Peritoneal metastasis is a common manifestation of advanced malignant tumors. Traditional imaging and cytology have insufficient sensitivity for detecting subcentimeter lesions, whereas Transformer models, leveraging self-attention mechanisms, exhibit unique advantages in global context modeling and multimodal fusion. These models have shown preliminary potential in the fields of imaging, pathological and molecular diagnosis, and prognosis prediction. However, existing studies are generally constrained by single-center, small-sample designs, limited cross-center generalizability, and a lack of prospective validation; model interpretability and the computational complexity of clinical deployment also constitute critical bottlenecks. In the future, adopting the pretraining-fine-tuning paradigm of large-scale medical foundation models, advancing pan-omics fusion and dynamic temporal modeling, and conducting prospective interventional clinical validation will be key pathways to propel Transformers from assistive tools toward core components of intelligent diagnosis and treatment for peritoneal metastasis. This paper summarizes and analyzes currently available research data, reviews the applications of Transformers in three major scenarios-imaging diagnosis, pathological and molecular subtyping, and prognosis prediction-focuses on analyzing translational bottlenecks such as data scarcity, model interpretability, and clinical deployment, and proposes corresponding solutions and future directions.
Objective: To investigate the clinical efficacy, safety, and post-resistance treatment strategies of ripretinib in the treatment of advanced gastrointestinal stromal tumors (GIST), and to provide evidence-based references for optimizing individualized treatment of advanced GIST. Methods: This is a single-center retrospective real-world study. Inclusion criteria: (1) GIST confirmed by histopathology; (2) disease progression after previous treatment with other targeted drugs including imatinib; (3) continuous administration of ripretinib for more than one month with at least one efficacy evaluation. Exclusion criteria: (1) Clinical data were seriously missing, and data such as patient dosage, efficacy evaluation results, and adverse reactions could not be obtained; (2) complicated with other serious underlying diseases, such as uncontrolled severe cardiovascular and cerebrovascular diseases, liver and kidney failure, etc.; (3) Allergic or severe drug intolerance to ripretinib. According to the above criteria, a total of 93 patients with advanced GIST treated in West China Hospital of Sichuan University from July 2021 to March 2025 were collected. In this study, evaluable patients were defined as those who met any of the following criteria: (1) baseline and follow-up imaging examinations were completed in our center with complete imaging data, and the long diameter of target lesions could be accurately measured and the efficacy could be evaluated; (2) The efficacy evaluation was completed in other hospitals, but the image data and report were complete, and the exact measurement data of target lesions could be obtained after review by the radiology department of our hospital. All patients with advanced GIST enrolled in the study initially received the standard dose of ripretinib (150 mg once daily). After disease progression (PD), the following treatment strategies could be selected after multi-disciplinary team (MDT) discussion: (1) the dose of ripretinib was increased from 150 mg once daily to 150 mg twice daily (ripretinib dose-escalation group); (2) The standard-dose ripretinib (150 mg, once daily) was combined with local treatment, including surgery, interventional therapy and radiotherapy (ripretinib combined with local treatment group); (3) standard-dose ripretinib combined with frontline TKI, including imatinib, sunitinib and regorafenib (ripretinib combined with frontline TKI group); (4) other TKI treatment, including imatinib, sunitinib, regorafenib and avapritinib (other TKI treatment group). The primary outcome was median progression-free survival (mPFS). Secondary outcomes included objective response rate [ORR, the proportion of patients with complete response (CR) or partial response (PR)], disease control rate [DCR, the proportion of patients with CR, PR, or stable disease (SD)], overall survival (OS), and adverse events. Results: A total of 93 patients with advanced GIST were enrolled. Among 59 evaluable patients, 6 had PR, 30 had SD, and 23 had PD, with ORR of 10.2% and DCR of 61.0%. With a median follow-up time of 13 (2-47) months, the