ObjectiveTo explore the potential mechanism of Weicanqing Formula （微残清方， WF） combined with chemotherapy in treating acute myeloid leukemia （AML） based on malic enzyme 2 （ME2）-mediated bone marrow immune-metabolic homeostasis and . MethodsSixty-five male C57BL/6N mice were randomly divided into control group， model group， WF group， chemotherapy group， and the combination group （WF plus chemotherapy）， with 13 mice per group. Except for the control group， mice were injected with C1498 cells （appro-ximately 1×10⁶ cells per mouse） via the tail vein on day 1 to establish an AML model. Starting from day 8， mice in the chemotherapy group and the combination group were administered with cytarabine at 30 mg/（kg·d） via subcutaneous injection， once daily for 3 consecutive days； WF group and the combination group received WF at 7.54 g/（kg·d） by gavage， once daily for 21 consecutive days. On days 1， 7， 14， 21 and 28， hemoglobin （Hb） and white blood cell （WBC） levels were determined in each group. On day 28， Giemsa staining was used to observe morphological changes in bone marrow cells. Flow cytometry was employed to detect the expression levels of bone marrow T lympthocyte subsets， including CD8⁺， CD4⁺， and regulatory T lymphocytes （Treg）. The contents of glutamine （Gln）， nicotinamide adenine dinucleotide phosphate （NADP⁺）， and reduced nicotinamide adenine dinucleotide phosphate （NADPH） in bone marrow were determined using visible spectrophotometry. Adenosine triphosphate （ATP） concentration in bone marrow was measured by chemiluminescence assay. The mRNA expression of malic enzyme 2 （ME2） in bone marrow was detected by RT-qPCR， and the protein expression level of ME2 was determined by Western blotting. ResultsCompared to the control group， the model group showed decreased Hb levels on day 14， 21， and 28， and increased WBC levels on day 7， 14， 21， and 28 （P＜0.05）. On day 28， bone marrow CD8⁺ and CD8⁺/CD4⁺ levels decreased， while Treg cells， ATP， Gln， NADP⁺， NADPH， ME2 mRNA， and their corresponding protein levels increased （P＜0.05）. Compared to the model group， the chemotherapy group and the combination group both exhibited reduced Hb level on day 14， 21 and 28， as well as the increased WBC level； the combination group showed increased CD8⁺ level， decreased Treg， ATP， Gln， and NADPH content， as well as reduced ME2 mRNA expression and protein levels （P＜0.05）. Compared to the chemotherapy group， the combination group showed significantly increased Hb level on days 21 and 28， and increased WBC level on day 28 （P＜0.05）. Bone marrow smear pathology revealed that， in the model group， myeloid blast cells exhibited cytoplasmic vacuoles indicative of abnormal metabolic activity. In contrast， both the chemotherapy group and the combination group showed large numbers of metamyelocytes and band neutrophils， with only a few immature granulocytic blast cells observed. ConclusionWF may improve the prognosis of AML when used as an adjunct to chemotherapy by modulating ME2 expression， inhibiting metabolic energy competition within the bone marrow microenvironment， and reshaping the distribution of T lymphocyte subsets in the bone marrow.

Objective: To evaluate the effectiveness of school-family-community comprehensive intervention aimed at reducing sugar sweetened beverage(SSB) consumption among primary and secondary school students, so as to provide scientific basis for relevant departments to formulate campus sugar reduction measures for primary and secondary school students. Methods: In October 2023, a multi stage random cluster sampling method was used to select four primary schools (grade 4) and four junior high schools (grade 7) in Nanjing City, and they were randomly divided into the intervention group ( n =1 601) and the control group ( n = 1 433 ) (primary and secondary schools). The intervention group received a one year comprehensive intervention activity with the theme of “drinking less SSBs and enjoying a healthy life” for one consecutive year. The measures included the school conducting health education courses (once a month, 15 minutes each time), environmental support (posting promotional posters, changing them once a month), class bulletin board and interest projects (once a semester); interventions for families included conducting parent lectures (once per semester 30 min each time), new media (once a month) and hand in hand activities (once per semester); community carried out square promotion and create a supportive environment (post promotional posters and replace them once a month). The control group did not receive any intervention measures except regular health education classes. Self administered questionnaires were used to collect knowledge, attitudes, and intake of SSB at the baseline and after the intervention among primary and secondary school students. Results: After the intervention, the proportion of students in the intervention group with an SSB related knowledge awareness rate of 60% or above was 91.4%, which was higher than that of the control group (81.9%) ( χ 2=60.35, P < 0.01 ). The reporting rate of the behavior of choosing to drink beverages when thirsty in the intervention group was 25.4%, which was lower than that of the control group (33.3%); the reporting rates of informing parents about the hazards of sugar sweetened beverages and paying attention to nutrition labels were 62.0% and 78.0% respectively, both of which were higher than those of the control group (52.3%, 65.9%); the reporting rate of having sugar sweetened beverages at home frequently was 43.7% in the intervention group, which was lower than that of the control group (62.3%); the reporting rate of parents restricting the consumption of sugar sweetened beverages was 84.1%, which was higher than that of the control group (78.4%) ( χ 2= 22.66, 29.05, 54.40, 104.84, 16.24, all P <0.05). The reporting rate of students in the intervention group who consumed sugar sweetened beverages more than 4 times per week was 21.5%, which was lower than that of the control group (28.6%), and the difference was statistically significant ( χ 2=20.36, P <0.01). Conclusion The comprehensive intervention of school-family-community can effectively improve primary and secondary school students knowledge and attitudes regarding SSBs and reduce their consumption of these beverages.

ObjectiveTo explore the effects of Jingui Shenqiwan （JSW） and Liuwei Dihuangwan （LDW） on the reproductive ability and brain function of normal mice and compare the actions of the two medications. MethodsSeven groups of female and male mice were divided at a ratio of 2∶1. Except for the control group， the other six groups were as follows： a group of both males and females receiving JSW （3.0 g·kg^-1）， a group of both males and females receiving LDW （4.5 g·kg^-1）， a group of males receiving water and females receiving JSW， a group of males receiving water while females receiving LDW， a group of females receiving water while males receiving JSW， and a group of females receiving water while males receiving LDW. Each group was administered the drug for 14 days and then caged together at a 2∶1 （female∶male） ratio to detect the number of pregnant mice and calculate the pregnancy rate. Pregnant mice continued receiving the drug until they naturally gave birth， which was followed by the observation of newborn mice， calculation of their average number， and the measurement of the offspring's preference for sugar water and neonatal recognition index. At the end of the experiment， the weights of the thymus and spleen were measured to calculate the organ coefficients， and mRNA or protein expression was analyzed in the brain and testes or ovaries. A 1% sucrose solution was used to examine the euphoria of their brain reward systems， while novel object recognition test （NOR） was applied to assess their memory capabilities. mRNA expression was detected using real-time quantitative polymerase chain reaction （Real-time PCR） assay， and protein expression was analyzed with Western blot. ResultsCompared with the control group， oral administration of JSW to both male and female mice for 14 days significantly increased the pregnancy rate of female mice on day 2 after being caged together （P<0.05）， while LDW showed a trend but no statistical significance. Additionally， compared with the control group， JSW could upregulate the gene expression of gonadotropin-releasing hormone （GnRH） in the thalamus， as well as reproductive stem cell factor （SCF） and tyrosine kinase receptor （c-Kit） in the testes and reproductive stem cell marker mouse vasa homologue （MVH） in the ovaries， upregulate the expression of proteins influencing neuronal functional activity， such as brain-derived neurotrophic factor （BDNF）， in hippocampal neurons （P<0.05）， and enhance sucrose preference in male mice （P<0.05）. Compared with the control group， JSW significantly increased sucrose preference and novel object recognition index in offspring mice （P<0.05）， which was related to the upregulation of hippocampal dopamine D1 receptor （D1R） and N-methyl-D-aspartate receptor （Nmdar） gene expression. Compared with the control group， both JSW and LDW could upregulate the protein expression of glucocorticoid receptor （GR）， BDNF， and tyrosine kinase receptor B （TrkB） in the hippocampus of offspring mice （P<0.05）. ConclusionJSW significantly enhances the reproductive ability of normal mice， which is not only related to the release of gonadotropin but also associated with its regulation of brain function. Additionally， JSW has a certain regulatory effect on the brain function of the offspring mice.

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.

