Objective To investigate the preoperative prediction of the expression level of programmed cell death ligand 1(PD-L1)in non-small cell lung cancer(NSCLC)by a nomogram model constructed with clinical data,conventional CT signs and spectral CT parameters.Methods A retrospective analysis was conducted on 52 patients with pathologically confirmed NSCLC and undergoing preoperative spectral CT examination.The patients were categorized into positive and negative groups according to PD-L1 expression level,and their clinical data,conventional CT signs and spectral CT parameters were collected.Specifically,clinical data included gender,age,Ki-67 and tumor markers;conventional CT signs included tumor density,margins,calcification,spiculation,lobulation,pleural indentation and cavitation;and spectral CT parameters measured in the arterial and venous phases included effective atomic number(Eff-Z),iodine concentration(IC),water concentration(WC)and normalized iodine concentration(NIC).Intergroup differences were analyzed,and multivariate Logistic regression was used to identify independent predictors and establish the prediction model which was evaluated for prediction performance and accuracy using receiver operating characteristic(ROC)curves,calibration curve and decision curve analyses.Results For clinical data,only the difference in gender between two groups had statistical significance(P<0.05).The spectral CT parameters(IC,NIC and Eff-Z)in the arterial and venous phases of PD-L1 positive group were all greater than those of PD-L1 negative group,with statistically significant differences(P<0.05).Multivariate Logistic regression analysis identified gender(P=0.024),venous-phase Eff-Z(P=0.002),and venous-phase IC(P=0.003)as independent predictive factors for PD-L1 expression.The nomogram prediction model constructed with these independent predictors had an area under curve of 0.80,a sensitivity of 88.00%,and a specificity of 59.00%.The calibration curve showed that the predicted values had a high consistency with the actual values.The decision curve revealed that when the high-risk threshold was between 0.10 and 0.83,the model could achieve the maximum net benefit.Conclusion The nomogram model constructed with spectral CT parameters and clinical data has certain value in predicting the expression level of PD-L1 in NSCLC.

Purpose To evaluate the value of preoperative MRI-based radiomic models for assessing tumor-infiltrating CD8+T-cell expression in glioblastoma patients,and to identify the most stable and efficient radiomic feature region for predicting prognosis following immunotherapy.Materials and Methods This retrospective study included 150 patients with histopathologically confirmed glioblastoma from Lanzhou University Second Hospital(January 2018 to April 2022).Tumor-infiltrating CD8+T-cell expression was quantitatively assessed using immunohistochemical staining,with patients stratified into CD8-high and CD8-low expression groups based on overall survival.A total of 1 185 radiomic features were extracted from each patient's contrast-enhanced T1C and T2WI images,covering the original tumor region and sequentially expanded peritumoral regions(2.5 mm,5.0 mm,7.5 mm,10.0 mm,12.5 mm,15.0 mm morphological dilation of tumor core+peritumoral area).Feature selection was performed using variance threshold,minimum redundancy maximum relevance,and least absolute shrinkage and selection operator methods.XGBoost classifier was employed to construct clinical,radiomic,and clinical-radiomic multimodal combined prediction models.Diagnostic performance was evaluated using receiver operating characteristic curve analysis.Results The radiomic model based on tumor expansion of 7.5 mm(tumor+peritumoral region)demonstrated optimal predictive performance.The clinical-radiomic multimodal combined model showed superior predictive capability compared to clinical and radiomic models alone,achieving an area under the curve of 0.991 and accuracy of 99.0%in the training set,and area under the curve of 0.840 with accuracy of 80.0%in the validation set.Conclusion MRI radiomics provides a feasible approach for evaluating tumor-infiltrating CD8+T-cell expression in glioblastoma patients,offering potential for preoperative prognosis prediction.

