ObjectiveTo observe the clinical efficacy of Anshen Buxin Gao in patients with coronary artery disease （CAD） complicated with somatization disorder after percutaneous coronary intervention （PCI）， as well as its effect on heart rate variability （HRV）. MethodsA total of 96 patients with somatization disorder after PCI were selected and randomized into control and treatment groups （48 cases）. On the basis of standardized Western medical treatment for CAD， the control group received Dailixin， while the treatment group received Dailixin combined with Anshen Buxin Gao. The somatic symptom scale （SSS）， generalized anxiety disorder 7-item scale （GAD-7）， patient health questionnaire-9 （PHQ-9）， and self-rating scale of sleep （SRSS） scores in both groups were recorded before and after treatment. The traditional Chinese medicine symptom efficacy， HRV， and incidence of adverse drug reactions were observed. ResultsA total of 90 patients completed the trial， encompassing 45 patients in the control group and 45 patients in the treatment group. Baseline characteristics between the two groups showed no statistically significant differences， indicating comparability. After treatment， both groups exhibited reductions in SSS， GAD-7， and PHQ-9 scores （P<0.05）， and the treatment group outperformed the control group in alleviating somatic symptoms and anxiety-depression symptoms （P<0.05）. The control group did not achieve a significant reduction in SRSS score， whereas the treatment group effectively lowered the SRSS score （P<0.05）. Regarding traditional Chinese medicine symptom efficacy， the total response rate in the treatment group was 91.1% （41/45）， which was higher than that （71.1%， 32/45） in the control group （Z=-2.663， P<0.05）. Both groups improved HRV in patients with somatization disorder， and the treatment group showed greater improvement （P<0.05）. There were no serious clinical adverse events during the study period. The incidence of adverse reactions in the treatment group was 6.7% （3/45）， which was lower than that （14/45， 31.10%） in the control group （χ²=7.252， P<0.05）. ConclusionThe addition of Anshen Buxin Gao to Dailixin therapy significantly alleviates the clinical symptoms and improves the sleep quality， treatment efficacy， and HRV in patients with CAD complicated with somatization disorder after PCI， while reducing the adverse effects associated with Dailixin alone. This approach demonstrates considerable clinical value and warrants further promotion.

Objective:To construct a nomogram model for predicting the risk factors of gastrointestinal bleeding following laparoscopic pancreaticoduodenectomy (LPD) based on relevant risk factors and evaluate its predictive value.Methods:A retrospective analysis was conducted on 466 patients with periampullary space occupying lesion who underwent LPD at the Department of Hepatobiliary Surgery, the Second Hospital of Hebei Medical University, from January 2021 to December 2024. Among them, there were 284 males and 182 females, aged (59.9±10.7) years. Patients were randomly divided into a training cohort ( n=326) and a validation cohort ( n=140) using a random number table (7: 3 ratio). Based on whether patients suffered gastrointestinal bleeding, the training cohort was further stratified into a gastrointestinal bleeding group ( n=23) and control group ( n=303). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for gastrointestinal bleeding. A nomogram was constructed based on multivariate results, and its predictive performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results:Compared to the control group, the gastrointestinal bleeding group exhibited significantly higher age, higher rates of postoperative pancreatic fistula (POPF) and intra-abdominal infection, along with lower body mass index, and lower levels of fibrinogen and albumin (all P<0.05). Multivariate analysis identified age ( OR=1.065, 95% CI: 1.002-1.132), fibrinogen ( OR=0.486, 95% CI: 0.243-0.969), albumin ( OR=0.840, 95% CI: 0.741-0.953), POPF ( OR=4.299, 95% CI: 1.348-13.716), and postoperative intra-abdominal infection ( OR=6.352, 95% CI: 1.476-27.341) as independent predictors of