ObjectiveTo investigate the mechanism by which Simiao Wan improve intestinal uric acid excretion in hyperuricemic （HUA） rats by inhibiting ferroptosis via the solute carrier family 7 member 11/glutathione peroxidase 4 （SLC7A11/GPX4） signaling pathway. MethodsForty-eight male SD rats were randomly assigned to a normal group， a model group， a low-dose Simiao Wan group （282.6 mg·kg^-1）， a high-dose Simiao Wan group （565.2 mg·kg^-1）， an etoricoxib group （5.4 mg·kg^-1）， and a ferroptosis inhibitor （Fer-1） group （2 mg·kg^-1）. Except for the normal group， rats in all other groups were intraperitoneally injected with potassium oxonate （100 mg·kg^-1） combined with intragastric administration of hypoxanthine （500 mg·kg^-1） to establish the HUA rat model. After 21 days， rats in each administration group received the corresponding dose of drug by gavage， rats in the Fer-1 group received intraperitoneal injection of Fer-1， and rats in the normal and model groups were given an equal volume of normal saline by gavage. After sampling， serum levels of uric acid （SUA）， creatinine （Cr）， and blood urea nitrogen （BUN） were measured using biochemical assays. The content of ferrous ion （Fe²⁺）， reduced glutathione （GSH）， and malondialdehyde （MDA）， as well as superoxide dismutase （SOD） activity in ileal tissues were determined. Hematoxylin and eosin （HE） staining was performed to observe the histopathological changes in the ileum， and transmission electron microscopy was used to observe mitochondrial alterations in the ileal tissue. Immunohistochemistry （IHC） and Western blot were used to detect the protein expression levels of GPX4， ferritin heavy chain 1 （FTH1）， acyl-CoA synthetase long-chain family member 4 （ACSL4）， SLC7A11， and ATP-binding cassette transporter G2 （ABCG2） in ileal tissue. Real-time quantitative polymerase chain reaction （Real-time PCR） was used to determine the mRNA expression of GPX4， FTH1， ACSL4， SLC7A11， and ABCG2 in the ileal tissue. ResultsCompared with the normal group， the model group exhibited significantly elevated serum UA， Cr， and BUN levels （P<0.01）， significantly increased content of MDA and Fe²⁺ in ileal tissue， and significantly decreased GSH content and SOD activity （P<0.01）. HE staining showed extensive shedding of the ileal villous epithelium， disrupted and disorganized villous structure， and incomplete local tissue architecture. Transmission electron microscopy revealed reduced mitochondrial volume， decreased or even vanished cristae， indicating ultrastructural features characteristic of ferroptosis. Molecular and immunohistochemical results demonstrated that the protein and mRNA expression levels of GPX4， FTH1， SLC7A11， and ABCG2 were significantly downregulated， whereas those of ACSL4 were significantly upregulated （P<0.05， P<0.01）. Compared with the model group， after intervention with Simiao Wan， the serum UA， Cr， and BUN levels significantly decreased in all dose groups （P<0.05，P<0.01）， the MDA and Fe²⁺ content in ileal tissues were significantly reduced （P<0.01）， and the GSH content and SOD activity significantly increased （P<0.01）. HE staining showed that the shedding of ileal villous epithelium was markedly alleviated， the villous structure became relatively intact and regularly arranged， and local tissue damage was obviously improved. Transmission electron microscopy showed attenuated mitochondrial damage， improvement in mitochondrial shrinkage， and partial restoration of mitochondrial cristae. Molecular and immunohistochemical results showed that Simiao Wan upregulated GPX4， FTH1， SLC7A11， and ABCG2， and downregulated ACSL4 in a dose-dependent manner. In the high‑dose group， all indices improved significantly （P<0.05，P<0.01）， whereas in the low‑dose group， only improving trends were observed for FTH1， SLC7A11 mRNA， and ABCG2 protein. ConclusionSimiao Wan may inhibit ferroptosis of ileal epithelial cells by regulating the SLC7A11/GPX4 signaling pathway， and upregulate the expression of the uric acid transporter ABCG2， thereby promoting intestinal uric acid excretion and improving HUA.

