Interactions of lactoferrin with cells involved in immune functionThis paper is one of a selection of papers published in this Special Issue, entitled 7th International Conference on Lactoferrin: Structure, Function, and Applications, and has undergone the Journal's usual peer review process.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The antimicrobial activities of lactoferrin (Lf) depend on its capacity to bind iron and on its direct interaction with the surface of microorganisms. Its protective effect also extends to the regulation of the host response to infections. Depending on the immune status of an individual, Lf can have anti-inflammatory properties that downregulate the immune response and prevent septic shock and damage to tissues. It also acts as a promoter of the activation, differentiation, and (or) proliferation of immune cells. Although most of the anti-inflammatory activities are correlated with the neutralization of proinflammatory molecules by Lf, the promoting activity seems to be related to a direct effect of Lf on immune cells. Although the mechanisms that govern these activities are not clearly defined, and probably differ from cell to cell, several cellular targets and possible mechanisms of action are highlighted. The majority of the molecular targets at the surface of cells are multiligand receptors but, interestingly, most of them have been reported as signaling, endocytosis, and nuclear-targeting molecules. This review focuses on the known and putative mechanisms that allow the immunoregulating effect of Lf in its interactions with immune cells.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it