gastrointestinal bleeding (all P<0.05). The nomogram demonstrated robust discrimination, with an AUC of 0.861 (95% CI: 0.784-0.939), sensitivity of 82.6%, and specificity of 82.2% in the training cohort. In the validation cohort, the AUC was 0.824 (95% CI: 0.675-0.973), with sensitivity and specificity of 80.0% and 83.8%, respectively. Calibration curves indicated excellent agreement between predicted and observed outcomes. DCA revealed superior net clinical benefit of the nomogram over " treat-all" or " treat-none" strategies within threshold probabilities of 0-0.9 (training) and 0-0.75 (validation). Conclusion:The nomogram based on age, fibrinogen, albumin, POPF, and intra-abdominal infection provides accurate prediction of gastrointestinal bleeding after LPD and demonstrates high clinical utility for risk stratification and decision-making in periampullary space occupying lesion patients.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Objective:To construct a nomogram model for predicting the risk factors of gastrointestinal bleeding following laparoscopic pancreaticoduodenectomy (LPD) based on relevant risk factors and evaluate its predictive value.Methods:A retrospective analysis was conducted on 466 patients with periampullary space occupying lesion who underwent LPD at the Department of Hepatobiliary Surgery, the Second Hospital of Hebei Medical University, from January 2021 to December 2024. Among them, there were 284 males and 182 females, aged (59.9±10.7) years. Patients were randomly divided into a training cohort ( n=326) and a validation cohort ( n=140) using a random number table (7: 3 ratio). Based on whether patients suffered gastrointestinal bleeding, the training cohort was further stratified into a gastrointestinal bleeding group ( n=23) and control group ( n=303). Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for gastrointestinal bleeding. A nomogram was constructed based on multivariate results, and its predictive performance was evaluated by receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results:Compared to the control group, the gastrointestinal bleeding group exhibited significantly higher age, higher rates of postoperative pancreatic fistula (POPF) and intra-abdominal infection, along with lower body mass index, and lower levels of fibrinogen and albumin (all P<0.05). Multivariate analysis identified age ( OR=1.065, 95% CI: 1.002-1.132), fibrinogen ( OR=0.486, 95% CI: 0.243-0.969), albumin ( OR=0.840, 95% CI: 0.741-0.953), POPF ( OR=4.299, 95% CI: 1.348-13.716), and postoperative intra-abdominal infection ( OR=6.352, 95% CI: 1.476-27.341) as independent predictors of gastrointestinal bleeding (all P<0.05). The nomogram demonstrated robust discrimination, with an AUC of 0.861 (95% CI: 0.784-0.939), sensitivity of 82.6%, and specificity of 82.2% in the training cohort. In the validation cohort, the AUC was 0.824 (95% CI: 0.675-0.973), with sensitivity and specificity of 80.0% and 83.8%, respectively. Calibration curves indicated excellent agreement between predicted and observed outcomes. DCA revealed superior net clinical benefit of the nomogram over " treat-all" or " treat-none" strategies within threshold probabilities of 0-0.9 (training) and 0-0.75 (validation). Conclusion:The nomogram based on age, fibrinogen, albumin, POPF, and intra-abdominal infection provides accurate prediction of gastrointestinal bleeding after LPD and demonstrates high clinical utility for risk stratification and decision-making in periampullary space occupying lesion patients.

Public hospitals play a dominant role in providing medical services.Meanwhile,they are also critical for un-dertaking missions to handle health emergencies.This paper analyzes the necessity,current situation,and existing weaknesses of the health emergency capacity of public hospitals.It also conducts a comparative study of the emergency response mechanisms of foreign medical institutions.This paper aims to explore a well-developed design for health emergency in public hospitals that is suitable for China's medical conditions and to provide a feasible model for promoting high-quality health emergency management.

