Autonomous driving paper index
Decoding aging clocks from a metabolomic perspective
One-line summary
Furthermore, we design a three-phase causal strategy structured as global screening, local verification, and dynamic validation.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Biological age quantifies functional decline beyond chronological aging; however, current epigenetic clocks exhibit limitations in resolving dynamic metabolic fluctuations and tissue-specific aging trajectories. Metabolomics emerges as a pivotal solution, representing the endpoint cascade of biological events shaped by multifactorial interactions that capture real-time physiological status. This review delineates aging clocks through a metabolomic lens and proposes an executable research workflow comprising data preprocessing, feature selection, model construction, and model application. Furthermore, we design a three-phase causal strategy structured as global screening, local verification, and dynamic validation. This integrated methodology aims to enhance the predictive accuracy of aging clocks while strengthening the biological plausibility and causal inference potential of metabolite-derived aging biomarkers. Additionally, we evaluate the translational prospects and applied value of metabolomic aging clocks, providing actionable guidance for extending human healthspan and advancing prevention and treatment strategies for aging-related pathologies.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments