Objective To explore the effect of different needle track management on Yttrium-90 microsphere selective internal radiation therapy (⁹⁰Y-SIRT) on liver cancer after liver biopsy. Methods A retrospective analysis was conducted on the clinical data of 21 patients with liver cancer who underwent Technetium-99m-macroaggregated albumin (^99mTc-MAA) evaluation and ⁹⁰Y-SIRT after liver biopsy from June 2023 to December 2024. The methods of needle track management, hepatic arteriovenous shunting, and lung shunt fraction (LSF) were recorded. The occurrence of hepatic arteriovenous fistula (HAVF), as well as the corresponding countermeasures were analyzed. Results Among the 21 liver cancer patients, 7 cases (medical glue group) underwent embolization of the needle tract with medical glue (N-butyl 2-cyanoacrylate [NBCA]) immediately after biopsy, and no significant HAVF was observed during the ^99mTc-MAA tests; 14 cases (non-medical glue group) were treated with delayed needle extraction or gelatin sponge particle blocking after biopsy, among which 7 cases developed significant HAVF, and the fistulas were treated with NBCA. The LSF of the medical glue group was significantly lower than that of the non-medical glue group ([7.06±2.33] % vs [12.43±7.73] %, P＝0.037). All 21 patients successfully completed ⁹⁰Y-SIRT. Conclusions Liver biopsy may affect ⁹⁰Y-SIRT by causing iatrogenic HAVF. Immediate NBCA-embolization of the needle tract after biopsy or timely NBCA-embolization of fistulas during ^99mTc-MAA tests may reduce the impact.

Objective:To construct a prognostic risk model based on lactate metabolism-related genes screened using bioinformatics methods in renal cell carcinoma patients，and investigate the clinical prognosis and immune characteristics of renal cell carcinoma.Methods:Gene expression data and clinical information of patients with renal cell carcinoma were downloaded from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma（TCGA-KIRC）dataset. Lactate metabolism-related gene sets were obtained from the Gene Set Enrichment Analysis（GSEA）database. The R package DEseq2 was employed to identify differentially expressed genes associated with lactate metabolism within the TCGA-KIRC dataset. GO and KEGG enrichment analyses were performed using the clusterProfiler package. Prognosis-related genes were screened via univariate Cox regression analysis and the intersection with lactate metabolism-related differentially expressed genes was obtained. A risk model was constructed using LASSO regression followed by multivariate Cox regression analysis to calculate risk scores. This risk model was subsequently validated using the GSE29609 dataset. Patients were stratified into high-risk and low-risk groups based on the median risk score. The expression profiles of key immune molecule genes and immune checkpoint genes were compared between the two groups. Survival analysis curves for immune checkpoint genes were generated using the survival and survminer R packages. Differences in tumor mutation burden（TMB）between the high-risk and low-risk groups were assessed，and corresponding TMB survival analysis curves were plotted. Finally，the tumor immune dysfunction and exclusion（TIDE）algorithm was used to evaluate disparities in immunotherapy response potential between the two risk groups.Results:An optimal prognostic risk model incorporating seven lactate metabolism- and prognosis-related genes（ LDHD，PER2，ACADM，FLI1，LIPA，TCIRG1，SLC25A4）was constructed and successfully validated in the GSE29609 dataset. Univariate Cox regression analysis revealed that a high-risk score was significantly associated with poor prognosis（ HR=2.915，95% CI：2.451-3.470， P<0.001）. Multivariate Cox regression analysis confirmed that this risk model could serve as an independent prognostic factor for patients with renal cell carcinoma（ HR=2.231，95% CI：1.829-2.722， P<0.001）. Patients in the high-risk group exhibited significantly worse outcomes compared to the low-risk group，regardless of whether they had early-stage or advanced-stage renal cell carcinoma（both P<0.001）. Analyses related to the immune microenvironment indicated an upregulated immunosuppressive phenotype in the high-risk group. Furthermore，the TMB was significantly higher in the high-risk group than in the low-risk group（ P=0.032），and patients within the high-risk group exhibiting higher TMB levels demonstrated even poorer survival（ P<0.001）. Finally，the TIDE score was significantly elevated in the high-risk group in comparison to the low-risk group（ P<0.001）. Conclusions:The risk model based on lactate metabolism-related genes constructed in this study can guide the prognosis of renal cell carcinoma. Patients in the high-risk group are more prone to immune escape and formation of an inhibitory immune microenvironment，leading to worse prognoses. This risk model may serve as a biomarker for predicting immunotherapy response.

