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.

ObjectiveTo systematically investigate the discrepancies between employment preferences and actual job placements among postgraduate students in rehabilitation medicine, explore the influencing factors, and elucidate the underlying mechanisms of their employment decisions. MethodsA cross-sectional questionnaire survey was conducted among 100 full-time postgraduate students who had graduated from Capital Medical University School of Rehabilitation in the past six years. A self-designed questionnaire was used to collect information on personal background, self-assessed competencies, employment preferences, and actual job placements. Logistic regression models were employed to analyze the factors influencing employment preferences and actual job placements, respectively. ResultsEmployment preferences among rehabilitation medicine postgraduates were highly concentrated on large tertiary hospitals (79.0%), yet the actual placement rate (61.0%) showed a significant gap. Preference for tertiary hospitals showed no significant association with individual factors such as gender, degree type or self-assessed competencies (P > 0.05). Univariate analysis revealed that those who entered tertiary hospitals scored significantly higher in self-assessed clinical skills, research ability, communication and coordination, and resource integration (|t| > 3.661, P < 0.001), and demonstrated clearer career planning (P = 0.012). Multivariate logistic regression analysis did not identify any independent predictors of actual employment within the context of this study sample (P > 0.05). ConclusionEmployment among rehabilitation medicine postgraduates is characterized by highly homogeneous preferences coexisting with complexity of factors influencing actual employment. It is recommended to optimize the training system, deepen personalized career education, and establish diversified employment guidance mechanisms to promote rational talent flow and facilitate the balanced development of the rehabilitation medical service system.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To analyze the influencing factors of plastic bronchitis in children with Mycoplasma pneumoniae infection and put forward targeted prevention suggestions. Methods The clinical data of children with Mycoplasma pneumoniae infection who were admitted to Chengdu Third People's Hospital from September 2022 to February 2024 were retrospectively analyzed . According to whether plastic bronchitis occurred, they were divided into plastic group (n=118) and non-plastic group (n=184), and the differences between the two groups were compared and analyzed. Univariate and multivariate logistics regression analysis equations were used to analyze the independent influencing factors of plastic bronchitis in children with mycoplasma pneumoniae infection. Results Among the 302 children with Mycoplasma pneumoniae infection , 118 cases were diagnosed with plastic bronchitis. Analysis showed that the children’s age, duration of fever, hospital stay, pleural effusion rate, number of bronchoscopic lavage, allergy history, endoscopic mucosal erosion rate, WBC, NE%, LY%, CRP, LDH, PCT and D-D were the single factors influencing the occurrence of plastic bronchitis in children with mycoplasma pneumoniae infection. Binary logistics regression analysis revealed that age (OR=2.137, P=0.033, 95% CI: 1.132-16.603), allergy history （OR=3.028, P=0.014, 95% CI: 1.261-864), NE% (OR=2.395, P=0.031, 95% CI: 1.087-5.274), CRP (OR=3.864, P=0.004, 95% CI: 1.563-3.864), PCT (OR=4.125, P=0.001, 95% CI: 1.793-3.864), and D-D (OR=3.920, P=0.002, 95% CI: 1.632-3.864) were independent risk factors for plastic bronchitis in children with mycoplasma pneumoniae infection (P<0.05). Conclusion Age, allergy history, NE%, CRP, PCT and D-D are independent risk factors for plastic bronchitis in children with mycoplasma pneumoniae infection . It is necessary to take clinical intervention measures to reduce the occurrence risk.

Objective: To analyze the epidemilogical and seasonal characteristics of foodborne Salmonella-associated diarrhea among children aged 0-6 years in Guizhou Province from 2016 to 2023, so as to provide a basis for the prevention and control of foodborne diseases. Methods: Data were extracted from the Foodborne Disease Survellance System for cases reported between January 1, 2016, and December 31, 2023. The incidence, seasonal characteristics, and peak periods were analyzed by the method of concentration and circular distribution. Results: A total of 6 434 cases of diarrhea in children aged 0-6 years were collected, and 455 cases of Salmonella were detected, with a positive detection rate of 7.07%. Salmonella typhimurium was the main serotype causing diarrhea (59.34%). The peak of the disease was from May 3 to September 30, with certain seasonal characteristics. The highest detection rate was found in children aged 1-3 years (8.66%). Among food types, the positive detection rates of Salmonella were relatively high in other foods (17.39%), fruits and their products (10.22%), infant and toddler foods (10.09%), and aquatic animals and their products (9.80%). The processing and packaging methods of food were mainly home-made (9.38%) and bulk food (7.54%). Conclusions The detection rate of Salmonella in children aged 0-6 years is high in Guizhou Province, with strong seasonal characteristics. The detection rates of other foods, fruits and their products, infant and toddler foods, and aquatic animals and their products are high. Enhanced pathogen surveillance for susceptible populations and high-risk foods, coupled with public health education during summer/autumn, is recommended.

