Background and objective Neoantigen reactive T cell(NRT)has the ability to inhibit the growth of tumors expressing specific neoantigens.However,due to the difficult immune infiltration and the inhibition of tumor micro en-vironment,the therapeutic effect of NRT in solid tumors is limited.In this study,we designed NRT cells(7×19 NRT)that can express both interleukin-7(IL-7)and chemokine C-C motif ligand 19(CCL19)in mouse lung cancer cells,and evaluated the difference in anti-tumor effect between 7×19 NRT cells and conventional NRT cells.Methods We performed next-generation sequencing and neoantigen prediction for mouse Lewis lung carcinoma(LLC),prepared RNA vaccine,cultured NRT cells,constructed retroviral vectors encoding IL-7 and CCL19,transduced NRT cells and IL-7 and CCL19 were successfully ex-pressed,and 7×19 NRT was successfully obtained.The anti-tumor effect was evaluated in vivo and in vitro in mice.Results The 7×19 NRT cells significantly enhanced the proliferation and invasion ability of T cells by secreting IL-7 and CCL19,achieved significant tumor inhibition in the mouse lung cancer and extended the survival period of mice.The T cell infiltration into tumor tissue and the necrosis of tumor tissue increased significantly after 7×19 NRT treatment.In addition,both 7×19 NRT treatment and conventional NRT treatment were safe.Conclusion The anti-solid tumor ability of NRT cells is significantly enhanced by the arming of IL-7 and CCL19,which is a safe and effective genetic modification of NRT.

Hepatocellular carcinoma(HCC),commonly known as primary liver cancer,is a major cause of malignant tumors and cancer-related deaths in China,accounting for approximately 85％of all cancer cases in the country.Several guidelines have been used to diagnose and treat liver cancer.However,these guidelines provide a broad definition for classifying advanced liver cancer,with an emphasis on a singular approach,without considering treatment options for individual patients.Therefore,it is necessary to establish a comprehensive and practical expert consensus,specifically for China,to enhance the diagnosis and treatment of HCC using the Delphi method.The classification criteria were refined for Chinese patients with HCC,and the corresponding optimal treatment regimen recommendations were developed.These recommendations took into account various factors,including tumor characteristics,vascular tumor thrombus grade,distant metastasis,liver function status,portal hypertension,and the hepatitis B virus replication status of patients with primary HCC,along with treatment prognosis.The findings and rec-ommendations provide detailed,scientific,and reasonable individualized diagnosis and treatment strategies for clinicians.

This study intends to establish a colorectal cancer(CRC)organoid model,expand and isolate CRC-reactive tumor-infiltrating lymphocytes(TILs),screen tumor-specific T cell receptors(TCRs)and perform functional verification,in order to provide a technological platform and research foundation for the clinical transformation of individualized adoptive T-cell immunotherapy for colorectal cancer.An organoid model derived from colon cancer patient tissues was constructed using in vitro 3D culture techniques,which then subjected to HE staining and immunohistochemistry for detecting morphological characteristics and representative molecular expression.Subsequently,CRC organoids were co-cultured with TILs for sorting reactive TILs using flow cytometry,and the characteristics of reactive TCR clones was analyzed through single T cell receptor gene cloning technology.Furthermore,the function of TCRs was verified through cytotoxicity experiments.Morphological analysis and representative molecules(CK20 and CDX2)expression indicated that there is high similarity between colorectal cancer organoids and patient tumors.In the in vitro expanded and cultured TILs,colorectal cancer-reactive T cells with upregulated CD137 expression and increased IFN-γ secretion were screened out successfully,among which TCR2-T cells demonstrated superior tumor reactivity and in vitro tumor killing function.In conclusion,a platform for screening and function validation of reactive TCRs based on CRC-Org has been established,providing a technological platform for the translational application of individualized T-cell therapy for colorectal cancer.

