Exploring the impact of diet and nutrition on vitiligo: A systematic review of dietary factors and nutritional interventions.

BACKGROUND: Vitiligo, an autoimmune skin disorder linked to hormonal and genetic factors, results in reduced pigmentation due to a gradual decline in melanocyte activity. This systematic review delves into the role of dietary intervention and nutrition in managing vitiligo. METHODS: A comprehensive search on PubMed, Google Scholar, and European PMC identified 214 studies, with 14 meeting inclusion criteria post-screening. The selected studies primarily explored the impact of dietary supplements on disease activity. RESULTS: Heavy metal exposure, specifically Cd, Pb, and Hg, indicated potential links to heightened reactive oxygen species and vitiligo development. Conflicting evidence emerged regarding the role of trace minerals (Zn and Cu), with some studies suggesting deficiencies and others proposing excesses in vitiligo patients. Vitamins with anti-inflammatory properties like vitamin C, D, and B12, along with antioxidants, were investigated for their potential in repigmentation strategies. Additionally, polyunsaturated fatty acids (PUFAs), especially in varying types of fat consumption, were implicated. Emphasizing the need to reduce reliance on pharmacological and phototherapy interventions, the review uncovers novel roles for dietary supplements as adjuncts or flare reducers. CONCLUSION: While dietary interventions cannot be thought of as a standalone therapy, they still make a case for being used as adjuncts. Large scale clinical trials are warranted to establish strong evidence and protocols, and might also help reduce the dependency on pharmacological methods, which come with their adverse effect profiles.

Exploring the current and prospective role of artificial intelligence in disease diagnosis.

Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems, providing assistance in a variety of patient care and health systems. The aim of this review is to contribute valuable insights to the ongoing discourse on the transformative potential of AI in healthcare, providing a nuanced understanding of its current applications, future possibilities, and associated challenges. The authors conducted a literature search on the current role of AI in disease diagnosis and its possible future applications using PubMed, Google Scholar, and ResearchGate within 10 years. Our investigation revealed that AI, encompassing machine-learning and deep-learning techniques, has become integral to healthcare, facilitating immediate access to evidence-based guidelines, the latest medical literature, and tools for generating differential diagnoses. However, our research also acknowledges the limitations of current AI methodologies in disease diagnosis and explores uncertainties and obstacles associated with the complete integration of AI into clinical practice. This review has highlighted the critical significance of integrating AI into the medical healthcare framework and meticulously examined the evolutionary trajectory of healthcare-oriented AI from its inception, delving into the current state of development and projecting the extent of reliance on AI in the future. The authors have found that central to this study is the exploration of how the strategic integration of AI can accelerate the diagnostic process, heighten diagnostic accuracy, and enhance overall operational efficiency, concurrently relieving the burdens faced by healthcare practitioners.