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Heterotaxy syndrome, also known as situs ambiguous, is a spectrum of pathology due to loss of the normal right-to-left asymmetry of the thoraco-abdominal organs. This report describes the case of a 39-year-old female, previously well, who presented with bowel obstruction. CT showed features of left isomerism, with malrotation and volvulus. Contribution: Heterotaxy syndrome consists of cardiac and non-cardiac manifestations. Imaging studies play a crucial role in the individualised management of the patient.
RESUMO
The connection between cardiovascular illnesses and the gut microbiota has drawn more and more attention in recent years. According to research, there are intricate relationships between dietary elements, gut bacteria, and their metabolites that affect cardiovascular health. In this study, the role of gut microbiota in cardiovascular disorders is examined, with an emphasis on the cardiac consequences brought on by changes in gut microbiota. This essay discusses the gut-heart axis in depth and in detail. It talks about clinical research looking at how soy consumption, probiotic supplements, and dietary changes affected gut microbiota and cardiovascular risk variables. Our goal is to clarify the possible pathways that connect gut microbiota to cardiovascular health and the implications for upcoming treatment approaches. The authors examine the composition, roles, and effects of the gut microbiota on cardiovascular health, including their contributions to hypertension, atherosclerosis, lipid metabolism, and heart failure. Endotoxemia, inflammation, immunological dysfunction, and host lipid metabolism are some of the potential processes investigated for how the gut microbiota affects cardiac outcomes. The research emphasizes the need for larger interventional studies and personalized medicine strategies to completely understand the complexity of the gut-heart axis and its implications for the management of cardiovascular disease. The development of novel treatment strategies and cutting-edge diagnostic technologies in cardiovascular medicine may be facilitated by a better understanding of this axis.
RESUMO
Esophageal cancer is a major cause of cancer-related mortality worldwide, with significant regional disparities. Early detection of precursor lesions is essential to improve patient outcomes. Artificial intelligence (AI) techniques, including deep learning and machine learning, have proved to be of assistance to both gastroenterologists and pathologists in the diagnosis and characterization of upper gastrointestinal malignancies by correlating with the histopathology. The primary diagnostic method in gastroenterology is white light endoscopic evaluation, but conventional endoscopy is partially inefficient in detecting esophageal cancer. However, other endoscopic modalities, such as narrow-band imaging, endocytoscopy, and endomicroscopy, have shown improved visualization of mucosal structures and vasculature, which provides a set of baseline data to develop efficient AI-assisted predictive models for quick interpretation. The main challenges in managing esophageal cancer are identifying high-risk patients and the disease's poor prognosis. Thus, AI techniques can play a vital role in improving the early detection and diagnosis of precursor lesions, assisting gastroenterologists in performing targeted biopsies and real-time decisions of endoscopic mucosal resection or endoscopic submucosal dissection. Combining AI techniques and endoscopic modalities can enhance the diagnosis and management of esophageal cancer, improving patient outcomes and reducing cancer-related mortality rates. The aim of this review is to grasp a better understanding of the application of AI in the diagnosis, treatment, and prognosis of esophageal cancer and how computer-aided diagnosis and computer-aided detection can act as vital tools for clinicians in the long run.