Objective To develop an artificial intelligence vaginal secretion analysis system based on deep learning and to evaluate the accuracy of automated microscopy in the clinical diagnosis of aerobic vaginitis(AV).Methods In this study,the vaginal secretion samples of 3 769 patients receiving treatment at the Department of Obstetrics and Gynecology,West China Second Hospital,Sichuan University between January 2020 and December 2021 were selected.Using the results of manual microscopy as the control,we developed the linear kernel SVM algorithm,an artificial intelligence(AI)automated analysis software,with Python Scikit-learn script.The AI automated analysis software could identify leucocytes with toxic appearance and parabasal epitheliocytes(PBC).The bacterial grading parameters were reset using standard strains of lactobacillus and AV common isolates.The receiver operating characteristic(ROC)curve analysis was used to determine the cut-off value of AV evaluation results for different scoring items were obtained by using the results of manual microscopy as the control.Then,the parameters of automatic AV identification were determined and the automatic AV analysis scoring method was initially established.Results A total of 3 769 vaginal secretion samples were collected.The AI automated analysis system incorporated five parameters and each parameter incorporated three severity scoring levels.We selected 1.5 μm as the cut-off value for the diameter between Lactobacillus and common AV bacterial isolates.The automated identification parameter of Lactobacillus was the ratio of bacteria≥1.5 μm to those＜1.5 μm.The cut-off scores were 2.5 and 0.5,In the parameter of white blood cells(WBC),the cut-off value of the absolute number of WBC was 103 μL-1 and the cut-off value of WBC-to-epithelial cell ratio was 10.The automated identification parameter of toxic WBC was the ratio of toxic WBC toWBC and the cut-off values were 1%and 15%.The parameter of background flora was bacteria＜1.5 μm and the cut-off values were 5×103 μL-1 and 3×104 μL-1.The parameter of the parabasal epitheliocytes was the ratio of PBC to epithelial cells and the cut-off values were 1%and 10%.The agreement rate between the results of automated microscopy and those of manual microscopy was 92.5%.Out of 200 samples,automated microscopy and manual microscopy produced consistent scores for 185 samples,while the results for 15 samples were inconsistent.Conclusion We developed an AI recognition software for AV and established an automated vaginal secretion microscopy scoring system for AV.There was good overall concordance between automated microscopy and manual microscopy.The AI identification software for AV can complete clinical lab examination with rather high objectivity,sensitivity,and efficiency,markedly reducing the workload of manual microscopy.

Objective:To explore the independent risk factors of portal vein thrombosis (PVT) in liver cirrhosis, and to establish and evaluate a risk prediction model for PVT in patients with cirrhosis.Methods:A total of 295 cases of cirrhosis hospitalized in Renmin Hospital of Wuhan University from December 2019 to October 2021 were divided into a modeling set ( n=207) and an internal validation set ( n=88) by the random number table. In addition, patients with cirrhosis hospitalized in Yichang Central People's Hospital, Wuhan Puren Hospital, No.2 People's Hospital of Fuyang City and People's Hospital of China Three Gorges University during the same period were collected as an external validation set ( n=92). The modeling set was divided into PVT group ( n=56) and non-PVT group ( n=151). Univariate analysis was used to preliminarily screen the related indicators of PVT, and then multivariate logistic regression analysis with forward stepwise regression was used to determine independent risk factors for PVT. A nomogram prediction model was constructed based on the independent risk factors obtained. The internal and external validation set were used to verify the predictive ability of the model. Distinction degree was used to evaluate the ability of the model to distinguish patients with or without PVT. Hosmer-Lemeshow goodness-of-fit test was used to evaluate the consistency between predicted risk and the actual risk of the model. Results:Univariate analysis showed that smoking, history of splenectomy, trans-jugular intrahepatic portosystemic shunt (TIPS), gastrointestinal bleeding and endoscopic variceal treatment, and levels of hemoglobin, alanine aminotransferase, aspartate aminotransferase and D-dimer were significantly different between the PVT group and the non-PVT group ( P<0.05). Multivariate logistic regression analysis found that smoking ( P=0.020, OR=31.21, 95% CI: 1.71-569.40), levels of D-dimer ( P=0.003, OR=1.12, 95% CI: 1.04-1.20) and hemoglobin ( P=0.039, OR=0.99, 95% CI: 0.97-1.00), history of TIPS ( P=0.011, OR=18.04, 95% CI: 1.92-169.90) and endoscopic variceal treatment ( P=0.001, OR=3.21, 95% CI: 1.59-6.50) were independent risk factors for PVT in patients with liver cirrhosis. Receiver operator characteristic (ROC) curve analysis showed that the area under the ROC curve (AUC) for the internal validation set was 0.802 (95% CI: 0.709-0.895) ( P<0.001), and the AUC for the external validation set was 0.811 (95% CI: 0.722-0.900) ( P<0.001). Both AUC were larger than 0.75. The calibration curve of Hosmer-Lemeshow goodness-of-fit test showed that the P values of both internal validation set ( χ2=3.602, P=0.891) and the external validation set ( χ2=11.025, P=0.200) were larger than 0.05. Conclusion:Smoking, history of TIPS or endoscopic variceal treatment, levels of D-dimer and hemoglobin are independent risk factors for PVT in patients with liver cirrhosis. The prediction nomogram model based on the above factors has strong predictive ability.

