ObjectiveTo establish a new noninvasive， simple， and convenient clinical predictive model by identifying independent predictive factors for rebleeding after endoscopic therapy in cirrhotic patients with esophagogastric variceal bleeding （EGVB）， and to provide a basis for individualized risk assessment and development of clinical intervention strategies. MethodsCirrhotic patients with EGVB who were diagnosed and treated in The First Affiliated Hospital of Xi’an Medical University from September 2018 to October 2023 were enrolled as subjects， and according to whether the patient experienced rebleeding within 1 year after endoscopic therapy， they were divided into rebleeding group with 93 patients and non-rebleeding group with 84 patients. Clinical data were collected and analyzed. The independent samples t-test was used for comparison of normally distributed continuous data between two groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups； the chi-square test was used for comparison of categorical data between two groups. A Logistic model was established based on the results of the univariate and multivariate analyses， and the receiver operating characteristic （ROC） curve and the area under the ROC curve （AUC） were used to assess the accuracy of the model. R software was used to visualize the model by plotting a nomogram， and the Bootstrap method was used for internal validation of the model. ResultsThe multivariate analysis showed that red blood cell count （RBC）， cholinesterase （ChE）， alkaline phosphatase （ALP）， albumin （Alb）， thrombin time （TT）， portal vein trunk diameter， sequential therapy， and primary prevention were independent predictive factors for rebleeding. Based on the results of the multivariate analysis， a logistic model was established as logit（P）=-0.805-1.978×（RBC）+0.001×（ChE）-0.020×（ALP）-0.314×（Alb）+0.567×（TT）+0.428×（portal vein trunk diameter）-2.303×［sequential therapy （yes=1， no=0）］-2.368×［primary prevention （yes=1， no=0）］. The logistic model （AUC=0.928， 95% confidence interval ［CI］： 0.893—0.964， P<0.001） had a better performance in predicting rebleeding than MELD score （AUC=0.603， 95%CI： 0.520—0.687， P=0.003）， Child-Pugh class （AUC=0.650， 95%CI： 0.578—0.722， P=0.001）， and FIB-4 index （AUC=0.587， 95%CI： 0.503—0.671， P=0.045）. The model had an optimal cut-off value of 0.607， a sensitivity of 0.817， and a specificity of 0.817. Internal validation confirmed that the model had good predictive performance and accuracy. ConclusionSequential therapy， implementation of primary prevention， an increase in RBC， and an increase in Alb are protective factors against rebleeding， while prolonged TT and widened main portal vein diameter are risk factors. The logistic model based on these independent predictive factors can predict rebleeding and thus holds promise for clinical application.

The emergence of teeth is a complex physiological process characterized by the formation of the tooth crown, its movement towards the occlusal plane, and subsequent penetration through the alveolar bone and oral mucosa to achieve functional positioning for contact with opposing teeth. Parathyroid hormone (PTH) and parathyroid hormone-related peptide (PTHrP) are critical regulators of calcium and phosphorus metabolism in the body, playing significant roles in tooth emergence. Their regulatory functions exhibit intricate temporal and spatial dynamics, with underlying mechanisms that remain incompletely understood. In recent years, an increasing number of researchers both domestically and internationally have investigated the role and mechanisms of PTH/PTHrP in tooth emergence, primarily focusing on aspects such as dental sac formation, basal alveolar bone development, coronal alveolar bone resorption, root formation, and periodontal ligament development. Literature reviews indicate that PTH and PTHrP regulate bone metabolism, coordinate various signaling pathways including OPG/RANK/RANKL, cAMP/PKA, and Wnt/β-catenin, and are allosterically modulated by Ca2+ and ATP. These processes contribute to the development of dental sacs, which transmit signals to recruit osteoclasts and promote the resorption of crown alveolar bone, thereby forming an eruption pathway. Additionally, PTH/PTHrP plays a role in the formation of basal alveolar bone, root development, and the periodontal ligament, generating the force necessary for tooth eruption. Through precise spatiotemporal regulation and coordinated efforts, alveolar bone remodeling is achieved, facilitating the intricate process of tooth eruption. Through stringent temporal regulation and multi-faceted cooperation, remodeling of the alveolar bone occurs to complete this intricate developmental process of tooth emergence. Future research should further elucidate the mechanisms underlying PTH/PTHrP actions while also considering optimal dosage regimens regarding timing and frequency for therapeutic applications.

