Esophageal cancer is a prevalent malignant tumor of the digestive tract in China, and radical surgery remains the cornerstone of its comprehensive treatment. However, multifactorial challenges such as postoperative gastrointestinal tract reconstruction, traumatic stress, and tumor-related metabolic disturbances render esophageal cancer patients highly susceptible to malnutrition. Perioperative nutritional support therapy plays a crucial role in enhancing surgical safety, improving clinical outcomes, and elevating patients' quality of life by regulating metabolic homeostasis, preserving organ function, and optimizing the immune microenvironment. This article reviews the mechanisms underlying malnutrition in esophageal cancer, methods for nutritional status assessment, and precision intervention pathways based on multi-omics evaluations. The aim is to strengthen clinicians' awareness of standardized perioperative nutritional management for esophageal cancer patients and promote its clinical implementation, thereby facilitating postoperative recovery and improving long-term quality of life.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

To address the scarcity of annotated data for pediatric abdominal CT imaging and the insufficient generalization capability of existing models, we constructed a self-supervised pretraining architecture tailored for pediatric CT domain adaptation based on the visual foundation model DINOv3, and validated its performance in the task of pediatric abdominal multi-organ segmentation.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective To observe the value of machine learning(ML)models based on ultrasound radiomics for preoperatively distinguishing atypical parathyroid tumor(APT)/parathyroid carcinoma(PC)and parathyroid adenoma(PA).Methods Totally 330 primary hyperparathyroidism patients who underwent surgical treatments were retrospectively enrolled and categorized into APT/PC group(n=78)and PA group(n=252)according to surgical pathology and clinical follow-up results,also divided into training set(n=231)and test set(n=99)at the ratio of 7∶3.Based on preoperative ultrasound,545 radiomics features were extracted,and recursive feature elimination(RFE),Kruskal-Wallis or analysis of variance methods were used to screen the features,respectively.Support vector machine(SVM),linear discriminant analysis(LDA),least absolute shrinkage and selection operator logistic regression(LRLASSO),also random forest(RF)and decision tree(DT)algorithms were adopted to construct ML models for differentiating APT/PC and PA,respectively.Then the models were trained in training set,their performance were verified in test set,and a 5-fold cross-validation was adopted to screen out the better combinations.Results Compared with Kruskal-Wallis and analysis of variance methods,the distinguishing efficacy of SVM,LDA,LRLASSO,RF and DT models constructed based on features screened out using RFE method in training set(area under the curve[AUC]=0.870,0.878,0.850,0.847,1.000)and test set(AUC=0.856,0.842,0.827,0.847 and 0.704)were all relatively higher.In test set,the AUC of SVM,LDA,LRLASSO and RF models constructed based on the features screened out using RFE method(included 25,23,17 and 23 features)were all higher than that of DT model(8 features)(all P＜0.001).No significant difference of AUC was found between SVM,LRLASSO or RF models and LDA model(all P＞0.05).The AUC of SVM and RF models were higher than that of LRLASSO model(both P＜0.05),while of SVM and RF models were not significantly different(P＞0.05),indicating that SVM,LDA and RF models were better ones.Conclusion SVM,LDA,LRLASSO,RF and DT models based on ultrasound radiomics could effectively distinguish APT/PC and PA preoperatively,among which SVM,LDA and RF models had better diagnostic efficacy.

Objective To explore the mechanism of action of jolkinolide B in the treatment of gastric cancer by network pharmacology combined with molecular docking technique.Methods The SwissTargetPrediction database was used to obtain the targets of the active compounds.Search Genecards,OMIM,Drugbank,TTD,and PharmGKB databases to obtain targets for gastric cancer.The intersection between the targets of jolkinolide B and those of gastric cancer was identified pinpoint potential targets for jolkinolide B in treating gastric cancer.The String database was utilized construct a protein-protein interaction(PPI)network.Bioconductor bioinformatics packages with R software was employed conduct Gene Ontology(GO)functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis on the shared targets.This process revealed significant regulatory pathways crucial for jolkinolide B's efficacy in treating gastric cancer.Cytoscape 3.7.1 software was utilized create the core network of"Potential Targets of Triptolide B in Gastric Cancer Treatment",and SYBYL-X2.1.1 software was employed conduct molecular docking validation of the selected main active ingredients and critical targets.Results Jolkinolide B may target multiple proteins,including MAPK1,glycogen synthase kinae-3β(GSK-3β),and JUN,impacting the proliferation,invasion,and metastasis of gastric cancer,ultimately inhibiting its growth.Conclusion We predicted the possible molecular mechanism of jolkinolide B in the treatment of gastric cancer to provide guide information for the subsequent experimental research and clinical application.

