Gastric cancer is a high-incidence malignancy that poses a serious threat to public health in China, ranking among the top three cancers in both incidence and mortality. The majority of patients are diagnosed at an advanced stage, resulting in limited treatment options and poor prognosis. To address key challenges in gastric cancer diagnosis and treatment, a research team led by Professor Jiafu Ji at Peking University Cancer Hospital has focused on the project "Development and Dissemination of Precision Medicine Approaches in Gastric Cancer Management". Through a series of high-quality multicenter clinical studies, the team established a set of new international standards in perioperative treatment, individua-lized drug selection, intelligent noninvasive diagnostics, and novel immunotherapy strategies. These advances have significantly improved treatment efficacy and reduced surgical trauma, achieving key technological breakthroughs in diagnosis, therapy, and mechanistic understanding, and systematically enhancing outcomes for gastric cancer patients. The project ' s findings had a broad international impact, including hosting China ' s first International Gastric Cancer Congress. Through nationwide dissemination, they have promoted the development of precision diagnosis and treatment of gastric cancer as a discipline, and led the formulation of the National Health Commission's guidelines for gastric cancer diagnosis and treatment. In recognition of its achievements, the project was awarded the First Prize of the 2024 Chinese Medical Science and Technology Award.
Stomach Neoplasms/genetics* ; Humans ; Precision Medicine/methods* ; China ; Immunotherapy/methods*

The establishment of a high-quality gastric cancer database significantly improves the efficiency and standardization of diagnosis and treatment of this disease. Our center has developed a specialized, single-center gastric cancer database and initiated the China Gastrointestinal Cancer Surgery Union, catalyzing the exploration of multi-center databases. This article encapsulates multi-level experience and provides a detailed overview of the quality control methods we implement in both constructing and managing the gastric cancer database. Utilizing an electronic medical record system and a multi-disciplinary treatment (MDT) approach, we have designed the database in a modular and multi-nodal manner. A synthesis of automatic retrieval of structured data and manual entry, coupled with a rigorous MDT system and real-time supervision at various nodes, bolster our real-time quality control efforts. Ensuring data security and digitized management plans alongside real-time review protocol and a multi-level review system, we maintain the highest standards in the initiation and management of the database. Through the establishment of the China Gastrointestinal Cancer Surgery Union platform, we endorse the concept that multi-center database construction should be driven by research objectives, consider data accessibility, while placing an emphasis on building inter-center consensus on data quality control. Moving forward, it is crucial that the development of multi-center databases promotes uniformity in medical standards across centers, cultivates stable public data sharing platforms, ensures robust data security protocols, routinely conducts data quality assessments, and bolsters multi-center cooperation and exchanges to promote the homogeneity of medical standards.

The establishment of a high-quality gastric cancer database significantly improves the efficiency and standardization of diagnosis and treatment of this disease. Our center has developed a specialized, single-center gastric cancer database and initiated the China Gastrointestinal Cancer Surgery Union, catalyzing the exploration of multi-center databases. This article encapsulates multi-level experience and provides a detailed overview of the quality control methods we implement in both constructing and managing the gastric cancer database. Utilizing an electronic medical record system and a multi-disciplinary treatment (MDT) approach, we have designed the database in a modular and multi-nodal manner. A synthesis of automatic retrieval of structured data and manual entry, coupled with a rigorous MDT system and real-time supervision at various nodes, bolster our real-time quality control efforts. Ensuring data security and digitized management plans alongside real-time review protocol and a multi-level review system, we maintain the highest standards in the initiation and management of the database. Through the establishment of the China Gastrointestinal Cancer Surgery Union platform, we endorse the concept that multi-center database construction should be driven by research objectives, consider data accessibility, while placing an emphasis on building inter-center consensus on data quality control. Moving forward, it is crucial that the development of multi-center databases promotes uniformity in medical standards across centers, cultivates stable public data sharing platforms, ensures robust data security protocols, routinely conducts data quality assessments, and bolsters multi-center cooperation and exchanges to promote the homogeneity of medical standards.

