The impact of maternal and early life malnutrition on health: a diet-microbe perspective
Bibliographic record
Abstract
BACKGROUND: Early-life malnutrition may have long-lasting effects on microbe-host interactions that affect health and disease susceptibility later in life. Diet quality and quantity in conjunction with toxin and pathogen exposure are key contributors to microbe-host physiology and malnutrition. Consequently, it is important to consider both diet- and microbe-induced pathologies as well as their interactions underlying malnutrition. MAIN BODY: Gastrointestinal immunity and digestive function are vital to maintain a symbiotic relationship between the host and microbiota. Childhood malnutrition can be impacted by numerous factors including gestational malnutrition, early life antibiotic use, psychological stress, food allergy, hygiene, and exposure to other chemicals and pollutants. These factors can contribute to reoccurring environmental enteropathy, a condition characterized by the expansion of commensal pathobionts and environmental pathogens. Reoccurring intestinal dysfunction, particularly during the critical window of development, may be a consequence of diet-microbe interactions and may lead to life-long immune and metabolic programming and increased disease risk. We provide an overview of the some key factors implicated in the progression of malnutrition (protein, fat, carbohydrate, iron, vitamin D, and vitamin B12) and discuss the microbiota during early life that may contribute health risk later in life. CONCLUSION: Identifying key microbe-host interactions, particularly those associated with diet and malnutrition requires well-controlled dietary studies. Furthering our understanding of diet-microbe-host interactions will help to provide better strategies during gestation and early life to promote health later in life.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".