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1,048 results for “aging effects”
Age-specific effects of deletions: Implications for ageing theories
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Data from: A cost-effective blood DNA methylation-based age estimation method in domestic cats, Tsushima leopard cats (Prionailurus bengalensis euptilurus), and Panthera species, using targeted bisulfite sequencing and machine learning models
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Data from: Sex-dependent effects of parental age on offspring fitness in a cooperatively breeding bird
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Data from: Effects of age, breeding strategy, population density, and number of neighbors on territory size and shape in Savannah Sparrows
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Data from: Effects of high dose aspartame-based sweetener on the gut microbiota and bone strength in young and aged mice
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No evidence for paternal age effects on sons or daughters, when accounting for paternal sperm storage
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Paternal environment effects are driven by female reproductive fluid but not sperm age in an external fertiliser
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Hidden causes of variation in offspring reproductive value: negative effects of maternal breeding age on offspring telomere length persist undiminished across multiple generations
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Effects of brain maintenance and cognitive reserve on age-related decline in three cognitive abilities
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Effects of developmental and adult environments on ageing
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On ageing and age-specific effects of spontaneous mutations
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Data from: Provenance variation in functional traits of European forest trees: Meta-analysis reveals effects of taxa and age despite critical research gaps
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Incorporating effects of age on energy dynamics predicts non-linear maternal allocation patterns in iteroparous animals
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Data from: Telomere heritability and parental age at conception effects in a wild avian population
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Data for: Effects of parental age on salt stress tolerance in an aquatic plant
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Maternal and paternal age effects on male antler flies: a field experiment
<p><span>In many species, parental age at reproduction can influence offspring performance and lifespan, but the direction of these effects and the traits affected vary among studies. Data on parental age effects are still scarce in non-captive populations, especially insects, despite species such as fruit flies being models in laboratory-based aging research. We performed a biologically relevant experimental manipulation of maternal and paternal age at reproduction of antler flies (<i>Protopiophila litigata</i>) in the laboratory and tracked the adult lifespan and reproductive success of their male offspring released in the wild. Increased paternal, but not maternal, age somewhat increased sons' adult lifespan, while parental ages did not influence sons' mating rate or reproductive senescence. Our results indicate that while parental age effects do exist in an insect in the field, they may be beneficial in such a short-lived animal, in contrast to results from most wild vertebrates and laboratory invertebrates.</span></p>
Data from: Development time mediates the effect of larval diet on ageing and mating success of male antler flies in the wild
<p class="western">High-quality developmental environments often improve individual performance into adulthood, but allocating toward early life traits, such as growth, development rate and reproduction, may lead to trade-offs with late-life performance. It is, therefore, uncertain how a rich developmental environment will affect the ageing process (senescence), particularly in wild insects. To investigate the effects of early life environmental quality on insect life-history traits, including senescence, we reared larval antler flies (<i>Protopiophila litigata</i>) on four diets of varying nutrient concentration, then recorded survival and mating success of adult males released in the wild. Declining diet quality was associated with slower development, but had no effect on other life-history traits once development time was accounted for. Fast-developing males were larger and lived longer, but experienced more rapid senescence in survival and lower average mating rate compared to slow developers. Ultimately, larval diet, development time and body size did not predict lifetime mating success. Thus, a rich environment led to a mixture of apparent benefits and costs, mediated by development time. Our results indicate that 'silver spoon' effects can be complex and that development time mediates the response of adult life-history traits to early life environmental quality.</p>
The effects of age on the demography of a perennial plant depend on interactions with size and environment
<p>Age-dependence of the demographic rates survival, fecundity and individual growth is a fundamental aspect of population biological theory. Knowledge about plant ageing can also be important for conservation and agriculture as it will improve the accuracy of population viability assessments and long-term performance assessments in perennial crops. Recent studies show age effects on demographic rates for several plant species, yet much remains to be learned about the patterns and mechanisms of plant ageing, particularly about how age effects interact with the environment and with plant size.</p> <p>We collected age-and-size-based demographic data, as well as individual-based environmental data, for the perennial herb Plantago lanceolata in Denmark over three annual transitions (four years). We combined frequent field monitoring of carefully mapped individuals with the underused technique of root histology to determine age of herbaceous plants. We used generalized linear mixed effects models to assess how age, soil properties, and year influenced survival, growth, and reproduction.</p> <p>Our results show no strong evidence of consistent age declines, rather, we found mostly positive effects of age on vital rates. For all vital rates, i.e. survival, growth, flowering, and reproductive output, age effects also differed significantly among years. Additionally, we detected an interactive effect of age and size in the growth model. Size, and temporal and spatial environmental variation also affected vital rates independently of age.</p> <p>Synthesis: Our study shows that age-dependence of demographic rates can depend both on individual size and environmental variation. These results suggest that a consideration of potential age-interactions may improve the accuracy of comparative studies of ageing and population projections. Moreover, this study shows that much is still unknown about how plant ageing can be affected by the environment, and illustrates how age determination using herb chronology provides an opportunity to increase our knowledge about ageing in herbaceous plants.</p>
In-house 3-D printed aligners: effect of in vivo ageing on mechanical properties
<p>Dataset for all analyses in the paper.</p>
Data from: Age-related variation in non-breeding foraging behaviour and carry-over effects on fitness in an extremely long-lived bird
1. Senescence has been widely documented in wild vertebrate populations, yet the proximate drivers of age-related declines in breeding success, including allocation trade-offs and links with foraging performance, are poorly understood. For long-lived, migratory species, the non-breeding period represents a critical time for investment in self-maintenance and restoration of body condition, which in many species is linked to fitness. However, the relationships between age, non-breeding foraging behaviour and fitness remain largely unexplored. 2. We performed a cross-sectional study, investigating age-related variation in the foraging activity, distribution and diet of an extremely long-lived seabird, the wandering albatross Diomedea exulans during the non-breeding period, and its links with subsequent reproductive performance. 3. We tracked the distributions of 82 adults aged 8 – 33 years with geolocator-immersion loggers and found an age-related decline in the number of landings (a proxy of foraging effort) during daylight hours. There was a decrease in body feather δ13C values in older males but not females, yet this did not accompany an age-related shift in distributions. Males conducted fewer landings than females, and the sexes were spatially segregated, with males foraging further south, likely due to their differential utilization of winds. 4. While younger (< 20 years) birds had higher foraging activity, all individuals went on to breed successfully the following season. In contrast, among older (20+ years) birds, individuals that landed more often were more likely to defer breeding or fail during incubation, suggesting they have lower foraging success. 5. As far as we are aware, this is the first demonstration of an age-specific carry-over effect of foraging behaviour in the non-breeding period on subsequent reproductive performance. This link between foraging behaviour and fitness in late but not early adulthood indicates that the ability of individuals to forage efficiently outside the breeding period may be an important driver of fitness differences in old age.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.