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Topic Review
Antioxidant and Anti-Inflammatory Phytochemicals for Inflammatory Bowel Disease
Inflammatory bowel disease (IBD) mainly comprises Crohn’s disease (CD) and ulcerative colitis (UC) and is a group of chronic relapsing disorders characterized by inflammation of the gastrointestinal tract with variable phenotypic expression. Multiple factors have been implicated in the etiology of IBD, including environmental, genetic, microbiological and immunological interactions. However, the exact reasons remain unclear, although substantial progress in elucidating the complexity of IBD manifestation has been made in the past decades. There is clinical overlap of symptoms of CD and UC, including bloody or watery diarrhea, recurrent abdominal pain, tenesmus as well as non-specific systemic symptoms such as fatigue, fever and weight loss. CD can affect various parts of the intestine, i.e., both small and large intestine, while UC is known to affect only the colon. IBD usually follows a lifelong pattern of remissions and flare-ups that impacts the quality of life of patients. The inflammation of the gastrointestinal tract during flare-ups is mediated by neutrophils that release cytokines, enzymes and reactive oxygen species (ROS) leading to damage and even ulceration of the mucosa.
  • 89
  • 19 Mar 2024
Topic Review
Apoptosis and Autophagy in Human Colorectal Cancer Development
Colorectal cancer (CRC) remains a major life-threatening malignancy. Apoptosis and autophagy are two processes that share common signaling pathways, are linked by functional relationships and have similar protein components. During the development of cancer, the two processes can trigger simultaneously in the same cell, causing, in some cases, an inhibition of autophagy by apoptosis or apoptosis by autophagy. Malignant cells that have accumulated genetic alterations can take advantage of any alterations in the apoptotic process and as a result, progress easily in the cancerous transformation. Autophagy often plays a suppressive role during the initial stages of carcinogenicity, while in the later stages of cancer development it can play a promoting role. It is extremely important to determine the regulation of this duality of autophagy in the development of CRC and to identify the molecules involved, as well as the signals and the mechanisms behind it. All the reported experimental results indicate that, while the antagonistic effects of autophagy and apoptosis occur in an adverse environment characterized by deprivation of oxygen and nutrients, leading to the formation and development of CRC, the effects of promotion and collaboration usually involve an auxiliary role of autophagy compared to apoptosis. 
  • 342
  • 20 Jun 2023
Topic Review
Appetite Regulation and Bariatric Surgery
Obesity remains a common metabolic disorder and a threat to health as it is associated with numerous complications. Lifestyle modifications and caloric restriction can achieve limited weight loss. Bariatric surgery is an effective way of achieving substantial weight loss as well as glycemic control secondary to weight-related type 2 diabetes mellitus.
  • 97
  • 07 Mar 2024
Topic Review
Artificial Endoscopy
Artificial intelligence (AI) is defined as any machine that has cognitive functions mimicking humans for problem solving or learning. AI has already been tested in several fields of endoscopy, such as in the detection of Barrett’s esophagus or the evaluation of adenoma detection rate during colonoscopy.
  • 423
  • 23 Feb 2022
Topic Review
Artificial Intelligence Application to Pancreas Imaging
Despite the increasing rate of detection of incidental pancreatic cystic lesions (PCLs), current standard-of-care methods for their diagnosis and risk stratification remain inadequate. Intraductal papillary mucinous neoplasms (IPMNs) are the most prevalent PCLs. The existing modalities, including endoscopic ultrasound and cyst fluid analysis, only achieve accuracy rates of 65–75% in identifying carcinoma or high-grade dysplasia in IPMNs. Furthermore, surgical resection of PCLs reveals that up to half exhibit only low-grade dysplastic changes or benign neoplasms. To reduce unnecessary and high-risk pancreatic surgeries, more precise diagnostic techniques are necessary. A promising approach involves integrating existing data, such as clinical features, cyst morphology, and data from cyst fluid analysis, with confocal endomicroscopy and radiomics to enhance the prediction of advanced neoplasms in PCLs. Artificial intelligence and machine learning modalities can play a crucial role in achieving this goal. 
  • 251
  • 30 Oct 2023
Topic Review
Artificial Intelligence for Gastrointestinal Diseases
The development of convolutional neural networks has achieved impressive advances of machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in the field of gastrointestinal (GI) diseases. AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall diagnostic accuracy. Nevertheless, there data are lacking on side effects of AI in the gastroenterology field, and high-quality studies comparing the performance of AI networks to health care professionals are still limited.
  • 553
  • 24 Sep 2021
Topic Review
Artificial Intelligence in Colonoscopy
The early endoscopic identification, resection, and treatment of precancerous adenoma and early-stage cancer has been shown to reduce not only the prevalence of colorectal cancer but also its mortality rate. Recent advances in endoscopic devices and imaging technology have dramatically improved the ability to detect colorectal lesions and predict their pathological diagnosis. In addition to this, rapid advances in artificial intelligence (AI) technology mean that AI-related research and development is now progressing in the diagnostic imaging field, particularly colonoscopy, and AIs (i.e., devices that mimic cognitive abilities, such as learning and problem-solving) already approved as medical devices are now being introduced into everyday clinical practice. There is an increasing expectation that sophisticated AIs will be able to provide high-level diagnostic performance irrespective of the level of skill of the endoscopist.
  • 371
  • 10 Jun 2022
Topic Review
Artificial Intelligence in Digestive Healthcare
With modern society well entrenched in the digital area, the use of Artificial Intelligence (AI) to extract useful information from big data has become more commonplace in our daily lives than we perhaps realize. A number of medical specialties such as Gastroenterology rely heavily on medical images to establish disease diagnosis and patient prognosis, as well as to monitor disease progression. Moreover, some such imaging techniques have been adapted so that they can potentially deliver therapeutic interventions. The digitalization of medical imaging has paved the way for important advances in this field, including the design of AI solutions to aid image acquisition and analysis.
  • 404
  • 08 May 2023
Topic Review
Artificial Intelligence in Endoscopic Ultrasound
Endoscopic Ultrasound (EUS) is widely used for the diagnosis of bilio-pancreatic and gastrointestinal (GI) tract diseases, for the evaluation of subepithelial lesions, and for sampling of lymph nodes and solid masses located next to the GI tract. The role of Artificial Intelligence in healthcare in growing.
  • 268
  • 16 Jun 2023
Topic Review
Artificial Intelligence in Monitoring Inflammatory Bowel Disease
Crohn’s disease and ulcerative colitis remain debilitating disorders, characterized by progressive bowel damage and possible lethal complications. The growing number of applications for artificial intelligence in gastrointestinal endoscopy has already shown great potential, especially in the field of neoplastic and pre-neoplastic lesion detection and characterization, and is under evaluation in the field of inflammatory bowel disease management. The application of artificial intelligence in inflammatory bowel diseases can range from genomic dataset analysis and risk prediction model construction to the disease grading severity and assessment of the response to treatment using machine learning. 
  • 323
  • 02 Mar 2023
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