Editorial: Pre-natal and post-natal environmental impacts on metabolic control
Bibliographic record
Abstract
Diverse environmental and maternal behavioural factors influence the future metabolic health of the offspring, including the pre-pregnancy health of the mother, the in utero environment, and early childhood development. Environmental risk factors are diverse and include maternal stress, nutrition, environmental pollutants, and lifestyle choices such as recreational drugs and alcohol. Such variables can impact diverse fetal tissues including the pancreas, liver, kidneys, skeletal muscle, adipose tissue, cardiovascular system, and brain. The placenta is a key mediator between maternal metabolic stress and altered fetal growth and development. Substantial gaps exist in our understanding of how individual organs and tissues are modified in both form and function by early life stressors, how limitations in tissue plasticity combine to build risk for adult disease, and where potential opportunities exist for metabolic rescue before or after birth.The intent of this Special Issue was to illustrate key structural and functional developmental changes to organs and tissues that arise in response to sub-optimal environmental conditions during pregnancy and neonatal life, and how these can mutually build risk for adult metabolic diseases. Mechanistic changes include altered tissue stem cell populations, altered hormone and growth factor presence, epigenetic modifications in key genes regulating metabolism, and cellular stress can alter maternal and newborn health. GDM is often associated with large-forgestational age birth size and an increased risk of adult chronic diseases in the offspring and developing Type 2 diabetes mellitus in the mother. A retrospective cohort study compared perioperative management options during caesarean section. An 'Enhanced recovery after surgery' protocol (ERAS) was compared to a normally managed group of women with GDM. ERAS includes a pre-operative low carbohydrate drink which induces anabolism through an increase in insulin release. This can stabilize perioperative glycemia and prevent post-operative complications. However, the impact on metabolism in women with GDM was unclear. Results showed that the differences in preoperative glucose levels between ERAS and control group were minimal, but the ERAS group experienced a substantial decrease in composite adverse outcome, including perioperative maternal and neonatal hypoglycemia and hypertension. This could be anticipated to result in a lower referral to neonatal intensive care with reduced associated costs.The papers included in this special issue highlight the range of environmental stressors during pregnancy that can impact the development of the fetus and the health of the offspring, from macronutrition to micronutrients and the host microbiome. The importance of early intervention and prevention strategies aimed at optimizing maternal health and the in utero environment is emphasized. While lifestyle and therapeutic interventions can improve maternal metabolic control and reduce the risk of abnormal neonatal outcomes, reversing the adverse metabolic programming remains a major challenge. Further, care protocols surrounding birth can also help to ensure neonatal health.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.020 | 0.009 |
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".