ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

ObjectiveTo explore the mechanism by which Sini San （SNS） inhibits ferroptosis， alleviates inflammation and myocardial injury， and improves myocardial infarction （MI）. MethodsThe active ingredients of SNS were obtained by searching the Traditional Chinese Medicine System Pharmacology Platform （TCMSP） database， its target sites were predicted using the SwissTargetPrediction Database， and the core components were screened out using the CytoNCA plug-in. The targets of MI and ferroptosis were obtained by using GeneCards， Online Mendelian Inheritance in Man （OMIM） database， DrugBank， Therapeutic Target Database （TTD）， FerrDb database and literature review， respectively. The intersection of these targets of SNS-MI-ferroptosis was plotted as a Venn diagram. The protein-protein interaction （PPI） network was constructed using the STRING database， and the visualization graph was prepared using Cytoscape. The core targets were screened out using the CytoNCA plug-in， and the biological functions were clustered by the MCODE plug-in. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed using the David database. Molecular docking was performed using AutoDock and visualized with PyMOL2.5.2. The Kunming mice were randomly divided into the control group， the model group， the SNS group， and the trimetazidine （TMZ） group. The mice were subcutaneously injected with isoprenaline （ISO， 5 mg·kg^-1·d^-1） to establish an MI model. The drug was continuously intervened for 7 days. The ST-segment changes were recorded by electrocardiogram （ECG）， and the tissue morphology changes were observed by hematoxylin-eosin （HE） staining. Cardiomyocyte ferroptosis was investigated by transmission electron microscopy. Serum creatine kinase （CK）， creatine kinase isoenzyme （CK-MB）， lactate dehydrogenase （LDH）， reduced glutathione （GSH）， and malondialdehyde （MDA） levels were detected by biochemical assay. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum levels of interleukin （IL）-6 and 4-hydroxynonenal （4-HNE）. Immunohistochemical staining was employed to detect IL-6 and phosphorylated signal transducer and transcription activator 3 （p-STAT3） in cardiac tissues. Western blot was used to detect STAT3 and p-STAT3 in cardiac tissues. Real-time PCR was used to detect the levels of IL-6， IL-18， solute carrier family 7 member 11 （SLC7A11）， arachidonic acid 15-lipoxygenase （ALOX15）， and glutathione peroxidase 4 （GPx4） in cardiac tissues. ResultsA total of 121 active ingredients of SNS were obtained， and 58 potential targets of SNS in the treatment of MI by regulating ferroptosis were screened. The three protein modules with a score5 were mainly related to the inflammatory response. The GO function was mainly related to inflammation， and KEGG enrichment analysis showed that SNS mainly regulated ferroptosis- and inflammation- related signaling pathways. Molecular docking indicated that the core component had a higher binding force to the target site. Animal experiments confirmed that SNS reduced the level of p-STAT3 （P0.01）， down-regulated the expression of ALOX15 mRNA （P0.01）， up-regulated the level of serum GSH， and the expressions of SLC7A11 and GPx4 mRNA， reduced MDA and 4-HNE levels （P0.05， P0.01）. Additionally， SNS improved the mitochondrial injury induced by cardiomyocyte ferroptosis， reduced the area of MI， alleviated inflammation and myocardial injury， lowered the levels of serum CK， CK-MB， LDH， IL-6， and the mRNA expression levels of IL-16 and IL-18 （P0.05）， and improved ST segment elevation. ConclusionSNS can reduce ISO-induced STAT3 phosphorylation levels， inhibit ferroptosis in cardiomyocytes， alleviate inflammation and myocardial injury， thereby improving MI.

Background Liver cancer is one of the common malignant tumors. Phthalates (PAEs), as a widely used class of plasticizers, can participate in the occurrence and progression of liver diseases through multiple pathways. Objective To explore the association between PAEs exposure and liver cancer risk and to provide a scientific basis for the prevention of environment-related tumor risk events. Methods Chi-square test and logistic regression were employed to analyze data from the National Health and Nutrition Examination Survey (NHANES) database between 2001 and 2018, to investigate the association between PAEs exposure and liver cancer. Network toxicology combined with machine learning was used to screen independent prognostic genes associated with PAEs and liver cancer, and to evaluate their correlations with tumor immunity, tumor pathway activation, and tumor drug resistance. Finally, the prediction results were validated using GEO datasets, molecular docking, and molecular dynamics simulations. Results After screening, 11378 eligible samples were obtained from the NHANES database, including 108 patients with liver cancer and 11270 healthy controls. The logistic regression analysis revealed that exposure to nine types of PAEs was positively correlated with liver cancer (OR > 1, P < 0.05). The network toxicology analysis indicated that the association between PAEs exposure and liver cancer was related to three independent prognostic genes: uridine-cytidine kinase 2 (UCK2), glucose-6-phosphate dehydrogenase (G6PD), and albumin (ALB). These three independent prognostic genes were significantly associated with the tumor immune microenvironment, tumor pathway activation, and tumor drug resistance, and exhibited complex interactions with each other. All three independent prognostic genes showed significant differential expression in the validation datasets GSE58043 and GSE115469 (P < 0.05). The results of both molecular docking and molecular dynamics simulations confirmed that these three independent prognostic genes can freely bind to PAEs and form stable complexes. Conclusion Exposure to PAEs is positively correlated with liver cancer. The intrinsic association between the two may involve metabolic disorders, immunosuppression, and activation of inflammatory and tumor-related pathways.