Objective:To compare the clinical efficacy of fixed and non-fixed coronoid process fractures in the treatment of terrible triad of the elbow.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, VIP, China Medical Journal Full-text Database, PubMed, Cochrane Library, Scopus and Web of Science were searched for relevant literatures on the treatment of elbow terrible triad. Postoperative elbow function score, range of motion, postoperative complications and other information were extracted, and meta-analysis was performed using Stata 18.0 statistical software.Results:A total of 139 patients from 5 literatures were included in the meta-analysis. All included literatures were in English, and the Newcastle-Ottawa Scale scores were 7-8 points. The results of meta-analysis showed that there was no statistically significant difference in the postoperative Mayo Elbow Performance Score (MEPS) between the two groups [ SMD=-0.33, 95% CI(-0.67, 0.01), P=0.061]. In Regan-Morrey type I and O'Driscoll type I coronoid process fractures, the MEPS of the coronoid fixation group was lower than that of the non-fixation group, and the difference was statistically significant [ SMD=-0.46, 95% CI(-0.88, -0.03), P=0.032]; the upper extremity functional disability score of the coronoid fixation group was higher than that of the non-fixation group, and the difference was statistically significant [ SMD=0.45, 95% CI(0.02, 0.89), P=0.041]. There were no statistically significant differences in the postoperative elbow flexion-extension range [ SMD=-0.31, 95% CI(-0.68, 0.07), P=0.109] and pronation-supination range [ SMD=-0.14, 95% CI(-0.51, 0.24), P=0.470] between the two groups. Conclusion:In the treatment of elbow terrible triad, the postoperative joint function score of non-fixation of Regan-Morrey type I and O'Driscoll type I coronoid process fractures is better than that of fixation.

Objective To develop a nomogram model based on cardiac computed tomography angiography(CCTA)features to evaluate the risk of stroke in patients with persistent atrial fibrillation(PAF).Methods A total of 387 patients with PAF were retrespectively selected.Among them,127 patients had a history of stroke.After collecting patient data,logistic regression analysis was used to screen independent predictors related to stroke outcome,and a nomogram model was constructed.The receiver operating characteristic(ROC)curve was used to analyze and compare the efficacy of the nomogram model and the conventional score for stroke risk assessment.The concordance index(CI)and decision curve analysis(DCA)were used to evaluate the performance of the model.Results Logistic regression analysis showed that age,CHA2DS2-VASc score,smoking history,left atrial appendage(LAA)shape,left atrial volume index(LAVI),LAA fractal dimension(FD)and left atrium(LA)FD were independent predictors of stroke in patients with PAF(P＜0.05).The area under the curve(AUC)of the training set model was 0.886.The AUC of the validation set was 0.763.DCA showed that the nomogram model had better overall net benefits.Conclusion The nomogram model based on CCTA can better evaluate the risk of stroke in patients with PAF,which is helpful for clinicians to make better clinical decisions.

Objective:To evaluate the role of a single PET-CT scan in predicting survival and prognosis in patients with non-small cell lung cancer (NSCLC) who did not undergo surgery but received radiotherapy after neoadjuvant chemotherapy combined with immunotherapy.Methods:A retrospective analysis was conducted on the data of 23 NSCLC patients treated at the Cancer Hospital of the Chinese Academy of Medical Sciences from May 2022 to June 2024. All patients were pathologically confirmed, received neoadjuvant chemotherapy combined with immunotherapy, did not undergo surgery for various reasons, and instead received radiotherapy. Each patient underwent only one PET-CT scan after neoadjuvant chemotherapy combined with immunotherapy and before radiotherapy. According to the maximum standardized uptake value (SUV max) on PET-CT, patients were divided into the low-uptake group (SUV max < 8, n=12) and high-uptake group (SUV max ≥ 8, n=11). Survival analysis was performed using the Kaplan-Meier method with survival curves plotted. Univariate analysis of influencing factors of survival was conducted using the Cox proportional hazards regression model. Clinical characteristics and survival outcomes of the two groups were compared, including progression-free survival (PFS) and overall survival (OS). Results:The 1-year PFS rates were 100% in the low-uptake group, 54.5% in the high-uptake group. This difference was statistically significant ( P=0.007). The 1-year and 2-year OS rates were both 100% in the low-uptake group, the 1-year and 2-year OS rates were both 90.9% in the high-uptake group, with no statistically significant difference ( P=0.394). Univariate Cox analysis identified age as an independent factor affecting PFS. Conclusions:For NSCLC patients who did not undergo surgical resection but received radiotherapy after neoadjuvant chemotherapy combined with immunotherapy, a single PET-CT scan before radiotherapy has potential value in predicting PFS. However, clinical studies with larger sample size and longer follow-up are required to evaluate its predictive value for OS.

