The biochemical indicators between the two groups were compared;their correlations were analyzed.Binary logistic regression was used to investigate the independent factors of serum magnesium and phosphorus levels in relation to vascular calcification and cardiovascular events in maintenance hemodialysis patients.ROC curve analysis was employed to assess the predictive value of serum magnesium and phosphorus for vascular calcification and cardiovascular events.Results The research group's patients exhibited significantly elevated levels of blood phosphorus,calcium-phosphorus product,iPTH,AACS,and 25-(OH)-VitD compared to the control group.In contrast,their blood magnesium and BMP-7 levels were notably lower than those of the control group,with statistical significance(P<0.05).Pearson correlation showed positive correlations between serum magnesium and serum calcium,phosphorus,calcium-phosphorus product,25-(OH)-VitD3,and BMP-7(r=0.385,0.183,0.141,0.131,0.458,P<0.05);between serum calcium and serum phosphorus,calcium-phosphorus product,iPTH,AACS,25-(OH)-VitD3,and BMP-7(r=0.318),correlation(r=0.318,0.311,0.098,0.170,0.277,0.485,P<0.05);between serum phosphorus and calcium-phosphorus product,iPTH,AACS,25-(OH)-VitD3(r=0.362,0.506,0.367,0.461,P<0.05);between calcium-phosphorus product and iPTH,AACS,25-(OH)-VitD3(r=0.542,0.373,0.434,P<0.05);between iPTH and AACS,25-(OH)-VitD3 showing positive correlations(r=0.553,0.616,P<0.05)and a negative correlation with BMP-7(r=-0.373,P<0.05);between AACS and 25-(OH)-VitD3 showing a positive correlation(r=0.402,P<0.05),and a negative correlation with BMP-7(r=-0.155,P<0.05),with statistically significant differences(P<0.05).Statistically significant differences were noted between the two groups in age,diabetes,serum magnesium,serum calcium,serum phosphorus,calcium-phosphorus product,25-(OH)-VitD3,and hs-CRP(P<0.05).Logistic regression analysis showed that age,serum magnesium,serum calcium,serum phosphorus,calcium phosphate product,25-(OH)-vitamin I were all risk factors for cardiovascular disease(CVD)mortality in maintenance hemodialysis(MHD)patients(P<0.05).ROC curve analysis showed that serum magnesium,serum calcium,and serum phosphorus had predictive areas under the curve(AUC)of 0.895,0.802,and 0.851 for CVD mortality in MHD patients,with sensitivities and specificities of 87.5%/98.7%,66.7%/90.8%,and 72.9%/100%,respectively.The combined prediction for CVD mortality in MHD patients showed an AUC of 0.921,with a sensitivity of 81.3%and specificity of 93.4%.Conclusion MHD patients exhibit low blood magnesium levels,elevated serum phosphorus concentrations,and increased calcium-phosphorus product,with complex correlations among these biomarkers.Age,magnesium,calcium,and phosphorus levels were all associated with CVD mortality.ROC curve analysis demonstrates that magnesium,calcium,and phosphorus,both individually and in combination,have high predictive value for CVD mortality risk.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

OBJECTIVE To construct a predictive tool for surgical site infections(SSIs)in spinal surgery for Chi-nese population to provide evidence support for reducing SSIs.METHODS A systematic review of Chinese and English database literature was conducted for Meta-analysis to obtain pooled risk values for influencing factors,and a risk prediction scoring tool was constructed based on the logistic regression model.Patients who underwent spinal surgery and completed postoperative follow-up in a tertiary hospital in Beijing from Jan.to Dec.2021 were selected to validate the predictive effect of the tool.RESULTS The predictive model for SSIs in Chinese spinal sur-gery patients was Logit(P)=—3.47+0.63(age 60 years)+0.31 ×(patient with cardiovascular disease)+0.69 ×(rheumatoid arthritis)+1.07 ×(diabetes)+1.06 ×(operation duration＞3 h)+1.17 ×(preopera-tive albumin＜35 g/L)+0.71 ×(history of spinal surgery)+0.67 ×(carrying internal implants)+0.73 ×(blood transfusion).The total score of the predictive tool was 92,with a cutoff score of≥24.50 indicating high-risk individuals.The area under the curve was 0.733,with the sensitivity 58.30％and the specificity 79.60％.CONCLUSION The established predictive model for SSIs in Chinese spine surgery demonstrates good predictive performance and can be used as a reference assessment tool in clinical practice.

Protein lysine β-hydroxybutyrylation (Kbhb) is a newly discovered post-translational modification associated with a wide range of biological processes. Identifying Kbhb sites is critical for a better understanding of its mechanism of action. However, biochemical experimental methods for probing Kbhb sites are costly and have a long cycle. Therefore, a feature embedding learning method based on the Transformer encoder was proposed to predict Kbhb sites. In this method, amino acid residues were mapped into numerical vectors according to their amino acid class and position in a learnable feature embedding method. Then the Transformer encoder was used to extract discriminating features, and the bidirectional long short-term memory network (BiLSTM) was used to capture the correlation between different features. In this paper, a benchmark dataset was constructed, and a Kbhb site predictor, AutoTF-Kbhb, was implemented based on the proposed method. Experimental results showed that the proposed feature embedding learning method could extract effective features. AutoTF-Kbhb achieved an area under curve (AUC) of 0.87 and a Matthews correlation coefficient (MCC) of 0.37 on the independent test set, significantly outperforming other methods in comparison. Therefore, AutoTF-Kbhb can be used as an auxiliary means to identify Kbhb sites.
Protein Processing, Post-Translational ; Lysine/chemistry* ; Proteins/chemistry* ; Machine Learning ; Algorithms