ObjectiveTo clarify the expression of TRIM28 in non-M3 acute myeloid leukemia （AML） and its correlation with clinical indicators and prognosis， and to further explore the effect of TRIM28 expression levels on the proliferation and apoptosis of AML cells using small interfering RNA. MethodsThe GSE34577 dataset was analyzed using R software to compare TRIM28 expression between healthy controls and non-M3 acute myeloid leukemia （AML） patients. Clinical samples from non-M3 AML patients were collected， with TRIM28 expression levels measured using real-time quantitative PCR （qPCR）. The analysis focused on correlations between TRIM28 expression and various clinical indicators， treatment efficacy， and patient prognosis. Furthermore， small interfering RNA （siRNA） technology was employed to downregulate TRIM28 expression in human primary AML cells （HL60 cell line）. The effects on cell proliferation and apoptosis were then assessed through CCK-8 assays and flow cytometry， respectively. ResultsThe results showed that TRIM28 was up-regulated in non-M3 AML of both online database GSE34577 and clinical samples （P<0.000 1）， TRIM28 expression of new diagnosis group and relapsed refractory group was higher than iron deficiency anemia group （P<0.01）， and there was no significance between different French-American-British classification systems subtype. TRIM28 expression was higher in non-M3 AML patients with a poor genetic prognosis stratified as moderate than in the good prognosis group， and TRIM28 expression was associated with NPM1 combined with the FLT3-ITD mutation， positively correlated with age， bone marrow blast， peripheral blood blast and white blood cell， negatively correlated with hemoglobin. In addition， interference TRIM28 greatly inhibited cell proliferation and promoted cell apoptosis. ConclusionThis study reveals that TRIM28 is highly expressed in non-M3 AML and associated with prognosis， and plays a key role in the proliferation and apoptosis of AML cells， suggesting that TRIM28 may serve as a novel therapeutic target for non-M3 AML.

Objective To explore the clinical values of non-invasive myocardial work (MW) and tissue motion annular displacement (TMAD) in evaluation of anthracycline therapy-related cardiac dysfunction in patients with non-Hodgkin lymphoma. Methods A total of 62 patients with non-Hodgkin lymphoma who received standardized chemotherapy based on doxorubicin. Two and three dimensional transthoracic echocardiography, along with two dimensional speckle tracking echocardiography, were performed one day before chemotherapy and at 3, 6, and 9 months after chemotherapy to assess left ventricular ejection fraction, global longitudinal strain (GLS), MW parameters, and TMAD. Logistic regression analysis was used to evaluate the risk factors for cancer therapy-related cardiac dysfunction (CTRCD). The receiver operating characteristic curve was used to assess the diagnostic values of MW- and TMAD-related parameters for CTRCD. Results Compared to baseline, GLS, global work index (GWI), global constructive work (GCW), global work efficiency (GWE), TMAD at midpoint (TMADmid), and TMADmid percentage of left ventricular long-axis diameter (TMADmid%) decreased at 3 months after chemotherapy, while global wasted work (GWW) increased at 6 months after chemotherapy (P＜0.05). Logistic regression analysis showed that the relative reduction in GLS and TMADmid% at 3 months after chemotherapy were independent predictors for CTRCD （P＜0.05), while MW parameters were not independent predictors for CTRCD. GLS reduction≥10.3% and TMADmid% reduction≥15.8% at 3 months after chemotherapy predicted CTRCD with 0.866 and 0.824 of area under the curve (AUC), 92% and 75% of sensitivity, and 74% and 80% of specificity, respectively. AUC of combination of two indexes improved to 0.905, with 75% of sensitivity and 90% of specificity. Conclusions In non-Hodgkin lymphoma patients, the combination of GLS and TMADmid% is helpful of predicting CTRCD early, TMAD may be a novel diagnostic index for CTRCD, and GLS has superior predictive performance than MW for CTRCD.

