Regulation of physiological and pathological Th1 and Th2 responses by lactoferrinThis 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.
Bibliographic record
Abstract
In recent years, Lf has gained increasing interest as a result of its protective effects against a variety of diseases. While iron binding and interactions with mammalian receptors and microbial components are the best described mechanisms of action, recent studies have provided evidence that Lf properties may be related to immunoregulatory effects on Th1/Th2 cell activities. In vitro and in vivo experiments show that Lf is able to stimulate the differentiation of T cells from their immature precursors through the induction of the CD4 antigen. Studies performed under nonpathogenic conditions have shown distinct results with regard to the ability of Lf to support the proliferation and differentiation of Th cells into the Th1 or the Th2 phenotype. In addition, Lf plays different roles in diseases by affecting the Th1/Th2 cytokine balance in a manner dependent on the host's immune status. Thus, Lf could cause a Th1 polarization in diseases in which the ability to control infection or tumor relies on a strong Th1 response. Lf may also reduce the Th1 component to limit excessive inflammatory responses. Finally, Lf may provide protection against Th1- or Th2-induced diseases, such as autoimmune or allergic diseases, through correction of the Th1/Th2 imbalance.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".