Longevity Papers

Metabolism unfolds within specific organelles in eukaryotic cells. Lysosomes are highly metabolically active organelles, and their metabolic states dynamically influence signal transduction, cellular homeostasis and organismal physiopathology. Despite the importance of lysosomal metabolism, a method for its in vivo measurement is currently lacking. Here we report a fluorescence-detected mid-infrared photothermal microscope (FILM) implemented with optical boxcar demodulation, artificial intelligence-assisted data denoising and spectral deconvolution, to map metabolic activity and composition of individual lysosomes in living cells and organisms. Using this method, we uncovered lipolysis and proteolysis heterogeneity across lysosomes within the same cell, as well as early-onset lysosomal dysfunction during organismal aging. In addition, we discovered organelle-level metabolic changes associated with diverse lysosomal storage diseases. This method holds the broad potential to profile metabolic fingerprints of individual organelles within their native context and quantitatively assess their dynamic changes under different physiological and pathological conditions, providing a high-resolution chemical cellular atlas.

Cellular senescence arises through replicative exhaustion or acute stress, yet whether these distinct triggers share a reproducible transcriptional organization has remained unresolved. Seven public human fibroblast RNA-seq datasets were integrated across both trigger types, moving from differential expression through Gene Ontology and Reactome enrichment to protein-protein interaction network embedding within a single harmonized framework. Both triggers converged on concordant repression of replication and chromatin programs alongside induction of inflammatory and extracellular matrix outputs. Cross-trigger combination identified 263 commonly repressed and 112 commonly induced GO terms, with consistently higher enrichment scores in the repressed set, and 145 versus 13 shared Reactome pathways. Conserved induction of calcium ion homeostasis and membrane potential regulation, and conserved repression of RHO GTPase-Formin signaling, extended the shared program beyond canonical SASP biology into dimensions not previously described in human fibroblasts. Interactome embedding, applied here for the first time in a cross-trigger senescence framework, identified ten genes occupying both induced and repressed neighborhoods simultaneously, a structural layer invisible to enrichment analysis alone. ELAVL1 coordinates SASP output and growth arrest post-transcriptionally, while suppressed PARP1 alongside active ATM defines a self-reinforcing damage configuration. These results provide a quantitative cross-study reference and a structured basis for senotherapeutic candidate prioritization.

Quantifying biological aging is crucial for understanding functional decline before the onset of morbidity. While many accelerated aging and frailty measures based on clinical data exist for humans and several for rodent models of aging, there are few options for non-human primates (NHPs). NHP clinical data has several unique features including a lack of clinically delineated normative values for features and variability in data collection over long lifespans. There are also wide discrepancies in the number of available clinical measures and number of animals across data sets. To address these challenges, we developed and validated "Aging Resilience" (AR) metrics using longitudinal, routine clinical data from two distinct non-human primate cohorts: 4,328 baboons and 281 rhesus macaques. We trained five computational models-including Linear Mixed-Effects Models, Random Forest, and Recurrent Neural Networks (RNN)-to predict chronological age, subsequently deriving AR metrics that represent the velocity (Rate of Aging) and cumulative burden (Normalized Cumulative Aging) of physiological deviation. While linear models achieved high precision in predicting chronological age (test R2 up to 0.99), they correlated poorly with actual lifespan. In contrast, AR metrics derived from non-linear models (RNN and Random Forest) displayed strong predictive validity for mortality (Pearson's r > 0.8). These findings highlight a critical paradox: models that best predict chronological age do not necessarily capture the biological resilience determining healthspan. This study establishes a scalable framework for monitoring biological aging in translational models using standard veterinary records.

Collagen, a central component of the extracellular matrix (ECM), precisely regulates tissue mechanical properties and biological functions through hierarchical assembly, playing a vital role in maintaining homeostasis. However, the molecular mechanism of assembly remains poorly understood, limiting insights into tissue remodeling, aging, and ECM-related diseases. Here, we employ time-resolved cryo-electron microscopy to resolve two critical hierarchical intermediates in fibrillar collagen assembly, proposing the 3D collagen assembly pathway. We identify a metastable triple-helical conformation as the fundamental assembly unit, whose structural lability propagates through the assembly cascade, rendering the process sensitive to microenvironmental perturbations. Through hierarchical assembly, metastable intermediates achieve enhanced structural stability, culminating in the formation of stable collagen that retains its integrity under physiological conditions. In contrast, structural defects in intermediates lead to aberrant assembly and disruption of ECM integrity. Functional assays reveal that intermediates lacking D-band retain biological activity. Our findings redefine the fibrillar collagen assembly as a hierarchical, time-resolved cascade driven by metastable intermediates and propose the fundamental F-Z-F rules. The metastable triple helix provides a structural basis for hierarchical assembly and suggests a potential link between abnormal fibrillar collagen assembly and aging-related matrix dysfunction, offering valuable insights into collagen assembly and its role in aging diseases.

Aging, stress-related disorders, and chronic disease are often examined across separate domains-stress physiology, nutrition, psychiatry, and geroscience-despite converging on shared phenotypes of functional decline and reduced resilience. Although adaptive responses to stress are well characterized, why comparable exposures yield sustained resilience in some individuals but progressive dysfunction in others remains insufficiently explained. We propose that the missing unifying constraint is not stress exposure itself, but the bioenergetic capacity to complete recovery. We reframe stress adaptation as a cyclical process comprising response, adaptation, and recovery, emphasizing that recovery is an active, ATP-dependent phase conditionally funded within a finite bioenergetic system. When mitochondrial processing capacity and redox flexibility are constrained, adaptive programs may persist beyond their functional window, contributing to mitochondrial congestion, epigenetic gridlock, and progressive loss of physiological plasticity-even in the absence of overt pathology. Within this perspective, we introduce Exposure-Related Malnutrition (ERM) as a proposed conceptual model describing a clinically interpretable and potentially reversible phenotype of unresolved bioenergetic triage. ERM is proposed to describe a state of relative undernutrition arising from chronic mismatch between energetic demand and recovery capacity, often occurring despite nominal intake and laboratory values within reference ranges. Distinct from frailty, sarcopenia, cachexia, metabolic syndrome, and classical malnutrition, ERM may reflect an upstream constraint in ATP-dependent recovery rather than structural loss, inflammatory wasting, metabolic thresholds, or inadequate intake. By integrating evolutionary allocation theory, developmental calibration, stress physiology, and mitochondrial mechanics, ERM is proposed to offer a unifying integrative framework for functional decline across aging and chronic disease. Clinically, this perspective shifts risk assessment from isolated thresholds toward coordinated biomarker patterns, trajectories, and recovery kinetics, potentially enabling recognition of vulnerability before incomplete resolution consolidates into irreversible pathology. We further outline translational implications of a recovery-centered approach, positioning mitochondrial processing capacity and intercellular bioenergetic support as modifiable determinants of long-term resilience.