Hepatic ischemia-reperfusion injury(IRI)is a pathological phenomenon that commonly occurs during liver surgery and transplantation.It leads to serious tissue damage and affects liver function.The mechanisms behind IRI are complex,involving oxida-tive stress,inflammatory responses,and calcium homeostasis disorder.Recently,scientists have paid more attention to the role of endo-plasmic reticulum stress(ERS)in IRI.ERS activates three classical signaling pathways,PERK,IRE1,and ATF6,through the unfolded protein response(UPR),aiming to preliminarily restore endoplasmic reticulum homeostasis and protect cells.However,if the stress re-sponse is excessive or persistent,ERS can activate apoptosis signaling pathways,such as CHOP and Bax/Bak,worsening cell injury.Additionally,ERS is closely related to other cellular stress responses,such as autophagy and oxidative stress,which jointly affect the survival and death of hepatocytes.Regulation of ERS,especially interventions targeting the three UPR pathways,is considered as a po-tential therapeutic pathway for alleviating hepatic IRI.Pharmacological interventions,such as 4-phenylbutyric acid and taurocholic acid,and gene therapies,such as knocking out PERK or IRE1,have shown positive effects in protecting liver function while inhibiting ERS.This paper reviews the mechanism of action of ERS in hepatic IRI,focuses on the specific roles of the three UPR pathways and their potential as therapeutic targets,and explores the future of re-lated therapeutic strategies.

Objective To identify the key biomarkers for diagnosing chronic obstructive pulmonary disease(COPD)complicated with pulmonary arterial hypertension(PAH)using bioinformatics,and validate their clinical significance.Methods High-throughput sequencing data analysis was employed to identify differentially expressed genes(DEGs)in COPD-PAH.Functional enrichment analysis was then conducted to explore the biological functions of these DEGs.Machine learning methods,including least absolute shrinkage and selection operator(LASSO),random forest(RF),and support vector machine-recursive feature elimination(SVM-RFE),were utilized to screen 5 potential biomarkers.Single-cell analysis was performed to reveal the expression patterns of these key genes in macrophages.The clinical significance of these biomarkers was further validated using peripheral blood mononuclear cells(PBMC)data.A mouse model of COPD-PAH was established using hypoxia exposure.Sixteen mice(either sexes,8 weeks old,weighing 20～22 g)were randomly divided into a hypoxia group[O2(10.0±0.5)%,COPD-PAH,n=8]and a normoxia group(COPD,n=8).Immunofluorescence assay was used to label the key biomarkers,and their expression levels were quantified.Results A total of 28 DEGs(|Log2FC|≥2,P<0.05)were identified in COPD-PAH patients.Functional enrichment analysis indicated that DEGs in COPD were primarily associated with major histocompatibility complex(MHC)Ⅱ and cell division,and involved in lysosomes,oxidative phosphorylation,and cell cycle pathways(P<0.05).Machine learning identified 5 potential biomarkers(GRN,KLF4,SHTN1,LRP1,and GPNMB),and subsequent single-cell analysis revealed that these markers exhibited reverse expression patterns during disease progression.A nomogram model constructed based on PBMC data yielded an area under the curve(AUC)of 0.907 in diagnosing COPD-PAH.GRN,KLF4,SHTN1,LRP1 and GPNMB were significantly upregulated in the COPD-PAH group(P<0.05).Conclusion GRN,KLF4,SHTN1,LRP1 and GPNMB are identified as key biomarkers for the prediction and diagnosis of COPD-PAH,which providing new insights for the clinical and treatment of the condition.

The development of forensic medicine is crucial to the national welfare,people's livelihood,social stability,and the construction of a Safe China.It plays an indispensable role in the comprehen-sive promotion of the rule of law.The establishment of forensic medicine as a first-level discipline,along with the transformation brought by the fifth research paradigm,makes the construction of forensic medicine stand at a new historical starting point.This paper reviews the current status and challenges of forensic medicine development,outlines the characteristics of the fifth research paradigm and its im-pact on the construction of forensic medicine,and proposes strategies for addressing these challenges.

