American journal of translational research最新文献

{"title":"Celastrol protects against diabetic nephropathy by modulating immune-related pathways: a bioinformatics and experimental validation.","authors":"Xiaojuan Wang, Mohamad Hafizi Abu Bakar, Mohd Asyraf Kassim, Khairul Anuar Shariff, Libing An, Yan Qin","doi":"10.62347/CBIP6642","DOIUrl":"10.62347/CBIP6642","url":null,"abstract":"<p><strong>Objectives: </strong>Celastrol has shown therapeutic effects in diabetic nephropathy (DN). This study aimed to elucidate its underlying mechanisms through bioinformatics analysis and experimental validation.</p><p><strong>Methods: </strong>Differentially expressed genes (DEGs) between DN and control groups were obtained from GSE30122 and GSE30528 datasets. Target genes of Celastrol were collected from relevant biological databases and intersected with the DEGs. Functional enrichment analysis was conducted to explore the associated biological processes. Immune cell infiltration in DN was analyzed, and a Lasso regression model was constructed to identify DN-associated gene markers with diagnostic potential. The binding affinity of celastrol to target proteins was evaluated using molecular docking. Additionally, high glucose (HG)-treated human kidney 2 (HK-2) cells were subjected to cell viability assays, flow cytometry, ELISA, and immunoblotting.</p><p><strong>Results: </strong>A total of 69 key target genes of celastrol were identified, primarily involved in oxidative stress, inflammation, and Phosphoinositide 3-Kinase (PI3K)/Protein Kinase B (Akt) signaling pathways. Immune cell infiltration analysis revealed significant differences in CD4⁺ and CD8⁺ T cell infiltration between the DN and control groups. Six key target genes were identified as strong diagnostic markers for DN, exhibiting high diagnostic accuracy. Molecular docking results revealed strong binding affinity between celastrol and three target proteins: Thrombospondin 2 (THBS2), membrane-associated guanylate kinase inverted 2 (MAGI2), and Fibroblast Growth Factor 9 (FGF9). <i>In vitro</i>, celastrol mitigated HG-induced damage in HK-2 cells, downregulating THBS2 expression while upregulating MAGI2 and FGF9 expression.</p><p><strong>Conclusion: </strong>Celastrol exerts protective effects on DN by modulating key molecular pathways, particularly those involved in inflammation and oxidative stress.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2467-2483"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082535/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A predictive model discloses independent risk factors for vascular complications in elderly cerebrovascular accident patients after trans-radial access cerebral angiography.","authors":"Yao Wang, Lingli Yang, Xin Li, Bei Gu","doi":"10.62347/DYLC6571","DOIUrl":"10.62347/DYLC6571","url":null,"abstract":"<p><strong>Objective: </strong>To identify the risk factors for vascular complications after total cerebral angiography by trans-radial access (TRA) in elderly cerebrovascular accident (CVA) patients and develop a predictive model.</p><p><strong>Methods: </strong>Data from 248 elderly CVA patients at Lianyungang Affiliated Hospital from December 2021 to March 2024 were retrospectively analyzed. The patients were divided into two groups: complicated (those with vascular complications) and non-complicated (those without vascular complications). Clinical data were collected and analyzed. Risk factors were identified using multifactorial logistic regression.</p><p><strong>Results: </strong>A total of 62 patients experienced vascular complications. Independent risk factors included intraoperative heparin dosage, number of radial artery punctures, timing of surgery, surgical time, mode of pressure hemostasis, duration of pressure hemostasis, and postoperative HAS-BLED (hypertension, abnormal renal/liver function, stroke, bleeding history or predisposition, labile international normalized ratio, elderly, drugs/alcohol concomitantly) score (P<0.05). The nomogram model for predicting complications showed a good Hosmer-Lemeshow fit (χ²=2.099, <i>P</i>=0.978). Receiver operating characteristic analysis revealed an area under the curve of 0.868 [95% confidence interval (CI) (0.800, 0.936)] for the training set and 0.822 [95% CI (0.723, 0.921)] for the validation set. Decision curve analysis showed a net benefit >0 in both sets within certain risk thresholds.</p><p><strong>Conclusions: </strong>Vascular complications following total cerebral angiography by TRA in elderly CVA patients are associated with multiple factors. The nomogram model developed from these risk factors has significant predictive value.