Gastroenterology

Recent Advances and Future Directions in Sonodynamic Therapy for Cancer Treatment.

Deep-tissue solid cancer treatment has a poor prognosis, resulting in a very low 5-year patient survival rate. The primary challenges facing solid tumor therapies are accessibility, incomplete surgical removal of tumor tissue, the resistance of the hypoxic and heterogeneous tumor microenvironment to chemotherapy and radiation, and suffering caused by off-target toxicities. Here, sonodynamic therap...

Prognostic Impact of Tumor Cell Nuclear Size Assessed by Artificial Intelligence in Esophageal Squamous Cell Carcinoma.

Tumor cell nuclear size (NS) indicates malignant potential in breast cancer; however, its clinical significance in esophageal squamous cell carcinoma (ESCC) is unknown. Artificial intelligence (AI) can quantitatively evaluate histopathological findings. The aim was to measure NS in ESCC using AI and elucidate its clinical significance. We investigated the relationship between NS assessed by AI and...

Current Status of Artificial Intelligence Use in Colonoscopy.

BACKGROUND: Artificial intelligence (AI) has significantly impacted medical imaging, particularly in gastrointestinal endoscopy. Computer-aided detect...

Pathomics-based machine learning models for predicting pathological complete response and prognosis in locally advanced rectal cancer patients post-neoadjuvant chemoradiotherapy: insights from two independent institutional studies.

BACKGROUND: Accurate prediction of pathological complete response (pCR) and disease-free survival (DFS) in locally advanced rectal cancer (LARC) patie...

Butyric acid alleviates LPS-induced intestinal mucosal barrier damage by inhibiting the RhoA/ROCK2/MLCK signaling pathway in Caco2 cells.

Butyric acid (BA) can potentially enhance the function of the intestinal barrier. However, the mechanisms by which BA protects the intestinal mucosal ...

Association between serum endocan levels and organ failure in hospitalized patients with cirrhosis.

BACKGROUND & AIMS: Acute-on-chronic liver failure is a syndrome characterized by organ failure and high short-term mortality. The lack of reliable bio...

Impact of a trace mineral injection at weaning on growth, behavior, and inflammatory, antioxidant, and immune responses of beef calves.

Two experiments evaluated the effects of an injectable trace mineral (ITM) solution at weaning on trace mineral (TM) status, inflammatory and antioxid...

Accuracy of machine learning models for pre-diagnosis and diagnosis of pancreatic ductal adenocarcinoma in contrast-CT images: a systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic ability and methodological quality of ML models in detecting Pancreatic Ductal Adenocarcinoma (PDAC) in Contrast C...

Construction of a random survival forest model based on a machine learning algorithm to predict early recurrence after hepatectomy for adult hepatocellular carcinoma.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) exhibits a propensity for early recurrence following liver resection, resulting in a bleak prognos...

Evaluating the Inhibitory Effects of Probiotic Bacteria and Propolis Extracts on the Growth and Histopathological Changes in Gastric Tissues of Challenged Wistar Rats.

BACKGROUND: is a significant contributor to a range of gastrointestinal conditions, with conventional treatment methods primarily relying on antibiot...

A comparative analysis of unilateral biportal endoscopic and open laminectomy in multilevel lumbar stenosis.

BACKGROUND: Approximately 103 million people across the globe suffer from symptomatic lumbar spinal stenosis, impacting their health and quality of li...

Deep Learning-Enabled Rapid Metabolic Decoding of Small Extracellular Vesicles via Dual-Use Mass Spectroscopy Chip Array.

The increasing focus of small extracellular vesicles (sEVs) in liquid biopsy has created a significant demand for streamlined improvements in sEV isol...

Application of artificial intelligence in gastrointestinal endoscopy in Vietnam: a narrative review.

The utilization of artificial intelligence (AI) in gastrointestinal (GI) endoscopy has witnessed significant progress and promising results in recent ...

Evaluation of the anti-spasmodic activity of essential oils of fruits and its main chemical component "perillaldehyde" on intestinal smooth muscle contractions of rodents: and approaches.

ETHNOPHARMACOLOGICAL RELEVANCE: In Moroccan traditional medicine, plants from the Apiaceae family are widely utilized in folk medicine to treat variou...

Biosecurity measures reducing spp. and hepatitis E virus prevalence in pig farms-a systematic review and meta-analysis.

spp. and hepatitis E virus (HEV) are significant foodborne zoonotic pathogens that impact the health of livestock, farmers, and the general public. T...

Cell-free supernatant of (RAMULAB51) from coconut inflorescence sap (Neera) enhances glucose uptake and PPAR-γ in 3T3-L1 adipocytes and inhibits α-glucosidase and α-amylase.

INTRODUCTION: Lactic acid bacteria are prized for their probiotic benefits and gut health improvements. This study assessed five LAB isolates from Nee...

A clinical pilot trial of an artificial intelligence-driven smart phone application of bowel preparation for colonoscopy: a randomized clinical trial.

BACKGROUND: High-quality bowel preparation is paramount for a successful colonoscopy. This study aimed to explore the effect of artificial intelligenc...

Machine learning analysis of CD4+ T cell gene expression in diverse diseases: insights from cancer, metabolic, respiratory, and digestive disorders.

CD4 T cells play a pivotal role in the immune system, particularly in adaptive immunity, by orchestrating and enhancing immune responses. CD4 T cell-r...

Ethics and trustworthiness of artificial intelligence in Hepato-Pancreato-Biliary surgery: a snapshot of insights from the European-African Hepato-Pancreato-Biliary Association (E-AHPBA) survey.

BACKGROUND: Hepato-Pancreato-Biliary (HPB) surgery is a complex specialty and Artificial Intelligence (AI) applications have the potential to improve ...

Application of machine learning methods for predicting esophageal variceal bleeding in patients with cirrhosis.

OBJECTIVE: To develop and compare machine learning models based on CT morphology features, serum biomarkers, and basic physical conditions to predict ...