Infant formula and its effects on microbes - An InVitro study
Bibliographic record
Abstract
The bacterial or plaque growth from the oral cavity produces a significant drop in the pH, as a result of the conversion of dietary carbohydrates to acidic metabolic end products. This relationship has encouraged the researchers to include bacterial fermentation and growth in studying the cariogenecity of a test food. To study the bacterial fermentation and growth in the presence of the infant formula. Streptococcus mutans strain MTCC 497 was dispersed in toddhewith broth and cultured onto mitissalivaris bacitracin agar (M.S.B). After the colonies were observed M.S.B.A was prepared. Morphological and confirmatory biochemical test were performed to check for the viability of Streptococcus mutans organisms. Finally, 14 the infant formula/control solution were subjected to serial dilutions, this was streaked onto the M.S.B agar, using a calibrated loop and bent glass rod was used to smear the entire plate and this was incubated . The number of colonies were counted using Quebec’s colony counter. Bacterial growth in the infant formulas ranged from 78% 0f optimal growth for Simyl MCT to 171% of optimal growth for Dexolac 2. Lactodex – 2, Lactogen -1, Lactodex -1 and Simyl MCT were bacteriostatic. When the infant formulas were compared with the control solutions, Bovine whole milk showed the greatest increase in the bacterial growth. The highest bacterial growth was found in Dexolac-2, Amulspray and lactodex low fat, and the least bacterial growth was found in Simyl MCT, Lactodex-1, Lactogen-1
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".