Lactoferin - A Neuroprotective Molecule in Children: Overview of Current Evidence and Future Prospects (Systematic Review and Metaanalysis)
Bibliographic record
Abstract
Background: This systematic review and meta-analysis aims to summarize the most recent literature data on the neuroprotective role of lactoferin and also to highlight its supporting effects during brain developmental injury or after perinatal brain injury in the pediatric population. Methods: We conducted a systematic review following PRISMA guidelines. A comprehensive search across PubMed, Scopus, Web of Science, and Cochrane Library identified studies assessing lactoferin’s impact on pediatric neurodevelopment, with quality appraisal performed using Cochrane, Newcastle-Ottawa, and GRADE criteria. Results: Out of 1,172 identified records, 13 studies (5 human, 8 animal) met the inclusion criteria. Human studies reported that lactoferin supplementation improved brain development, cognitive function, neurodevelopmental scores, and sleep quality in children. Animal models supported these findings, showing enhanced neuroprotection and reduced oxidative damage. A meta-analysis of two RCTs revealed a moderate positive effect of lactoferin on cognitive function (SMD = 0.53), with low heterogeneity (I² = 0%). Overall, evidence quality ranged from moderate to low, as assessed by GRADE. Conclusions: Lactoferin, by its multiple properties and mechanisms of action, seems to have a neuroprotective role in children, demonstrated both in clinical and preclinical studies. Further investigations are needded for the establishment of an effective dose range in the pediatric population.
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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 | 0.020 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".