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Objective To investigate the clinicopathological characteristics and prognosis of patients with Borrmann type Ⅳ gastric cancer. Methods A cohort retrospective analysis of 2386 patients with gastric cancer who underwent radical surgery was used to screen out Borrmann type Ⅳ patients, and analyze their clinical features and prognostic factors. Results Among 2386 patients with gastric cancer, 363 cases (15.21%) were Borrmann type Ⅳ. Compared with non-Borrmann type Ⅳ gastric cancer patients, Borrmann type Ⅳ patients had higher rates of simultaneous liver metastasis, metachronous liver metastasis, lymph node metastasis and vascular infiltration. Moreover, the age of onset tended to be younger and the pathological type tended to be poorly differentiated-undifferentiated (all P < 0.05). The 5-year OS of the entire group was 49.32% and the 5-year DFS was 44.61%. There were significant differences in 5-year OS and DFS between Borrmann type Ⅳ and non-Borrmann type Ⅳpatients (all P < 0.001). The subgroup analyses showed that there were statistically significant differences in 5-year OS and DFS of gastric cancer patients between Borrmann type Ⅳ and non-Borrmann type Ⅳ in pT2-pT4a and pN0-pN3a stages (all P < 0.005). Multivariate analysis showed that the poorly differentiated-undifferentiated tumor, the T4a-pT4b stage of tumor invasion depth, lymph node metastasis, the ⅢA-ⅢC pTNM stage of the tumor, postoperative liver metastasis and peritoneal metastasis were independent risk factors affecting the prognosis of Borrmann type Ⅳ gastric cancer patients (all P < 0.05). Conclusion Borrmann type Ⅳ gastric cancer is prone to liver metastasis, lymph node metastasis, peritoneal metastasis and poor prognosis, and it's prognosis is affected by a variety of independent risk factors.

Aim: In this research, we aimed to develop a model for the accurate prediction of gastric cancer based on H&E findings combined with machine learning pathomics., Methods: Transcriptome data, pathological images, and clinical data from 443 cases were retrieved from TCGA (The Cancer Genome Atlas Program) for survival analysis. The images were segmented using the Otsu algorithm, and features were extracted using the PyRadiomics package. Subsequently, the cases were randomly divided into a training cohort of 165 cases and a validation cohort of 69 cases. Features selected via minimum Redundancy - Maximum Relevance (mRMR)- recursive feature elimination (RFE) screening were used to train a model using the Gradient Boosting Machine (GBM) algorithm. The model's performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC), calibration curves, and decision curves. Additionally, the correlation between the Pathomics score (PS) and immune genes was examined., Results: In the multivariate analysis, heightened infiltration of activated CD4 memory T cells was strongly associated with improved overall survival (HR = 0.505, 95% CI = 0.342-0.745, P < 0.001). The pathomic model, exhibiting robust predictive capability, demonstrated impressive AUC values of 0.844 and 0.750 in both study cohorts. The Decision Curve Analysis (DCA) unequivocally underscored the model's exceptional clinical utility. In a subsequent multivariate analysis, heightened infiltration of the PS also emerged as a significant protective factor for overall survival (HR = 0.506, 95% CI = 0.329-0.777, P = 0.002)., Conclusion: The pathomic model based on H&E slides for predicting the infiltration degree of activated CD4 memory T cells, along with integrated bioinformatics analysis elucidating potential molecular mechanisms, offers novel prognostic indicators for the precise stratification and individualized prognosis of gastric cancer patients., Competing Interests: Declaration of Competing Interest All authors have no conflict of interest in this manuscript., (Copyright © 2024. Published by Elsevier Ltd.)

In order to make up for the defects of traditional anaerobic fermentation systems, such as low energy utilization rates and the slow growth and reproduction of microorganisms, an Fe 0 /GO (zero-valent iron/graphene oxide) anaerobic biological treatment system was used as a treatment process in this paper, and the impact of temperature shock on the system during the treatment of high-concentration organic wastewater was studied. The experimental results showed that temperature shock reduced the COD Cr removal rate and gas production level in each system, but the Fe 0 /GO group maintained a higher level and had the highest COD Cr degradation rate after shocking. After temperature shock, the acetic acid content in each system was higher (above 90%), and the volatile fatty acid (VFA) content in the Fe 0 /GO group was the lowest. The mixed liquor suspended solids (MLSS) in all systems decreased after impact; the decrease was less in the Fe 0 /GO group and the increase was largest after temperature recovery. After shocking, the extracellular polymer substance (EPS) protein (PN) and polysaccharide (PS) levels in each system were both low. After temperature recovery, the PN/PS ratio of the Fe 0 /GO group was the highest, showing a strong impact resistance to temperature., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)