Objective:To investigate the diagnostic performance of a new artificial intelligence (AI) model incorporating SAM-YOLOV 5 deep learning network and image processing techniques for Breast Imaging Reporting and Data System (BI-RADS) 4 category breast masses in dynamic ultrasound classification.Methods:A total of 530 pathologically proven breast lesions of BI-RADS category 4 in 458 patients were retrospectively collected from May 2019 to June 2023 at the First Affiliated Hospital of Shantou University Medical College. The model was trained and tested at ratio of 7∶3, the area under the ROC curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value of the model were determined. Firstly, the test results of the model were compared with a single static image, then, compared with the three conventional deep learning networks as well as senior and junior radiologists. The diagnostic efficiency of the new model in BI-RADS categories 4a, 4b, and 4c masses were analyzed.Results:The AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model based on dynamic ultrasound video were higher than those using a single ultrasound static imaging (all P<0.05). Based on dynamic ultrasound video, the AUC, sensitivity, specificity, positive predictive value and negative predictive value of the new model were significantly higher than those of YOLOV 5, VGG 16, Resnet 50 and the junior group (all P<0.05), lower than the senior group (just specificity and negative predictive value, P<0.05). The diagnostic efficiency of new model for BI-RADS category 4b masses was the lowest. Conclusions:Based on the SAM-YOLOV 5 deep learning network and image processing techniques, the new model has a high diagnostic value for breast mass dynamic ultrasound classification and is expected to be used in assisting clinical diagnosis.

Background:Early diagnosis and treatment can effectively improve the prognosis of colon cancer.Simple,effective and sensitive screening indicators are of great significance for identification of early cancer and precancerous lesions.L-selectin is a cell adhesion molecule,and podocalyxin(PODXL)is its ligand,both of them play key roles in the development of cancer.Aims:To investigate the expression and significance of L-selectin and its ligand PODXL in colon cancer.Methods:A total of 120 cases of pathological specimens(40 hyperplastic polyp,40 colon adenoma,and 40 colon cancer)from Nov.2020 to Nov.2022 at the Frist People's Hospital of Hangzhou Lin'an District and the First Affiliated Hospital of Zhejiang Chinese Medical University were collected,and 20 cases of normal intestinal mucosal tissue were served as controls.qRT-PCR and immunohistochemistry were used to detect the mRNA and protein expressions of L-selectin and PODXL,respectively.Western blotting was used to determine the expressions of L-selectin and PODXL,and their relations with different clinicopathological parameters of colon cancer were analyzed.In addition,60 serum specimens of colon cancer were collected.ELISA was used to detect serum concentrations of L-selectin and PODXL.Results:Expressions of L-selectin and PODXL mRNA and protein in colon adenoma group were significantly higher than those in normal controls and hyperplastic polyp group(P<0.05),and mRNA and protein expressions of L-selectin and PODXL in colon cancer group were significantly higher than those in normal controls,hyperplastic polyp group and colon adenoma group(P<0.05).Significant differences in protein expressions of L-selectin and PODXL were found in different pathological types,lymph node metastasis,Dukes staging in colon cancer(P<0.05).Expression of L-selectin was positive correlated with expression of PODXL in colon cancer(r=0.855,P<0.001).Serum concentrations of L-selectin and PODXL were significantly lower in the initial group than in the relapse group(P<0.05),and serum concentrations of L-selection and PODXL was significantly lower in the non-metastatic group than in the metastatic group(P<0.05).Serum concentrations of L-selectin and PODXL at 3 months after surgery was significantly lower than 3 days after surgery and before surgery(P<0.05).Conclusions:L-selectin and PODXL may be involved in the development and progression of colon cancer.They are carcinogenic proteins,and their detection could provide reference value for the prevention and early diagnosis of colon cancer,and through early screening of lesion could improve the prognosis of colon cancer to a certain extent.

Objective:To establish standard spatial brain template and ROIs template of 11C-methyl- N-2β-carbomethoxy-3β-(4-fluorophenyl)tropane (CFT) PET images for automated quantitative analysis of dopamine transporter (DAT) distribution. Methods:From May 2014 to December 2015, 11C-CFT PET and MRI T 1 brain images of 16 healthy volunteers (3 males, 13 females; age (63.3±6.9) years) from Huashan Hospital, Fudan University were co-registered and smoothed using statistical parametric mapping(SPM)5 software based on MATLAB to create a standard spatial brain template. The ROIs template was established by ScAnVp procedures. These templates were clinically verified by using 11C-CFT PET images of 37 healthy volunteers (23 males, 14 females; age (61.7±7.1) years), 32 Parkinson′s disease (PD) patients (20 males, 12 females; age (61.1±5.4) years), 10 multiple system atrophy with predominant parkinsonism (MSA-P) patients (7 males, 3 females; age (60.8±7.1) years) and 10 progressive supranuclear palsy (PSP) patients (5 males, 5 females; age (58.4±6.1) years) from Huashan Hospital, Fudan University between January 2014 and March 2019. One-way analysis of variance was used to analyze data. Results:Based on the 11C-CFT PET images and MRI T 1 images of healthy volunteers, a standard spatial brain template for normalization of 11C-CFT PET images was created. The ROIs template was established including seven regions: bilateral caudate, anterior putamen, posterior putamen (along the long axis) and the occipital cortex. The ROIs template was accurately aligned in each verification group. The normal reference values of semi-quantitative DAT distribution in caudate, anterior putamen and posterior putamen were obtained (1.84±0.13, 2.18±0.16, 1.77±0.11). The semi-quantitative values of 11C-CFT uptake in each ROI in patients were significantly lower than those in healthy volunteers ( F values: 49.79-283.83, all P<0.05). Conclusion:The established brain templates with accurate spatial alignment for 11C-CFT image analysis can provide foundational tools for the application of 11C-CFT PET imaging in clinical practice and scientific research.

