Aim To evaluate the ameliorative effects of different ratios of Renshen-Huangjing(RH) on SPS-induced PTSD-like behaviors in mice,and to investi-gate the action mechanism using bioinformatics analysis and experimental studies.Methods The aqueous ex-tract was extracted in four ratios of RH in a total weight of 60 g,i.e.1∶0(RH1),2∶1(RH2),1∶2(RH3),and 0∶1(RH4).The extraction rates of Rg1,Rb1,and polysaccharides from different ratios of RH were then detected using UPLC-UV method.The SPS model was established,and RH1,RH2,RH3 and RH4(400 mg·kg-1)were administered by intragas-tric gavage for 14 day,followed by behavioral tests to e-valuate the PTSD-like behaviors.The serum CORT,IL-1β and IL-10 were determined by ELISA.The possible targets of action were analyzed using bioinformatics.The expression levels of Calpain-1,PSD95,BDNF and GluN2B in the hippocampus were detected by Western blot.Results The SPS model induced PTSD-like be-haviors in mice.Serum levels of CORT and IL-1β in-creased and level of IL-10 decreased in SPS model.After treatment with different ratios of RHs,RH2 showed the best therapeutic effect,which was manifes-ted in the suppression of PTSD-like behaviors,the re-duction of CORT and IL-1β levels,and the promotion of IL-10 levels;160 overlapping targets might explain the therapeutic effects of RH on PTSD,and these tar-gets were enriched in inhibiting synaptic damage,exer-ting antioxidant properties and suppressing neuroin-flammation,respectively.RH2 prevented the SPS-in-duced decrease in the expression of Calpain-1,PSD95,BDNF and the elevation of GluN2B.Molecular docking showed strong binding of Rg1 and Rb1 to Calpain-1,PSD95,and BDNF,respectively.Conclusions The a-queous extract of RH in a 2∶1 ratio can more effec-tively prevent SPS-induced PTSD-like behaviors,and its effect may be related to targets such as Calpain-1,PSD95,BDNF and GluN2B.

Objective:To explore the characteristics of systemic immune microenvironment during the progression of dextran sulfate sodium(DSS)-induced acute ulcerative colitis(UC)induced in mice by Mass cytometry(CyTOF).Methods:Male C57BL/6 mice were randomly divided into control group and model group.The control group was given normal drinking water for 15 d.The mouse in the model group were given 5%DSS in drinking water,which was changed to normal drinking water after 7 days.In the model group,peripheral blood was collected on days 4,9 and 15,respectively.CyTOF was used to detect the expressions of 33 immune cell markers and changes in cell subsets in peripheral blood of mice,and the characteristics of systemic immune microenvironment in mice with acute UC were analyzed.Results:The cluster analysis of 33 kinds of immune cell markers showed that CD45+cells in peripheral blood of mice with DSS induced acute UC were divided into 23 fine subgroups,among which the proportions of B cell subgroup,T cell subgroup and neutrophil subgroup showed significant changes.A further dimensional reduction cluster analysis of T cell subsets found significant differences in the composition and proportion of the 10 identified T cell subsets.Conclusion:The systemic immune micro-environment map of mice with acute UC induced by DSS has been successfully constructed,and heterogeneity has been found in the systemic immune microenvironment of mice with acute UC.The changes and activation degree of T cell subpopulations are closely re-lated to disease progression and inflammation level.The results of this study provide theoretical basis for assisting the diagnosis,moni-toring the risk,progression,treatment and prognosis of acute UC.

Integrated medical curriculum is an important direction for the development of medical education. While integrated theoretical courses have been practiced for many years, integrated experiments are still in the exploratory stage. Taking the integrated experiments of medical microbiology and immunology in Xi'an Jiaotong University as an example, this article introduces the design concept, implementation details, effectiveness evaluation, improvements, and prospects of integrated experiments established based on clinical practice principles, so as to provide a reference for further optimization of integrated experiments in the future.

Colorectal cancer stands as a leading cause of cancer-related morbidity and mortality globally,with liver metastases being a significant determinant of patient prognosis.Conventional diagnostic methods,includ-ing imaging studies and biomarker testing,frequently exhibit inadequate sensitivity and specificity,underscoring the necessity for more advanced technologies.Recent advancements in genomics,transcriptomics,proteomics,me-tabolomics,and epigenomics have revolutionized our understanding of the biological mechanisms driving colorectal cancer.These methodologies enable comprehensive analyses of genetic mutations,gene expression profiles,protein modifications,and metabolic reprogramming,all of which are pivotal to the metastatic process.This article high-lights the advanced capabilities of artificial intelligence(AI)technologies in processing complex multi-omics data,thereby enhancing diagnostic accuracy and supporting personalized treatment strategies.It also addresses the challenges AI encounters in multi-omics analyses,such as ensuring data quality,improving model interpretability,and facilitating clinical translation.Additionally,it explores the potential integration of emerging technologies like single-cell sequencing and spatial omics into large-scale,multicenter studies to further enhance the clinical utility of these tools.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

