The Role of Garlic, Turmeric and Ginger in Preventing Chronic Disease in Prediabetic and Pre-Hyperlipidemia Population (Published)
This study looks up to the preventive role of garlic, turmeric, and ginger for delaying or reducing the progression of metabolic disturbances among individuals diagnosed with pre-diabetes and pre-hyperlipidaemia. These intermediary metabolic states are characterised by impaired glucose regulation, elevated lipid levels, increased oxidative stress, and low-grade chronic inflammation, which significantly increase the risk of developing type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD). Early nutritional interventions during this reversible stage may therefore offer an effective strategy to slow disease advancement. By integrating findings from experimental animal studies, human clinical trials, and phytochemical investigations, this research explores the multifaceted mechanisms through which these bioactive spices exert therapeutic effects. Garlic contains organosulfur compounds such as allicin, turmeric is rich in curcumin, and ginger provides gingerols and shogaols each possessing compelling antioxidant and anti-inflammatory properties. These composites are believed to reduce oxidative damage, suppress inflammatory pathways, enhance insulin sensitivity, improve pancreatic β-cell function, and regulate lipid metabolism. Evidence from preclinical and clinical studies indicates that supplementation with these spices may improve glycaemic parameters such as blood glucose in fasting and HbA1c, optimize lipid reports by controlling the cholesterol, good and bad cholesterol profile that results in reducing biomarkers of oxidative stress and systemic inflammation. Collectively, these findings suggest that garlic, turmeric, and ginger may serve as valuable nutraceutical agents in preventing or delaying the transition from pre-metabolic disorders to overt chronic diseases. However, despite promising findings, variations in dosage, bioavailability, and study design highlight the necessity for larger, well-controlled clinical tries to confirm long-term efficiency and ssecurity. Continued investigation will help establish standardized therapeutic guidelines and clarify the synergistic potential of combined supplementation.
Keywords: Diabetes Mellitus, cardiovascular disease, low density lipoprotein
Wearable Technology in Cardiovascular Health Monitoring: Current Trends and Future Directions (Published)
Recent Technological Advancements has shown tremendous impact in healthcare especially in personalized remote healthcare monitoring and management. Integration of this advancement in cardiovascular disease monitoring and management through Wearable biosensor technological advancements have emerged as powerful tools for personalized continuous monitoring of cardiovascular activities outside traditional clinical settings. The significant of these wearable technologies can be seen in 5Ps of clinical medicine for cardiovascular disease where it transformed patient care and improve its outcomes. This review provides an overview of wearable technologies’ evolution, advancements, challenges, applications clinical impact and future trends in cardiovascular medicine. We discussed the biosensor miniaturization, artificial intelligence (AI) and Machine learning integration, challenges and limitations of proliferating remote patient monitoring solutions for cardiovascular diseases. The impact of smartwatch wearables in the early detection of cardiovascular conditions through personalized health tracking, and remote patient management. Challenges such as data privacy concerns and regulatory hurdles are also addressed. The adoption of wearable technologies holds promise for shifting healthcare from reactive to proactive, enabling precision diagnostics, treatment optimization, and preventive strategies. Collaboration among healthcare stakeholders is essential to harnessing the full potential of wearables in cardiovascular medicine and ushering in a new era of personalized, proactive healthcare.
Keywords: Artificial Intelligence (AI), Biosensor, Machine Learning (ML), Wearable Technologies, cardiovascular disease