Gastrointestinal tumors(GT)are characterized by both high malignancy and high mortality and have become the major diseases for prevention in the elderly.GT often present detectable changes, including bleeding and abnormal mucosal morphology.However, many technical difficulties remain in accurately monitoring the tumor itself and related abnormal lesions mentioned above, which are the key factors affecting the early detection rate of gastrointestinal tumors.In recent years, with progresses in artificial intelligence(AI)applications for digestive endoscopy image analysis, biosensors, new biomarkers and other areas, AI holds promise for the detection of bleeding, morphological and structural abnormalities of the mucosa, tumors and other major disorders.Here we review the progress of AI applications in geriatric digestive diseases affecting digestive organs and the mucosa in light of morphology and function, to provide a reference for reducing the incidence of both geriatric emergencies and GT.

Objective:To investigate the protective mechanism of TAK242, a specific inhibitor of Toll-like receptor 4 (TLR4), on the liver of septic rats.Methods:Eighteen male Sprague-Dawley (SD) rats were randomly divided into three groups ( n = 6 in each group). The septic model was established by intraperitoneal injection of lipopolysaccharide (LPS) 15 mg/kg. The rats in the TAK242 intervention group received intraperitoneal injection of TAK242 (5 mg/kg) before modeling, while the rats in the septic model group and the control group were injected with the same amount of solvent [10% dimethyl sulfoxide (DMSO) + 90% corn oil]. Six hours later, the blood of abdominal aorta was collected and the levels of serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were measured by enzyme linked immunosorbent assay (ELISA). The rats were sacrificed to obtain liver, the expression levels of TLR4, tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6), cysteinyl aspartate-specific proteinase-3 (caspase-3), nuclear factor-κB p65 (NF-κB p65) and phosphorylated NF-κB p65 (p-NF-κB p65) were detected by Western blotting. Immunohistochemical staining was used to observe NF-κB p65 protein expression in liver, and hepatocyte injury was assessed by hematoxylin-eosin (HE) staining. Results:Serum ALT and AST levels in the septic model group were significantly higher than those in the control group [ALT (μg/L): 26.639±7.814 vs. 2.847±2.150, AST (μg/L): 28.442±8.417 vs. 5.779±3.019, both P < 0.01]. The ALT and AST levels in the TAK242 intervention group were significantly lower than those in septic model group [ALT (μg/L): 7.269±3.398 vs. 26.639±7.814, AST (μg/L): 3.580±3.115 vs. 28.442±8.417, both P < 0.01]. Light microscopy showed that the hepatocytes in the septic model group were disordered, with obvious cell edema and increased inflammatory cells infiltration; the hepatocytes in the TAK242 intervention group were more neatly arranged, with significantly reduced hepatocyte edema and reduced inflammatory cells infiltration. Western blotting results showed that caspase-3 protein expression in hepatic tissue of septic model group was significantly higher than that in the control group (caspase-3/GAPDH: 0.794±0.164 vs. 0.482±0.055, P < 0.05), and caspase-3 protein expression in the TAK242 intervention group significantly decreased than that in the septic model group (caspase-3/GAPDH: 0.482±0.056 vs. 0.794±0.164, P < 0.05), which indicated that TAK242 could attenuate hepatocytes apoptosis of septic rats. The expression of IL-6, TNF-α and TLR4 protein and the ratio of p-NF-κB p65/NF-κB p65 in hepatic tissue of septic model group were significantly higher than those in control group (IL-6/GAPDH: 1.442±0.204 vs. 1.019±0.024, TNF-α/GAPDH: 1.089±0.098 vs. 0.806±0.005, TLR4/GAPDH: 1.292±0.085 vs. 0.941±0.087, p-NF-κB p65/NF-κB p65 ratio: 1.936±0.081 vs. 1.579±0.183, all P < 0.05), IL-6, TNF-α and TLR4 protein expression and p-NF-κB p65/NF-κB p65 ratio in the TAK242 intervention group were significantly lower than those in septic model group (IL-6/GAPDH: 1.035±0.042 vs. 1.442±0.204, TNF-α/GAPDH: 0.572±0.096 vs. 1.089±0.098, TLR4/GAPDH: 0.984±0.078 vs. 1.292±0.085, p-NF-κB p65/NF-κB p65 ratio: 1.484±0.255 vs. 1.936±0.081, all P < 0.05), it is suggested that LPS-induced sepsis could activate the inflammatory response mediated by TLR4/NF-κB pathway in liver, and the activation of TLR4/NF-κB pathway was inhibited by TAK242 through the TLR4 pathway, therefore, the inflammation of liver in septic rats was reduced. Immunohistochemical staining showed that the positive expression of NF-κB p65 in liver was significantly increased in the septic model group compared with the control group; the positive expression of NF-κB p65 was significantly reduced in the TAK242 intervention group compared with the septic model group, and there was almost no positive expression in the nucleus. Conclusion:TAK242 could reduce liver function injury and protect the liver by inhibition TLR4/NF-κB pathway in septic rats.

