ABSTRACT
The gut-brain axis (GBA) is a two-way communication system that is influenced by signals from the nervous system, hormones, metabolism, the immune system, and microbes. The GBA may play a key role in gastrointestinal and neurological illnesses. Signaling events from the gut can regulate brain function. As a result, mounting data point to a connection between autoimmune disorders (AIDs), both neuroinflammatory and neurodegenerative diseases, and the GBA. Clinical, epidemiological, and experimental studies have shown that a variety of neurological illnesses are linked to alterations in the intestinal environment, which are suggestive of disease-mediated inter-organ communication between the gut and the brain. This review's objective is to draw attention to the clinical and biological relationship between the gut and the brain, as well as the clinical importance of this relationship for AIDs, neurodegeneration, and neuroinflammation. We also discuss the dysbiosis in the gut microbiota that has been linked to various AIDs, and we make some assumptions about how dietary changes such as prebiotics and probiotics may be able to prevent or treat AIDs by restoring the composition of the gut microbiota and regulating metabolites.
ABSTRACT
Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.
ABSTRACT
The rise in the cases of acute hepatitis of unknown aetiology in the paediatric population is a public health concern worldwide and investigations to ascertain the exact cause of this outbreak are being carried out extensively by the concerned authorities. In early April 2022, the World Health Organisation (WHO) issued a warning on acute hepatitis of unknown origin in children. Since then, there have been continuing additional reports of the cases globally. The recent cases of acute hepatitis of unknown aetiology are more prevalent in children aged <10 years, are more clinically severe, and a high percentage of infected individuals develop acute liver failure in contrast to the previous cases. The aetiology of this disease and its complete pathogenesis is still unclear. This review critically focuses on the current leading hypothesis and provides comprehensive information regarding this recent outbreak that can help in handling the situation by a better understanding of its aetiology.
