Adverse weather during<i>in utero</i>development is linked to higher rates of later-life herpesvirus reactivation in adult European badgers,<i>Meles meles</i>
Bibliographic record
Abstract
Maternal immune and/or metabolic conditions relating to stress or nutritional status can affect in utero development among offspring with subsequent implications for later-life responses to infections. We used free-ranging European badgers as a host-pathogen model to investigate how prenatal weather conditions affect later-life herpesvirus genital tract reactivation. We applied a sliding window analysis of weather conditions to 164 samples collected in 2018 from 95 individuals born between 2005–2016. We test if the monthly mean and variation in rainfall and temperature experienced by their mother during the 12 months of delayed implantation and gestation prior to parturition subsequently affected individual herpes reactivation rates among these offspring. We identified four influential prenatal seasonal weather windows that corresponded with previously identified critical climatic conditions affecting badger survival, fecundity and body condition. These all occurred during the pre-implantation rather than the post-implantation period. We conclude that environmental cues during the in utero period of delayed implantation may result in changes that affect an individual's developmental programming against infection or viral reactivation later in life. This illustrates how prenatal adversity caused by environmental factors, such as climate change, can impact wildlife health and population dynamics—an interaction largely overlooked in wildlife management and conservation programmes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".