Objective:To investigate the efficacy of CT imaging features in evaluating occult peritoneal metastasis (OPM) of diffuse infiltrating gastric cancer (Borrmann Type Ⅳ).Methods:Totally 101 patients with locally advanced Borrmann type Ⅳ gastric cancer were retrospectively collected who were admitted to Peking University Cancer Hospital from March 2014 to March 2021. The patients were divided into OPM group (53 cases) and the non-OPM group (48 cases) according to the results of preoperative CT and laparoscopic exploration/peritoneal cytology examination. The pathological examination results were recorded, including the degree of histological differentiation and Lauren classification. The evaluation indicators included the tumor center position, the number of tumor-occupied portions, involved orientation, mucosal broadband sign, stratified enhancement, serosa invasion, increased density of peripheral fat tissue, and enlarged lymph nodes. The maximum thickness of the primary tumor, average CT value of the primary tumor (arterial phase, venous phase, and delayed phase), difference between venous phase and arterial phase, difference between delayed phase and venous phase, and pattern of the enhanced curve were recorded. The Mann-Whitney U or Chi-square test was used to compare the differences of pathological and CT features between two groups. The multivariate logistic regression was used to screen independent predictors and establish a nomogram. The receiver operating characteristic curve was used to evaluate the performance of the nomogram in predicting OPM, and the Hosmer-Lemeshow test was used to test the model′s goodness of fit. Results:There was statistical significance in the seven indicators between the OPM and non-OPM groups, including tumor-occupied portions of stomach, mucosal broadband sign, stratified enhancement, serosa invasion, increased density of peripheral fat tissue, the enhanced curve pattern and the degree of histological differentiation ( P<0.05). Among them, the degree of histological differentiation (OR=0.19, P=0.033), stratified enhancement (OR=7.02, P=0.005) and serosa invasion (OR=14.27, P<0.001) were independent predictors of OPM. The nomogram was established based on the three significant features. The area under the curve for predicting OPM was 0.826 (95%CI 0.745-0.908), the sensitivity was 0.566 and the specificity was 0.938. The Hosmer-Lemeshow test showed a good agreement between the OPM risk predicted by the nomogram and the actual risk ( P=0.525). Conclusions:The CT features of Borrmann type Ⅳgastric cancer complicated with OPM have specific characteristics. The diagnosis model based on the degree of histological differentiation, stratified enhancement, and serosa invasion had high efficacy in evaluating OPM.

Since the outbreak of Corona Virus Disease 2019 occurred in December 2019, the reduction of population mobility has curbed the spread of the epidemic to some extent but also prolonged the waiting time for the treatment of patients with gastric cancer. Based on fully understanding the different staging characteristics of gastric cancer, clinical departments should develop reasonable out-of-hospital management strategies. On one hand, reasonable communication channels should be established to allow patients to receive adequate guidance out of the hospital. On the other hand, shared decisions with patients should be made to adjust treatment strategies, and education on viral prevention should be implemented to minimize the impact of the epidemic on tumor treatment.