Objective To analyze the effects of target volume optimization on oral mucosal reaction and salivary gland function in oropharyngeal cancer patients receiving intensity-modulated radiotherapy(IMRT).Methods A total of 120 patients with oropharyngeal cancer admitted to Affiliated Hospital of Jiangsu University from April 2020 to August 2022 were selected and randomly grouped into control group(n=60,conventional IMRT)and treatment group(n=60,cervical region Ⅱ and the oral target region were optimized during IMRT).The therapeutic efficacy,parotid gland dose,incidence of acute oral mucosal reaction,dry mouth and oral pain at 3 months after IMRT were compared between two groups.The resting-state apparent diffusion coefficient(ADC)values of parotid and submandibular glands at different time points(before radiotherapy,the 4th week of radiotherapy,the end of radiotherapy and 3 months after radiotherapy)were recorded.Results The difference in the objective reaction rate between two groups was trivial[80.00％(48/60)vs 75.00％(45/60),P>0.05].The mean dose(Dmean)and V34 of the unaffected parotid gland and the Dmean and V30 of the oral cavity in treatment group were lower than those in control group(P<0.05).The incidences of acute oral mucosal reaction,dry mouth and oral pain at 3 months after radiotherapy in treatment group were 41.67％,50.00％,and 58.33％,lower than those in control group(75.00％,78.33％,and 85.00％)(P<0.05).The resting-state ADC values of parotid and submandibular glands at the 4th week of radiotherapy,the end of radiotherapy,and 3 months after radiotherapy in both two groups were higher than those before radiotherapy(P<0.05).At the 4th week of radiotherapy,the end of radiotherapy,and 3 months after radiotherapy,the resting-state ADC values of parotid and submandibular glands in treatment group were lower than those in control group(P<0.05).Conclusion Optimizing target volume during oropharyngeal IMRT can effectively prevent the occurrence of radiation-induced mucositis,alleviate oral mucosal reaction,oral pain and dry mouth,reduce parotid gland dose,and diminish the effects of IMRT on salivary gland function in patients.

Objective To explore the feasibility and diagnostic value of ultra-fast scanning scheme based on deep learning-based reconstruction(DLR)for cervical MR examination.Methods Thirty-six subjects were prospectively enrolled and underwent both conventional scheme(scan time:6 min 14 s)and ultra-fast scheme(2 min)cervical spine MR scanning to acquire encompassing sagittal T1WI,sagittal adipose suppression T2WI and axial T2WI.The ultra-fast MRI were reconstructed using DLR method.The subjective and objective evaluations on imaging qualities of different MRIs were compared,along with the inter-observer agreement for diagnosing intervertebral disc degeneration and herniation.Results Compared with conventional MRI,artifacts in ultra-fast DLR images significantly reduced(P＜0.05).The subjective evaluation results of MRI had good agreement(all Kappa≥0.60).Compared with conventional MRI,the sagittal T1WI,T2WI and axial T2WI obtained with ultra-fast DLR showed significantly improved signal-to-noise ratio(SNR)of the spinal cord,cerebrospinal fluid(CSF)and vertebral body,as well as the spinal cord/CSF contrast(all P＜0.001).The Kappa value of 2 physicians for diagnosing intervertebral disc degeneration based on ultra-fast DLR and conventional scheme images was 0.94 and 1.00,respectively,of intervertebral disc herniation was 0.96 and 0.98,respectively.Conclusion Compared with conventional scanning scheme,using ultra-fast DLR scheme in cervical MR examination could shorten scanning time while achieve similar image quality and diagnostic accuracy.

