ObjectiveTo delineate imaging findings using an imaging platform and investigate the correlation between MRI characteristics of spinal cord atrophy and clinical diagnosis in children with spinal cord injury (SCI). MethodsImaging data of 150 children with SCI admitted to Beijing Bo'ai Hospital, China Rehabilitation Research Center, from January, 2002 to March, 2024 were collected and imported into the imaging platform. The anteroposterior and transverse diameters of the middle part of the spinal cord at the cross-section with the most severe atrophy were measured, and the relevant indicators of the previous normal spinal cord segment were measured as controls; the radiomic features were extracted. Clinical data of the children including gender, age, cause of injury, sensory level, motor level, spinal cord injury level, injury severity and disease course were collected. ResultsSpinal cord atrophy was identified in 81 cases (54%), among which 78 cases (96%) were American Spinal Injury Association Impairment Scale (AIS) grade A and 3 cases (4%) were AIS grade C. The upper boundary of the spinal cord atrophy site strongly correlated with the injury level, motor level and sensory level (r > 0.8, P < 0.001). ConclusionMore than half of children with SCI may develop secondary spinal cord atrophy, the vast majority of whom suffer from complete spinal cord injury; the upper boundary of spinal cord atrophy is correlated with the injury level.

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.

Objective To analyze the case data of farmers' foodborne disease surveillance reports in Guizhou Province from 2022 to 2024, and to provide reference for the precise prevention and control of foodborne diseases among farmers in Guizhou Province. Methods Case data of foodborne disease surveillance reports of farmers were systematically collected from 2022 to 2024 in Guizhou Province. Descriptive epidemiological methods were used to analyze the temporal, geographical, and demographic distribution of foodborne diseases among farmers, along with their primary clinical symptoms and pathogen detection results. Results From 2022 to 2024, a total of 22,882 cases of foodborne diseases were reported among farmers in Guizhou Province. The majority of clinical symptoms (97.81%) were related to the digestive system, with summer being the peak season. While females outnumbered males, the gender difference was statistically insignificant (P >0.05). The 36-55 age group accounted for the highest proportion (38.83%), with Zunyi City (34.89%) and Qiandongnan Prefecture (23.21%) reporting the most cases. Fungal products were the most frequently reported suspected food items (26.96%), and home-made preparation was the primary processing method (58.63%). A total of 1 210 fecal samples were collected through active monitoring with an overall detection rate of 13.22%. Norovirus showed the highest detection rate (9.92%, 120/1 210). Statistically significant differences were observed among different seasons, age groups, regions, types and processing methods of suspected food exposure, and pathogen detection rates (P <0.001). Conclusion Foodborne disease prevention and control among farmers in Guizhou Province should focus on the risks of wild mushroom poisoning in summer and homemade foods, and continuously improve farmers' awareness of the dangers of foodborne diseases and food safety.

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.

Pathologic myopia(PM)is characterized by progressive axial elongation, posterior staphyloma, and fundus degenerative changes, representing a leading cause of blindness in Asian countries.Posterior scleral reinforcement(PSR)is currently the only surgical intervention to slow axial elongation. Its mechanisms involve mechanical reinforcement, improved blood circulation, and biological stimulation of scleral remodeling. This article reviews recent advances in PSR: surgical techniques have evolved from complex, classic procedures to standardized single-strip methods, incorporating 3D MRI to quantify posterior staphyloma morphology for personalized graft design and facilitating minimally invasive, precision surgery. Among implant materials, biomaterials such as allogeneic dura mater are being continuously optimized, while biomimetic piezoelectric smart materials actively promote scleral collagen synthesis through electrical signals, achieving a paradigm shift from “passive support”to “active reinforcement”. Clinical outcomes indicate advantages in regulating axial length, enhancing visual function and blood circulation, and facilitating early intervention in children. Combined procedures with ICL implantation, cataract surgery or vitrectomy provide comprehensive treatment regimens for individual patients with varied conditions. This article also analyzes long-term issues and core controversies including ectopic posterior staphyloma and reoperation, and prospects future research directions such as artificial intelligence assistance, translation of smart materials and full-cycle prevention and treatment systems, so as to provide references for clinical practice and scientific research.

