Review and Perspectives on Bifidobacterium lactis for Infants’ and Children’s Health
Bibliographic record
Abstract
The influence of microbiota dysbiosis in early life is increasingly recognized as a risk factor for the development of several chronic diseases later in life, including an increased risk of asthma, eczema, allergies, obesity, and neurodevelopmental disorders. The question whether the potential lifelong consequences of early life dysbiosis could be mitigated by restoring microbiota composition remains unresolved. However, the current evidence base suggests that protecting the normal development of the microbiome during this critical developmental window could represent a valuable public health strategy to curb the incidence of chronic and lifestyle-related diseases. Probiotic Bifidobacteria are likely candidates for this purpose in newborns and infants considering the natural dominance of this genus on microbiota composition in early life. Moreover, the most frequently reported microbiota composition alteration in association with newborn and infant diseases, including necrotizing enterocolitis and diarrhea, is a reduction in Bifidobacteria levels. Several studies have assessed the effects of B. animalis subsp. lactis strains in newborns and infants, but recent expert opinions recommend analyzing their efficacy at the strain-specific level. Hence, using the B94 strain as an example, this review summarizes the clinical evidence available in infants and children in various indications, discussing the safety and potential modes of actions while providing perspectives on the concept of “non-infant-type” probiotics for infants’ health.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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".