Objective:To compare the clinical efficacy of fixed and non-fixed coronoid process fractures in the treatment of terrible triad of the elbow.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, VIP, China Medical Journal Full-text Database, PubMed, Cochrane Library, Scopus and Web of Science were searched for relevant literatures on the treatment of elbow terrible triad. Postoperative elbow function score, range of motion, postoperative complications and other information were extracted, and meta-analysis was performed using Stata 18.0 statistical software.Results:A total of 139 patients from 5 literatures were included in the meta-analysis. All included literatures were in English, and the Newcastle-Ottawa Scale scores were 7-8 points. The results of meta-analysis showed that there was no statistically significant difference in the postoperative Mayo Elbow Performance Score (MEPS) between the two groups [ SMD=-0.33, 95% CI(-0.67, 0.01), P=0.061]. In Regan-Morrey type I and O'Driscoll type I coronoid process fractures, the MEPS of the coronoid fixation group was lower than that of the non-fixation group, and the difference was statistically significant [ SMD=-0.46, 95% CI(-0.88, -0.03), P=0.032]; the upper extremity functional disability score of the coronoid fixation group was higher than that of the non-fixation group, and the difference was statistically significant [ SMD=0.45, 95% CI(0.02, 0.89), P=0.041]. There were no statistically significant differences in the postoperative elbow flexion-extension range [ SMD=-0.31, 95% CI(-0.68, 0.07), P=0.109] and pronation-supination range [ SMD=-0.14, 95% CI(-0.51, 0.24), P=0.470] between the two groups. Conclusion:In the treatment of elbow terrible triad, the postoperative joint function score of non-fixation of Regan-Morrey type I and O'Driscoll type I coronoid process fractures is better than that of fixation.

Colorectal cancer is one of the most common malignant tumors of the digestive system in clinical practice.The early detection of colorectal cancer based on artificial intelligence and its further assistance in clinical diagnosis and treatment hold significant clinical importance for achieving long-term benefits for patients.The development and validation of artificial intelligence software rely on high-quality,large-volume,and annotated colorectal cancer imaging datasets.This paper aims to provide a reference for constructing a high-quality colorectal cancer CT database,taking the construction of the database as an example.It discusses the complete process of database establishment,including database description,lesion annotation and storage,database quality evaluation and maintenance.The purpose is to ensure the high quality and exploitability of the source materials in the database,promote the sustainable and healthy development of the medical imaging artificial intelligence industry ecosystem,and accelerate the research,development,and application of industries related to artificial intelligence in colorectal cancer CT imaging.

Colorectal cancer is one of the most common malignant tumors of the digestive system in clinical practice.The early detection of colorectal cancer based on artificial intelligence and its further assistance in clinical diagnosis and treatment hold significant clinical importance for achieving long-term benefits for patients.The development and validation of artificial intelligence software rely on high-quality,large-volume,and annotated colorectal cancer imaging datasets.This paper aims to provide a reference for constructing a high-quality colorectal cancer CT database,taking the construction of the database as an example.It discusses the complete process of database establishment,including database description,lesion annotation and storage,database quality evaluation and maintenance.The purpose is to ensure the high quality and exploitability of the source materials in the database,promote the sustainable and healthy development of the medical imaging artificial intelligence industry ecosystem,and accelerate the research,development,and application of industries related to artificial intelligence in colorectal cancer CT imaging.

