Biology subjects

Cam, E.

Publications and source records attributed to Cam, E..

8 recordsLinked to original sources

bioRxiv2026

Conceptualising and quantifying phenological plasticity through latent responses to seasonal environmental progression

Quantifying how individuals adjust the seasonal timings of life-history events (i.e. their phenology) in response to seasonal environmental conditions is fundamental to predicting impacts of changing seasonality. However, the current standard approach of inferring phenological responses by directly analysing observed event dates relies on foundational assumptions that could be invalidated by changing seasonality, and excludes individuals that do not express focal events, potentially generating misleading inferences. To overcome these limitations, we devised a Phenological Threshold Model (PTM) that conceptualizes phenological events as switches between discrete life-history states and primarily estimates variation in underlying latent dynamic responses to seasonal progression, from which event dates secondarily arise. We demonstrate that the PTM can accurately retrieve simulated parameter values, including given incomplete seasonal field observations. Application to multi-year data on annual breeding in black-legged kittiwakes (Rissa tridactyla) demonstrated substantial among-individual variation in latent responses to seasonally varying environmental drivers, and associated daily probabilities that individuals will initiate breeding, revealing how annual distributions of breeding dates and proportions of non-breeders jointly arise. We thereby formalise a new conceptual and statistical framework for quantifying the potential for, and constraints on, rapid plastic and micro-evolutionary changes in phenology in changing seasonal climatic and environmental regimes.

ecology↗

bioRxiv2025

Microgravity Remodels Longevity Networks in Astronaut PBMCs: Integrated Findings of Telomere Elongation, DNA Repair Responses, and miRNA Suppression

Microgravity provides a unique environment for elucidating the fundamental mechanisms of human aging. In the Microgravity Associated Genetics (MESSAGE) Science Mission--Turkiyes first human space biology experiment--we performed an integrative analysis of telomere dynamics, transcriptomic remodeling, and microRNA regulation in peripheral blood mononuclear cells (PBMCs) collected before launch (L-7day), after suborbital ascent (L+3hrs), and during days 4-10 aboard the International Space Station (ISS). Spaceflight induced a striking early elongation of telomeres, accompanied by transcriptional activation of DNA repair, oxidative stress mitigation, mitochondrial homeostasis, and immune regulatory pathways. Concurrently, microgravity triggered robust suppression of longevity-associated microRNAs, including members of the miR-17-92, miR29, and miR34 families, suggesting coordinated epigenetic reprogramming of genome stability and stress responses. Notably, the adaptor protein gene AP2A1, recently implicated in cellular rejuvenation and mechanotransductive aging processes, emerged as a consistently microgravity-responsive hub, linking cytoskeletal signaling to telomere maintenance and DNA repair networks. Together, these findings reveal that short-duration spaceflight initiates a multi-layered molecular longevity program in human immune cells, characterized by telomere extension, stabilization of genome maintenance pathways, and suppression of aging-associated miRNA regulators. This systems-level view provides foundational insight into how human biology adapts to short-term microgravity exposure and identifies AP2A1-centered networks as promising targets for enhancing astronaut health and performance and ultimately understanding terrestrial aging.

molecular biology↗

bioRxiv2025

Hypothetical LOC Genes as Biomarkers of Spaceflight Adaptation: A Comparative Study from ISS, Suborbital, and Earth-Based Experiments

