A long‐term study of stable isotope ratios of fingernail keratin and amino acids in a mother–infant dyad
Bibliographic record
Abstract
OBJECTIVE: To evaluate the potential of compound-specific isotope analysis of amino acids (CSIA-AA) for investigating infant feeding practices, we conducted a long-term study that compared infant and maternal amino acid (AA) nitrogen isotope ratios. MATERIALS AND METHODS: Fingernail samples were collected from a single mother-infant dyad over 19 months postpartum. Carbon and nitrogen stable isotope ratios were measured in the bulk keratin of the fingernail samples. Selected samples were then hydrolyzed and derivatized for compound-specific nitrogen isotope analysis of keratin AAs. RESULTS: As in previous studies, infant bulk keratin nitrogen isotope values increased during exclusive breastfeeding and fell with the introduction of complementary foods and eventual cessation of breastfeeding. Infant trophic AAs had elevated nitrogen isotope values relative to the mother, while the source AAs were similar between the mother and infant. Proline and threonine appeared to track the presence of human milk in the infant's diet as the isotopic composition of these AAs remained offset from maternal isotope values until the cessation of breastfeeding. DISCUSSION: Although CSIA-AA is costly and labor intensive, it appears to hold potential for estimating the duration of breastfeeding, even after the introduction of complementary foods. Through the analysis of a full suite of AAs, it may also yield insights into infant physiology and AA synthesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".