Objective:To explore the distribution of Traditional Chinese Medicine constitution among patients with impaired awareness of hypoglycemia (IAH) and identify risk factors for IAH in patients with diabetes mellitus, to develop a risk prediction model. The aim is to validate the models′ predictive accuracy to facilitate early prevention and treatment of IAH.Methods:A case control study employing convenience sampling model was conducted on 1351 hospitalized patients with diabetes mellitus in the endocrinology departments of Changshu Hospital Affiliated to Nanjing University of Chinese Medicine and Affiliated Hospital of Jiangsu University, between August 2021 and December 2023. Traditional Chinese medicine constitution types were determined using the Traditional Chinese Medicine Constitution Classification and Judgment (ZYYXH/T157-2009). Data were divided into training and test sets at a ratio of 7∶3. Two prediction models were developed: Model 1, a conventional IAH prediction model for patients with diabetes mellitus, and Model 2, an IAH prediction model for patients with diabetes mellitus incorporating traditional Chinese medicine constitution. Nomograms were drawn for both models. The Hosmer-Lemeshow goodness-of-fit test, calibration curve, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were calculated to evaluate the effectiveness of models 1 and 2. The improvement in prediction performance between Models 1 and 2 was assessed using Delong test, AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).Results:The study included 1 283 patients with diabetes mellitus, including 578 males and 705 females, aged (59.61 ± 14.09) years. The incidence of IAH among patients with diabetes mellitus was 20.50% (263/1283), with yang deficiency constitution being the most prevalent traditional Chinese medicine constitution type, at 47.53% (125/263). Multivariate analysis revealed that age, body mass index, course of diabetes, neurological hypoglycemia symptoms, hypoglycemia symptoms and severe hypoglycemia history were the influencing factors of Model 1 (all P<0.05); age, body mass index, neurological hypoglycemic symptoms, hypoglycemic symptoms, history of severe hypoglycemia, and traditional Chinese medicine constitution were the influencing factors of Model 2 (all P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed a good fit of Model 2 [training set ( χ2=8.48, P>0.05), test set ( χ2=3.92, P>0.05)]. The Delong test results showed that the AUC for Model 2 was 0.96 for both the training and test sets, significantly higher than the AUCs of the 0.90 and 0.91 for Model 1 ( Z=-7.27, -3.70, both P<0.01). Furthermore, NRI was 0.66 ( 95%CI 0.53-0.79, P<0.01) and IDI was 0.02 (95% CI 0.01-0.03, P<0.05) for Model 2. Comparative analysis of clinical utility demonstrated that the net benefit of Model 2 for predicting IAH in patients with diabetes mellitus surpassed that of Model 1 across threshold probabilities ranging from 5% to 100%. Conclusions:The study constructed a nomogram prediction model included traditional Chinese medicine constitution with good predictive performance for IAH in patients with diabetes mellitus, and is of significant clinical value for identifying high-risk IAH populations.IAH patients mainly have a biased constitution, indicating that medical staff can reduce the incidence of IAH by improving the patients′ constitution.