Objective:To explore the therapeutic effect of compound Kuijie Ankang Decoction on ulcerative colitis (UC) model mice by non targeted metabonomics; To explore its mechanism.Compound Kuijie Ankang.Methods:The mice were randomly divided into blank control group, model group, Kuijie Ankang Decoction group and sulfasalazine group, with 12 mice in each group. Except the blank control group, the other groups were given 1.5% DSS solution for free drinking to prepare UC model. After successful modeling, Kuijie Ankang Decoction group was intragastrically administered with compound Kuijie Ankang Decoction of 9.68 g/kg, sulfasalazine group was intragastrically administered with sulfasalazine capsule suspension of 320 mg/kg, model group and blank control group were intragastrically administered with equal volume of purified water, once a day, for 7 consecutive days. The body mass and disease activity index (DAI) score of mice were measured. ELISA was used to measure the levels of tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-6 (IL-6), and interleukin-10 (IL-10) in the colon tissue of mice; the protein expressions of Claudin-1 and Zo-1 in colon tissue were detected by immunofluorescence method. HE staining was used to observe the pathological changes in the colon, and UHPLC-OE-MS technology was used to analyze the endogenous metabolite structure of mouse colon tissue, differential metabolites and related metabolic pathways were screened.Results:Compared with the model group, the colon length in Kuijie Ankang Decoction group and sulfasalazine group increased ( P<0.01), the DAI score decreased ( P<0.01), the levels of TNF-α, IL-1β and IL-6 in colon tissue decreased ( P<0.01), the level of IL-10 increased ( P<0.01), and the average optical density of Claudin-1 and Zo-1 protein increased ( P<0.01 or P<0.05). Metabolomics analysis identified 26 potential differential metabolites, including nicotinamide adenine dinucleotide, guanine, gamma aminobutyric acid, and thiamine, affecting 26 key metabolic pathways, including lysine biosynthesis, thiamine metabolism, cysteine and methionine metabolism. Conclusion:Kuaijie Ankang Decoction may improve metabolites such as Gamma aminobutyric acid and thiamine through metabolic pathways such as lysine biosynthesis to alleviate inflammatory reactions, thereby exerting therapeutic effects on ulcerative colitis in mice.

Objectives:To explore the value of non-invasive myocardial work combined with myocardial contrast echocardiography(MCE)in the early diagnosis of coronary artery disease and its efficacy in stratifying the severity of coronary vessel lesions.Methods:A total of 130 patients with suspected coronary artery disease admitted to the First Affiliated Hospital of Dalian Medical University from June 2024 to January 2025 were enrolled in this study.All patients underwent echocardiography and MCE after admission,and coronary angiography(CAG).Based on CAG results,patients were divided into non-CAD group(n=45,coronary artery stenosis<50%)and CAD group(n=85,coronary artery stenosis≥50%).Patients in CAD group were further divided into low-score CAD group(≤49 points,n=43)and high-score CAD group(>49 points,n=42)according to the median of Gensini score(49 points).Non-invasive MW indices and quantitative MCE parameters were assessed.A binary logistic regression model was used to construct a combined diagnostic model,and the value of each parameter in diagnosing CAD and evaluating the severity of coronary lesions was calculated.The receiver operating characteristic(ROC)curve of subjects was estimated,and the area under the curve(AUC)was calculated to evaluate its sensitivity and specificity for early diagnosis of coronary heart disease.Results:Compared with the non-CAD group,the global longitudinal strain,global work index(GWI),and global constructive work(GCW)in both low-score and high-score CAD groups were significantly lower(all P<0.05),and the global work efficiency in the high-score CAD group was significantly reduced(P<0.05).MCE indices in both low-score and high-score CAD groups were significantly lower than those in the non-CAD group(all P<0.05).The multivariate logistic stepwise regression analysis and ROC curve showed that GWI(OR=0.997,95%CI:0.995-0.999,P=0.003)and A value(representing the peak intensity of the curve,reflecting myocardial blood volume(OR=0.415,95%CI:0.246-0.698,P=0.001)were independent predictors of low-score CAD.The combined diagnostic sensitivity and specificity for low-score coronary artery disease were 72.1%and 88.9%respectively,with an AUC of 0.851.GCW(OR=0.997,95%CI:0.995-1.000,P=0.019)and β-value(OR=0.000,95%CI:0.000-0.003,P<0.001)were independent predictors of high-score CAD.The combined diagnostic sensitivity and specificity for high-score coronary artery disease were 88.1%and 88.9%respectively,with an AUC of 0.934.Conclusions:Both non-invasive myocardial work parameters and MCE parameters have high diagnostic efficacy for coronary artery lesions of various degrees.The combined application of the two methods significantly improves the accuracy of coronary artery disease diagnosis,with improved sensitivity and specificity than single technique.Our results provide a new non-invasive comprehensive diagnostic model for clinical early diagnosis and risk stratification of coronary artery disease.