Cognitive dysfunction refers to dysfunction of individual perception,memory,understanding,learning,creation and other dysfunctions caused by abnormal brain function and structure.Based on the fact that the spleen can't regulate transportation and transformation,govern blood and send up essential substance,combined with the microbiota-gut-brain axis,this article discussed the etiology and pathogenesis of intestinal flora imbalance affecting cognitive dysfunction in TCM.It was proposed that the spleen in TCM and intestinal flora are connected in physiology and pathology:the spleen regulates spirit and governs cognition,when the spleen fails to function normally that it can't dominate transportation and transformation,govern blood and send up essential substance will cause that the brain spirit can not be nourished;intestinal flora is closely related to the spleen in TCM,and affects brain function through the nervous system,endocrine,immune and metabolic mechanisms.This article can provide explore new ideas for the clinical research and treatment of cognitive dysfunction of traditional Chinese and Western medicine.

The incidence of orthopedic trauma-related diseases keeps rising annually, which brings an urgent need to optimize the diagnostic and treatment processes to enhance treatment efficiency and improve patients′ prognosis. Traditional diagnostic methods in traumatic orthopedics primarily rely on manual film interpretation and classification, resulting in a substantial workload for physicians and consequently a low efficiency. Furthermore, during multidisciplinary consultations and cross-hospital referrals for patients with orthopedic trauma, accessing medical records and facilitating information exchange can be challenging, leading to delays in surgical intervention. The rapid advancement of artificial intelligence (AI) technology, characterized by feature engineering, artificial neural networks, and deep learning, has transformed the landscape of rapid diagnosis and precision treatment for orthopedic trauma. Nonetheless, centralized storage during task training poses risks of privacy disclosure and security concerns that impede the widespread application of AI models. In contrast, the decentralized nature of blockchain technology offers a secure operational environment for AI-driven diagnostics and treatments and the integration of blockchain and AI can deliver more accurate, efficient, and safe services for patients with orthopedic trauma. Currently, challenges remain in the inter-institutional sharing of data, constant phenomenon of data silos and absence of standardized protocols for developing collaborative models in clinical settings. To address these challenges, the authors reviewed the research advancements in integrated application of blockchain technology and artificial intelligence in diagnosing and treating orthopedic trauma, aiming to provide insights into the development of a digital diagnostic system tailored to this field in China.

The incidence of orthopedic trauma-related diseases keeps rising annually, which brings an urgent need to optimize the diagnostic and treatment processes to enhance treatment efficiency and improve patients′ prognosis. Traditional diagnostic methods in traumatic orthopedics primarily rely on manual film interpretation and classification, resulting in a substantial workload for physicians and consequently a low efficiency. Furthermore, during multidisciplinary consultations and cross-hospital referrals for patients with orthopedic trauma, accessing medical records and facilitating information exchange can be challenging, leading to delays in surgical intervention. The rapid advancement of artificial intelligence (AI) technology, characterized by feature engineering, artificial neural networks, and deep learning, has transformed the landscape of rapid diagnosis and precision treatment for orthopedic trauma. Nonetheless, centralized storage during task training poses risks of privacy disclosure and security concerns that impede the widespread application of AI models. In contrast, the decentralized nature of blockchain technology offers a secure operational environment for AI-driven diagnostics and treatments and the integration of blockchain and AI can deliver more accurate, efficient, and safe services for patients with orthopedic trauma. Currently, challenges remain in the inter-institutional sharing of data, constant phenomenon of data silos and absence of standardized protocols for developing collaborative models in clinical settings. To address these challenges, the authors reviewed the research advancements in integrated application of blockchain technology and artificial intelligence in diagnosing and treating orthopedic trauma, aiming to provide insights into the development of a digital diagnostic system tailored to this field in China.

Acute lung injury (ALI), as a common clinical emergency, is pulmonary edema and diffuse lung infiltration caused by inflammation. The lack of non-invasive alert strategy, resulting in failure to carry out preventive treatment, means high mortality and poor prognosis. Stimulator of interferon genes (STING) is a key molecular biomarker of innate immunity in response to inflammation, but there is still a lack of STING-targeted strategy. In this study, a novel STING-targeted PET tracer, [¹⁸F]FBTA, was labeled with high radiochemical yield (79.7 ± 4.3%) and molar activity (32.5 ± 2.9 GBq/μmol). We confirmed that [¹⁸F]FBTA has a strong STING binding affinity (K_d = 26.86 ± 6.79 nmol/L) and can be used for PET imaging in ALI mice to alert early lung inflammation and to assess the efficacy of drug therapy. Our STING-targeted strategy also reveals that [¹⁸F]FBTA can trace ALI before reaching the computed tomography (CT) diagnostic criteria, and demonstrates its better specificity and distribution than [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG).

In recent years, artificial intelligence-related technologies have been deeply combined with many medical fields, and the intersection of medicine and engineering has become a hot topic. There are problems with heavy data and difficulty making decisions in orthopedic disease diagnosis and treatment. Machine learning is an important method of artificial intelligence. Since it can automatically analyze and predict medical big data, it is widely used in the field of orthopedics. It also assists physicians in completing disease diagnosis and treatment efficiently. In this review paper, the application and progress of machine learning in preoperative, intraoperative, and postoperative diagnosis and treatment in orthopedics are reviewed, providing new ways for exploring more rational diagnosis and treatment strategies.

Objective:To analyse the influence of endometrial polyps (EPs) treatment on the frozen-thawed embryo transfer (FET) pregnancy outcome.Methods:Using a retrospective case-control study, the data of patients were collected who received in vitro fertilization (IVF) and hysteroscopy in the Reproductive Medicine Center of Children's Hospital of Shanxi and Women Health Center of Shanxi from June 2021 to December 2022. Patients undergoing hysteroscopy were studied. According to the diagnosis results of hysteroscopy and pathology, they were selected as the EPs group or the non-endometrial polyps (NEPs) group. Then analysis of EPs risk factors was made, and the pregnancy outcome of FET after the EPs treatment was compared. Results:A total of 3 413 patients underwent hysteroscopy in this study. The EPs group included 444 patients and the NEPs group included 1 501 patients respectively. The prevalence of EPs was 13.01% (444/3 413). There were significant differences between EPs group and NEPs group in gravidity, parity, spontaneous abortion times, induced abortions times, basal follicle-stimulating hormone (bFSH), basal luteinizing hormone (bLH), infertility duration, infertility types, the prevalence of chronic endometritis, the history of polyps removal and endometriosis (all P<0.05). Multivariate logistic regression analysis of risk factors associated with EPs showed that infertility duration ( OR=1.068, 95% CI: 1.029-1.109, P<0.001), chronic endometritis ( OR=1.925, 95% CI: 1.481-2.502, P<0.001), primary infertility ( OR=1.803, 95% CI: 1.408-2.308, P<0.001), history of polyps removal ( OR=9.424, 95% CI: 5.586-15.897, P<0.001), endometriosis ( OR=2.432, 95% CI: 1.344-4.401, P=0.003) were independent risk factors for EPs, and bLH ( OR=0.954, 95% CI: 0.916-0.993, P=0.022) was an independent protective factor for EPs. Compared with NEPs transplantation group, there were no significant differences in clinical pregnancy rate, on-going pregnancy rate and none implantation rate in the EPs treatment transplantation group (all P>0.05). Conclusion:Infertility duration, chronic endometritis, primary infertility, history of polyps removal, endometriosis were independent risk factors, and bLH was an independent protective factor. Patients in EPs treatment transplantation group could achieve the similar pregnancy outcome as NEPs transplantation group.

Objective:To analyse the influence of endometrial polyps (EPs) treatment on the frozen-thawed embryo transfer (FET) pregnancy outcome.Methods:Using a retrospective case-control study, the data of patients were collected who received in vitro fertilization (IVF) and hysteroscopy in the Reproductive Medicine Center of Children's Hospital of Shanxi and Women Health Center of Shanxi from June 2021 to December 2022. Patients undergoing hysteroscopy were studied. According to the diagnosis results of hysteroscopy and pathology, they were selected as the EPs group or the non-endometrial polyps (NEPs) group. Then analysis of EPs risk factors was made, and the pregnancy outcome of FET after the EPs treatment was compared. Results:A total of 3 413 patients underwent hysteroscopy in this study. The EPs group included 444 patients and the NEPs group included 1 501 patients respectively. The prevalence of EPs was 13.01% (444/3 413). There were significant differences between EPs group and NEPs group in gravidity, parity, spontaneous abortion times, induced abortions times, basal follicle-stimulating hormone (bFSH), basal luteinizing hormone (bLH), infertility duration, infertility types, the prevalence of chronic endometritis, the history of polyps removal and endometriosis (all P<0.05). Multivariate logistic regression analysis of risk factors associated with EPs showed that infertility duration ( OR=1.068, 95% CI: 1.029-1.109, P<0.001), chronic endometritis ( OR=1.925, 95% CI: 1.481-2.502, P<0.001), primary infertility ( OR=1.803, 95% CI: 1.408-2.308, P<0.001), history of polyps removal ( OR=9.424, 95% CI: 5.586-15.897, P<0.001), endometriosis ( OR=2.432, 95% CI: 1.344-4.401, P=0.003) were independent risk factors for EPs, and bLH ( OR=0.954, 95% CI: 0.916-0.993, P=0.022) was an independent protective factor for EPs. Compared with NEPs transplantation group, there were no significant differences in clinical pregnancy rate, on-going pregnancy rate and none implantation rate in the EPs treatment transplantation group (all P>0.05). Conclusion:Infertility duration, chronic endometritis, primary infertility, history of polyps removal, endometriosis were independent risk factors, and bLH was an independent protective factor. Patients in EPs treatment transplantation group could achieve the similar pregnancy outcome as NEPs transplantation group.