ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

The development of intestinal-type gastric cancer follows a progression from non-atrophic gastritis — atrophic gastritis — intestinal metaplasia — epithelial dysplasia — gastric cancer，known as the " inflammation-cancer transformation. " Leveraging the advantages of integrated traditional Chinese and Western medicine，while collaborating to inhibit this transformation，remains a research focus and challenge. The incidence of gastric cancer in China has declined with the continuous elucidation of the mechanisms behind inflammation-cancer transformation，innovations in early screening and diagnosis techniques in Western medicine，the establishment of risk stratification and treatment systems，and effective interventions through traditional Chinese medicine. Leveraging the theoretical and practical advantages of the " preventing disease before it occurs" philosophy of traditional Chinese medicine，particularly the concept of " preventing transformation in existing diseases，" is essential. This approach emphasizes shifting the focus of prevention and treatment to earlier stages of disease progression. Developing more effective and reliable strategies and innovative drugs that block the dynamic progression of the " inflammation-cancer transformation" in gastric cancer remains a key goal. This article reviews the latest progress in both basic and clinical research in this field，the issues related to high-level clinical research in traditional Chinese medicine，the construction of integrated diagnosis and treatment pathways combining Chinese and Western medicine，the establishment of efficacy evaluation standards，and the elucidation of the integration mechanisms of the complex system of traditional Chinese medicine. It also explores research directions and solutions within the context of multidisciplinary collaboration to provide insights and references to block inflammation-cancer transformation and to construct a gastric cancer prevention and control system with Chinese characteristics，thereby further enhancing the level of gastric cancer prevention and control.

Objective: To investigate factors influencing perioperative blood transfusion in patients with scarred uterus during pregnancy undergoing cesarean section, construct and validate a transfusion risk prediction model, and provide evidence for preoperative assessment and blood management. Methods: Clinical data of 405 patients undergoing cesarean section for scarred uterus during pregnancy at the First Affiliated Hospital of Xi'an Jiaotong University from January 2020 to December 2024 were retrospectively collected. The dataset was randomly divided into a training set (n=284) and a validation set (n=121) at a 7∶3 ratio. Within the training set, Firth-penalized logistic regression was employed for multivariate analysis to identify independent factors influencing perioperative blood transfusion and construct a predictive model. Model performance was evaluated in the validation set. Results: Multivariate Firth regression analysis showed that severe placenta previa (OR=75.566, 95%CI: 8.603-9979.174) and placenta accreta (OR=4.591, 95%CI: 1.120-19.416) were independent risk factors for perioperative blood transfusion, while preoperative red blood cell count (OR=0.189, 95%CI: 0.083-0.405) and fibrinogen levels (OR=0.588, 95%CI: 0.395-0.855) were protective factors. The predictive model constructed based on these four variables demonstrated good discriminatory performance, with areas under the receiver operating characteristic curves of 0.803 (95%CI: 0.740-0.867) and 0.753 (95%CI: 0.644-0.862) in the training and validation sets, respectively. Conclusion: For patients with scarred uterus during pregnancy undergoing cesarean section, severe placenta previa and placenta accreta significantly increase the risk of transfusion, while higher preoperative red blood cell count and fibrinogen levels exert a protective effect. The predictive model established in this study facilitates the identification of patients requiring transfusion, thereby enabling preoperative blood preparation and optimized blood management.

