Esophageal carcinoma is a malignant disease with a high incidence rate and poor prognosis. The mitochondrial apoptosis pathway plays a pivotal role in the regulation of cell death and has become a focal point in current cancer therapeutics research. Various active components from traditional Chinese medicine （TCM） can target the mitochondrial apoptosis pathway to inhibit esophageal carcinoma， presenting as potential therapeutic agents for this disease. This paper summarizes relevant research on the inhibition of esophageal carcinoma by active components in TCM via targeting the mitochondrial apoptosis pathway. It has been found that flavonoids （casticin， icariin， luteolin， kaempferol， hesperetin， deguelin， etc.）， terpenoids （oridonin， Jaridonin， artesunate， ethyl acetate fraction of pleurotus ferulatus triterpenoid， etc.）， alkaloids （matrine， swainsonine， etc.）， polyphenols （curcumin， epigallocatechin-3-gallate， corilagin， etc.）， steroids （α-hederin， polyphyllin Ⅵ， etc.）， phenols （optimized scorpion venom peptide CT-K3K7， gecko active polypeptide， etc.）， volatile oils （cinnamaldehyde， α -asarone， etc.） and other active components from TCM can target the intrinsic mitochondrial apoptosis pathway， induce apoptosis in esophageal carcinoma cells， and inhibit their proliferation， invasion and migration by regulating oxidative stress， blocking the cell cycle， regulating signaling pathways such as PI3K/Akt and MAPK.

Approximately 10% of the global adult population has diabetes, with accumulating evidence linking suboptimal vitamin D levels to an increased risk of type 2 diabetes and its complications. Current clinical studies suggest that vitamin D supplementation may enhance insulin sensitivity and improve glycemic control, prompting significant interest in its potential as a therapeutic intervention. However, further high-quality, large-scale randomized controlled trials are required to validate its efficacy in glucose metabolism regulation and clarify the underlying molecular mechanisms. These investigations will provide critical evidence to inform precision medicine approaches for diabetes prevention and management.

OBJECTIVES: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy, with disease progression driven by cytogenetic abnormalities and a complex bone marrow microenvironment. This study aims to construct a prognostic model for MM based on transcriptomic data and lipid metabolism related genes (LRGs), and to identify potential drug targets for high-risk patients to support clinical decision-making. METHODS: In this study, 2 transcriptomic datasets covering 985 newly diagnosed MM patients were retrieved from the Gene Expression Omnibus (GEO) database. Univariate Cox regression and 101 machine learning algorithms were used for gene selection. An LRG-based prognostic model was constructed using Stepwise Cox (both directions) and random survival forest (RSF) algorithms. The association between the prognostic score and clinical events was evaluated, and model performance was assessed using time-dependent receiver operating characteristic (ROC) curves and the C-index. The added predictive value of combining prognostic scores with clinical variables and staging systems was also analyzed. Differentially expressed genes between high- and low-risk groups were identified using limma and clusterProfiler and subjected to pathway enrichment analysis. Drug sensitivity analysis was conducted using the Genomics of Drug Sensitivity in Cancer (GDSC) database and oncoPredict to identify potential therapeutic targets for high-risk patients. The functional role of key LRGs in the model was validated via in vitro cell experiments. RESULTS: An LRG-based prognostic model (LRG17) was successfully developed using transcriptomic data and machine learning. The model demonstrated robust predictive performance, with area under the curve (AUC) values of 0.962, 0.912, and 0.842 for 3-, 5-, and 7-year survival, respectively. Patients were stratified into high- and low-risk groups, with high-risk patients showing significantly shorter overall survival (OS) and event-free survival (EFS) (both P<0.001) and worse clinical profiles (e.g., lower albumin, higher β2-microglobulin and lactate dehydrogenase levels). Enrichment analysis revealed that high-risk patients were significantly enriched for pathways related to chromosome segregation and mitosis, whereas low-risk patients were enriched for immune response and immune cell activation pathways. Drug screening suggested that AURKA inhibitor BMS-754807 and FGFR3 inhibitor I-BET-762 may be more effective in high-risk patients. Functional assays demonstrated that silencing of key LRG PLA2G4A significantly inhibited cell viability and induced apoptosis. CONCLUSIONS LRGs serve as promising biomarkers for prognosis prediction and risk stratification in MM. The overexpression of chromosomal instability-related and high-risk genetic event-associated genes in high-risk patients may explain their poorer outcomes. Given the observed resistance to bortezomib and lenalidomide in high-risk patients, combination therapies involving BMS-754807 or I-BET-762 may represent effective alternatives.
Humans ; Multiple Myeloma/mortality* ; Prognosis ; Lipid Metabolism/genetics* ; Transcriptome ; Machine Learning ; Male ; Female ; Gene Expression Profiling ; Algorithms

Malignant tumors continue to pose a significant threat to human life and safety and their development is primarily due to the activation of proto-oncogenes and the inactivation of suppressor genes.Among these,the activation of proto-oncogenes possesses greater potential to drive the malignant transformation of cells.Targeting oncogenes involved in the malignant transformation of tumor cells has provided a novel approach for the development of current antitumor drugs.Several preclinical and clinical studies have revealed that the development pathway of B cells,and the malignant transformation of mature B cells into tumors have been regulated by oncogenes and their metabolites.Therefore,summarizing the key oncogenes involved in the process of malignant transformation of mature B cells and elucidating the mechanisms of action in tumor development hold significant importance for the clinical treatment of malignant tumors.

