γ-Interferon-inducible Lysosomal Thiol Reductase (GILT) Maintains Phagosomal Proteolysis in Alternatively Activated Macrophages
Bibliographic record
Abstract
Although it is known that lysosomal cysteine cathepsins require a reducing environment for optimal activity, it is not firmly established how these enzymes are maintained in their reduced-active state in the acidic and occasionally oxidative environment within phagosomes and lysosomes. γ-Interferon-inducible lysosomal thiol reductase (GILT) has been the only enzyme described in the endosomes, lysosomes, and phagosomes with the potential to catalyze the reduction of cysteine cathepsins. Our goal in the current study was to assess the effect of GILT on major phagosomal functions with an emphasis on proteolytic efficiency in murine bone marrow-derived macrophages. Assessment of phagosomal disulfide reduction upon internalization of IgG-opsonized experimental particles confirmed a major role for GILT in phagosomal disulfide reduction in both resting and interferon-γ-activated macrophages. Furthermore we observed a decrease in early phagosomal proteolytic efficiency in GILT-deficient macrophages, specifically in the absence of an NADPH oxidase-mediated respiratory burst. This deficiency was more prominent in IL-4-activated macrophages that inherently possess lower levels of NADPH oxidase activity. Finally, we provide evidence that GILT is required for optimal activity of the lysosomal cysteine protease, cathepsin S. In summary, our results suggest a role for GILT in maintaining cysteine cathepsin proteolytic efficiency in phagosomes, particularly in the absence of high NADPH oxidase activity, which is characteristic of alternatively activated macrophages.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".