AIM:To investigate the therapeutic effects and potential mechanism of pachymic acid(PA)on li-popolysaccharide(LPS)-induced acute kidney injury(AKI)in mice.METHODS:(1)Genes related to AKI were screened using the DAVID database.Core genes were identified by intersecting related genes and analyzed using Cyto-scape software.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analyses were performed through the DAVID database for the cross-targets.Molecular docking and activity assays were conducted on the primary core targets.(2)A total of 100 C57BL/6J mice were randomly divided into five groups:normal control(NC),model(LPS),solvent control(LPS+DMSO),and treatment groups(LPS+PA-10 and LPS+PA-20),with 20 mice in each group.The LPS-AKI model was established by intraperitoneal injection of 18 mg/kg LPS.The treatment groups received 10 mg/kg and 20 mg/kg PA,respectively,and the solvent control group was administered an equivalent dose of DMSO.Mice were euthanized 24 h after injection.Serum was collected for biochemical analysis,and Western blot was used to detect neutro-phil gelatinase-associated lipocalin(NGAL),kidney injury molecule-1(KIM-1),caspase-3,cleaved caspase-3,interleu-kin-1β(IL-1β),and monocyte chemoattractant protein-1(MCP-1)protein expression.RT-qPCR was employed to detect inflammatory factor mRNA levels.Molecular docking was used to simulate the optimal binding site of PA to caspase-3.En-zyme activity assays were performed to assess caspase protein activity,and renal lesions were observed via hematoxylin and eosin(HE)staining.Apoptosis was detected by TUNEL staining.RESULTS:(1)Thirty-one potential targets of PA against AKI were identified through network pharmacology.GO and KEGG enrichment analyses indicated that these tar-gets were primarily involved in immune response,inflammatory processes,apoptosis and survival,angiogenesis and hemo-dynamics,oxidative stress,and endoplasmic reticulum stress.Key targets included CASP3(caspase-3),PTGS2,BCL2,CCL2,and CYP219.(2)PA treatment improved renal function and reduced tubular epithelial injury.It significantly de-creased NGAL,KIM-1,and cleaved caspase-3 protein levels,as well as inflammatory factors TNF-α,IL-1β,and MCP-1 mRNA and protein expression.PA also reduced apoptosis of renal tubular epithelial cells.Enzyme activity assays and mo-lecular docking revealed that PA exerted its anti-apoptotic effect by directly binding to caspase-3,thereby inhibiting its ac-tivation by caspase-8.CONCLUSION:PA demonstrated a therapeutic effect in LPS-AKI,potentially through the inhibi-tion of inflammatory factor synthesis and release,as well as the inhibition of caspase-3 activation by caspase-8,reducing apoptosis in renal tubular epithelial cells.

Objective:To investigate the iodine nutrition status of children aged 8 - 10 and pregnant women in Xining City, Qinghai Province.Methods:From 2019 to 2021, a stratified cluster sampling method was used to divide 7 counties (districts) under the jurisdiction of Xining City, Qinghai Province into 5 sampling areas according to east, west, south, north, and center each year. One township (town, street) was selected from each area. Forty non boarding students aged 8 to 10 from each primary school (half male and half female, age balanced) and 20 pregnant women from each township (town, street) location were selected to collect edible salt samples at home and a random urine sample to measure salt iodine and urinary iodine level. B-ultrasound was used to measure thyroid volume in children and the goiter rate was calculated.Results:A total of 6 534 samples of household edible salt were collected from children and pregnant women, with an average salt iodine concentration of 25.58 mg/kg. The coverage rate of iodized salt was 97.50% (6 371/6 534), and the qualified iodized salt consumption rate was 89.46% (5 845/6 534). A total of 4 362 urine samples were collected from children, with a median urinary iodine level of 183.10 μg/L. The difference between different years was statistically significant ( H = 20.27, P < 0.001). A total of 2 169 urine samples were collected from pregnant women, with a median urinary iodine level of 168.90 μg/L. The difference between different years was statistically significant ( H = 107.09, P < 0.001). A total of 3 336 cases of thyroid gland examination were conducted in children, including 33 cases of thyroid enlargement, with a goiter rate of 0.99%. There was a statistically significant difference between different years (χ 2 = 15.00, P < 0.001). Conclusion:From 2019 to 2021, children aged 8 to 10 and pregnant women in Xining City are at an appropriate level of iodine, and the achievements in prevention and treatment of iodine deficiency disorders still need to be continuously consolidated.