Hepatocellular carcinoma （HCC） is a common tumor in the digestive tract， the formation mechanism of which remains to be fully elucidated. Although surgery， radiation， chemotherapy， targeted therapy， and immunotherapy have achieved significant results in the treatment of HCC， these methods are accompanied by a considerable number of adverse reactions and complications. In recent years， Chinese medicine has shown remarkable efficacy in the treatment of HCC， and both basic experiments and clinical studies have confirmed the effectiveness of Chinese medicine， which exerts therapeutic effects via multiple components and multiple targets. However， the pathogenesis of HCC is exceptionally complex and not fully understood， which means that studies remain to be carried out regarding the specific mechanism of Chinese medicine in preventing and treating HCC. Network pharmacology and molecular biology can be employed to decipher the mechanism of Chinese medicine in the treatment of diseases. Studies have shown that Chinese medicine can regulate various pathways such as the mitogen-activated protein kinase （MAPK）， phosphatidylinositol 3-kinase/protein kinase B （PI3K/Akt）， Hedgehog， Wnt/β-catenin， nuclear factor-κB （NF-κB）， Janus kinase 2/signal transducer and activator of transcription 3 （JAK2/STAT3）， and transforming growth factor-β （TGF-β）/Smad signaling pathways. Chinese medicine can exhibit its anti-HCC effects by inducing cell apoptosis， inhibiting cell proliferation and migration， and blocking the cell cycle via the above pathways. However， the specific mechanisms remain to be systematically studied. This study comprehensively reviews the regulatory effects of Chinese medicine on HCC-related signaling pathways to reveal the molecular mechanisms of Chinese medicine in the treatment of HCC. This view holds the promise of providing new targets， new perspectives， and new therapies for HCC treatment and advancing the modernization and development of Chinese medicine.

Objective To compare H_p(3) calibration with a homemade (A) thermoluminescent dosimeter (TLD) and an imported (B) TLD in a standard X-ray RQR radiation field, to explore the different responses of A and B, and to provide foundation for the calibration of H_p(3). Methods A column mode was selected. H_p(3) calibration was performed using A and B in a standard X-ray RQR radiation field in the Secondary Standard Dosimetry Laboratory, National Institute for Radiological Protection, China Center for Disease Control and Prevention. Angle response, energy response, and linear response were calibrated with RQR4 (60 kV), RQR7 (90 kV), and RQR9 (120 kV), respectively. Results In terms of angle response, the calibration results of A were relatively high, while the calibration results of B were relatively low. In terms of energy response, the calibration results showed a similar pattern to angle response. In terms of linear response, the calibration results of both A and B were satisfactory. Conclusion Both A and B can be used for normal calibration of H_p(3) in a standard X-ray RQR radiation field. However, in actual monitoring, attention should be paid to the energy and angle response values of TLDs.

Objective To investigate the value of serum cell cycle protein-dependent kinase 1(CDK1)and aurora kinase A(AURKA)in the diagnosis of patients with hepatitis B virus-related hepatocellular carcinoma(HBV-HCC).Methods A total of 50 HBV-HCC patients,50 patients with hepatitis B virus-related liver cirrhosis(HBV-LC),and 50 chronic hepatitis B(CHB)patients who were hospitalized in Department of Gastroenterology,Gansu Provincial Hospital,from June 2022 to December 2023 were enrolled,and 50 healthy individuals,matched for age and sex,who received physical examination at Physical Examination Center during the same period of time were enrolled as control group.Related data were recorded for all patients,including age,sex,complications,and the results of routine blood test,liver function,and coagulation for the first time after admission.ELISA was used to measure the serum levels of CDK1 and AURKA.A one-way analysis of variance was used for comparison of normally distributed continuous data between multiple groups,and the least significant difference t-test was used for further comparison between two groups;the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between multiple groups and the least significant difference Bonferroni test was used for further comparison between two groups;the chi-square test or the Fisher's exact test was used for comparison of categorical data between groups.The Spearman correlation analysis was used to investigate the correlation between CDK1 and AURKA,and the receiver operating characteristic(ROC)curve and the area under the ROC curve(AUC)were used to investigate the value of CDK1 and AURKA in the diagnosis of HBV-HCC.Results There were significant differences in liver function parameters between the HBV-HCC patients and the control group(all P<0.05);there were significant differences between the CHB group and the HBV-HCC group in albumin,Glb,direct bilirubin,aspartate aminotransferase(AST),gamma-glutamyl transpeptidase(GGT),and alkaline phosphatase(all P<0.05);there were significant differences between the HBV-LC group and the HBV-HCC group in Glb,AST,and GGT(all P<0.05).The HBV-HCC group had significantly higher serum levels of CDK1 and AURKA than the HBV-LC group,the CHB group,and the control group(all P<0.05).There was a significant positive correlation between CDK1 and AURKA in the overall study population and the HBV-HCC patients(r=0.526 6 and 0.815 2,P<0.001).With the control group as reference,CDK1 had an AUC of 0.832 3 in the diagnosis of HBV-HCC,with a sensitivity of 92.86%and a specificity of 75%,and AURKA had an AUC of 0.886 6 in the diagnosis of HCC,with a sensitivity of 95.80%and a specificity of 74%.With the CHB group as reference,CDK1 had an AUC of 0.833 3 in the diagnosis of HBV-HCC,with a sensitivity of 93.75%and a specificity of 75%,and AURKA had an AUC of 0.972 7 in the diagnosis of HBV-HCC,with a sensitivity of 95.83%and a specificity of 91.67%.With the HBV-LC group as reference,CDK1 had an AUC of 0.608 5 in the diagnosis of HBV-HCC,with a sensitivity of 66.67%and a specificity of 54.17%,and AURKA had an AUC of 0.762 2 in the diagnosis of HBV-HCC,with a sensitivity of 95.83%and a specificity of 47.92%.Conclusion The serum levels of CDK1 and AURKA increase with the progression of hepatitis B-associated chronic liver disease,and significant increases in serum CDK1 and AURKA have a certain value in the diagnosis of HBV-HCC.

