Know Yourself Inside Out Mastering Health Metrics

In the age of personalized medicine, flying blind with your health optimization strategy is no longer acceptable. Dr. Jin-Xiong She, founder of Jinfiniti and leading researcher in cellular energy metabolism, presents a masterclass in transforming your approach to health monitoring from reactive to predictive, from generic to precision-targeted.

This comprehensive session breaks down the science behind meaningful health metrics, with special focus on cellular energy biomarkers like NAD+ that serve as foundational indicators of aging and vitality. Dr. She will guide attendees through the critical process of selecting appropriate tests, understanding the nuanced interpretation of results, and most importantly, translating data into actionable optimization protocols. You'll discover which biomarkers provide the most valuable insights for longevity, how to establish your personal baseline, and when to retest for maximum effectiveness.

Drawing from Jinfiniti's groundbreaking work in NAD+ testing and optimization, the presentation reveals why precision testing beats guesswork every time. Learn to identify the subtle cellular signals that precede age-related decline, understand the interconnected nature of metabolic health markers, and develop a systematic approach to tracking your optimization journey. Dr. She shares real-world case studies demonstrating how targeted interventions based on accurate testing deliver superior outcomes compared to generic supplementation approaches.

This session equips longevity enthusiasts and biohackers with the analytical frameworks needed to make informed decisions about their health optimization strategies. Walk away with practical tools for building your personal health dashboard, understanding when interventions are working, and course-correcting when they're not. In a field often dominated by trends and testimonials, this evidence-based approach to self-quantification provides the foundation for sustainable, measurable improvements in healthspan.