OBJECTIVE: To investigate the expression of four-jointed box kinase 1 (FJX1) in gastric cancer (GC), its correlation with survival outcomes of the patients, and its role in GC progression. METHODS: The expression level of FJX1 in GC tissues and normal gastric mucosal tissues and its correlation with the survival outcomes of GC patients were analyzed using TCGA and GEO database GC cohort. Immunohistochemistry was used to detect FJX1 expression level in clinical specimens of GC tissue, and its correlations with the patients' clinicopathological parameters and prognosis were analyzed. Bioinformatic analysis was performed to identify the potential pathways of FJX1 in GC. The effects of FJX1 overexpression or FJX1 silencing on GC cell proliferation and expressions of proliferation-related proteins, PI3K, AKT, p-PI3K, and p-AKT were evaluated using CCK-8 assay and Western blotting. The effect of FJX1 overexpression on GC cell tumorigenicity was evaluated in nude mice. RESULTS: GC tissues showed significantly higher expressions of FJX1 mRNA and protein compared with normal gastric mucosa tissues (P < 0.05). The high expression of FJX1 was associated with poor prognosis of GC patients (P < 0.05) and served as an independent risk factor for poor survival outcomes in GC (P < 0.05). FJX1 was expressed mainly in the cytoplasm of GC cells in positive correlation with Ki67 expression (R=0.34, P < 0.05), and was correlated with CA199 levels, depth of tumor infiltration and lymph node metastasis of GC (P < 0.05). In the cell experiment, FJX1 level was shown to regulate the expressions of Ki67 and PCNA and GC cell proliferation (P < 0.05). Gene set enrichment analysis indicated that the PI3K/AKT pathway potentially mediated the effect of FJX1, which regulated the expressions of PI3K and AKT and their phosphorylated proteins. In nude mice, FJX1 overexpression in GC cells significantly promoted the growth of the transplanted tumors (P < 0.05). CONCLUSION FJX1 is highly expressed in GC tissues and is correlated with poor prognosis of GC patients. FJX1 overexpression promotes GC cell proliferation through the PI3K/AKT signaling pathway, and may serve as a potential prognostic biomarker and therapeutic target for GC.
Animals ; Mice ; Cell Proliferation ; Ki-67 Antigen ; Mice, Nude ; Phosphatidylinositol 3-Kinases ; Proto-Oncogene Proteins c-akt ; Signal Transduction ; Stomach Neoplasms/pathology* ; Humans ; Intercellular Signaling Peptides and Proteins/genetics*

OBJECTIVE: To investigate the prognostic value of death-associated protein 5 (DAP5) in gastric cancer (GC) and its regulatory effect on aerobic glycolysis in GC cells. METHODS: We analyzed DAP5 expression levels in GC and adjacent tissues and its association with survival outcomes of GC patients using public databases. We collected paired samples of GC and adjacent tissues from 102 patients undergoing radical resection of GC in our hospital from June, 2012 to July, 2017, and analyzed the correlation of DAP5 expression level detected immunohistochemically with the clinicopathological parameters of the patients. Cox regression analysis, Kaplan-Meier analysis, and ROC curves were used to explore the independent risk factors and the predictive value of DAP5 expression for 5-year survival of the patients. In the cell experiments, we observed the changes in aerobic glycolysis in MGC-803 cells following lentivirus-mediated DAP5 knockdown or overexpression by measuring glucose uptake and cellular lactate level and using qRT-PCR and Western blotting. RESULTS: Analysis using the public databases showed that DAP5 was highly expressed in GC and correlated with tumor progression and poor survival outcomes of the patients (P < 0.05). In the clinical samples, DAP5 expression was significantly higher in GC than in the adjacent tissues (3.19±0.60 vs 1.00±0.12; t=36.863, P < 0.01), and a high expression of DAP5 was associated with a reduced 5-year survival rate of the patients (17.6% vs 72.5%; χ²=29.921, P < 0.05). A high DAP5 expression, T3-4, N2-3, and CEA≥5 ng/mL were identified as independent risk factors affecting 5-year survival outcomes of GC (P < 0.05), for which DAP5 expression showed a prediction sensitivity, specificity and accuracy of 73.2%, 80.4% and 79.0%, respectively. In MGC-803 cells, DAP5 knockdown significantly reduced glucose uptake, lactate level and the expressions of GLUT1, HK2 and LDHA, and DAP5 overexpression produced the opposite effects (P < 0.05). CONCLUSION A high expression of DAP5 in GC, which enhances cellular aerobic glycolysis to promote cancer progression, is correlated with a poor survival outcome and may serve as a biomarker for evaluating long-term prognosis of GC patients.
Humans ; Stomach Neoplasms ; Blotting, Western ; Databases, Factual ; Glucose ; Lactates