Background The positive rate of work-related musculoskeletal disorders (WMSDs) among coal mine workers remains high, which seriously affects the quality of life of the workers. Objective To estimate the prevalence of WMSDs among coal miners in Shanxi Province and analyze their influencing factors. Methods From May to December 2023, 2315 coal miners from a coal mine enterprise inShanxi Province were selected by convenience sampling, and the self-administered Basic Situation Survey Scale, Musculoskeletal Disorders Questionnaire, Effort-Reward Imbalance Questionnaire, and Pittsburgh Sleep Quality Scale were used to evaluate general demographic characteristics, work organization characteristics, living habits, sleep quality, occupational stress, and occurrence of WMSDs symptoms and the corresponding absences (sickness absence) in past 1 year. The positive rate and absenteeism rate of WMSDs were caculated, and Pearson's chi-square test was used for identify influencing factors of WMSDs, and finally a binary logistic regression method was used to further studying the factors. Results A total of 2577 questionnaires were distributed in this survey, and 2315 valid questionnaires were recovered, with an effective recovery rate of 89.9%. The positive rate of WMSDs symptoms was 48.7% (1127/2315), the absenteeism rate due to WMSDs was 22.6% (523/2315), and the waist (17.5%), neck (11.7%), and knee (9.0%) were the most common areas presenting WMSDs symptoms. The results of logistic regression showed that compared with ≤10 years of service, the risk of WMSDs was higher for those with > 20 years of service (OR=2.167, 95%CI: 1.419, 3.311). Compared with the daily working time of ≤8 h, the risk of WMSDs was higher for those >8 h daily working time (OR=1.463, 95%CI: 1.211, 1.767). A higher risk of WMSDs was reported in workers with moderate labor intensity (OR=1.247, 95%CI: 1.009, 1.542) or heavy labor intensity (OR=1.570, 95%CI: 1.215, 2.027) than those with light labor intensity. The higher the education level (OR _{high school and technical secondary school}=1.866, 95%CI: 1.435, 2.425; OR _{junior college/bachelor degree or above}=1.953, 95%CI: 1.445, 2.639), the higher the risk of WMSDs. The risk of WMSDs was higher in workers reporting smoking (OR=1.225, 95%CI: 1.021, 1.470) or alcohol consumption (OR=1.345, 95%CI: 1.122, 1.612). The risk of WMSDs in coal miners with high occupational stress (OR=1.229, 95%CI:1.030, 1.466) or those with sleep disorders (OR=3.616, 95%CI:2.824, 4.629) was higher than that in workers with low occupational stress or no sleep disorders respectively. Conclusion The positive rate of WMSDs among coal mine personnel in Shanxi Province is high, and education level, length of service, daily working hours, smoking, alcohol consumption, labor intensity, sleep disorders, and occupational stress are influencing factors for WMSDs.

OBJECTIVES: To explore the therapeutic mechanism of Arctium lappa extract for treatment of Post-Viral Pneumonia Pulmonary Fibrosis (PPF). METHODS: The chemical constituents of Arctium lappa extracts were identified using UHPLC-Q-TOF-MS/MS. Mouse models of pulmonary fibrosis established by tracheal instillation of bleomycin were treated with Arctium lappa extract, and body weight changes were recorded and lung tissue pathology was examined using HE and Masson staining. Metabolomics analysis was used to identify the differential metabolites and the associated metabolic pathways in the treated mice. The common targets of viral pneumonia and pulmonary fibrosis were acquired from the publicly available databases, and the core targets and active constituents were screened using the protein-protein interaction (PPI) network, GO and KEGG enrichment analyses, and molecular docking, and a "gene-metabolite" regulatory network was constructed. The expressions of the core targets were detected in the lung tissues of the treated mice using Western blotting. RESULTS: Fifty-three chemical constituents were identified from Arctium lappa extract. In the mouse models of pulmonary fibrosis, treatment with Arctium lappa extract significantly improved weight loss and ameliorated lung inflammation and fibrosis. The differential metabolites in the treated mice were enriched in energy metabolism pathways involving citrate cycle, pentose phosphate pathway, glycolysis, tryptophan metabolism, glutamate metabolism and glutathione metabolism, which regulated the production of energy metabolism intermediates. Twenty-three key active compounds (mostly lignans and phenolic acids) and 82 core targets were screened, which were associated with the non-canonical Smad signaling pathways (including PI3K/AKT, HIF-1, MAPK, and Foxo) that participated in the regulation of energy metabolism. Arctium lappa extract also regulated the expressions of epithelial-mesenchymal transition (EMT)‑related proteins (fibronectin, vimentim, and Snail, etc.) and inhibited MAPK signaling pathway activation. CONCLUSIONS Preliminary findings suggest that Arctium lappa treats fibrosis by regulating metabolism to inhibit EMT and involves the modulation of non-canonical Smad signaling pathways, such as MAPK providing theoretical support for its clinical application and further research in treating PPF.
Arctium/chemistry* ; Animals ; Pulmonary Fibrosis/metabolism* ; Mice ; Metabolomics ; Network Pharmacology ; Plant Extracts/pharmacology* ; Signal Transduction ; Drugs, Chinese Herbal/pharmacology* ; Molecular Docking Simulation

