Oral lactoferrin treatment resolves amoebic intracecal infection in C3H/HeJ mice<sup>1</sup>This article is part of a Special Issue entitled Lactoferrin and has undergone the Journal’s usual peer review process.
Bibliographic record
Abstract
Entamoeba histolytica is a protozoan parasite that causes amoebiasis, an illness that affects many people around the world. We have previously reported that lactoferrin is able to kill E. histolytica in in vitro cultures. The aim of the present study was to evaluate the therapeutic effect of orally administered bovine lactoferrin in the control of intestinal amoebiasis of susceptible C3H/HeJ mice. The results showed that 20 mg lactoferrin/kg orally administered each day for 1 week was able to eliminate the infection in 63% of the mice, since neither trophozoites nor evidence of epithelial damage and (or) swelling were found in tissue sections of the cecum. The rest of the treated animals (37%) showed a decrease in trophozoite numbers and mucus secreted to the lumen, as compared with untreated and infected mice (p < 0.05). By immunohistochemistry, the profile of secreted cytokines in the cecum revealed that infected but untreated animals showed a mixed Th1/regulatory cytokines profile, whereas the cecum of mice treated (cured) showed a Th2 cytokine profile (IL-4) and expression of the multifunctional IL-6. In addition, cytokines and increasing cecal production of total IgA antibodies were found associated with little inflammation and disease control observed in the cecum of lactoferrin-treated animals. These results suggest that oral administration of lactoferrin can control intestinal amoebic infection probably by killing amoebas or favoring their removal and reestablish the antiinflammatory intestinal environment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".