Objective:To explore the distribution of Traditional Chinese Medicine constitution among patients with impaired awareness of hypoglycemia (IAH) and identify risk factors for IAH in patients with diabetes mellitus, to develop a risk prediction model. The aim is to validate the models′ predictive accuracy to facilitate early prevention and treatment of IAH.Methods:A case control study employing convenience sampling model was conducted on 1351 hospitalized patients with diabetes mellitus in the endocrinology departments of Changshu Hospital Affiliated to Nanjing University of Chinese Medicine and Affiliated Hospital of Jiangsu University, between August 2021 and December 2023. Traditional Chinese medicine constitution types were determined using the Traditional Chinese Medicine Constitution Classification and Judgment (ZYYXH/T157-2009). Data were divided into training and test sets at a ratio of 7∶3. Two prediction models were developed: Model 1, a conventional IAH prediction model for patients with diabetes mellitus, and Model 2, an IAH prediction model for patients with diabetes mellitus incorporating traditional Chinese medicine constitution. Nomograms were drawn for both models. The Hosmer-Lemeshow goodness-of-fit test, calibration curve, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were calculated to evaluate the effectiveness of models 1 and 2. The improvement in prediction performance between Models 1 and 2 was assessed using Delong test, AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).Results:The study included 1 283 patients with diabetes mellitus, including 578 males and 705 females, aged (59.61 ± 14.09) years. The incidence of IAH among patients with diabetes mellitus was 20.50% (263/1283), with yang deficiency constitution being the most prevalent traditional Chinese medicine constitution type, at 47.53% (125/263). Multivariate analysis revealed that age, body mass index, course of diabetes, neurological hypoglycemia symptoms, hypoglycemia symptoms and severe hypoglycemia history were the influencing factors of Model 1 (all P<0.05); age, body mass index, neurological hypoglycemic symptoms, hypoglycemic symptoms, history of severe hypoglycemia, and traditional Chinese medicine constitution were the influencing factors of Model 2 (all P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed a good fit of Model 2 [training set ( χ2=8.48, P>0.05), test set ( χ2=3.92, P>0.05)]. The Delong test results showed that the AUC for Model 2 was 0.96 for both the training and test sets, significantly higher than the AUCs of the 0.90 and 0.91 for Model 1 ( Z=-7.27, -3.70, both P<0.01). Furthermore, NRI was 0.66 ( 95%CI 0.53-0.79, P<0.01) and IDI was 0.02 (95% CI 0.01-0.03, P<0.05) for Model 2. Comparative analysis of clinical utility demonstrated that the net benefit of Model 2 for predicting IAH in patients with diabetes mellitus surpassed that of Model 1 across threshold probabilities ranging from 5% to 100%. Conclusions:The study constructed a nomogram prediction model included traditional Chinese medicine constitution with good predictive performance for IAH in patients with diabetes mellitus, and is of significant clinical value for identifying high-risk IAH populations.IAH patients mainly have a biased constitution, indicating that medical staff can reduce the incidence of IAH by improving the patients′ constitution.

Objective:To construct a prognostic risk model based on lactate metabolism-related genes screened using bioinformatics methods in renal cell carcinoma patients，and investigate the clinical prognosis and immune characteristics of renal cell carcinoma.Methods:Gene expression data and clinical information of patients with renal cell carcinoma were downloaded from the Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma（TCGA-KIRC）dataset. Lactate metabolism-related gene sets were obtained from the Gene Set Enrichment Analysis（GSEA）database. The R package DEseq2 was employed to identify differentially expressed genes associated with lactate metabolism within the TCGA-KIRC dataset. GO and KEGG enrichment analyses were performed using the clusterProfiler package. Prognosis-related genes were screened via univariate Cox regression analysis and the intersection with lactate metabolism-related differentially expressed genes was obtained. A risk model was constructed using LASSO regression followed by multivariate Cox regression analysis to calculate risk scores. This risk model was subsequently validated using the GSE29609 dataset. Patients were stratified into high-risk and low-risk groups based on the median risk score. The expression profiles of key immune molecule genes and immune checkpoint genes were compared between the two groups. Survival analysis curves for immune checkpoint genes were generated using the survival and survminer R packages. Differences in tumor mutation burden（TMB）between the high-risk and low-risk groups were assessed，and corresponding TMB survival analysis curves were plotted. Finally，the tumor immune dysfunction and exclusion（TIDE）algorithm was used to evaluate disparities in immunotherapy response potential between the two risk groups.Results:An optimal prognostic risk model incorporating seven lactate metabolism- and prognosis-related genes（ LDHD，PER2，ACADM，FLI1，LIPA，TCIRG1，SLC25A4）was constructed and successfully validated in the GSE29609 dataset. Univariate Cox regression analysis revealed that a high-risk score was significantly associated with poor prognosis（ HR=2.915，95% CI：2.451-3.470， P<0.001）. Multivariate Cox regression analysis confirmed that this risk model could serve as an independent prognostic factor for patients with renal cell carcinoma（ HR=2.231，95% CI：1.829-2.722， P<0.001）. Patients in the high-risk group exhibited significantly worse outcomes compared to the low-risk group，regardless of whether they had early-stage or advanced-stage renal cell carcinoma（both P<0.001）. Analyses related to the immune microenvironment indicated an upregulated immunosuppressive phenotype in the high-risk group. Furthermore，the TMB was significantly higher in the high-risk group than in the low-risk group（ P=0.032），and patients within the high-risk group exhibiting higher TMB levels demonstrated even poorer survival（ P<0.001）. Finally，the TIDE score was significantly elevated in the high-risk group in comparison to the low-risk group（ P<0.001）. Conclusions:The risk model based on lactate metabolism-related genes constructed in this study can guide the prognosis of renal cell carcinoma. Patients in the high-risk group are more prone to immune escape and formation of an inhibitory immune microenvironment，leading to worse prognoses. This risk model may serve as a biomarker for predicting immunotherapy response.