Microgravity constitutes one of the most profound environmental stressors encountered by humans during spaceflight, capable of altering fundamental cellular processes and gene regulatory networks. While the effects of spaceflight on well-characterized protein-coding genes have been widely documented, little is known about the behavior of uncharacterized or poorly annotated genomic regions under these conditions. LOC (Locus) genes, often classified as long non-coding RNAs and excluded from conventional analyses, represent a largely unexplored component of the human transcriptome. In this study, we systematically investigated the transcriptional responses of LOC genes as part of the MESSAGE (Microgravity Associated Genetics) Science Mission, Turkiyes first human space biology initiative. Peripheral blood samples were collected from astronauts across five mission phases: pre-launch baseline, post-suborbital flight ([~]100 km), and on International Space Station (ISS) Days 4, 7, and 10 ([~]400 km). RNA-Seq analyses revealed six LOC genes with statistically significant expression changes (p < 0.05, Kruskal-Wallis test), alongside additional transcripts that, while not statistically significant, exhibited biologically meaningful temporal fluctuations. These dynamic profiles included continuous upregulation, transient activation with subsequent return to baseline, and delayed induction at later ISS stages, highlighting the functional diversity of LOC responses. To assess their translational potential, Open Reading Frame (ORF) analyses were performed on significant transcripts, revealing conserved ORF structures--most notably identical ORF33 sequences in LOC124905103 and LOC124900480-- suggesting coding capacity. Phylogenetic analyses further supported evolutionary clustering consistent with expression and ORF similarities. Collectively, these findings challenge the notion of LOC genes as transcriptional noise, instead positioning them as candidate biomarkers and functional elements of microgravity adaptation. By extending space biology research into the "dark genome," this study provides novel insights with potential implications for astronaut health monitoring and therapeutic development in long-duration missions.

molecular biology↗

bioRxiv2025

Assessing Immune Stability in Space: Haematological and T Cell Profiling of Astronauts During the MESSAGE Science Mission in Axiom-3 on the ISS

Microgravity presents unique challenges to human physiology, particularly the immune system, during spaceflight. T lymphocytes, key components of adaptive immunity, play a vital role in immune regulation, yet the effects of microgravity on T-cell function and gene expression remain incompletely understood. This study, conducted as part of the MESSAGE (Microgravity Associated Genetics) Science Mission in the Axiom-3 mission (https://www.nasa.gov/mission/station/research-explorer/investigation/?#id=9100). We aimed to investigate how microgravity influences immune cell responses by analysing blood samples from three astronauts between pre-flight and during their space mission on the ISS (post-launch Day 4, Day 7, and Day 10 in ISS). Hemogram analysis revealed no statistically significant differences in leukocyte, erythrocyte, haemoglobin, and haematocrit levels between pre-flight and in-flight samples, suggesting a stable haematological profile under microgravity conditions. T cell subpopulation analysis indicated fluctuations in effector memory T cells (TemEARLY and TemLATE), but these changes did not reach statistical significance. These findings suggest that, within the short duration of spaceflight, haematological and immune parameters remain largely stable, underscoring the need for further research into long-term immune adaptations in microgravity. As a next step, transcriptomic analysis will be performed to identify microgravity-associated gene candidates, and CRISPR-based knock-out of the genes in T cells will be generated to explore their functional roles in microgravity-induced immune modulation.

molecular biology↗

bioRxiv2022

Mark loss can strongly bias demographic rates in multi-state models: a case study with simulated and empirical datasets

O_LIThe development of methods for individual identification in wild species and the refinement of Capture-Mark-Recapture (CMR) models over the past few decades have greatly improved the assessment of population demographic rates to address ecological and conservation questions. In particular, multi-state models, which offer flexibility in analysing complex study systems, have gained popularity within the ecological community. In this study, we focus on the issue of mark loss and the associated recycling of remarked individuals, which requires further exploration given the increasing use of these models. C_LIO_LITo fill this knowledge gap, we employed a wide range of simulation scenarios that reflect commonly encountered real case studies, drawing inspiration from the survival rates of 700 vertebrate species. Using a multi-state, Arnason-Schwartz (AS) modelling framework, we estimated the effects of mark loss and recycled individuals on parameter estimates. We assessed parameter bias by simulating a metapopulation system with varying capture and survival rates. Additionally, we demonstrated how mark loss can be easily estimated and accounted for using a 10-year empirical CMR dataset of bats. The bats were individually identified using Passive Integrated Transponder (PIT) tag technology as potentially lost marks and multi-locus genotypes as permanent marks. C_LIO_LIOur simulation results revealed that the occurrence of bias and the affected parameters were highly dependent on the study system, making it difficult to establish general rules to predict bias a priori. The model structure and the interdependency among parameters pose challenges in predicting the impact of bias on estimates. C_LIO_LIOur findings underscore the importance of assessing the effect of mark loss when using AS models. Ignoring such violations of model assumptions can have significant implications for ecological inferences and conservation policies. In general, the use of permanent marks, such as genotypes, should always be preferred when modelling population dynamics. If that is not feasible, an alternative is to combine two independent types of temporary marks, such as PIT tags and bands. C_LIO_LIAnalysis of our empirical dataset on Myotis myotis bats revealed that tag loss is higher in juveniles than in adults during the first year after tagging. The use of surgical glue to close the injection hole reduces tag loss rate from 28% to 19% in juveniles, while it has no effect on the tag loss rate in adults ([~]10%). The main bias observed in our metapopulation system appears in the survival rate, with up to a 20% underestimation if tag loss is not accounted for. C_LI