ObjectiveTo construct and validate a risk assessment model for post-transplant diabetes mellitus （PTDM） using multiple machine learning algorithms， and to realize the early identification of PTDM. MethodsA retrospective analysis was performed for the clinical data of the patients who underwent allogeneic liver transplantation in The First Hospital of Shanxi Medical University from April 1， 2020 to December 31， 2024， and they were randomly divided into a training set and a validation set at a ratio of 7∶3. The LASSO regression analysis combined with 5-fold cross-validation was used for feature selection. Seven machine learning models were developed in the training set， i.e.， logistic regression （LR）， decision tree （DT）， Naive Bayes （NB）， random forest （RF）， K-nearest neighbor （KNN）， extreme gradient boosting （XGBoost）， and adaptive boosting （AdaBoost）. In the validation set， various methods were used to assess the predictive performance of each model， such as accuracy， precision， recall rate， specificity， F1 score， area under the receiver operating characteristic curve （AUROC）， and area under the precision-recall curve （AUPRC）. The Brier score and decision curve analysis were used to assess the calibration and clinical practicability of the models， and the SHAP method was used to analyze feature importance. The independent-samples t test or the Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsA total of 135 liver transplant recipients were enrolled， among whom 26 developed PTDM， and there were 94 patients in the training set and 41 in the validation set. Feature extraction and screening identified 7 key features of sex， overweight or obesity， anhepatic phase， time of operation， length of hospital stay， early postoperative hypomagnesemia， and impaired fasting glucose （IFG）. In the validation set， the XGBoost model showed the best predictive performance， with an AUROC of 0.907 （95% confidence interval ［CI］： 0.807 — 0.989）， an AUPRC of 0.649 （95%CI： 0.339 — 0.955）， an accuracy of 0.878， a precision of 0.667， a recall rate of 0.750， an F1-score of 0.706， a specificity of 0.909， and a Brier score of 0.104. The decision curve analysis showed that when the threshold probability was below 0.667， application of the XGBoost model in clinical decision-making provided relatively high net benefit. The SHAP analysis showed that the length of hospital stay ranked first in terms of feature importance， followed by time of operation， overweight or obesity， sex， IFG， anhepatic phase， and early postoperative hypomagnesemia. ConclusionThe risk assessment model for PTDM in liver transplant recipients based on XGBoost algorithm has excellent performance and can effectively identify high-risk individuals； however， multicenter large-sample data are needed for further validation.

Objective To propose a framework for risk assessment and stepwise management of pulmonary nodules based on existing guidelines and key studies, and to clarify the boundaries for triage, workup escalation, and referral in different detection scenarios. Methods A problem-oriented evidence synthesis approach was used, prioritizing Chinese expert consensus, Fleischner Society Guidelines, British Thoracic Society (BTS) Guidelines, and Lung-RADS. This was supplemented by studies on risk models, imaging measurements, liquid biopsy, tissue sampling, and surgical treatments. This paper is not presented as a formal consensus or a validated clinical pathway. Results A three-tiered framework consisting of basic non-invasive assessment, advanced assessment, and invasive diagnosis was established. It specified the applicable populations, boundaries for the use of risk models, imaging review, management of conflicting results, evaluation of histopathological consistency, and post-intervention follow-up. Liquid biopsy, genetic testing, and artificial intelligence were defined as investigational or adjunctive tools. Conclusion This framework can serve as a preliminary reference for multidisciplinary teams in developing local protocols. It cannot replace applicable guidelines, pathological diagnosis, shared decision-making with patients, or real-world validation.

A prediction model for the risk of childhood allergic asthma was established through the analysis of public datasets. By using bioinformatics analysis methods, two datasets, GSE40732 and GSE40888, were selected, which included the whole-genome expression profile data of 222 children. Among them, GSE40732 was used as the training dataset to detect differentially expressed genes in peripheral blood mononuclear cells of children with the disease, and the master regulator analysis (MRA) algorithm was used to screen the master regulator genes in the inflammation-related pathway (GO: 0006954). After obtaining the master regulator genes, the expression of these master regulator genes in the GSE40732 and GSE40888 datasets was detected, and a prediction model was constructed through logistic regression, based on which risk scores were assigned to children. By comparing the risk scores of healthy children and children with the disease, the area under the curve (AUC) was used to evaluate the classification performance of the model. The average value of the risk scores of all children with the disease output by the model was calculated as the threshold. According to this threshold, the children with the disease in the two datasets were divided into high-risk and low-risk groups. The CIBERSORT algorithm was applied to analyze the infiltration of immune cells in the high-risk and low-risk groups, and the enrichment analysis of signaling pathways was completed using the msigdbr package in R software. The results showed that compared with healthy children, there were 377 up-regulated genes and 255 down-regulated genes in the peripheral blood mono-nuclear cells of children with the disease. The MRA algorithm analysis showed that there were five genes ( MUC5B, CST4, CCR7, TNF-α, and THBS1) that were the master regulator genes in the regulatory network. Risk score= MUC5B×3.47 +CST4×2.17 +CCR7×0.59 +TNF- α×0.54 +THBS1×1.67. The AUC in the GSE40732 and GSE40888 datasets were 0.874 and 0.682, respectively. Compared with the low-risk group, the resting memory CD4 +T cells and regulatory T cells in the peripheral blood of children with the disease in the high-risk group significantly decreased ( P<0.05), and both the IL-33 and IL-13 pathways were highly enriched. In conclusion, the model constructed in this study has a good predictive efficiency for the risk of allergic asthma and also has a certain effect on risk stratification.