ObjectiveTo investigate the mechanism of Huangqi Gegentang （HGT） in the treatment of type 2 diabetes mellitus （T2DM） through the application of proteomic techniques. MethodsThe rat model of T2DM was established by streptozotocin combined with a high-fat， high-sugar diet. Thirty-two male SD rats were randomized into four groups： blank， model， HGT （8.10 g·kg^-1·d^-1）， and positive control （metformin hydrochloride， 76.5 mg·kg^-1·d^-1）. After 6 weeks of drug intervention， the fasting blood glucose level was measured， and an oral glucose tolerance test （OGTT） was performed. The area under the curve （AUC） was calculated. Enzyme-linked immunosorbent assay was performed to assess the level of glycated hemoglobin （GHbA1c） in the serum. The limulus amebocyte lysate assay was employed to measure the serum level of lipopolysaccharide （LPS）. Pathological changes in the colon were observed by hematoxylin-eosin staining. The mRNA levels of pro-inflammatory cytokines including tumor necrosis factor （TNF）-α， interleukin （IL）-6， and IL-1β in the colon tissue were quantified via Real-time fluorescence quantitative polymerase chain reaction （Real-time PCR）. Additionally， the protein and mRNA levels of zonula occludens-1 （ZO-1）， Occludin， and Claudin-1 in the colon tissue were assessed by Western blot and Real-time PCR， respectively. Label-free quantitative proteomics was employed to identify the differentially expressed proteins between the colon tissue samples from the blank， model， and HGT groups. Key proteins identified were subsequently validated by Western blot and Real-time PCR. Finally， bioinformatics analysis was conducted on the differentially expressed proteins. ResultsCompared with the blank group， the model group exhibited increased fasting blood glucose， AUC， and GHbA1c levels （P<0.01）， damaged colonic mucosal epithelial structure and inflammatory cell infiltration， up-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon and an increase in serum LPS content （P<0.05， P<0.01）， and down-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.01）. Compared with the model group， the HGT group showed reductions in fasting blood glucose， AUC， and GHbA1c （P<0.01）， alleviated damage to the colonic mucosal epithelium， down-regulated mRNA levels of TNF-α， IL-6， and IL-1β in the colon， a reduction in serum LPS content （P<0.05， P<0.01）， and up-regulated protein and mRNA levels of ZO-1， Occludin， and Claudin-1 in the colon （P<0.05， P<0.01）. Proteomics analysis identified 70 differentially expressed proteins that exhibited a downward trend in the model group relative to the blank group and an upward trend in the HGT group relative to the model group. These findings were corroborated by Western blot and Real-time PCR， which confirmed that the protein and mRNA levels of mucin 2 （Muc2） and transforming growth factor （TGF）-beta receptor 1 （Tgfbr1） in the colon tissue were consistent with the proteomic data. Bioinformatics analysis showed that these 70 differentially expressed proteins identified were significantly enriched in multiple signaling pathways， among which the TGF-β and advanced glycation endproduct （AGE）/receptor for advanced glycation endproduct （RAGE） signaling pathways were closely associated with damage to the intestinal mucosal barrier. This suggests that HGT may ameliorate intestinal mucosal barrier damage by regulating these pathways. ConclusionHGT potentially exerts anti-T2DM effects by influencing AGE/RAGE and TGF-β signaling pathways， thereby contributing to the restoration of the intestinal mucosal barrier.

Objective To develop an ultra-high performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS） method to simultaneously determine 10 main components, including berberine, phellodendrine, specnuezhenide, mangiferin, loganin, paeoniflorin, geniposide, baicalin, and acteoside in Compound Dihuang oral solution. Methods An UPLC-MS/MS method was established with an ACQUITY UPLC BEH-C18 （2.1 mm×100 mm, 1.7 μm）column and mobile phase of 0.1% formic water（A）-methanol solution（B） in a gradient elution manner. The flow rate of mobile phase was 0.2 ml/min.The temperature of column was 30℃. The injection volume was 2 μl. The MS detection was in MRM mode. Results 10 components in Compound Dihuang oral solution had a good linear relationship within their concentration range,and the precision, repeatability, stability and recovery met the requirements. The contents of berberine, phellodendrine, specnuezhenide, mangiferin, loganin, paeoniflorin, geniposide, baicalin, and acteoside in 7 batches of samples were （89.7-95.6） μg/ml, （164.0-177.7） μg/ml, （540.0-610.0） μg/ml, （408.7-429.0） μg/ml, （726.0-825.0） μg/ml, （503.7-572.0） μg/ml, （1380.0-1540.0） μg/ml, （2596.7-2896.7) μg/ml, （4866.7-5520.0) μg/ml, （61.8-67.2) μg/ml, respectively. Conclusion The established method was easy to be repeated and operated. The contents of 10 components in Compound Dihuang oral solution could be determined quickly and accurately, which provided a reference for the quality control of hospital preparation.