median mPFS was 7.0 (95%CI: 4.9-9.1) months, and the 1-year OS rate was 86.1%. Genotyping analysis showed that the mPFS in the KIT exon 11 mutation group was significantly longer than that in the exon 9 mutation group (12.0 months vs. 4.0 months, P=0.007). No statistically significant difference in mPFS was observed among different recurrence/metastasis sites (liver, peritoneum, or liver + peritoneum, P = 0.149). A total of 60 patients experienced progression on standard-dose ripretinib. According to the subsequent treatment strategy, the patients were divided into 4 groups: ripretinib dose-escalation group (16 patients), ripretinib combined with local therapy group (9 patients), ripretinib combined with frontline TKI group (6 patients), and other TKI group (9 patients). The mPFS in these groups was 4.0 months (95% CI: 1.5-6.5), not reached, 4.0 (95%CI: could not be estimated) and 12.0 months (95%CI: 1.0-25.5), respectively. There was no significant difference in mPFS among the four groups (P=0.345). In terms of safety, no grade 3-4 serious adverse reactions were observed in the whole group, and dose-escalation or combination therapy did not increase toxicity. Conclusion: Ripretinib can serve as an effective treatment option for Chinese patients with advanced GIST after failure of first-line or multiple prior TKI therapies, and it demonstrates a favorable safety profile. Although no standard treatment is currently available for patients with resistance to ripretinib, dose escalation of ripretinib, combination with local therapy, combination with prior TKIs, or switching to alternative TKIs can be considered, and all regimens exhibit a favorable safety profile.
Objective: To construct a survival prognostic prediction model for whole-slide histopathological images (WSIs) of gastric cancer based on multi-instance learning with sequential feature reconstruction, and to explore its predictive value. Methods: Retrospectively collected hematoxylin-eosin stained WSIs and clinical prognostic data of gastric cancer patients treated at the 1st, 8th and 9th Medical Centers of Chinese PLA General Hospital from January 2015 to December 2022. The sample sizes of the three medical centers were 386, 284 and 216 cases, denoted as Dataset 1, Dataset 2 and Dataset 3 respectively. This study developed a multi-instance learning model based on sequential feature reconstruction, named sequence reordering and sparse autoencoder-based enhanced representation transformer for multiple instance learning (S²ERT-MIL). After extracting patch features of pathological images via a pre-trained model, the model reconstructed and optimized patch instance features through sequence reordering, regional feature enhancement, sparse autoencoding and cross-regional information fusion, and finally output patient-level survival risk scores. Five-fold cross-validation was adopted to evaluate model performance, and comparisons were conducted with representative MIL models including Attention-Based Multiple Instance Learning (ABMIL), Clustering-constrained Attention Multiple Instance Learning (CLAM), Dual-Scale Multiple Instance Learning (DSMIL), Dual-Tier Feature Distillation Multiple Instance Learning (DTFD-MIL) and Representation Refinement and Transformation Multiple Instance Learning (RRT-MIL). The concordance index (C-index) was used to assess the survival prediction performance of the model. Patients were divided into high-risk and low-risk groups according to the median risk score, and the Kaplan-Meier method with Log-rank test was applied to evaluate the risk stratification ability. Visualization analysis of high- and low-attention patches was also performed. Results: S²ERT-MIL achieved the highest C-index across all three datasets, with values of 0.7493±0.0486, 0.6758±0.0347 and 0.7232±0.0362 in Dataset 1, Dataset 2 and Dataset 3, respectively, all higher than those of the comparison models. Kaplan-Meier survival analysis showed that S²ERT-MIL stratified patients into high-risk and low-risk groups with significantly different survival outcomes in all three datasets. Attention-region visualization showed that high-attention patches were mainly derived from areas with dense tumor cells, complex tissue architecture or marked stromal reaction, whereas low-attention patches mostly represented low-information regions or areas relatively weakly associated with prognosis. Conclusion: S²ERT-MIL can predict patient survival prognosis based on H&E-stained gastric cancer WSIs and showed favorable risk discrimination and stratification performance across three datasets.