OBJECTIVE To explore the potential mechanism by which drug-containing serum of Dianxianqing granules （DXQ） inhibits microglial ferroptosis. METHODS Male SD rats were given normal saline and Dianxianqing granules solution via intragastric administration to prepare normal serum and DXQ， respectively. Mice microglia BV2 cells were collected and successfully transfected with a negative control small interfering RNA （si-NC）， and then they were included in the si-NC group and cultured under normal conditions. Cells successfully transfected with small interfering RNA targeting glutathione peroxidase 4 （GPX4） （si-GPX4） were divided into the si-GPX4 group， the CsA group （treated with 1 μmol/L cyclosporine A）， and the DXQ- L， DXQ-M and DXQ-H groups （treated with 5%， 7% and 10% DXQ， respectively）. These groups were subsequently treated with their corresponding drug solutions and ferroptosis inducer Erastin （10 μmol/L）. The intracellular levels of total iron ions， glutathione （GSH）， reactive oxygen species （ROS）， and the expression of mitochondrial superoxide were determined in each group after 48 h of treatment. Additionally， mitochondrial membrane potential， the opening degree of mitochondrial permeability transition pore （MPTP）， and mRNA expressions of GPX4 and cyclophilin D （CypD） were detected. Furthermore， the expressions of ferroptosis-related proteins[GPX4， transferrin receptor 1 （TfR1） and ferritin heavy chain 1 （FTH1）]， as well as MPTP-related proteins [adenine nucleotide translocator （ANT）， cytochrome C （CytC）， mitochondrial calcium uniporter （MCU） and CypD] were assessed. RESULTS Compared with si-NC group， the levels of total iron ions and ROS， the expression level of mitochondrial superoxide， the opening degree of MPTP， protein and its mRNA expressions of CypD as well as protein expressions of TfR1 and MCU were increased or up-regulated significantly （P＜0.01）； however， GSH content， mitochondrial membrane potential， protein and mRNA expressions of GPX4， and protein expressions of FTH1， ANT and CytC were decreased or down-regulated significantly （P＜0.01）. Compared with the si-GPX4 group， the cells in the DXQ-M， DXQ-H groups showed a general improvement in the above quantitative indicators （P＜0.01 or P＜0.05）. CONCLUSIONS DXQ can enhance antioxidant capacity by activating the GSH/GPX4 pathway， regulate the expressions of TfR1 and FTH1 protein to correct iron ion homeostasis， inhibit excessive opening of MPTP to improve mitochondrial function， and ultimately suppress microglial ferroptosis.

Objective To analyze the influencing factors of respiratory failure in patients with sepsis, and to construct and validate a risk prediction model. Methods A total of 308 patients with sepsis in Ganzi Tibetan Autonomous Prefecture People's Hospital from August 2021 to September 2024 were enrolled and divided into a modeling group and a validation group. According to whether respiratory failure occurred during hospitalization, the patients were divided into a respiratory failure group and a non-respiratory failure group. Single-factor and binary logistic regression analysis were used to construct a risk prediction model, and the ROC, calibration, and DCA curves were used to assess the model's predictive performance. Results The incidence of respiratory failure was 20.83% (45/216) in the modeling group and 20.65% (19/92) in the validation group. Albumin, D-dimer, serum calcium, procalcitonin at admission, and sequential organ failure assessment were independent influencing factors of respiratory failure in patients with sepsis. The ROC curve analysis nomogram model predicted that the AUC of respiratory failure in the modeling group was 0.994 (95%CI: 0.985-1.000), and the AUC of the validation group was 0.897 (95%CI: 0.826-0.968). The calibration curve analysis showed that the calibration curve fit well with the ideal curve. DCA curve analysis showed that the net benefit was greater than 0 across all threshold probability ranges. Conclusion The risk prediction model constructed in this study is highly effective and can provide reference for medical staff to evaluate respiratory failure in patients with sepsis.

Theory and technology of Medical Immunology are widely used in scientific research.Our teaching and research group uses experimental teaching of Medical Immunology as a platform to carry out practice of scientific research project-based experi-mental system among"5+3"integration students.By completing a mini-project research including experimental design-experimental operation-research article writing,students cultivated scientific research thinking and exercised scientific research practice ability,and generally reported that the course is very difficult,but after completing it,it is very rewarding.