Objective To explore the mechanism of cinobufagin(CBG)in treating gastric cancer based on network pharmacology combined with bioinformatics and molecular docking technology.Methods Active ingredients and potential targets of CBG in treating gastric cancer were collected from PubChem,TCMSP,and SwissTargetPrediction databases.Transcriptional data of gastric cancer samples were obtained from TGGA database,and gastric cancer-related targets were identified through differential gene analysis.Intersection of targets between CBG and gastric cancer diseases was subjected to Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis.Protein-protein interaction(PPI)network of common targets was constructed using STRING database,and core targets were selected using Cytoscape software.Molecular docking verification of core targets screened with SYBYL-X 2.1.1 software was conducted with CBG.Results CBG treatment of gastric cancer involved 59 targets,with 19 key targets identified.Key targets such as aurora kinase A(AURKA),cyclin-dependent kinase 1(CDK1),enhancer of zeste homolog 2(EZH2),hepatocyte growth factor receptor(MET),matrix metallopeptidase 3(MMP-3),progesterone receptor(PGR),prostaglandin-endoperoxide synthase 1(PTGS1),and thymidylate synthase(TYMS)which exhibited good binding activity with CBG and were closely associated with gastric cancer prognosis.Conclusion CBG may exert anti-gastric cancer effects through multiple targets and pathways.

Objective:To establish a quality and safety evaluation index system for the daytime chemotherapy in the Day Medical Management Quality Control Center of Fujian Province, providing references for objectively evaluating the quality of day chemotherapy.Methods:From December 2023 to August 2024, this study screened the initial indexes of the quality and safety evaluation index system for daytime chemotherapy through literature search and expert discussions. An index system and its weights were determined by using two rounds of Delphi method and precedence chart method. The quality of daytime chemotherapy services in 8 hospitals was evaluated by using a thousand point scale checklist based on this index system.Results:The expert motivation of both rounds of Delphi method was 100%, and the expert authority coefficient was 0.92. The quality and safety evaluation index system for daytime chemotherapy included 3 first-level indicators, 13 second-level indicators, and 54 third-level indicators; Among them, the weights of the first-level indicator included structure quality, process quality, and result quality were 0.334, 0.556, and 0.110, respectively. The quality and safety scores of daytime chemotherapy in 8 hospitals ranged from 812 to 980 points, with an average of 933 points.Conclusions:The quality and safety evaluation index system for daytime chemotherapy could objectively and comprehensively evaluate the quality and safety of hospital daytime chemotherapy.

