Effect of Pinto Bean Supplementation on Pregnancy Outcomes and Metabolic Markers of Obese Mice
Bibliographic record
Abstract
Objectives: Pasteurized donor human milk (DM) is milk from screened donors, that is donated frozen (often several months postpartum and may not provide full-breast expressions), thawed, pooled, pasteurized (62.5 C for 30 min), frozen, distributed, and thawed for feeding.Therefore, the nutrient composition of DM may differ from what a breastfed newborn receives.DM is largely distributed to hospitals for feeding preterm infants, but there is recent interest in offering DM to termborn infants.However, there is a paucity of data on DM mineral and trace element contents, thus precluding assessment of its appropriateness as an alternative to mother's milk for term-born infants if used longer than a short-term bridge to establish breastfeeding.We aimed to determine mineral and trace element concentrations in DM and compare these to reference adequate intake cut-off values established by the U.S. National Academies of Medicine (NAM).Methods: Sodium, potassium, calcium, phosphorus, magnesium, copper, zinc, and iodine were quantified using inductively coupled mass spectrometry and compared to NAM adequate intake values for infants aged 0-6 months.Results: DM samples (N 196 pooled batches) were collected from two Canadian milk banks (2014-2015 and 2021-2023) as part of two clinical trials.Median (IQR) values for sodium (94 (84, 108) mg/L), potassium (417 (377, 470) mg/L), and magnesium (31 (28, 34) mg/L) were significantly (p< 0.05) below the adequate intake cut-offs (100%, 92%, and 77% of values, respectively, below the cut-off value).Calcium (250 (227, 274) mg/L), phosphorus (128 (113, 143) mg/L), copper (260 (219, 306) g/L), zinc (1.5 (1.2, 1.8) mg/L), and iodine (174 (125, 233) g/L) were not different (p >0.05) from reference values.Conclusions: Long-term provision of DM to term-born infants may not provide adequate sodium, potassium or magnesium.Understanding the nutrient content of DM will aid clinicians in determining its appropriate use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".