Objective To investigate the predictive value of Rotterdam CT score combined with serum soluble cluster of differentiation antigen 40 ligand (sCD40L) and fibulin-5 for prognosis of patients with severe traumatic brain injury (sTBI). Methods A total of 186 sTBI patients were divided into good prognosis group (n=104) and poor prognosis group (n=82). CT images were analyzed and Rotterdam CT scores were obtained; the enzyme-linked immunosorbent assay (ELISA) was used to detect serum sCD40L and fibulin-5 levels on the 1st, 3rd and 7th day of admission; the Spearman analysis was used to assess the correlations of serum sCD40L and fibulin-5 levels on the first day of admission with the Rotterdam CT score and Glasgow Coma Scale (GCS) score; the Multivariate Logistic regression analysis was conducted to explore the risk factors for poor prognosis in sTBI patients; the receiver operating characteristic (ROC) curve was performed to analyze the predictive value of Rotterdam CT score combined with serum sCD40L and fibulin-5 levels on the first day of admission for prognosis of sTBI patients. Results On the 1st, 3rd and 7th day of admission, compared with the good prognosis group, the serum levels of sCD40L and fibulin-5 in the poor prognosis group were significantly elevated (P < 0.05); serum sCD40L and fibulin-5 levels were negatively correlated with GCS scores (r=-0.505, -0.421, P < 0.05) and positively correlated with Rotterdam CT score (r=0.495, 0.397, P < 0.05); sCD40L (OR=2.768, 95%CI, 1.537 to 4.983) and fibulin-5 (OR=2.539, 95%CI, 1.301 to 4.953) were independent risk factors for poor prognosis in sTBI patients (P < 0.001); the area under the curve (AUC) of Rotterdam CT score combined with serum sCD40L and fibulin-5 levels on the first day of admission for predicting poor prognosis in sTBI patients was 0.969 (95%CI, 0.933 to 0.989), with a sensitivity of 86.59% and a specificity of 94.23%; the diagnostic performance of Rotterdam CT score combined with sCD40L and fibulin-5 was superior to that of each individual indicator (Z=4.233, 4.274, 4.433, P < 0.001); the Bootstrap internal validation results showed that the predictive performance curve of the combined prediction model was consistent with the actual clinical occurrence curve. Conclusion Rotterdam CT score combined with serum sCD40L and fibulin-5 has certain predictive value for poor prognosis in sTBI patients.