Objective:To develop a risk prediction model of acute cerebral infarction (ACI) in patients with type 2 diabetes mellitus (T2DM).Methods:It was a cross-sectional study. The clinical data of 798 patients with T2DM hospitalized in the Department of Endocrinology and Neurology of Shanxi Bethune Hospital from August 2021 to October 2023 were collected. Based on whether they had concurrent ACI, the patients were divided into T2DM with ACI group (case group) and pure T2DM group (control group). The patients were then allocated to a training set ( n=558) and a validation set ( n=240) in a 7∶3 ratio by the sample functions in R software. LASSO regression was employed to screen and optimize variables, and a multivariate logistic regression analysis was used to establish the nomogram prediction model. The discriminative ability, calibration, and clinical usefulness of the risk prediction model were assessed with receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis, respectively. Results:LASSO regression identified gender, age, systolic blood pressure, fasting plasma glucose (FPG), albumin (ALB), and carotid vascular condition as the variables for prediction. The multivariable logistic regression analysis showed that female ( OR=0.489, 95% CI: 0.308-0.778) and ALB ( OR=0.846, 95% CI: 0.795-0.901) were protective factors for ACI occurrence in T2DM patients, while age ( OR=1.051, 95% CI:1.025-1.077), systolic blood pressure ( OR=1.047, 95% CI: 1.034-1.059), FPG ( OR=1.185, 95% CI: 1.089-1.288), and carotid plaque ( OR=7.359, 95% CI: 3.050-17.756) were risk factors. The area under the ROC curve (AUC) for risk of ACI in the training set was 0.863(95% CI: 0.833-0.893), and it was 0.846(95% CI: 0.797-0.896) for the validation set. Calibration curves and the Hosmer-Lemeshow goodness-of-fit test indicated good model fit (training set χ2=8.311, P=0.404; validation set χ2=3.957, P=0.861). Decision curve analysis showed that the clinical effectiveness of the model was higher when the threshold probabilities of the training set and the validation set was 0.02-0.93 and 0.12-0.99, respectively. Conclusion:In this study, a prediction model of ACI risk in T2DM patients was successfully established.

Objective:To evaluate the effect of strict intraoperative blood glucose control on postoperative hepatic allograft dysfunction in patients undergoing liver transplantation.Methods:A total of 164 patients of both sexes, aged 18-64 yr, with body mass index of 18-30 kg/m 2, of American Society of Anesthesiologists Physical Status classification Ⅲ or Ⅳ, undergoing orthotopic liver transplantation, were divided into strict intraoperative blood glucose control group (group S, 6.0-7.8 mmol/L) and routine blood glucose control group (group C, 4.1-10.0 mmol/L) using a random number table method. From the completion of anesthesia induction to the end of operation, arterial blood glucose was measured every 1 h, and blood glucose management was carried out in combination with the goal-oriented blood glucose control process. The occurrence of postoperative hepatic allograft dysfunction, infection within 30 days after surgery, offline extubation time, duration of intensive care unit stay and total length of hospital stay were recorded. Results:Compared with group C, the incidence of postoperative liver dysfunction and infection within 30 days after operation were significantly decreased ( P<0.05), and no significant change was found in the offline extubation time, duration of intensive care unit stay and total length of hospital stay in group S ( P>0.05). Conclusions:Strict blood glucose control during liver transplantation can decrease the development of postoperative liver dysfunction in patients.

This paper reviews the definition and current situation of virtual reality, the application conditions, intervention mechanisms, effectiveness evaluation indicators, application forms and effects, shortcomings and prospects of virtual reality intervention in smoking cessation, in order to provide guidance and basis for the clinical practice and nursing of virtual reality intervention in smoking cessation in China.