Objective This study aims to analyze the factors influencing per capita current health expenditure in Guizhou Province from 2016 to 2022 using the gray correlation analysis method.Methods Based on the"SHA2011"accounting results of current health expenditure in Guizhou Province,as well as data from the"Guizhou Statistical Yearbook"and"Guizhou Health Statistical Yearbook",the gray correlation analysis method was used to analyze the factors influencing per capita current health expenditure in Guizhou Province from 2016 to 2022.Results The factors with the highest correlation to per capita current health expenditure in Guizhou Province were health expenditure(0.829),followed by the number of health technical personnel per thousand people(0.715),the number of practicing(assistant)physicians per thousand people(0.705),and per capita GDP(0.704).The factor with the lowest correlation was the proportion of the tertiary industry to GDP(0.543).Conclusion Health expenditure investment has the strongest correlation with per capita current health expenditure in Guizhou Province.Health re-source investment and health service capacity are the main influencing factors of per capita current health expenditure in Guizhou Province.At the same time,the impact of economic and social factors on current health expenditure should be fully recognized.

Objective To synthesize high-quality synthetic CT (sCT) images from cone beam CT (CBCT) by learning lung CT domain image features with a deep learning algorithm. Methods A sCT generation algorithm which employs perceptual loss-based cyclic generative adversarial network model (CycleGAN) and iterative registration was presented. CycleGAN model was trained to generate high-quality sCT images by combining perceptual loss and cycle consistency loss;and Elastix was used to register the generated sCT image and the planned CT (pCT) image,and iterate CycleGAN generator model. Results Experiments were conducted on the obtained pCT and CBCT data of 70 patients with lung tumors. From a quantitative perspective,the SSIM between sCT generated by the proposed algorithm and pCT was improved by 11.9％ as compared with that between CBCT and pCT,increasing from 0.825 to 0.923;additionally,RMSE dropped from 110.97 HU to 78.62 HU,PSNR increased from 32.21 dB to 34.74 dB,and mutual information increased from 1.187 to 1.418. The visual evaluation revealed that the proposed algorithm greatly eliminated the scattering artifacts of CBCT slices,highlighted the bone structure,and repaired the soft tissue structure. The comparisons with U-CycleGAN,R-CycleGAN and CUT models confirmed the effectiveness of the proposed algorithm. Conclusion Using the proposed algorithm for sCT images generation can effectively reduce the dose error and structural error between CBCT and pCT,making it possible to apply the proposed algorithm to accurate dose calculations and assist doctors in clinical diagnosis.

Objective:To discuss the correlation between Helicobacter pylori(Hp) infection and serum 25-hydroxyvitamin D3(25(OH)D 3)level in the elderly physical examination population. Methods:It was a cross-sectional study. Selecting individuals who met the inclusion and exclusion criteria as the subjects of the study and underwent health check-ups between January 2018 and December 2019 in the Second Medical Center of Chinese PLA General Hospital.According to the Delta Over Baseline (DOB) value of 13C urea breath test, the subjects were divided into two groups: those with DOB value≥4 ( n=1 018) were diagnosed as Hp-positive and were included in the positive group, and the others were Hp-negative and were included in the negative group (DOB value<4, n=2 067). The age, gender, height, weight, disease history, family disease history and other basic medical records were recorded; and blood samples were drawn for analysis of blood test, blood biochemical test etc. Then the serum 25(OH)D 3 levels were compared between the two groups. The influencing factors of Hp infection were analyzed using a multifactor logistic regression model and the confounding factors were also adjusted. Results:A total of 3 085 elderly people (male 1 838, female 1 247) were selected in this study, the median age is 64 years, the detection rate of Hp was 33%. Single factor analysis showed that the serum 25(OH)D 3 level in the positive group was significantly lower than that in the negative group (20.59 ng/ml vs 21.07 ng/ml, P=0.012). Binary logistic regression analysis showed that the serum 25(OH)D 3 level was a negative influence factor on Hp infection( OR=0.984, P=0.008). High level of serum 25(OH)D 3 can reduce the risk of Hp infection ( OR=0.707, P=0.002). The three constructed Hp infection risk prediction models still showed statistically significant after controlling for confounding factors. Conclusion:The study shows a correlation between serum 25(OH)D 3 level and the Hp infection in the elderly people, and low level of serum 25(OH)D 3 is an independent risk factor for Hp infection in the elderly population.