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2872-2884"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research progress on the role of Claudin family proteins in mediating blood-brain barrier selective permeability in tumor metastasis.","authors":"Dianfang Wei, Ming Xu, Weitong Cui, Xiaoyu Feng, Lei Wei, Kai Wang, Shuai Li, Shuping Gao","doi":"10.62347/GGGX3909","DOIUrl":"10.62347/GGGX3909","url":null,"abstract":"<p><p>The blood-brain barrier (BBB) serves as a critical protective mechanism for the central nervous system (CNS), controlling the selective passage of molecules between the brain and the bloodstream. Claudin proteins, key components of tight junctions, play a central role in maintaining BBB integrity and regulating its permeability. Recent research has increasingly focused on how Claudins contribute to brain metastasis, where tumor cells alter Claudin expression to breach the BBB and invade brain tissue. While Claudin family such as Claudin-1 and Claudin-5 are essential for maintaining BBB function, their dysregulation in tumor cells facilitates BBB disruption, promoting metastasis. This review explores the dual role of Claudins in tumor progression, detailing how they regulate BBB permeability and enable tumor cells to cross the barrier. Additionally, we discuss the potential of Claudin proteins as therapeutic targets in cancer treatment, offering new insights into mechanisms of brain metastasis.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2411-2421"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082546/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning algorithms for the clinical diagnosis of acute atypical asthma exacerbation.","authors":"Feng Ma, Weihua Zhu, Piping Jiang, Xuelian Bai, Wenya Li","doi":"10.62347/YUOT5902","DOIUrl":"10.62347/YUOT5902","url":null,"abstract":"<p><strong>Objective: </strong>To develop a predictive model for the clinical diagnosis of acute atypical asthma attacks using machine learning algorithms and investigate the risk factors related to the diagnosis of atypical asthma.</p><p><strong>Methods: </strong>This study retrospectively collected data on characteristics, symptoms, general examinations, pulmonary functional tests, and FeNO results of patients in the Aerospace Center Hospital. Five machine learning algorithms (logistic regression, decision tree, random forest, support vector machine, extreme gradient boosting) were employed to select variables for predicting outpatient cases of atypical asthma exacerbation in routine practice. A predictive model for diagnosing atypical asthma exacerbation was then developed, optimized, and subjected to explanatory analysis.</p><p><strong>Results: </strong>After screening, 214 cases were included, with 98 diagnosed with acute exacerbation of atypical asthma and 116 undiagnosed. All patients were randomly assigned into a training set (n=149) or a validation set (n=65) at a ratio of 7:3. The predictive capabilities of five models were evaluated in the validation set. This demonstrated that all models could effectively identify patients with acute exacerbation of atypical asthma; among them, Logistic regression, random forest, and extreme gradient boosting achieved accuracies of 93.1%, and extreme gradient boosting reached 95.4%. The logistic regression model showed the best predictive performance. Model interpretation analysis revealed that FeNO, EOS, FEV1 variability, history of allergic rhinitis, and wheezing during acute attacks were significant risk factors for predicting acute exacerbations of atypical asthma.</p><p><strong>Conclusions: </strong>The application of machine learning methods for variable selection in predicting acute exacerbations of atypical asthma has shown promising results. FeNO, EOS, FEV1 variability, history of allergic rhinitis, and wheezing during acute episodes were crucial predictors of exacerbations.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2916-2926"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082529/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fast track surgery nursing models accelerate physical rehabilitation in perioperative patients undergoing hepatobiliary surgery.","authors":"Ting Zhang, Jianhong Xu, Qianjuan Wang, Jiayun Li","doi":"10.62347/CQCF2993","DOIUrl":"10.62347/CQCF2993","url":null,"abstract":"<p><strong>Objective: </strong>To compare the effects between primary hepatic carcinoma (PHC) patients undergoing laparoscopic partial hepatectomy receiving Fast track surgery (FTS) nursing and traditional nursing, aiming to select an effective nursing intervention plan for such patients.</p><p><strong>Methods: </strong>This study included 84 patients with PHC who underwent laparoscopic partial hepatectomy, randomly divided into an observation group (n42) and a control group (n=42). The observation group received FTS nursing, while the control group received traditional nursing care. Intraoperative and postoperative conditions, serological indicators, and complication rates were compared between the groups.