Amino acid stable carbon isotopes in nail keratin illuminate breastfeeding and weaning practices of mother – infant dyads
Bibliographic record
Abstract
Abstract Compound-specific stable carbon isotope analysis of amino acids (CSIA-AA) is widely used in ecological studies to analyze food-webs and is gaining use in archaeology for investigating past diets. However, its use in reconstructing breastfeeding and weaning practices is not fully understood. This study evaluates the efficacy of stable carbon isotope analysis of amino acids in early life diet reconstruction by analyzing keratin from fingernail samples of three mother-infant pairs during late gestation and early postpartum periods. Our results show that stable carbon isotope ratios ( δ 13 C) of glycine, and to a lesser extent glutamate, effectively trace the onset of exclusive breastfeeding and the end of weaning in infants. We propose that glycine’s ‘conditionally essential’ metabolic pathway during infancy allows it to reflect maternal glycine δ 13 C, indicating breastmilk consumption. Subtle changes in glutamate δ 13 C likely result from its ‘non-essential’ status. Additionally, δ 13 C values of glycine and glutamate indicate maternal physiological and pathological stress due to catabolic effects such as gluconeogenesis. These findings have significant implications for ecological and archaeological research using CSIA-AA for dietary reconstructions. They highlight the need to understand how metabolic pathways affecting δ 13 C of amino acids may change over an individual’s lifespan or be altered due to various forms of stress.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".