Point-of-care human milk concentration by passive osmosis: comprehensive analysis of fresh human milk samples
Bibliographic record
Abstract
OBJECTIVE: Preterm infants need enrichment of human milk (HM) for optimal growth. This study evaluated a novel, point-of-care human milk concentration (HMC) process for water removal from fresh HM samples by passive osmotic concentration. STUDY DESIGN: Nineteen fresh HM samples were concentrated by incubation with the HMC devices for 3 h at 4 °C. Pre- and post-concentration HM samples were compared by HM properties for: pH, osmolality, macronutrients, enzyme activity, bioactive, and total cell viability. RESULTS: Passive osmotic concentration reduced HM volume by an average of 16.3% ± 3.8% without a significant effect on pH or cell viability. Ten of the 41 HM components did not differ significantly (p > 0.05) between pre- and post-concentration samples. Twenty-three increased within the expected range by volume reduction. Six increased more than expected, two less than expected, and none decreased significantly. CONCLUSION: Passive osmotic concentration of fresh HM can concentrate HM components by selective removal of water. HM osmolality and pH remained within neonatal feeding parameters.
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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 | 0.001 |
| 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 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".