</p><p><strong>Results: </strong>The observation group showed significantly reduced postoperative drainage tube removal time, anal exhaust time, hospitalization expenses, and length of stay (LOS) compared to the control group (all P<0.05). C-reactive protein (CRP), total bilirubin (Tbil), alanine aminotransferase (ALT), and cholinesterase (ChE) levels in the observation group were notably lower than those in the control group on postoperative days 1, 3, and 5 (all P<0.05). No significant difference was found in postoperative complication rates between the observation (14.29%) and control groups (16.67%) (<i>P</i>>0.05).</p><p><strong>Conclusions: </strong>Compared with traditional nursing, FTS nursing effectively reduces inflammation and liver function injury in patients undergoing PHC surgery, shortens LOS, lowers hospitalization expenses, and accelerates physical rehabilitation without increasing postoperative complications.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2976-2983"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082528/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Infection characteristics and risk factors in ovarian cancer patients with concomitant vaginitis.","authors":"Xiaoping Feng, Ping Wu, Fenghua Chen, Li Xing, Yun Zheng, Baomei Shi","doi":"10.62347/UPWG5358","DOIUrl":"10.62347/UPWG5358","url":null,"abstract":"<p><strong>Objective: </strong>To investigate the infection characteristics in ovarian cancer (OC) patients with concomitant vaginitis and identify the risk factors for the patients.</p><p><strong>Methods: </strong>A retrospective analysis was conducted on the clinical data from 100 OC patients treated at the Yiwu Central Hospital from July 2019 to July 2024. Patients were assigned to the infection group (n=34) or non-infection group (n=66) based on the presence of vaginitis. Outcome measures included the infection rate and vaginal microbial characteristics of vaginitis, serum HE4 level, and concentrations of interleukin (IL)-4, IL-6, and IL-10 in vaginal secretions. Multivariate logistic regression analysis was performed to determine the influencing factors for vaginal infection in OC patients. Receiver operator characteristic (ROC) curve analysis was conducted to assess the predictive performance of independent risk factors for the occurrence of vaginal infections in OC patients.</p><p><strong>Results: </strong>Among the 100 OC patients, 34 cases (34%) had concomitant vaginitis. Among the 34 patients, the composition ratio of infection types from most to least common was as follows: 10 patients with vulvovaginal candidiasis (29.41%), 8 patients with bacterial vaginosis (23.53%), 7 patients with microbial imbalance (20.59%), 5 patients with mixed infections (14.71%), 3 patients with aerobic vaginitis (8.82%), and 1 patient with trichomonal vaginitis (2.94%). The two groups did not differ notably in HE4 levels (P=0.2366). However, IL-4, IL-6, and IL-10 levels were notably higher in the infection group compared to the non-infection one (P<0.0001). Multivariate logistic regression analysis identified education level, sexual frequency, self-vaginal douching, and history of vaginitis as independent factors influencing vaginal infection in OC patients, and the joint prediction of the vaginal infections with independent factors had an area under curve of 0.858, presenting better performance than a single factor.</p><p><strong>Conclusion: </strong>Vulvovaginal candidiasis is the predominant type of vaginitis in OC patients, followed by BV. Education level, sexual frequency, self-vaginal douching, and a history of vaginitis are independent factors influencing vaginal infection in OC patients.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2927-2936"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082514/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive value of liver and kidney function and bone metabolism markers for postoperative outcomes in diabetic retinal surgery.","authors":"Fang Zhang, Qianqian Zhai, Nana Wang, Zhanhui Zhu","doi":"10.62347/MDVM6037","DOIUrl":"10.62347/MDVM6037","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to explore liver and kidney function as well as bone metabolism in patients undergoing diabetic retinal surgery, and to evaluate their clinical significance in predicting postoperative outcomes.