Effect of Lactoferrin in Combination with Penicillin on the Morphology and the Physiology of Staphylococcus aureus Isolated from Bovine Mastitis
Bibliographic record
Abstract
The objective of the present study was to evaluate the therapeutic potential of bovine lactoferrin or lactoferricin in combination with penicillin G against Staphylococcus aureus. Minimal inhibitory concentrations of lactoferrin, lactoferricin, penicillin, and combinations of lactoferrin or lactoferricin with penicillin were determined for 15 S. aureus strains including several strains resistant to beta-lactam antibiotics. The fractional inhibitory concentration index indicated a synergistic effect between lactoferrin and penicillin. Combination of lactoferrin with penicillin increased the inhibitory activity of penicillin by two- to fourfold and reduced the growth rate in S. aureus strains tested, whereas the increase in the inhibitory activity of lactoferrin by penicillin was 16- to 64-fold. The addition of iron to the medium containing a combination of penicillin and lactoferrin had no effect on growth inhibition. Electron microscopy revealed that concentration below the minimal inhibitory concentrations of penicillin induced important ultrastructure alterations, which were further enhanced by the presence of lactoferrin. When S. aureus cells were grown in the presence of a combination of penicillin and lactoferrin, changes in the protein profile of the bacteria, including the disappearance of several protein bands due to the presence of lactoferrin, were observed. These data suggest that bovine lactoferrin or lactoferricin in combination with beta-lactam antibiotics can increase the antibacterial activity of these antibiotics against S. aureus resistant to antibiotics.
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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) | 0.001 | 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 | 0.000 |
| 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".