Aim To investigate the therapeutic effects of a newly developed Tadalafil tablets on pathological myocardial hypertrophy induced by abdominal aortic constriction(AAC)in rats,as well as its influence on the activation of the NF-κB signaling pathway in myo-cardial cells.Methods SD rats were randomly divid-ed into 4 groups:the sham operation group(Sham),the model group(AAC),the tadalafil new tablet treat-ment group(N-Tad,5 mg·kg-1),and the positive control drug treatment group(Cialis,10 mg·kg-1g).The AAC model group and treatment group rats under-went blunt dissection and constrictive ligation of the abdominal aorta at the left renal artery branch point during surgery,while the Sham group rats only had their arteries separated without any constrictive liga-tion.Rats in the treatment groups received either N-Tad or Cialis via gavage three days after modeling,while rats in the sham group and the model group re-ceived physiological saline daily for 8 weeks.Small an-imal ultra-high-resolution echocardiography and hemo-dynamic assessment were applied to evaluate left ven-tricular function in each group of rats,and the calcula-tion of the left ventricular mass index was conducted.By employing Western blot and RT-PCR.we assessed the impact of this treatment on the expression of the hy-pertrophy factor atrial natriuretic peptide(ANP),phosphorylated NF-κB p65 protein(p-NF-κB p65),and phosphorylated IκB-α in the left heart tissue of rats and in H9c2 cardiomyocytes.Results Compared to the Sham group,the AAC rats exhibited a significant decrease in left heart function,an increase in left ven-tricular mass index,and a notable increase in ANP and p-p65 expression in the left heart tissue(P＜0.05).Both N-Tad and Cialis treatments could significantly enhance left ventricular function,decrease left ventric-ular mass index,and inhibit the expression of ANP and phosphorylated NF-κB p65 in rats with myocardial hy-pertrophy(P＜0.05).Notably,the therapeutic effect of low-dose N-Tad was comparable to that of high-dose Cialis.At the cellular level,Tadalafil significantly in-hibited the activation of the NF-κB signaling pathway and reduced the expression of associated proteins in H9c2 cardiomyocytes.Conclusions N-Tad can sig-nificantly inhibit p65 and IκB-α phosphorylation,and the activation of the NF-κB signaling pathway,reduce ANP expression,and improve pathological myocardial hypertrophy,as well as mitigate left heart function damage caused by abdominal aortic constriction.

Objective:To evaluate the application value of artificial intelligence (AI) and robot of stereotactic surgery (ROSS)-assisted ultra-early thalamic hematoma drainage in elderly patients with minor thalamus and internal capsule hematoma (TICH) and severe hypoperfusion in the internal capsule area.Methods:A retrospective cross-sectional study was performed; 278 patients with TICH and severe hypoperfusion in the internal capsule area identified by AI medical imaging diagnostic system were enrolled from Department of Neurosurgery, Xingtai Central Hospital from January 2023 to August 2024. Among them, 134 patients (study group) received AI and ROSS-assisted ultra-early thalamic hematoma drainage, and 144 patients (control group) received drug treatment. Differences in baseline data and therapy efficiency between the two groups of patients were compared. Multivariate Logistic regression analysis was used to screen the independent influencing factors for prognosis in the study group 180 days after onset (good prognosis: modified Rankin scale scores of 0-3).Results:Compared with the control group, the study group had significantly higher Glasgow coma scale (GCS) score and regional cerebral blood flow (rCBF) in the internal capsule area 14 days after onset, and statistically higher therapy efficiency and good prognosis rate 180 days after onset ( P<0.05). In the study group, 84 patients had a good prognosis and 50 had a poor prognosis 180 days after onset; compared with the good prognosis group, the poor prognosis group had significantly higher proportion of patients with hyper-homocysteinemia history, lower GCS score on admission, larger volume of thalamic hematoma, higher proportions of patients with combined intraventricular hemorrhage and shunt-dependent hydrocephalus, and lower rCBF in the internal capsule area on admission ( P<0.05). Multivariate Logistic regression analysis showed that thalamic hematoma volume ( OR=2.527, 95% CI: 1.504-4.247, P<0.001), combined intraventricular hemorrhage ( OR=2.325, 95% CI: 1.460-3.703, P<0.001), shunt dependent hydrocephalus ( OR=2.371, 95% CI: 1.267-4.078, P=0.006), and rCBF in the internal capsule area on admission ( OR=0.672, 95% CI: 0.314-1.025, P<0.001) were independent risk factors for prognosis of patients in the study group. Conclusion:AI and ROSS-assisted ultra-early thalamic hematoma drainage is effective for elderly patients with minor TICH and severe hypoperfusion in the internal capsule area; patients with large thalamic hematoma volume, combined intraventricular hemorrhage, shunt-dependent hydrocephalus, and low rCBF in the internal capsule area on admission are prone to have a poor prognosis.