</p><p><strong>Methods: </strong>A total of 150 patients (172 eyes) with proliferative diabetic retinopathy (PDR) who underwent retinal surgery were retrospectively analyzed and categorized into a vitrectomy group (n=78) and a photocoagulation group (n=72). Additionally, 50 healthy adults were included as the control group. Hepatic and renal function parameters, along with bone metabolism markers, were assessed before and after surgery. Logistic regression analysis was employed to evaluate their association with postoperative prognosis, while receiver operating characteristic (ROC) curves were used to assess the predictive performance of key indicators.</p><p><strong>Results: </strong>Compared to the control group, patients with PDR showed significantly elevated levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBIL), urinary albumin-to-creatinine ratio (UACR), serum creatinine (Scr), and serum cystatin C (sCys-C), along with markedly reduced levels of glomerular filtration rate (GFR) and osteocalcin (all P < 0.05). When comparing treatment groups, the vitrectomy group exhibited a significantly higher overall improvement rate than the photocoagulation group (80.00% vs. 37.80%). Moreover, patients in the vitrectomy group demonstrated lower levels of AST, ALT, TBIL, UACR, Scr and sCys-C, and higher levels of GFR and osteocalcin (all <i>P</i><0.05). Among all 150 surgical patients, the incidence of poor prognosis was 46.0%. Logistic regression analysis identified AST, ALT, TBIL, GFR, and surgical type as independent prognostic factors, irrespective of adjustment for confounding variables (<i>P</i><0.05). ROC analysis showed that ALT and TBIL had moderate sensitivity (0.725 and 0.754, respectively), while AST and GFR exhibited high specificity (0.875 and 0.889, respectively) in predicting the prognosis of diabetic retinal surgery.</p><p><strong>Conclusion: </strong>In diabetic patients undergoing retinal surgery, hepatic and renal function, along with bone metabolism, are significantly altered and appear to improve following surgical intervention. Specifically, levels of AST, ALT, TBIL, and GFR are closely associated with postoperative prognosis and may serve as valuable predictors of clinical outcomes.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"3207-3218"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined assessment of placental growth factor, uterine artery pulsation index, and mean arterial pressure for predicting preeclampsia.","authors":"Xiaozhi Wu, Zhaoyu Xu","doi":"10.62347/JHZE8553","DOIUrl":"10.62347/JHZE8553","url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the clinical significance of combined detection of placental growth factor (PLGF), uterine artery pulse index (UTPI), and mean arterial pressure (MAP) in predicting preeclampsia (PE).</p><p><strong>Methods: </strong>A total of 332 pregnant women who underwent regular prenatal check-ups at The Third Affiliated Hospital of Zunyi Medical University (The First People's Hospital of Zunyi) from January 2022 to December 2023 were retrospectively included in this study. Medical histories and laboratory examination data were collected. The participants were divided into a PE group and a normal group based on the occurrence of PE. Clinical data, including MAP, UTPI, and PLGF were recorded between 11 and 13⁺⁶ weeks of pregnancy. A multivariate logistic regression analysis was performed with a significance level of P<0.05 to construct a predictive model for PE. The diagnostic efficacy of the combined MAP + UTPI + PLGF model for early pregnancy PE was assessed using ROC curves. In addition, 182 pregnant women who underwent regular prenatal check-ups in our hospital between February 1, 2023, and December 31, 2024, were selected for external verification.</p><p><strong>Results: </strong>Multivariate logistic regression analysis identified age, body mass index (BMI), pregnancy associated plasma protein-A (PAPP-A), MAP, UTPI, and PLGF as independent predictors of early pregnancy PE (all P<0.05). The AUC values for age, BMI, PAPP-A, MAP, UTPI, and PLGF were 0.660, 0.669, 0.749, 0.869, 0.781, and 0.943, respectively. The AUC of the combined MAP + UTPI + PLGF model was 0.990 (95% CI: 0.938-0.998), with specificity and sensitivity values of 83.98% and 98.80% respectively. Internal validation showed a mean absolute error (MAE) of 0.012, and the consistency index was 0.99 (95% CI: 0.983-0.997). The AUC for external validation of the prediction model was 0.975 (95% CI 0.955-0.995, P<0.001). Bootstrap analysis (1000 repetitions) using the Hosmer-Lemeshow test showed a good model fit (χ²=4.039, P=0.854), with the slope of the calibration curve close to 1.</p><p><strong>Conclusion: </strong>Age, BMI, PAPP-A, MAP, UTPI, and PLGF were all effective predictors for early PE. Furthermore, the combined detection of high-risk factors (MAP, UTPI, PLGF) has a high predictive value for PE early in pregnancy.