Background The association between occupational physical activity (OPA) and cardiometabolic risk factors remains controversial, potentially due to differences in the associations between OPA and various cardiometabolic indicators, as well as the lack of a clearly defined optimal OPA range for multiple-indicator synergistic benefits. Objective To investigate the relationship between OPA and cardiometabolic risk factors in individuals at high risk of cardiovascular disease (CVD) in Hubei Province, and to explore an optimal OPA range for multi-indicator improvements. Methods Data were derived from the Hubei Province dataset of the China Health Evaluation And Risk Reduction Through Nationwide Teamwork from 2015 to 2023, including 19028 high-risk CVD individuals. OPA (metabolic equivalent·h·d⁻¹, MET·h·d⁻¹) was assessed using the China Kadoorie Biobank physical activity questionnaire, anthropometric measurements (height, weight, waist circumference) and cardiometabolic indicators (blood pressure, fasting blood glucose, lipid profiles) were measured. Multivariate logistic regression was used to analyze the association between logOPA quartiles (Q1-Q4) and abnormal cardiometabolic indicators, while restricted cubic spline (RCS) models were employed to explore their dose-response relationships. Subgroup and interaction analyses were also conducted by gender. Results The median OPA of all participants was 12.86 MET·h·d⁻¹ (male: 14.40 MET·h·d⁻¹, female: 11.14 MET·h·d⁻¹). After adjusting for confounders, compared with the Q1 group, logOPA in the Q4 group was associated with 20% (OR=0.80, 95%CI: 0.72, 0.89), 14% (OR=0.86, 95%CI: 0.78, 0.96), and 13% (OR=0.87, 95%CI: 0.79, 0.95) reduction in the risk of abdominal obesity, low high-density lipoprotein cholesterol (HDL-C), and metabolic syndrome (MS), respectively, and 33% (OR=1.33, 95%CI: 1.18, 1.49), 33% (OR=1.33, 95%CI: 1.18, 1.50), and 38% (OR=1.38, 95%CI: 1.21, 1.57) increase in the risk of high total cholesterol (TC), high low-density lipoprotein cholesterol (LDL-C), and high non-HDL-C, respectively. Similar trends were observed in males and females, with significant positive associations of logOPA with high TC and high non-HDL-C in males (P_interaction<0.05). The risk of low HDL-C decreased rapidly when logOPA was more than 2.213 (OPA>9.14 MET·h·d⁻¹), showing an inverted L-shaped trend. The risk of high TC, high LDL-C, and high non-HDL-C increased beyond logOPA thresholds of 3.244, 2.476, and 3.377 (OPA >25.64, 11.89, and 29.28 MET·h·d⁻¹), respectively, showing a J-shaped trend. However, logOPA exhibited a U-shaped nonlinear dose-response relationship with blood pressure and fasting blood glucose abnormalities (P_non-linear<0.05) , with minimal risks at logOPA 2.969 and 2.372 (OPA of 19.47 and 10.72 MET·h·d⁻¹). Conclusion OPA exhibits heterogeneous dose-response patterns across cardiometabolic indicators. Integrating the inverted L-, J-, and U-shaped association patterns, we suggest an optimal OPA range of 9.14−25.64 MET·h·d⁻¹ for multiple cardiometabolic indicators in total individuals at high-risk of CVD, with ranges of 9.61−31.34 MET·h·d⁻¹ for males and 8.97−22.87 MET·h·d⁻¹ for females. These findings provide critical evidence for developing OPA interventions strategies targeting high-risk population for CVD.

Elemene is widely recognized as an effective anti-cancer compound and is routinely administered in Chinese clinical settings for the management of several solid tumors,including non-small cell lung cancer(NSCLC).However,its detailed molecular mechanism has not been adequately demonstrated.In this research,it was demonstrated that elemene effectively curtailed NSCLC growth in the patient-derived xenograft(PDX)model.Mechanistically,employing high-throughput screening techniques and subsequent biochemical validations such as microscale thermophoresis(MST),microRNA-145-5p(miR-145-5p)was pinpointed as a critical target through which elemene exerts its anti-tumor effects.Inter-estingly,elemene serves as a binding stabilizer for miR-145-5p,demonstrating a strong binding affinity(dissociation constant(KD)=0.39±0.17 μg/mL)and preventing its degradation both in vitro and in vivo,while not interfering with the synthesis of the primary microRNA transcripts(pri-miRNAs)and precursor miRNAs(pre-miRNAs).The stabilization of miR-145-5p by elemene resulted in an increased level of this miRNA,subsequently suppressing NSCLC progression through the miR-145-5p/mitogen-activated pro-tein kinase kinase kinase 3(MAP3K3)/nuclear factor kappaB(NF-κB)pathway.Our findings provide a new perspective on revealing the interaction patterns between clinical anti-tumor drugs and miRNAs.