Search

Chronic atrophic gastritis plays an important role in the process of gastric cancer. Deep learning is gradually introduced in the medical field, and how to better apply a convolutional neural network (CNN) to the diagnosis of chronic atrophic gastritis remains a research hotspot. This study was designed to improve the performance of CNN on diagnosing chronic atrophic gastritis by constructing and evaluating a network structure based on the characteristics of gastroscopic images.Three endoscopists reviewed the endoscopic images of the gastric antrum from the Gastroscopy Image Database of Zhongnan Hospital and labelled available images according to pathological results. Two novel modules proposed recently were introduced to construct the Multi-scale with Attention net (MWA-net) considering the characters of similar medical images. After training the network using images of training sets, the diagnostic ability of the MWA-net was evaluated by comparing it with those of other deep learning models and endoscopists with varying degrees of expertise.As a result, 5,159 images of the gastric antrum from 2,240 patients were used to train and test the MWA-net. Compared with the direct application of famous networks, the MWA-net achieved the best performance (accuracy, 92.13%) with an increase of 1.80% compared to that of ResNet. The suspicious lesions indicated by the network are consistent with the conclusion of experts. The sensitivity and specificity of the convolutional network for gastric atrophy diagnosis are 90.19% and 94.51%, respectively, which are higher than those of experts.Highly similar images of chronic atrophic gastritis can be identified by the proposed MWA-net, which has a better performance than other well-known networks. This work can further reduce the workload of gastroscopists, simplify the diagnostic process and provide medical assistance to more residents.Chronisch atrophische Gastritis spielt eine wichtige Rolle im Verlauf von Magenkrebs. Deep Learning wird sukzessive im medizinischen Bereich eingeführt. Die Frage, wie ein Convolutional Neural Network (CNN) besser zur Diagnose der chronisch atrophischen Gastritis angewendet werden kann, bleibt nach wie vor ein Forschungsschwerpunkt. Diese Studie wurde entwickelt, um die Leistung von CNN bei der Diagnose von chronisch atrophischer Gastritis zu verbessern, indem eine Netzwerkstruktur basierend auf den Eigenschaften gastroskopischer Bilder konstruiert und bewertet wird.3 Endoskopiker überprüften die endoskopischen Bilder der Magenhöhle aus der Gastroskopie-Bilddatenbank des Zhongnan-Krankenhauses und markierten die verfügbaren Bilder entsprechend den pathologischen Ergebnissen. 2 kürzlich vorgeschlagene neue Module wurden eingeführt, um das „Multi-Scale with Attention Net“ (MWA-net) unter Berücksichtigung der Merkmale ähnlicher medizinischer Bilder zu konstruieren. Nach dem Training des Netzwerks mit Bildern von Trainingssets wurde die diagnostische Fähigkeit des MWA-Netzes durch Vergleich mit anderen Deep-Learning-Modellen und Endoskopikern mit unterschiedlichem Fachwissen bewertet.Infolgedessen wurden 5.159 Bilder des Magenantrums von 2.240 Patienten verwendet, um das MWA-net zu trainieren und zu testen. Im Vergleich zur direkten Anwendung bekannter Netzwerke erzielte das MWA-net die beste Leistung (Genauigkeit 92,13%) mit einer Steigerung von 1,80% im Vergleich zu ResNet. Die vom Netzwerk angezeigten verdächtigen Läsionen stimmen mit den Schlussfolgerungen der Experten überein. Die Sensitivität und Spezifität des CNN für die Diagnose von Magenatrophie betragen 90,19% bzw. 94,51% und liegen damit höher als die der Experten.Hochgradig ähnliche Bilder einer chronisch atrophischen Gastritis können durch das vorgeschlagene MWA-net identifiziert werden, das eine bessere Leistung als andere bekannte Netzwerke aufweist. Diese Arbeit kann die Arbeitsbelastung von Gastroskopikern weiter reduzieren, den Diagnoseprozess vereinfachen und mehr medizinische Hilfe für Niedergelassene zur Verfügung stellen.

Background and Aims Existing biliopancreatic duct endoscopy is deficient in the examination of early biliary and pancreatic tumors. This study aimed to evaluate the usefulness and feasibility of a novel ultrafine, separable, biliopancreatic duct endoscopy device with dual modalities of intraductal US (IDUS) and optical coherence tomography (OCT) for the in vivo assessment of the biliopancreatic duct system during ERCP. Methods Five Bama miniature pigs were selected to probe their common bile duct and branches by using this novel equipment during ERCP. The feasibility of the procedure was evaluated by clear, clinically interpretable images obtained by using spiral scanning with the pull-back method. The clinical usefulness of the novel product was evaluated by postoperative choledochoscopy and assessment of the animal's general condition. Results One hundred forty-one pairs of images from 5 Bama miniature pigs were acquired. Visualization of the bile duct using both OCT and IDUS was characterized by a differentiated 3-layer architecture, whereas IDUS had poor clarity when compared with OCT. Postoperative choledochoscopy showed no local lesion in the bile duct wall, and the general condition of animals was normal. Conclusions This prospective evaluation indicated the feasibility and potential clinical value of the novel, ultrafine, separable biliopancreatic duct endoscopy device. The fusion of the 2 imaging modalities can shed light on the early diagnosis of biliary and pancreatic tumors. Further studies will be carried out to establish diagnosis criteria with the dual-modality imaging using an animal pathologic model and a human clinical study.

