Gastroesophageal reflux disease (GERD) is a complex disease with a high worldwide prevalence. The Los Angeles classification (LA-grade) system is meaningful for assessing the endoscopic severity of...

The risk of gastric cancer can be predicted by gastroscopic manifestation recognition and the Kyoto Gastritis Score. This study aims to validate the applicability of AI approaches for recognizing gastroscopic manifestations according to the definition of Kyoto Gastritis Score, with the goal of improving early gastric cancer detection and reducing gastric cancer mortality. In this retrospective study, 29013 gastric endoscopy images were collected and carefully annotated into five categories according to the Kyoto Gastritis Score, i.e. atrophy (A), diffuse redness (DR), enlarged folds (H), intestinal metaplasia (IM), and nodularity (N). As a multi-label recognition task, we propose a deep learning approach composed of five GAM-EfficientNet models, each performing a multiple classification to quantify gastroscopic manifestations, i.e. no presentation or the severity score 0–2. This approach was compared with endoscopists of varying years of experience in terms of accuracy, specificity, precision, recall, and F1 score. The approach demonstrated good performance in identifying the five manifestations of the Kyoto Gastritis Score, with an average accuracy, specificity, precision, recall, and F1 score of 78.70%, 91.92%, 80.23%, 78.70%, and 0.78, respectively. The average performance of five experienced endoscopists was 72.63%, 90.00%, 77.68%, 72.63%, and 0.73, while that of five less experienced endoscopists was 66.60%, 87.44%, 70.88%, 66.60%, and 0.66, respectively. The sample t-test indicates that the approach’s average accuracy, specificity, precision, recall, and F1 score for identifying the five manifestations were significantly higher than those of less experienced endoscopists, experienced endoscopists, and all endoscopists on average (p < 0.05). Our study demonstrates the potential of deep learning approaches on gastric manifestation recognition over junior, even senior endoscopists. Thus, the deep learning approach holds potential as an auxiliary tool, although prospective validation is still needed to assess its clinical applicability.

Purpose: Type 2 diabetes mellitus (T2DM) is among the risk factors for the occurrence and development of cancer. Metformin is a potential anticancer drug. Epidermal growth factor receptor (EGFR) plays an important role in the progression of oral squamous cell carcinoma(OSCC), but the relationship between metformin and EGFR expression in OSCC remains unclear.Methods: This study involved the immunohistochemical detection of EGFR expression in cancer tissues of patients with T2DM and OSCC. The patients were divided into groups according to whether they were taking metformin for the treatment of T2DM, and the expression of EGFR in different groups was compared. Correlation analysis between the expression of EGFR and the fluctuation value of fasting blood glucose (FBG) was carried out. Immunohistochemistry was used to detect the expression of EGFR in cancer tissues of patients with recurrent OSCC. These patients had normal blood glucose and took metformin for a long time after the first operation.Results: EGFR expression in T2DM patients with OSCC taking metformin was significantly lower than that in the non-metformin group. FBG fluctuations were positively correlated with the expression of EGFR in the OSCC tissues of the non-metformin group of T2DM patients. In patients with recurrent OSCC with normal blood glucose, metformin remarkably reduced the expression of EGFR in recurrent OSCC tissues.Conclusion: Metformin may regulate the expression of EGFR in a way that does not rely on lowering blood glucose. These results may provide further evidence for metformin in the treatment of OSCC.