ObjectiveTo determine the incidence and characteristics of adverse events following immunization （AEFI） in 2016‒2020 in Dazu District of Chongqing， and evaluate the AEFI surveillance information system and provide scientific evidence for vaccine safety. MethodsDescriptive epidemiological analysis was performed on the cases collected by the AEFI surveillance system. Incidence and coverage of AEFI were then presented. ResultsA total of 319 AEFI cases were reported in 2016‒2020. Reported incidence of AEFI was determined to be 24.64/10⁵ doses. The proportion of timely reporting AEFI within 48 hours was 94.04% and that of timely investigation within 48 hours was 98.41%. The proportion of completing the AEFI survey was 100.00% and that of AEFI classification was 99.69%. The male to female ratio was 1.28∶1. Majority of the AEFI cases were less than 1 year old （64.26%， 205/319）， from April to September （68.97%， 220/319）， and reported at 0‒1 day post-immunization （89.34%， 285/319）. Moreover， the reported incidence differed significantly between time periods （χ²=32.481，P<0.05） and time intervals from vaccination to occurrence of AEFI （χ²=961.408， P<0.05）. Coverage of reporting AEFI at county level reached 100％. In addition， non-severe AEFI cases accounted for 98.43% （314/319） and no death case was reported. General events， such as fever， redness， and scleroma， accounted for 80.56% （257/319）， whereas rare adverse events accounted for 15.99% （51/319）. The reported incidence of NIP vaccines was highest in the diphtheria tetanus acellular pertussis combined vaccine， followed by measles and rubella combined attenuated vaccine and diphtheria tetanus combined vaccine. Clinical diagnosis of rare adverse events was mainly allergic rashes. ConclusionThe AEFI surveillance information system in Dazu District of Chongqing achieves efficient monitoring of AEFI. It has proven that the vaccines are generally safe and immunization strategies may be continuously implemented. Furthermore， the sensitivity of AEFI surveillance should be improved through multiple approaches.

Remdesivir (RDV) is the only US Food and Drug Administration (FDA)-approved drug for treating COVID-19. However, RDV can only be given by intravenous route, and there is a pressing medical need for oral antivirals. Significant evidence suggests that the role of the parent nucleoside GS-441524 in the clinical outcomes of RDV could be largely underestimated. We performed an

"The Expert Group on Tumor Ablation Therapy of Chinese Medical Doctor Association, The Tumor Ablation Committee of Chinese College of Interventionalists, The Society of Tumor Ablation Therapy of Chinese Anti-Cancer Association and The Ablation Expert Committee of the Chinese Society of Clinical Oncology" have organized multidisciplinary experts to formulate the consensus for thermal ablation of pulmonary subsolid nodules or ground-glass nodule (GGN). The expert consensus reviews current literatures and provides clinical practices for thermal ablation of GGN. The main contents include: (1) clinical evaluation of GGN, (2) procedures, indications, contraindications, outcomes evaluation and related complications of thermal ablation for GGN and (3) future development directions.
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Of all known small molecules targeting human immunodeficiency virus (HIV) capsid protein (CA), PF74 represents by far the best characterized chemotype, due to its ability to confer antiviral phenotypes in both early and late phases of viral replication. However, the prohibitively low metabolic stability renders PF74 a poor antiviral lead. We report herein our medicinal chemistry efforts toward identifying novel and metabolically stable small molecules targeting the PF74 binding site. Specifically, we replaced the inter-domain-interacting, electron-rich indole ring of PF74 with less electron-rich isosteres, including imidazolidine-2,4-dione, pyrimidine-2,4-dione, and benzamide, and identified four potent antiviral compounds (