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Latumalea, D.

Publications and source records attributed to Latumalea, D..

3 recordsLinked to original sources

Old worms, new tricks: dynamical instability explains late-life rejuvenation in C. elegans

How is it possible to double the lifespan of an organism already close to death? Many biological theories of aging fail to explain this phenomenon. At the Physics of Aging workshop, we presented and discussed late-life lifespan extension in Caenorhabditis elegans to illustrate how a simple stochastic dynamical systems model can account for dramatic geriatric interventions. We build on a Langevin-type instability framework in which aging is a manifestation of dynamical instability-a scenario where stochastic fluctuations amplify over time, driving the system toward a failure thresh-old at which death occurs as a first-passage event. The instability rate (equivalently, the inverse of the mortality-rate doubling time) quantifies the speed of this divergence: a larger means faster exponential growth of z, a steeper Gompertz slope, and a shorter lifespan. The failure threshold zmax{approx} /g, where g is the strength of nonlinear feedback, marks the point beyond which the system diverges irreversibly--physiologically, the saturation of metabolic and regulatory capacity. Within this dynamical-systems framework, auxin-induced degradation of the insulin/IGF-1 receptor DAF-2 in very old animals is naturally interpreted as a late shift in stability parameters that nearly doubles remaining lifespan without resetting accumulated structural damage. This interpretation reconciles the persistence of many senescent pathologies with restored proteostasis and stress resilience, and it shows that targeting the dynamical instability of the regulatory network-rather than reversing damage--can strongly reshape survival trajectories in unstable animals. More broadly, our work exemplifies how physics-inspired low-dimensional stochastic models can capture key features of aging, and we hope it will inspire more collaborations between biologists and physicists to work on late-life interventions.

biochemistry↗

A metabolic atlas of mouse aging

Humans are living longer, but this is accompanied by an increased incidence of age-related chronic diseases. Many of these diseases are influenced by age-associated metabolic dysregulation, but how metabolism changes in multiple organs during aging in males and females is not known. Answering this could reveal new mechanisms of aging and age-targeted therapeutics. In this study, we describe how metabolism changes in 12 organs in male and female mice at 5 different ages. Organs show distinct patterns of metabolic aging that are affected by sex differently. Hydroxyproline shows the most consistent change across the dataset, decreasing with age in 11 out of 12 organs investigated. We also developed a metabolic aging clock that predicts biological age and identified alpha-ketoglutarate, previously shown to extend lifespan in mice, as a key predictor of age. Our results reveal fundamental insights into the aging process and identify new therapeutic targets to maintain organ health.

molecular biology↗

A lipidome Aging Clock shows Age Acceleration in individuals with Autism

Aging is a multifaceted process influenced by intrinsic and extrinsic factors, with lipid alterations playing a critical role in brain aging and neurological disorders. This study introduces DoliClock, a lipid-based biological aging clock designed to predict the age of the prefrontal cortex using post-mortem lipidomic data. Significant age acceleration was observed in samples with autism, schizophrenia, and Down syndrome, with autism showing the most pronounced effects in aging-rate. An increase in entropy around age 40, suggests dysregulation of the mevalonate pathway and dolichol accumulation. Dolichol, a lipid integral to N-glycosylation and intracellular transport, emerged as a potential aging biomarker, with specific variants such as dolichol-19 and dolichol-20 showing unique age-related associations. These findings suggest that lipidomics can provide valuable insights into the molecular mechanisms of brain aging and neurological disorders. By linking dolichol levels and entropy changes to aging, this study highlights the potential of lipid-based biomarkers for understanding and predicting biological age, especially in conditions associated with premature aging.

neuroscience↗