OBJECTIVE: To explore the effects of different endotracheal tube cuff pressure management modes on cuff sealing and the pressure exerted on the tracheal wall. METHODS: A prospective self-controlled study was conducted. Eleven patients undergoing endotracheal intubation and mechanical ventilation with an automatic airway management system (AGs) admitted to the Second Medical Centre of the Chinese People's Liberation Army General Hospital from October 1, 2020, to April 1, 2022, were enrolled as the study subjects. Within 24 hours after the establishment of artificial airway and mechanical ventilation, four cuff pressure management modes were randomly applied to each patient for 24 hours in sequence: automatic cuff pressure management mode [modeI: the safe range of cuff pressure was set at 20-35 cmH₂O (1 cmH₂O≈0.098 kPa), and the CO₂ pressure above the endotracheal tube cuff was automatically detected by AGs every 5 minutes to determine the cuff sealing status, and the cuff pressure was automatically adjusted], constant cuff pressure (25 cmH₂O) management mode (mode II: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 25 cmH₂O via a pressure pump), constant cuff pressure (30 cmH₂O) management mode (mode III: the cuff pressure was monitored by AGs through a pressure sensor, and the cuff pressure was maintained at 30 cmH₂O via a pressure pump), and manual cuff pressure management mode (mode IV: the cuff pressure was manually measured by nurses every 6-8 hours using a cuff pressure gauge to keep the cuff pressure at 25-30 cmH₂O after inflation). The CO₂ pressure above the endotracheal tube cuff (at 60-minute intervals) and the cuff pressure changes (at 50-ms intervals) were recorded to compare the differences in number of cuff leaks [no leak was defined as CO₂ pressure = 0, small leak as 0 < CO₂ pressure < 2 mmHg (1 mmHg≈0.133 kPa), and large leak as CO₂ pressure ≥ 2 mmHg] and cuff pressure among modesI-IV. RESULTS: A total of 24 CO₂ pressure measurements were taken per patient across the four modes, resulting in a total of 264 detections for each mode. Regarding the cuff leak, the total number of leak and large leak in modeIwas significantly lower than that in modes II-IV [total leak: 30 cases (11.36%) vs. 81 cases (30.68%), 70 cases (26.52%), 103 cases (39.02%); large leak: 15 cases (5.68%) vs. 50 cases (18.94%), 48 cases (18.18%), 66 cases (25.00%), all P < 0.05]. There was no significant difference in the number of cuff leak between modes II and III, and mode IV had the most severe cuff leak. In terms of cuff pressure, since mode IV required blocking the cuff tube from the AGs tube and the AGs cuff pressure management module did not actually work, real-time monitoring of cuff pressure was not possible. Therefore, cuff pressure changes were only analyzed in modes I-III. Each of the 11 patients underwent 24-hour cuff pressure monitoring under modes I-III, with 19 008 000 monitoring times for each mode. The cuff pressure in mode I was between that in modes II and III [cmH₂O: 27.09 (26.10, 28.14) vs. 26.60 (25.92, 27.47), 31.01 (30.33, 31.88), both P < 0.01]. Moreover, the number of extreme values of cuff pressure > 50 cmH₂O in mode I was significantly lower than that in modes II and III [19 900 cases (0.105%) vs. 22 297 cases (0.117%), 27 618 cases (0.145%), both P < 0.05]. CONCLUSION Dynamically monitoring the CO₂ pressure above the cuff to guide the adjustment of endotracheal tube cuff pressure can achieve better cuff sealing with a relatively lower cuff pressure load.
Humans ; Intubation, Intratracheal/instrumentation* ; Pressure ; Prospective Studies ; Respiration, Artificial ; Male ; Airway Management/methods* ; Female ; Middle Aged

Liver diseases have become a major challenge threating the global health, posing a heavy burden on both social and personal well-being. In recent years, the development of the gut-liver axis theory has provided new research perspectives and intervention strategies for the prevention and treatment of liver diseases. Natural products, recognized as biological molecules with diverse sources, rich activities, and minimal side effects, demonstrate great potential in regulating intestinal flora and improving liver health. Studies have shown that natural products such as saponins, polyphenols, polysaccharides, and alkaloids can regulate the composition and metabolites of intestinal flora, thereby intervening in liver diseases. In this paper, we systematically review the role of natural products in the regulation of the intestinal flora-gut-liver axis and summarize recent research progress in the prevention and treatment of liver diseases. Furthermore, we outline the challenges and limitations currently facing the study in this field. Finally, this paper makes an outlook on the clinical application of natural products in treating liver diseases and discusses future research directions, aiming to give new insights into the mechanisms by which natural products regulate the intestinal flora-gut-liver axis and the applications of these products in the prevention and treatment of liver diseases.
Humans ; Gastrointestinal Microbiome/drug effects* ; Liver Diseases/prevention & control* ; Biological Products/pharmacology* ; Polyphenols/pharmacology* ; Saponins/pharmacology* ; Intestines/microbiology* ; Alkaloids/pharmacology* ; Polysaccharides/pharmacology* ; Liver