Objective: To investigate the role of ferroptosis in Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) with renal injury. Methods: GSE104954 and GSE108112 were retrieved from the GEO database and concatenated into one dataset. Expression of ferroptosis-related genes (FRGs) was extracted for differential analysis. The ferroptosis signature genes were identified by LASSO regression and SVM-RFE, and their differential expression levels and diagnostic efficacy were verified by independent data sets. The ceRNA (miRNA-TF-mRNA) regulatory network and clinical diagnostic model were constructed respectively. By using consensus clustering, ferroptosis subtypes were identified. ssGSEA and GSVA were employed to assess immune response and pathway activation. Pan-cancer genes were found in TCGA and GTEx. Differential expression of CD44 in was validated by qPCR and immunohistochemistry from HPA database. Results:Twenty-four FRGs were differentially expressed in patients with AAV kidney injury. Furthermore, five ferroptosis signature genes were identified by two machine learning algorithms. Not only were differentially expressed in independent datasets, the clinical diagnostic model constructed by these genes provided reference for clinical decision-making, but also the ceRNA network revealed their complex regulatory mechanisms. Unsupervised clustering analysis discovered two ferroptosis subtypes with distinct gene expression, immunological microenvironment, and biological functioning pathways. Notably, CD44 was found to be closely associated with many immune cells, most immune responses, and HLA genes, as well as prognosis, immune cell infiltration, TMB, and MSI in patients with a variety of tumors, suggesting it may be a potential intervention target for human diseases including AAV renal injury and tumors. Conclusions:Ferroptosis in AAV with renal injury is significantly correlated with the immunological microenvironment. For AAV with renal injury and tumors, CD44 could be a useful intervention target.

Cuproptosis is the most recently identified copper-dependent cell death form that influences tricarboxylic acid (TCA) cycle. However, the relationship between cuproptosis and clinical prognosis, tumor microenvironment infiltration (TME), and response to immunotherapy remains unclear. Thus, we performed the following analysis. Single-sample gene-set enrichment analysis (ssGSEA) was employed to construct cuproptosisScore (cpS) and 1378 gastric cancer (GC) patients from five independent public datasets were classified into high- or low-cpS groups according to the median of cpS. Then the impacts of cuproptosis on tumor microenvironment infiltration (TME), biological function, response to immunotherapy, and clinical prognosis of GC were evaluated. RiskScore and nomogram were constructed using Lasso Cox regression algorithm to validate its predictive capability in GC patients. Compared to patients with high cpS, patients with low cpS exhibited poorer prognosis, higher TNM stage, and stronger stromal activation. Meanwhile, the analysis of response to immunotherapy confirmed patients with high cpS could better benefit from immunotherapy and had a better susceptibility to chemotherapeutic drugs. 9 prognosis-related signatures were collected based on differentially expressed genes (DEGs) of cpS groups. Finally, a riskScore model was constructed using the multivariate Cox (multi-Cox) regression coefficients of prognosis-related signatures and had an excellent capability of predicting 1-, 3-, and 5-year survival in GC patients. In summary, this study revealed the role of curproptosis in TME, response to immunotherapy, and clinical prognosis in GC, which highlighted the significant clinical implications of curproptosis and provided novel ideas for the therapeutic application of cuproptosis in GC.

(1) Background: To assess whether the start time influences the outcomes of esophagogastroduodenoscopy (EGD). (2) Methods: We retrospectively analyzed the clinical data of patients who underwent EGD between January 2021 and December 2021 in our endoscopy center. The EGD were divided into three shifts, according to the start time. The lesion detection rate (LDR) and endoscopy biopsy rate (EBR) were used to evaluate the quality of the EGD. (3) Results: A total of 14,597 procedures were included in this study. The LDR of shift 2 was significantly lower than that of shift 1 (62.4% vs. 58.5%; p < 0.001). The EBR of shift 1 (37.4% vs. 31.5%; p < 0.001) and shift 3 (35.5% vs. 31.5%; p = 0.024) were significantly higher than that of shift 2; the EBR in shift 1 did not differ significantly from shift 3 (p = 0.280). The multivariable analysis for the EGD performed before 14:00 demonstrated a graded decrease in the LDR and EBR after adjusting the confounders (p < 0.001). (4) Conclusion: In a continuous working period, the lesion detection and biopsy submission of EGD are superior to those in the first three hours compared to the last three hours; the LDR and EBR decreased as the day progressed, probably due to the endoscopists’ fatigue.