Utilization of lactoferrin to fight antibiotic-resistant mammary gland pathogens1,2
Bibliographic record
Abstract
The widespread use of antibiotics has lead to the increased presence of pathogens that are less susceptible to their antibacterial effect. Lactoferrin (Lf) is naturally produced by the mammary gland. Lactoferrin is the main whey protein in human milk and is also present in cow's milk but at a much lower concentration than in human milk. This protein appears to have many biological functions, including antibacterial and antiinflammatory activities. The best-known effect of Lf is to bind iron that is essential for bacterial growth. However, the cationic nature of this protein also appears to be important for the antimicrobial activity of this protein. Lactoferrin has a weak antibacterial effect when used alone, but interestingly, Lf appears much more effective when used at low concentration in combination with several antibiotics. The most striking observation is that Lf increases the inhibitory activity of penicillin up to 4-fold in most penicillin-susceptible Staphylococcus aureus strains, whereas this increase was 4- to 16-fold in penicillin-resistant strains. Indeed, Lf reduces beta-lactamase activity in S. aureus strains producing this enzyme. Transcription of beta-lactamase gene is dramatically repressed in the presence of Lf. We evaluated the efficacy of intramammary treatments containing penicillin G or bovine Lf (bLf), or both, to cure chronic mastitis caused by a clinical isolate of S. aureus highly resistant to beta-lactam antibiotics. In a first trial, mastitis was induced in lactating cows by injecting a low dose of S. aureus through the teat canal of all quarters. Bacterial cure rate was null for control quarters, 11.1% for bLf, 9.1% for penicillin, and 45.5% for the combination of bLf and penicillin. A second trial was undertaken to investigate the effect of an extended therapy on chronic mastitis acquired in a previous lactation. Quarters were treated with 100,000 IU of penicillin G with or without 250 mg of bLf for 7 d. Bacterial cure rate was greater for the bLf + penicillin combination (33.3%) compared with penicillin alone (12.5%). In conclusion, bLf added to penicillin is an effective combination for the treatment of stable S. aureus infections resistant to beta-lactam 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".