Effect of lactoferrin on <i>Helicobacter felis</i> induced gastritis
Bibliographic record
Abstract
Lactoferrin possesses antibiotic, antiinflammatory, and immune-modulating properties that may be active against the gastritis-, ulcer- and cancer-inducing bacterium Helicobacter pylori. In vitro testing of bovine and human lactoferrin by several laboratories has shown significant bacteriostatic and bactericidal activity. Subsequent in vivo testing of bovine lactoferrin in animal models of H. pylori infection has shown beneficial effects of this agent. Our laboratory has utilized a mouse model that is infected with the feline strain of this bacterium, H. felis. The resulting gastritis that develops in this model and the effects of bovine lactoferrin and recombinant human lactoferrin (from Aspergillus niger var. awamori, Agennix Inc., Houston, Tex.) treatment were assessed by various measures. Infected animals treated with orally administered lactoferrin showed reversals in all parameters. In addition, when recombinant human lactoferrin was used in combination with low doses of amoxicillin or tetracycline, there was an enhancement in gastritis-reducing activity. Possible mechanisms for these effects of lactoferrin are discussed. Lactoferrin has significant, orally active in vivo actions and should be further investigated for clinical situations involving Helicobacter infections where it may have utility when administered alone and also when given in combination with established antibiotic agents.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".