Aim To explore the mechanism of the syn-ergistic effect of the ferroptosis inducer erastin com-bined with shikonin in promoting ferroptosis in human hypertrophic scar fibroblasts(HSFBs).Methods Hypertrophic scar tissues provided by the General Hos-pital of Ningxia Medical University were collected,and HSFBs were extracted.HSFBs were identified by HE staining and immunofluorescence.The inhibitory rates of Era and SHK on HSFBs at different concentrations were detected by CCK-8 assay,and the IC50 value was calculated.CompuSyn software was used to calculate the co-use index(CI).Control group,Erastin(Era)group,shikonin(SHK)group and Era+SHK group were set up,and the number and morphological chan-ges of cells were observed after 24 hours of interven-tion.The ability of cell migration and invasion was de-tected by scratch test and Transwell test.The changes of malondialdehyde(MDA),total iron ion and reactive oxygen species(ROS)were detected by corresponding biochemical kits.The expressions of collagen I,α-SMA and GOT1,SLC7A11,GPX4 and FTH1 were detected by Western blot.Results The IC50 value of Era and SHK of primary HSFBs was 2.22 μmol·L-1 and 3.94μmol·L-1 respectively,which was used as the single drug concentration for subsequent experiments.The CompuSyn software was employed to calculate the CI value when the two drugs were used in combination,and the concentrations corresponding to CI=0.39597(Era:1.2 μmol·L-1+SHK:1.5 μmol·L-1)were selected as subsequent combination concentrations(Because when CI was equal to 0.395 97,the concen-tration of each drug was lower than the concentration of single drug,and the inhibition rate of combined drug was greater than 50％).Compared with the monother-apy group,the number of HSFBs in the SHK+Era group was significantly reduced,cell membrane showed breakage and vesiculation,cell wrinkling became smal-ler,and cytoplasm was concentrated.The migration and invasion ability of HSFBs in the SHK+Era group were obviously weakened(P＜0.05),and the expres-sion of fibrosis-related proteins collagen Ⅰ and α-SMA was reduced(P＜0.05);the contents of MDA,total i-ron ions,and ROS in HSFBs of the SHK+Era group increased(P＜0.05),and the protein expression lev-els of SLC7A11,GOT1,GPX4,and FTH1 further de-creased(P＜0.05).Conclusions Erastin in combi-nation with shikonin can synergistically inhibit the pro-liferation,migration and fibrosis levels of HSFBs.The mechanism may be that erastin enhances the inhibition of shikotin on GOT1,increases the levels of cellular i-ron ions,ROS,and lipid peroxides,thereby promoting ferroptosis in HSFBs.

Objective:To investigate the effects of individual versus connected microdroplet culture modes in time-lapse (TL) incubators on embryo development parameters and pregnancy outcomes in patients undergoing whole embryo culture to blastocyst stage.Methods:Using a retrospective cohort study, clinical data from 3 507 fresh blastocyst transfer cycles were analyzed. These cycles involved patients who underwent assisted reproductive technology treatment with whole embryo culture to blastocyst stage at the Reproductive Medical Center of Northwest Women's and Children's Hospital between January 2019 and December 2023. Based on different culture modes, patients were divided into two groups, connected group ( n=2 446, using connected microdroplet culture) and individual group ( n=1 061, using individual microdroplet culture). Baseline characteristics, embryo development parameters, pregnancy outcomes, and neonatal outcomes were compared between the two groups. Generalized linear models (GLM) were used to adjust for confounding factors and analyze the effect of culture mode. Results:Embryo development assessment showed the day 3 (D3) high-quality embryo rate in the connected group [60.12% (12 136/20 187)] was significantly lower than that in the individual group [63.62% (4 705/7 395), P<0.001], whereas the high-quality blastocyst formation rate [34.93% (7 052/20 187)] and the available blastocyst formation rate [56.07% (11 319/20 187)] were both significantly higher than those in the individual group [33.08% (2 446/7 395), P=0.004; 51.45% (3 805/7 395), P<0.001], with statistically significant differences. The implantation rate [67.40% (1 774/2 632)], the clinical pregnancy rate [70.20% (1 717/2 446)], and the live birth rate [60.66% (1 469/2 446)] in the connected group were all significantly higher than those in the individual group [63.40% (724/1 142), P=0.017; 66.73% (708/1 061), P=0.041; 55.89% (593/1 061), P=0.021], with statistically significant differences. Neonatal outcomes showed no statistically significant difference between the two groups (all P>0.05). After adjusting for confounding factors using GLM, connected culture was an independent influencing factor for D3 high-quality embryo rate (a MD=-0.017, 95% CI: -0.034-0.000, P=0.046), high-quality blastocyst formation rate (a MD=-0.020, 95% CI: 0.002-0.037, P=0.026), available blastocyst formation rate (a MD=0.032, 95% CI: 0.015-0.048, P<0.001), live birth rate (a OR=1.182, 95% CI: 1.006-1.388, P=0.042). However, it had no effect on D3 available embryo rate, clinical pregnancy rate, or early miscarriage rate (all P>0.05). Conclusion:In TL incubator systems, individual and connected microdroplet culture modes exert different effects at various stages of embryo development. Individual microdroplet culture can significantly enhance cleavage-stage embryo quality, whereas the connected microdroplet culture was more beneficial for enhancing the blastocyst formation rate and quality, ultimately improving the live birth rate without increasing neonatal risks.