Lysosomal pH Gradient is Required for Lysosomal Tubulation in Macrophage Cells
Bibliographic record
Abstract
The cells of innate immune system utilize the acidic and hydrolytic lysosome to eliminate invading pathogens through degradation, antigen presentation, and overall immune activation. Activated immune cells change their lysosomes from punctae-shaped structures to form long tubules throughout the cell. Lysosomal remodelling and adaptation have been correlated with increased antigen presentation and T cell activation, but the exact mechanism for this change is yet to be elucidated. Here, we aimed to understand the role of lysosomal pH gradient in the process of lysosomal tubulation. We show that NH4Cl and CQ mediated lysosomal alkalinization decreases lysosomal tubules. We also show marked decrease in lysosomal motility and microtubule structure upon NH4Cl and CQ treatment. This implied that lysosomal pH may be impacting lysosomal tubulation by way of motor proteins or microtubule tracks. Future work is required to understand the role of pH in this immune-relevant process and expand our collective knowledge.
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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) | 0.002 | 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".