Objective To investigate the sagittal hip-pelvic kinematics in symptomatic cam-type femoroacetabular impingement (FAI) patients in the process of sitting down and compare their difference between patients with sitting pain complaint and those without. Methods Twenty-nine symptomatic cam-type FAI patients were recruited from our clinic between May 2018 and October 2018. Patients were categorized into two groups depending on whether they complain of pain in prolonged sitting or not. The pelvic-femoral measurements were assessed with a set of lateral pelvic radiography in sitting and standing respectively. Pelvic incidence (PI), sacral slope (SS), and proximal femoral shaft angle (PFSA) were measured on lateral pelvic radiography, and then pelvic tilting, apparent hip flexion, true hip flexion, and the pelvic-femoral ratio were calculated to investigate the kinematic change from standing to sitting position. Demographic measurements, hip morphology measurements, functional measurements, visual analog scale (VAS), and pelvic-femoral measurements were compared between the two groups. Results Thirteen cases without sitting pain complaint and 16 cases with sitting pain complaint were stratified to Group N and Group P respectively. No was significant difference in age, body mass index (BMI), and gender between the two groups. Hip morphology measurements (α angle and lateral center-edge angle) and functional measurements (iHOT-12) showed no significant difference between the two groups. However, the mean VAS of pain while sitting was 0.5 ± 0.4 and 1.6 ± 0.6 in Group N and Group P respectively (P = 0.005). Patients with sitting pain complaint have increased pelvic PI compared to those without (50.1° ± 6.5° and 44.2° ± 7.6°, P = 0. 042). The changes in SS (pelvic tilting) from standing to sitting in Group N was significantly larger than that in Group P (21.8° ± 7.0° and 15.1° ± 6.5°, P = 0.012). Although no significant difference in apparent hip flexion and true hip flexion was found. Patients without sitting pain complaint demonstrated a higher pelvic-femoral ratio (22.8% ± 7.9% and 16.1% ± 7.5%, P = 0.010) compared to those with sitting pain complaint. Conclusion Sagittal pelvic-femoral kinematics could have an influence on the symptomology of cam-type FAI. The small PI and insufficient sagittal pelvic tilting in the process of sitting down could be related to the complaint of sitting pain in patients with symptomatic cam-type FAI.

Bacterial liver abscess (BLA), accounting for approximately 80% of all liver abscesses, is a severe suppurative infection of the liver. Although gut microbiota dysbiosis has been implicated in BLA pathogenesis, causal evidence remains limited. Here, we integrate Mendelian randomization (MR) and clinical cohort studies to systematically evaluate the causal role of gut microbiota in BLA. Using summary-level genetic data from MiBioGen, GWAS Catalog, and the Pan-UK Biobank, we identified several causal microbial taxa: Coprococcus, Veillonellaceae (including Dialister), and Klebsiella were positively associated with BLA risk, whereas Bacteroides and Bifidobacterium appeared protective. Clinical validation confirmed significant enrichment of Veillonella, Dialister, and Streptococcus in the gut and oral microbiota of BLA patients, contrasting with the predominance of Bacteroides and Bifidobacterium in healthy controls. Klebsiella was the most abundant genus in abscess pus, and gut microbial metabolic profiling revealed marked upregulation of glycolytic pathways in BLA patients. These results indicate that gut dysbiosis exacerbates BLA development through microenvironmental disruption and metabolic reprogramming. Our findings provide mechanistic insights into BLA etiology and suggest microbiota-targeted interventions as promising strategies for prevention and treatment.

Colorectal cancer is the third most common cancer and the second leading cause of cancer‐related deaths. Immune cells in the tumor microenvironment play an important role in the development of tumors. In this study, CIBERSORT was used to estimate the subset of the immune cells using bulk gene expression data (i.e., TCGA, GEO, and cBioPortal databases). 1,087 samples were included in the analysis. The results revealed that among the 22 immune cell subsets that were evaluated, resting and activated NK cells, macrophage M1 and M2, and resting mast cells are associated with significant improvements in patient survival of colorectal cancer. The 15‐year survival rates for the training cohort showed 49.1% and 32.5%, respectively, for the low‐ and high‐risk groups. Likewise, the validation and entire cohorts showed 77.3% versus 47.2% and 65.3% versus 46.5%, respectively, for the low‐ and high‐risk groups. Also, the prognostic immune score in predicting the chemotherapy effects showed that the low‐risk group had a better survival superiority over the high‐risk group, whether patients received chemotherapy or not. The gene set enrichment analysis showed that the low‐risk group was highly enriched in pathways or processes related to immune response. The immune checkpoint assessment revealed significantly higher mRNA expressions of CTLA4 in the lower risk group than in the higher risk group. Altogether, this study offers information that could improve the prognosis of colorectal cancer.