Objective:To investigate the correlation between vasoactive-inotropic score and 30-day mortality after surgery in acute Stanford type A aortic dissection(ATAAD) patients.Methods:The clinical data of 242 patients with ATAAD who underwent surgical treatment was retrospectively analyzed between November 2015 and May 2024. There were 172 males and 70 females. The average age was(53.1±11.9) years, ranging from 28 to 85 years. Patients were divided into death group(18 cases) and survival group(224 cases) according to the 30-day outcomes after surgery. The VIS at different time points and perioperative indexes of two groups of patients were analyzed, and multivariate logistic regression was used to analyze the risk factors of 30-day mortality after surgery in ATAAD patients. The receiver operating characteristic curve( ROC) was drawn to evaluate the predictive value of vasoactive-inotropic score. Results:Among 242 ATAAD patients, 18 patients died within 30 days after surgery, with a mortality rate of 7.4%. The age, incidence of pericardial tamponade/cardiogenic shock, incidence of malperfusion syndrome, cardiopulmonary bypass time, red blood cell transfusion intraoperative and in 24 hours postoperatively, ventilator assisted time, and incidence of major postoperative complications of patients in the death group were significantly higher than those in the survival group( P<0.05). The VIS of the death group was significantly higher than that of the survival group at all time points( P<0.05). The area under the receiver operating characteristic curve( AUC) of VIS for predicting death at each time point was greater than 0.500( P<0.05), with the highest AUC(0.906) of the second 24 hours(VISmax48h) in ICU. The optimal cut off value was determined to be 9, with a sensitivity of 0.944 and a specificity of 0.821. Logistic regression analysis showed that the VISmax48h of the second 24 hours in ICU was an independent risk factor for 30-day mortality after surgery in ATAAD patients( OR=1.462, 95% CI: 1.230-1.737, P<0.05). Conclusion:When VISmax48h≥9, patients with ATAAD have an increased risk of mortality after surgery. VISmax48h, cardiopulmonary bypass time, and red blood cell transfusion intraoperative in 24 hours postoperatively are independent risk factors for the 30-day mortality of ATAAD patients.

Objective To explore the value of diffusion tensor imaging analysis index along the perivascular space(DTI-ALPS)for assessing age-related functional changes in glymphatic system(GS).Methods Totally 27 healthy subjects from Meizhou People's Hospital and 100 healthy subjects from neuroimaging informatics tools and resources collaborator database who underwent T1-weighted magnetization-prepared rapid gradient echo(T1-MPRAGE)and DTI scanning were retrospectively enrolled and divided into youth group(n=38),middle-aged group(n=57)and elderly group(n=32).Automated DTI-ALPS index analysis procedure was used to minimize manual errors and derive DTI-ALPS index.The general data,neuropsychological assessment results and DTI-ALPS indices were compared among groups.Spearman correlation analysis was performed to observe the relationships of DTI-ALPS index and age,gender,as well as neuropsychological scores.Results The average age in youth group,middle-aged group and elderly group was(28.5±5.8),(53.7±6.8)and(73.8±2.3)years,respectively.No significant difference of DTI-ALPS index was found between middle-aged group and elderly group(P＞0.05),which were both lower than that in youth group(both P＜0.05).DTI-ALPS index was weakly negatively correlated with age(rs=-0.340,P＜0.001),but not significantly correlated with gender nor neuropsychological assessment results(both P＞0.05).Conclusion DTI-ALPS index was negatively correlated with age in healthy individuals,hence having potential utility for assessing age-related functional changes in GS.