ecology↗

bioRxiv2020

When to depart from a stopover site? Time-since-arrival matters more than weather conditions

On the journey to wintering sites, migratory birds usually alternate between flights and stopovers where they rest and refuel. Migration strategies are assumed to differ according to season: a time-minimization pre-breeding migration strategy towards breeding locations, and an energy-minimization post-breeding migration strategy to wintering ones. The duration of flights and stopovers determines the energy requirements and the total duration of the journey. Since migrating birds actually spend most of the time at stopovers, selection to minimize the amount of energy or time spent on migration is very likely to operate on the effectiveness of stopover rest and refueling. Here we address the relative contribution of factors to departure decisions from stopover sites during the post-breeding migration in a long-distance migratory songbird. When capture probability is low it is impossible to assess the variation in body condition over the entire duration of the stopover. To get around this, we use Time Since Arrival (TSA) as a proxy for the changes in the state of individuals during the stopover. We propose that TSA is an integrative proxy for resting, feeding and fattening efficiency. We develop a capture-recapture model to address the relationship between departure probability, estimated TSA, and weather conditions. Using a 20-year dataset from sedge warblers, we show that TSA has a larger effect on departure probability than weather conditions. Low humidity and an increase in atmospheric pressure in the days preceding departure are associated with higher departure probability, but these effects are smaller than that of TSA.

ecology↗

bioRxiv2018

Power spectrum slope and motor function recovery after focal cerebral ischemia in the rat

EEG changes across vigilance states have been observed after ischemic stroke in patients and experimental stroke models, but their relation to functional recovery remains unclear. Here, we evaluate motor function, as measured by single pellet reaching (SPR), as well as local EEG changes in NREM, REM and wakefulness during a 30-day recovery period after middle cerebral artery occlusion (MCAO) or sham surgery in rats. Small cortical infarcts resulted in poor SPR performance and induced widespread changes in EEG spectra in the ipsilesional hemisphere in all vigilance states, without causing major changes in sleep-wake architecture. Ipsilesional 1-4 Hz power was increased after stroke, whereas power in higher frequencies was reduced, resulting in a steeper slope of the power spectrum. Multielectrode array analysis of ipsilesional M1 showed that these spectral changes were present on the microelectrode level throughout M1 and were not related to increased synchronization between electrodes. Spectrum slope was significantly correlated with post-stroke motor function.

neuroscience↗

bioRxiv2017

Individual heterogeneity and capture-recapture models: what, why and how?

Variation between and within individuals in life history traits is ubiquitous in natural populations. When affecting fitness-related traits such as survival or reproduction, individual heterogeneity plays a key role in population dynamics and life history evolution. However, it is only recently that properly accounting for individual heterogeneity when studying population dynamics of free-ranging populations has been made possible through the development of appropriate statistical models. We aim here to review case studies of individual heterogeneity in the context of capture-recapture models for the estimation of population size and demographic parameters with imperfect detection. First, we define what individual heterogeneity means and clarify the terminology used in the literature. Second, we review the literature and illustrate why individual heterogeneity is used in capture-recapture studies by focusing on the detection of life-history trade-offs, including senescence. Third, we explain how to model individual heterogeneity in capture-recapture models and provide the code to fit these models (https://github.com/oliviergimenez/indhet_in_CRmodels). The distinction is made between situations in which heterogeneity is actually measured and situations in which part of the heterogeneity remains unobserved. Regarding the latter, we outline recent developments of random-effect models and finite-mixture models. Finally, we discuss several avenues for future research.

ecology↗