Objective To explore the changes of serum angiopoietin-like protein 4(ANGPTL4)and NOD-like receptor protein 3(NLRP3)levels after traumatic brain injury(TBI)and their diagnostic value for sec-ondary massive cerebral infarction.Methods A total of 100 TBI patients admitted to the hospital from Au-gust 2019 to August 2021 were enrolled as the TBI group,meantime,100 healthy people in the hospital were enrolled as the control group.The serum levels of ANGPTL4 and NLRP3 were detected by enzyme-linked im-munosorbent assay(ELISA).The clinical characteristics of TBI patients with and without secondary massive cerebral infarction were compared.Receiver operating characteristic(ROC)curve was applied to analyze the serum levels of ANGPTL4 and NLRP3 on their diagnostic value for TBI patients with secondary massive cere-bral infarction.Multivariate Logistic regression analysis was applied to analyze the factors affecting the occur-rence of secondary massive cerebral infarction in TBI patients.Results The serum ANGPTL4 level in TBI group was lower than that in the control group,and the serum NLRP3 level was higher than that in the con-trol group(P<0.05).There were obvious differences in proportion of brain hernia,proportion of subarach-noid hemorrhage,serum levels of ANGPTL4 and NLRP3 between patients with secondary massive cerebral infarction and patients without secondary massive cerebral infarction(P<0.05).ROC curve analysis showed that the area under the curve(AUC)of serum ANGPTL4 and NLRP3 in diagnosing secondary massive cere-bral infarction in TBI patients was 0.792 and 0.812 respectively,with sensitivity of 77.80%and 83.30%re-spectively,and specificity of 86.60%and 64.60%respectively.The sensitivity,the specificity and AUC of the combined detection were 83.30%,82.90%and 0.867 respectively.Multivariate Logistic regression analysis showed that serum NLRP3 level was a risk factor for TBI patients with secondary massive cerebral infarction(P<0.05).After treatment,it was found that serum ANGPTL4 level increased and NLRP3 level decreased in TBI patients(P<0.05).Conclusion The serum level of ANGPTL4 in TBI patients decreases,while the level of NLRP3 increases,and the level of ANGPTL4 in the serum of patients with secondary massive cerebral in-farction decreases and the level of NLRP3 increases,both of them are of great significance in the diagnosis of secondary massive cerebral infarction in TBI patients.

Objective:To preliminarily observe the clinical efficacy of microwave hyperthermia combined with intensity-modulated radiotherapy (IMRT) and chemotherapy for patients with locally advanced gastric cancer.Methods:Forty patients who could not been operated or refused operation were enrolled in this clinical trial, who were confirmed as locally advanced proximal or distal gastric cancer by gastroscopy pathology and imaging. Radiotherapy was delivered by IMRT technology for 5 times per week with a total dose of 46 to 56 Gy (median dose of 50 Gy) in 25 to 28 fractions. Synchronous hyperthermia was given at 42 to 44℃ twice a week, 45 min/time. S-1 or capecitabine-based synchronous chemotherapy was performed, d1-14/3 weeks. The symptom remission rate, adverse reactions, objective remission rate (complete and partial remission) and survival were observed.Results:A total of 40 patients, aged between 56 and 83 years (median age of 71 years), were enrolled in this study. The male-to-female ratio was 7: 1. Among them, 38 cases (95%) showed symptom remission. The most common adverse reactions were grade 1-2 gastrointestinal reactions and leukopenia. The objective remission rate was 87.5%, the 2-year progression-free survival and overall survival rates were 68.6% and 70.5%, respectively.Conclusion:Preliminary findings demonstrate that microwave hyperthermia combined with chemoradiotherapy achieve satisfactory outcomes and yield tolerable toxicity in patients with locally advanced gastric cancer.

Objective:To explore disorienting dilemmas during postgraduate study period experienced by postgraduates with master of nursing specialist who participated in the national postgraduate entrance examination and provide a basis for teaching reform based on transformative learning theory.Methods:Using the purposive sampling method and the maximum difference method, 23 full-time masters of nursing specialist who participated in the national postgraduate entrance examination from 3 universities of Jiangsu Province were selected as the research objects from March to June 2019. The descriptive qualitative research method was used to conduct semi-structured interviews, and the traditional content analysis method was used to analyze the interview data.Results:Four themes of disorienting dilemmas of masters of nursing specialist were extracted: the expected hypothesis of challenges of new environment in course learning, a gap between scientific research ability and training target, adjustment of self-positioning in clinical practice and insufficient preparations for graduation of master of nursing specialist.Conclusions:Master of nursing specialist have disorienting dilemmas in course study, scientific research, clinical practice and graduation preparation, and nursing educators can use this as a trigger point to carry out teaching reform based on transformative learning theory.