Bovine lactoferrin: benefits and mechanism of action against infectionsThis paper is one of a selection of papers published in this Special Issue, entitled 7th International Conference on Lactoferrin: Structure, Functions, and Applications, and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
Ingestion of bovine lactoferrin (bLF) has been reported to show anti-infective, anti-cancer, and anti-inflammatory effects. In particular, it has become evident that oral bLF had a beneficial effect on infections of both digestive and nondigestive tract tissue in various animal models. Furthermore, the effects of bLF have been indicated in clinical studies on patients with Helicobacter pylori infection, chronic hepatitis C, tinea pedis, and other diseases. Immunomodulation in the intestine and systemic sites has been suggested to mediate the protective effects of oral bLF against infection. Recently, we demonstrated the beneficial effects of oral bLF in influenza virus infected mice. BLF administration reduced the lung consolidation score and the number of infiltrating leukocytes in bronchoalveolar lavage fluid. We also investigated the effect of oral bLF on the transcription of genes related to immunity in the small intestine of mice using the quantitative RT-PCR method. We found that intake of bLF increased the expression of IL-12p40, IFN-beta, and NOD2. Thus, oral bLF activates the transcription of important immune-related genes in the small intestine, and such transcriptional activation may promote systemic host immunity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".