EFFECT OF <i>BIFIDOBACTERIUM BREVE</i> ON THE GROWTH OF <i>ENTEROBACTER SAKAZAKII</i> IN REHYDRATED INFANT MILK FORMULA
Bibliographic record
Abstract
ABSTRACT The effect of Bifidobacterium breve on the survival and growth of Enterobacter sakazakii in rehydrated infant milk formula stored at 4–45C was studied. A commercial culture of B. breve and a five‐strain cocktail E. sakazakii were mixed with rehydrated formula and stored up to 8 h. The populations of B. breve and E. sakazakii at each storage time/temperature were determined. There was a two‐way interactive effect between B. breve numbers and temperature on the number of E. sakazakii in the rehydrated formula at 3–8 h of storage. E. sakazakii did not grow in the rehydrated formula at 4C. At 12 and 20C, the numbers of E. sakazakii in the presence of B. breve were lower than those in the formula without B. breve at 8 h of storage, and at 45C, when the bacteria were combined, a similar result was obtained at 6‐ and 8‐h storage. The presence of B. breve in the formula appeared to enhance the growth of E. sakazakii at 37C in the rehydrated formula stored at 2–8 h. Other more competitive inhibitory probiotic cultures would be more appropriate to control E. sakazakii growth in unrefrigerated rehydrated milk‐based formula. PRACTICAL APPLICATIONS Results obtained showed that the probiotic organisms Bifidobacterium breve did not reduce Enterobacter sakazakii levels in rehydrated infant formula if held >2 h at >30C. At 37C, B. breve stimulated the growth of the pathogen after 2 h. Choice of probiotic bacteria for inclusion in these products to improve infant gut microflora should be based on their neutral or negative influence on E. sakazakii survival/growth to reduce the risk to health associated with the contamination of these products during manufacture.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".