Oral recombinant human or mouse lactoferrin reduces <i>Mycobacterium tuberculosis</i> TDM induced granulomatous lung pathology
Bibliographic record
Abstract
Trehalose 6′6-dimycolate (TDM) is the most abundant glycolipid on the cell wall of Mycobacterium tuberculosis (MTB). TDM is capable of inducing granulomatous pathology in mouse models that resembles those induced by MTB infection. Using the acute TDM model, this work investigates the effect of recombinant human and mouse lactoferrin to reduce granulomatous pathology. C57BL/6 mice were injected intravenously with TDM at a dose of 25 μg·mouse−1. At day 4 and 6, recombinant human or mouse lactoferrin (1 mg·(100 μL)−1·mouse−1) were delivered by gavage. At day 7 after TDM injection, mice were evaluated for lung pathology, cytokine production, and leukocyte populations. Mice given human or mouse lactoferrin had reduced production of IL-12p40 in their lungs. Mouse lactoferrin increased IL-6 and KC (CXCL1) in lung tissue. Increased numbers of macrophages were observed in TDM-injected mice given human or mouse lactoferrin. Granulomatous pathology, composed of mainly migrated leukocytes, was visually reduced in mice that received human or mouse lactoferrin. Quantitation of granulomatous pathology demonstrated a significant decrease in mice given human or mouse lactoferrin compared with TDM control mice. This report is the first to directly compare the immune modulatory effects of both heterologous recombinant human and homologous mouse lactoferrin on the development of TDM-induced granulomas.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".