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"3074-3084"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Factors influencing pathological response after neoadjuvant therapy for advanced gastric cancer.","authors":"Yuanyuan Wang, Xiaoxia Li, Jing Huang, Nianqiu Wu, Chenglu Tang","doi":"10.62347/SKZE1345","DOIUrl":"10.62347/SKZE1345","url":null,"abstract":"<p><strong>Objective: </strong>To identify the factors influencing pathological responses after neoadjuvant therapy in advanced gastric cancer and to construct an effective prediction model for an improved response.</p><p><strong>Methods: </strong>Clinical data from 100 patients with advanced gastric cancer who received neoadjuvant therapy at The Fifth Hospital of Wuhan from January 2020 to December 2023 were retrospectively analyzed. Basic data, laboratory test results, and other patient information were collected. Univariate and multivariate logistic regression were used to analyze the factors influencing good disease recovery after neoadjuvant therapy. Based on the results of multi-factor analysis, a nomogram risk prediction model was constructed, and its effectiveness was validated. The model's discriminatory power was assessed using the receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC), while its fit was evaluated using a calibration curve. The model's consistency was assessed using the Hosmer-Lemeshow (HL) test.</p><p><strong>Results: </strong>Among the 100 patients, 22 (22%) had a good pathological response. Multivariate analysis showed that tumor differentiation, carcinoembryonic antigen (CEA), longest tumor diameter, and cN stage were significant factors influencing the pathological response of patients after neoadjuvant therapy. Based on the above indicators, a nomogram prediction model was constructed, with the following formula: Logit (P) = -1.653 + 1.562 × (tumor differentiation degree) + 1.925 × (CEA) + 1.620 × (longest tumor diameter) + 1.483 × (cN stage). The AUCs of the training set and the test set were 0.884 (95% CI: 0.778-0.990) and 0.861 (95% CI: 0.709-1.000), respectively. The HL test showed good fit (χ² = 4.939, P = 0.764). The calibration curve demonstrated that the predicted values closely matched the observed values.</p><p><strong>Conclusion: </strong>Tumor differentiation, CEA, longest tumor diameter, and cN stage are significant factors influencing the pathological response to neoadjuvant therapy in advanced gastric cancer. The prediction model developed based on these factors demonstrates good predictive performance and may aid in clinical decision-making.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2907-2915"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk factors and predictive model for secondary hypoxemia following transthoracic drainage in traumatic pneumothorax.","authors":"Meng-Ling Tian, Xiao-Yan Wang, Jian-Na Zhang","doi":"10.62347/TLBC2902","DOIUrl":"10.62347/TLBC2902","url":null,"abstract":"<p><strong>Objective: </strong>To analyze the risk factors for secondary hypoxemia in emergency traumatic pneumothorax (TP) patients following transthoracic drainage to provide a scientific basis for clinical prevention and treatment.</p><p><strong>Methods: </strong>This single-center retrospective study included 130 TP patients who underwent chest drainage between January 2021 and May 2024 at West China Hospital, Sichuan University. Patient demographics and clinical data were collected via the electronic medical record system. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for secondary hypoxemia. A predictive model was developed based on multifactorial logistic regression analysis and presented as a Nomogram to assess its discrimination, calibration and clinical utility.</p><p><strong>Results: </strong>Advanced age, high body mass index (BMI), history of smoking, use of conventional drains, and prolonged lung reopening time were identified as independent risk factors for secondary hypoxemia. The constructed Nomogram model demonstrated strong discrimination (AUC=0.92) and calibration (Hosmer-Lemeshow test, P=0.515). Decision curve analysis (DCA) confirmed its clinical application.</p><p><strong>Conclusion: </strong>This study identifies key risk factors for secondary hypoxemia in TP patients after transthoracic drainage and presents a validated predictive model to support clinical decision-making. These findings may help clinicians recognize high-risk patients, implement preventive measures, and reduce hypoxemia incidence, ultimately improving patient outcomes.</p>","PeriodicalId":7731,"journal":{"name":"American journal of translational research","volume":"17 4","pages":"2764-2772"},"PeriodicalIF":1.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12082557/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}