Resveratrol(Res) is a kind of polyphenolic compound, possessing multiple biological activities such as antioxidant, anti-inflammatory, cardioprotective, and anticancer effects. In recent years, the cardiovascular protective mechanism of Res has become a research hotspot. Studies have shown that Res has a protective effect on the cardiovascular system through various pathways, such as inhibiting oxidative stress, regulating ferroptosis of cells, improving ischemia-reperfusion(I/R) injury, regulating lipid metabolism, suppressing inflammatory responses, and enhancing endothelial function. It can also alleviate cardiotoxicity caused by drugs and chemicals. In terms of oxidative stress, Res reduces the level of intracellular reactive oxygen species(ROS) by enhancing the expression of proteins such as silent information regulator 1(SIRT1) and regulating mitochondrial function, thereby alleviating myocardial cell damage. Regarding ferroptosis, Res inhibits the occurrence of ferroptosis by regulating the expression of proteins related to iron metabolism. Res can also improve I/R injury through mechanisms such as activating autophagy and the mitochondrial quality control network. In regard to improving endothelial function, Res protects the function of endothelial cells by regulating multiple signaling pathways, such as downregulating the PREP1-mediated pathway. Res can also regulate lipid metabolism and inhibit the progression of atherosclerosis. In terms of inflammatory responses, Res exerts anti-inflammatory effects through mechanisms such as inhibiting the nuclear factor-kappa B(NF-κB) signaling pathway. In addition, Res has an improving effect on cardiotoxicity caused by different drugs or environmental factors. However, the clinical application of Res still faces limitations such as poor pharmacokinetic properties. In the future, in-depth exploration is needed at multiple levels from basic research to clinical application to clarify the dose-response relationship and standardize the standards of medication regimens with the expectation of providing more effective strategies for the prevention and treatment of cardiovascular diseases.
Humans ; Resveratrol/pharmacology* ; Animals ; Cardiotonic Agents/pharmacology* ; Oxidative Stress/drug effects* ; Cardiovascular Diseases/genetics* ; Cardiovascular System/metabolism* ; Signal Transduction/drug effects*

As a new type of production factor that can empower the development of new quality productivity, the data element is an important engine to promote the high quality development of the industry. Traditional Chinese medicine(TCM) dispensing is the most basic work of TCM clinical pharmacy, and its quality directly affects the clinical efficacy of TCM. The integration of data elements and TCM dispensing can stimulate the innovation and vitality of the TCM dispensing industry and promote the high-quality and sustainable development of the industry. A large-scale, detailed, and systematic study on TCM dispensing was conducted. The innovative practice path of data fusion construction in the whole process of TCM dispensing was investigated by integrating the digital resources "nine full activities" of TCM dispensing, creating the digital dictionary of "TCM clinical information data elements", and exploring innovative applications of TCM dispensing driven by data and technology, so as to promote the standardized, digital, and intelligent development of TCM dispensing in medical health services. The research content of this project was successfully selected as the second batch of "Data element×" typical cases of National Data Administration in 2024, which is the only selected case in the field of TCM.
Medicine, Chinese Traditional/methods* ; Drugs, Chinese Herbal ; Humans