The gut microbiota, acknowledged as the human body's 'second genome', plays a pivotal role in maintaining health. Digestive tract reconstruction surgery profoundly alters the anatomical structure and physiological environment of the gastrointestinal tract, thereby inducing significant shifts in the intestinal microbiota. These microbial changes subsequently influence host physiological functions through metabolic, immune, neuroendocrine, and other pathways. For instance, Roux-en-Y gastric bypass surgery enriches short-chain fatty acid(SCFA)-producing Bacteroides, improving systemic insulin sensitivity. Conversely, pancreaticoduodenectomy leads to a marked enrichment of potential pathobionts such as Klebsiella and Clostridium, which may elevate the risk of infections and tumor recurrence. This review comprehensively summarizes the characteristic changes in the gut microbiota following various digestive tract reconstruction procedures and discusses their multifaceted impacts on host physiology, aiming to provide insights for future experimental research and clinical practice.
Objective: To analyze the implementation status of bariatric and metabolic surgery and the provincial resource distribution characteristics in Guangdong Province in 2025. Methods: Descriptive analysis was performed based on the aggregated data of bariatric and metabolic surgeries reported by 39 hospitals in Guangdong Province in 2025. Using the 2024 provincial data as annual control, we analyzed the total surgical volume, surgical procedure composition, distribution of performing hospitals, urban distribution, and application of novel procedures, with comparative analysis combined with external data (national, Shanghai, and international public databases). External reference materials included the 2024 Annual Report of China Obesity and Metabolic Surgery Database, the 2024 Annual Report of Greater China Bariatric and Metabolic Surgery Database, the Analysis of Quality Control Data of Bariatric and Metabolic Surgery in Shanghai from 2012 to 2023, the global registry report of the International Federation for the Surgery of Obesity and Metabolic Disorders (IFSO), and public data released by the American Society for Metabolic and Bariatric Surgery (ASMBS)/Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP). National and Shanghai data were used for horizontal regional comparison, while US data served as a reference for international industry trends. Results: A total of 1611 bariatric and metabolic surgeries were completed in Guangdong Province in 2025, representing an 18.3% increase compared with 1362 cases in 2024; the number of hospitals performing such surgeries rose from 22 to 39. Procedure composition: conventional laparoscopic sleeve gastrectomy (SG) accounted for 1,086 cases (67.4%); Roux-en-Y gastric bypass (RYGB) for 142 cases (8.8%); sleeve gastrectomy with transit bipartition (SG-TB) for 82 cases (5.1%); single-port SG for 87 cases (5.4%); one-anastomosis gastric bypass (OAGB) for 61 cases (3.8%); revisional bariatric surgery for 59 cases (3.7%); bypass stent for 73 cases (4.5%), and robot-assisted SG for 4 cases (0.2%). No cases of hydrogel balloon therapy or endoscopic sleeve gastroplasty (ESG) were reported. The top 10 hospitals ranked by surgical volume in Guangdong Province in 2025 showed an obvious hierarchical distribution. The cumulative volume proportions of the top 3, top 5 and top 10 hospitals reached 71.8%, 81.8% and 90.6%, respectively. In terms of urban distribution, Guangzhou, Shenzhen and Zhongshan contributed 95.8% (1543 cases) of the provincial total. The total number of bariatric surgeries nationwide in China reached 32 342 in 2024, while Shanghai recorded 1430 cases in 2023. Sleeve gastrectomy (SG) accounted for 75.6% of all national procedures in 2024 versus 87.9% in Shanghai in 2023. Roux-en-Y gastric bypass (RYGB) made up 4.7% of national surgeries in 2024 and 7.7% in Shanghai in 2023. There were 1234 one-anastomosis gastric bypass (OAGB) procedures nationwide in 2024, accounting for 3.8%. In the United States, 4587 ESG procedures and 1461 intragastric balloon placements were performed in 2023. Conclusion: The annual volume of bariatric and metabolic surgeries in Guangdong Province maintained an upward trend in 2025, with SG remaining the predominant procedure; however, the distribution of surgeries was highly concentrated by hospital and city. Compared with published national and Shanghai data, Guangdong Province recorded a relatively high surgical volume nationwide and featured a more diverse procedural spectrum. In contrast to international published data, the application volume of novel surgical techniques and new modalities performed in Guangdong Province remained limited at present.
