Objective To develop a predictive model for postoperative pulmonary complications (PPC) following video-assisted thoracic surgery (VATS) in lung cancer patients by integrating cardiopulmonary exercise testing (CPET) parameters and machine learning techniques. Methods A retrospective analysis was conducted on patients with early-stage non-small cell lung cancer who underwent CPET and VATS at Guangdong Provincial People’s Hospital between October 2021 and July 2023. Patients were divided into a PPC group and a non-PPC group. The least absolute shrinkage and selection operator (LASSO) regression was used to select important features associated with PPC. Six machine learning algorithms were utilized to construct prediction models, including logistic regression, support vector machine, k-nearest neighbors, random forest, gradient boosting machine, and extreme gradient boosting. The optimal model was interpreted using SHapley Additive exPlanations (SHAP). Results A total of 325 patients were included, with an average age of 60.36 years, and 55.1% were male. Significant differences were observed between the PPC and non-PPC groups in age, diabetes, coronary heart disease, surgical approach, forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FVC% predicted, peak oxygen uptake (peak VO2), anaerobic threshold (AT), and ventilatory equivalent for carbon dioxide slope (VE/VCO2 slope) (P<0.05). In the predictive model constructed by selecting 7 key features using LASSO regression, the random forest model demonstrated the best overall performance across various metrics, with an area under the receiver operating curve of 0.930, an F1 score of 0.836, and a Brier score of 0.133 in the training set. It also exhibited good predictive ability and calibration in the test set. SHAP analysis ranked feature importance as follows: peak VO2, VE/VCO2 slope, age, FEV1, smoking history, diabetes, and surgical approach. Conclusion Integrating CPET parameters, the random forest model can effectively identify high-risk patients for PPC and has the potential for clinical application.

Objective:To construct pancreatic cancer cell lines expressing luciferase and mesothelin (MSLN), and evaluate the feasibility of using them as target cells in analyzing the cytotoxicity activity of immune cells.Methods:Lentiviral vectors expressing luciferase and MSLN genes were constructed, and pancreatic cancer cell lines were infected after lentivirus packaging. Single-cell clones were obtained by limited dilution following antibiotic screening, and the stable expression of the target genes were verified. These cells were used as target cells to detect the cytotoxicity of immune cells by real-time cell analysis (RTCA) and luciferase activity. Besides, these luciferase-expressing cells were transplanted into B-NDG mice to establish the animal models of pancreatic cancer, and in vivo optical imaging technology was used to detect the expression of luciferase and monitor the tumor growth in mice. The cytotoxicity of chimeric antigen receptor T (CAR-T) cells was verified in these animal models. Results:Three pancreatic cancer cell lines, panc-1-luc, panc-1-luc-MSLN and capan-2-luc, that could stably express luciferase and MSLN genes were successfully constructed. The expression of the reporter gene in these cells were high, and positively correlated with the number of cells. There were 95.6% of panc-1-luc-MSLN cells expressing MSLN. MSLN-CAR-T cells had specific killing effect on MSLN-positive panc-1-luc-MSLN cells and capan-2-luc cells, with the minimum killing rates of (70.00±18.19)% and (57.00±5.29)%, respectively. But they had no cytotoxicity to MSLN-negative panc-1-luc cells. RTCA results showed that MSLN-CAR-T cells were able to lyse all three pancreatic cancer cell lines, and the minimum killing rates were (56.33±7.64)%, (93.00±2.65)% and (26.33±28.15)%, respectively. The killing of target cells by NK-92MI cells was not depended on MSLN expression. The cytotoxicity in the mice models of pancreatic cancer was consistent with the results in vitro. The in vivo and in vitro test results suggested that the expression of luciferase by target cells could reflect the cytotoxicity of immune cells. Conclusions:This study establishes three pancreatic cancer cell lines stably expressing luciferase, which can be used to evaluate the cytotoxicity of immunotherapy products targeting tumor cells in vitro and in vivo.

Objective To evaluate the manifestations and diagnostic value of CT enterography (CTE) in primary intestinal T-cell lymphoma (PITCL).Methods Eighteen patients with PITCL confirmed by pathology were reviewed retrospec tively.The characteristics of lesion site,amount of foci,pattern and degree of contrast enhancement,lymphadenopathy,involvement of other organs and complications were recorded.Results In all of the 18 patients with PITCL,multiple lesions were seen in 13 cases (13/18,72.22％),and solitary involvement was seen in 5 cases (5/18,27.78％).Twelve ca ses were located at jejunum/ileum,3 of them were also involved in the colon.Five cases were located only in the colon,and 1 in the duodenum.Six cases were complicated with intestinal perforation.The patients were categorized into 6 types according to the CT manifestation:infiltration type (n=7),diffuse jejunum mucosa ileum metaplasia type (n =3),luminal aneurismal dilatation type (n =3),polypoid mass type (n =2),mesentery type (n=1),mixed type (n =2).Conclusion CTE can clearly display the imaging of PITCL and it has high value for the diagnosis of PITCL.