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Data analysis models may assist the transmission of traditional Chinese medicine （TCM） experience and clinical diagnosis and treatment， and the possibility of constructing a “data-knowledge” dual-drive model was explored by taking gastric precancerous state as an example. Data-driven is to make clinical decisions around data analysis， and its syndrome-differentiation decision-making research relies on hidden structural models and partially observable Markov decision-making processes to identify the etiology of diseases， syndrome elements， evolution of pathogenesis， and syndrome differentiation protocols； knowledge-driven is to make use of data and information to promote decision-making and action processes， and its syndrome-differentiation decision-making research relies on convolutional neural networks to improve the accuracy of local disease identification and syndrome differentiation. The “data-knowledge” dual-driven model can make up for the shortcomings of single-drive numerical simulation accuracy， and achieve a balance between local disease identification and macroscopic syndrome differentiation. On the basis of previous research， we explored the construction method of diagnostic assisted decision-making platform for gastric precancerous state， and believed that the diagnostic and decision-making ability of doctors can be extended through the assistance of machines and algorithms. Meanwhile， the related research methods were integrated and the core features of gastric precancerous state based on TCM syndrome differentiation and endoscopic pathology diagnosis and prediction were obtained， and the elements of endoscopic pathology recognition based on TCM syndrome differentiation were explored， so as to provide ideas for the in-depth research and innovative application of cutting-edge data analysis technology in the field of intelligent TCM syndrome differentiation.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

Objective To investigate the therapeutic effects and mechanisms of Maxing Shigan Decoction on cough variant asthma(CVA)rats.Methods Sixty rats were randomly divided into normal group,model group,low and high dose groups of Maxing Shigan Decoction,and high-dose of Maxing Shigan Decoction + signal transducer and activator of transcription 3(STAT3)activator Colivelin(Col)group,12 rats in each group.Except for the normal group,the CVA model was constructed by intraperitoneal injection of ovalbumin combined with moxa fumigation in all other groups of rats.After the corresponding treatment,the rats were observed for signs and cough counts,airway resistance(RE)was detected by pulmonary function meter,eosinophils(EOS)were counted by Diff-Quik staining,histopathological features of the lungs and bronchial tubes were observed by hematoxylin-eosin(HE)staining method,and the lung tissues were detected by enzyme-linked immunosorbent assay(ELISA)for monocyte chemotactic protein 1(MCP-1),and tumor necrosis factor α(TNF-α),and the protein expression levels of interleukin 6(IL-6),STAT3,and transient receptor potential vanilloid-1 channel(TRPV1)were detected by Western Blot.Results Compared with the normal group,rats in the model group showed obvious asthma symptoms,severe inflammatory cell infiltration was seen in the lung tissue,bronchial epithelial cell necrosis,ciliated adhesion,mucus,and RE,EOS number,MCP-1 and TNF-α contents,and protein expression levels of IL-6,STAT3,TRPV1 were elevated(P＜0.05);compared with the model group,rats in the low-and high-dose groups of Maxing Shigan Decoction showed significant improvement in asthma symptoms,reduction in lung and bronchial injury,and dose-dependent reduction in RE,EOS number,MCP-1 and TNF-α contents,and protein expression levels of IL-6,STAT3,and TRPV1(P＜0.05);compared with the high-dose group of Maxing Shigan Decoction,the rats in the high-dose Maxing Shigan Decoction+Col group showed increased asthma,increased lung and bronchial injury,and increased RE,EOS number,MCP-1 and TNF-α contents,and protein expression levels of IL-6,STAT3,and TRPV1(P＜0.05).Conclusion Maxing Shigan Decoction can effectively improve cough variant asthma in rats,and its mechanism is related to the inhibition of IL-6/STAT3 signaling pathway and the high expression of TRPV1.

Rare diseases still lack effective treatments, and the development of drugs for rare diseases (known as orphan drugs) is an urgent medical problem. As natural active ingredients in living organisms, some biomacromolecule drugs have good biocompatibility, low immunogenicity, and high targeting. They have become one of the most promising fields in drug research and development in the 21st century. However, there are still many obstacles in terms of in vivo delivery. In view of the unique advantages of nanocarriers prepared from polymers, lipids, organic biomimetic and inorganic materials in drug delivery, researchers are committed to building an efficient delivery system with versatility and synergy to solve the bottleneck issues in treating rare diseases with biomacromolecule drugs. Therefore, this article reviews the research progress of nanocarrier delivering proteins, peptides and nucleic acids in the field of rare disease treatment in the past ten years, which provides ideas for researches on biomacromolecule drug nanosystems in the field of treatment of rare diseases.