Evidence map›Paper›PMID 41287051›Full record

ArticleBMC ecology and evolution2025

Timing of mortality during development alters the evolution of aging.

Peter Lenart, Sacha Psalmon, Benjamin D Towbin

Abstract read
In one paragraph

Article in BMC ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Peter LenartInstitute of Cell Biology, University of Bern, Bern, Switzerland. peter.lenart@unibe.ch.ORCID 0000-0002-6811-0762
Sacha PsalmonInstitute of Cell Biology, University of Bern, Bern, Switzerland.ORCID 0009-0002-1844-6679
Benjamin D TowbinInstitute of Cell Biology, University of Bern, Bern, Switzerland. benjamin.towbin@unibe.ch.ORCID 0000-0001-7046-1257

Funding

Swiss National Science Foundation (SNSF) 310030_207475Swiss National Science Foundation (SNSF) PCEFP3_181204Swiss National Science Foundation (SNSF) TMPFP3_209681
6 · The paper itself

Abstract

backgroundFor most animals, intrinsic senescence-induced mortality increases with age, while deaths from extrinsic threats, such as predation or accidents, decline during development as individuals grow and mature. Age-dependent modulation of extrinsic mortality is known to influence the evolution of aging. Yet, how the precise timing of changes in mortality shapes evolutionary forces, i.e., when they enhance and when they slow-down aging, remains poorly understood.

resultsTo address this, we developed two complementary mathematical models that integrate survival benefits arising during development with the progressive increase in mortality associated with senescence. Agent-based simulations and deterministic analyses revealed a strong and consistent influence of the timing of developmental survival benefits on their evolutionary impact: early-life survival benefits accelerate the rate of ageing, while late-acting benefits slow it down. This difference arises because early-life benefits more strongly enhance individual reproductive success. Early-life benefits thereby increase the overall growth potential of the population more strongly than late-life benefits, thereby diminishing the relative evolutionary advantage of increased longevity.

conclusionsOur results underscore the importance of mortality timing in the evolution of aging and provide a theoretical framework for connecting developmental trajectories to aging dynamics.

Indexed as

AgingBiological EvolutionMortalityAnimalsLongevityModels, BiologicalAgingDevelopmentExtrinsic mortalityMortality ratesNegligible senescence

Identifiers

PMID41287051
PMCPMC12642333

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.