ObjectiveTo explore the current situation and influencing factors of humanistic care experience among patients visiting traditional Chinese medicine （TCM） outpatient clinics in China， and to provide a basis for optimizing TCM-characterized services in both TCM and Western medicine hospitals. MethodsA multi-center cross-sectional study was conducted using convenience sampling to select 35 hospitals across 13 provinces in China （including 3 TCM hospitals and 32 TCM outpatient clinics in general hospitals）. A total of 3，430 patients were surveyed using the general information questionnaire and the Outpatient Humanistic Care Experience Questionnaire， with data collected via Questionnaire Star. Univariate analysis and multiple linear regression were employed to examine the impacts of patient characteristics， visit characteristics， hospital type （TCM hospital/general hospital）， and geographic region （eastern/central/western） on humanistic care experience. ResultsThe total score of humanistic care experience was 194 （188， 233）. Univariate analysis showed that gender， educational level， current residence， per capita monthly household income， location attribute of medical institutions， number of previous visits to this hospital， payment method of medical expenses， previous hospitalization history in this hospital， frequency of outpatient visits within the past 12 months， self-rated disease severity， familiarity with the outpatient procedures， implementation of the follow-up service provided by the hospital， satisfaction with follow-up services， the grade of the hospital visited， geographical region of the hospital visited， and the department visited had an impact on the humanistic care experience during outpatient visits （P<0.05）. Multivariate analysis demonstrated that educational level （β=0.609， P=0.011）， self-rated disease severity （β=-0.646， P=0.047）， familiarity with outpatient procedures （β=4.784， P<0.001）， satisfaction with follow-up services （β=6.365， P<0.001）， and the grade of the hospital visited （β=-5.487， P<0.001） affected the humanistic care experience in outpatient medical treatment， explaining 24.4% of the total variation. ConclusionHumanistic care experience in TCM outpatient clinics is influenced by multiple factors. It is recommended to optimize the medical treatment process， strengthen doctor-patient communication training， and establish a precise follow-up mechanism， with a focus on improving care perceptions among patients with lower education levels and those attending primary-level hospitals， to refine the TCM-characterized service system.

Objective To explore the influencing factors of cognitive impairment in non-dialysis patients with chronic kidney disease(CKD).Methods A total of 60 hospitalized non-dialysis patients with CKD in the Department of Nephrology of Northern Jiangsu People's Hospital Affiliated to Yangzhou University from September 2022 to September 2023 were enrolled as research objects.According to the estimated glomerular filtration rate(eGFR),they were divided into stage 1 to 2 of CKD group[eGFR ≥60 mL/(min·1.73 m2)]with 23 cases,the stage 3 of CKD group[eGFR 30～＜60 mL/(min·1.73 m2)]with 20 cases,and stage 4 to 5 of CKD group[eGFR＜30 mL/(min·1.73 m2)]with 17 cases.The Montreal Cognitive Assessment Scale(MoCA)was used to evaluate the cognitive function of the patients.Basic data and common clinical laboratory in-dicators on hospital admission were collected to analyze the differences in cognitive function levels under different renal function statuses and to explore the influencing factors of cognitive impairment.Results The incidence rates of cognitive impairment in the stage 1 to 2 of CKD group,stage 3 of CKD group,and stage 4 to 5 of CKD group were 47.8％,85.0％,and 94.1％respectively,the median MoCA scored 26,24 and 20 respectively,with statistically significant between-group differ-ences(P＜0.05).Cognitive function was significantly negatively correlated with age(r=-0.634,P＜0.001),blood urea nitrogen(BUN)(r=-0.574,P＜0.001),serum creatinine(Cr)(r=-0.417,P＜0.001),cystatin C(Cys-C)(r=-0.327,P=0.011),serum β2-microglobulin(β2-MG)(r=-0.259,P=0.046),and N-terminal pro-brain natriuretic peptide(NT-proBNP)(r=-0.474,P＜0.001),and was significantly positively correlated with hemoglobin(HB)(r=0.401,P=0.001)and eGFR(r=0.485,P＜0.001).Multivariate Logistic regression analysis showed that age(P=0.006)and NT-proBNP(P=0.041)were influencing factors of cognitive im-pairment in non-dialysis patients with CKD.Receiver operating characteristic(ROC)curve analysis showed that the area under the curve(AUC),sensitivity,and specificity of age for prediction were 0.860,0.864 and 0.812 respectively,the AUC,sensitivity,and specificity of NT-proBNP for pre-diction were 0.808,0.795 and 0.875 respectively,and the combined prediction of age and NT-proBNP had an AUC,sensitivity,and specificity of 0.893,0.955,and 0.750,respectively.Conclusion As renal function deteriorates,the incidence rate and severity of cognitive impairment in non-dialysis patients with CKD tend to increase.Advanced age,renal function deterioration,high NT-proBNP level,and anemia are associated with the occurrence of cognitive impairment in non-di-alysis patients with CKD,among which age and NT-proBNP are influencing factors for cognitive im-pairment.