Objective:To investigate the iodine nutrition status of children aged 8 - 10 and pregnant women in Xining City, Qinghai Province.Methods:From 2019 to 2021, a stratified cluster sampling method was used to divide 7 counties (districts) under the jurisdiction of Xining City, Qinghai Province into 5 sampling areas according to east, west, south, north, and center each year. One township (town, street) was selected from each area. Forty non boarding students aged 8 to 10 from each primary school (half male and half female, age balanced) and 20 pregnant women from each township (town, street) location were selected to collect edible salt samples at home and a random urine sample to measure salt iodine and urinary iodine level. B-ultrasound was used to measure thyroid volume in children and the goiter rate was calculated.Results:A total of 6 534 samples of household edible salt were collected from children and pregnant women, with an average salt iodine concentration of 25.58 mg/kg. The coverage rate of iodized salt was 97.50% (6 371/6 534), and the qualified iodized salt consumption rate was 89.46% (5 845/6 534). A total of 4 362 urine samples were collected from children, with a median urinary iodine level of 183.10 μg/L. The difference between different years was statistically significant ( H = 20.27, P < 0.001). A total of 2 169 urine samples were collected from pregnant women, with a median urinary iodine level of 168.90 μg/L. The difference between different years was statistically significant ( H = 107.09, P < 0.001). A total of 3 336 cases of thyroid gland examination were conducted in children, including 33 cases of thyroid enlargement, with a goiter rate of 0.99%. There was a statistically significant difference between different years (χ 2 = 15.00, P < 0.001). Conclusion:From 2019 to 2021, children aged 8 to 10 and pregnant women in Xining City are at an appropriate level of iodine, and the achievements in prevention and treatment of iodine deficiency disorders still need to be continuously consolidated.

Objective:To explore perioperative management strategies for hiatal hernia in patients 70 years old or above.Methods:The perioperative clinical data of 102 patients (≥70 years) undergoing minimally invasive hiatal hernia repair from January 2019 to December 2024 was retrospectively analyzed.Results:The elderly group age ranged from 70 to 95 years,including 32 males and 70 females with disease duration of 0.67-51 years (mean 10.1 years), showing 68.63% comorbidity incidence (70 cases). Postoperative complication rates were 22.55%, with no severe complications occurring within one month after surgery.Conclusions:Hiatal hernia patients 70 years old or above exhibit longer disease histories, higher comorbidity rates, and increased postoperative complications. Comprehensive preoperative assessment, precise minimally invasive intraoperative techniques, and enhanced perioperative management ensure safe anesthesia and surgical implementation, improve surgical safety, and facilitate patient recovery.

Objective To explore the relationship between serum chitosinase 3-like protein 1(CHI3L1)and Syndecan-1(SDC1)levels and bone metabolism in elderly patients with type 2 diabetes mellitus and their predictive efficacy on osteoporosis.Methods A total of 412 elderly patients with type 2 diabetes admitted to this hospital from May 2019 to May 2023 were included in this study,and were divided into normal bone mass group(n=151),reduced bone mass group(n=138)and osteoporosis group(n=123)according to the iffer-ences in bone mineral density.Serum CHI3L1 and SDC1 levels were detected by enzyme-linked immunosor-bent assay,and serum levels of type 1 collagen cross-linked carboxyl terminal peptide(CTX),25-hydroxyvita-min D[25-(OH)D],osteocalcin(OC),and type 1 procollagen N-terminal propeptide(P1NP)were deter-mined by automatic chemiluminescence immunoassay.Pearson correlation analysis was used to investigate the relationship between serum CHI3L1,SDC1 and bone metabolism in elderly patients with type 2 diabetes.Re-ceiver operating characteristic(ROC)curve was drawn to evaluate the predictive value of serum CHI3L1 and SDC1 on osteoporosis in elderly patients with type 2 diabetes.Multivariate Logistic regression analysis was used to investigate the influencing factors of osteoporosis in elderly patients with type 2 diabetes.Results There were significant differences in diabetes course,fasting blood glucose,HbA1c and HDL-C a-mong normal bone mass group,decreased bone mass group and osteoporosis group(P＜0.05).The levels of serum CHI3L1,25-(OH)D,P1NP and osteocalcin in osteoporosis group were lower than those in osteopenia group,and those in osteopenia group were lower than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum SDC1 and CTX levels in osteoporosis group were higher than those in osteopenia group,and those in osteopenia group were higher than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum CHI3L1 was positively correlated with 25-(OH)D,P1NP and OC(P＜0.05),and negatively correlated with CTX(P＜0.05).Serum SDC1 was negatively correlated with 25-(OH)D,P1NP,OC(P＜0.05),and positively correlated with CTX(P＜0.05).The area under the curve(AUC)of serum CHI3L1,SDC1 and their combination predicted osteoporosis in elderly pa-tients with type 2 diabetes were 0.851,0.772 and 0.904,respectively.Multivariate Logistic regression analysis showed that long duration of diabetes,increased HbA1c,high expression of OC,CHI3L1＞4.16 ng/mL,SDC1≥50.94 ng/mL were all influential factors for osteoporosis in elderly patients with type 2 diabetes(P＜0.05).Conclusion Low expression of CHI3L1 and high expression of SDC1 in serum are associated with ab-normal bone metabolism in elderly patients with type 2 diabetes.These two indexes are expected to be used as biological markers to predict osteoporosis in elderly patients with type 2 diabetes.