Nutritional adversity, sex and reproduction: 30 years of DOHaD and what have we learned?
Bibliographic record
Abstract
It is well established that early life environmental signals, including nutrition, set the stage for long-term health and disease risk - effects that span multiple generations. This relationship begins early, in the periconceptional period and extends into embryonic, fetal and early infant phases of life. Now known as the Developmental Origins of Health and Disease (DOHaD), this concept describes the adaptations that a developing organism makes in response to early life cues, resulting in adjustments in homeostatic systems that may prove maladaptive in postnatal life, leading to an increased risk of chronic disease and/or the inheritance of risk factors across generations. Reproductive maturation and function is similarly influenced by early life events. This should not be surprising, since primordial germ cells are established early in life and thus vulnerable to early life adversity. A multitude of 'modifying' cues inducing developmental adaptations have been identified that result in changes in reproductive development and impairments in reproductive function. Many types of nutritional challenges including caloric restriction, macronutrient excess and micronutrient insufficiencies have been shown to induce early life adaptations that produce long-term reproductive dysfunction. Many pathways have been suggested to underpin these associations, including epigenetic reprogramming of germ cells. While the mechanisms still remain to be fully investigated, it is clear that a lifecourse approach to understanding lifetime reproductive function is necessary. Furthermore, investigations of the impacts of early life adversity must be extended to include the paternal environment, especially in epidemiological and clinical studies of offspring reproductive function.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".