A Weak Base‐Generating System Suitable for Selective Manipulation of Lysosomal pH
Bibliographic record
Abstract
pH varies widely among the different intracellular compartments. The establishment and maintenance of a particular pH appears to be critical for proper organellar function. This has been deduced from experiments where intraorganellar pH was altered by means of weak acids or bases, ionophores or inhibitors of the vacuolar H(+)-ATPase (V-ATPase). These manipulations, however, are not specific and simultaneously alter the pH of multiple compartments. As a result, it is difficult to assign their effect to a defined organelle. To circumvent this limitation, we designed and implemented a procedure to selectively manipulate the pH of a compartment of choice, using lysosomes as a model organelle. The approach is based on the targeted and continuous enzymatic generation of weak electrolyte, which enabled us to overcome the high buffering capacity of the lysosomal lumen, without altering the pH of other compartments. We targeted jack-bean urease to lysosomes and induced the localized generation of ammonia by providing the membrane-permeant substrate, urea. This resulted in a marked, rapid and fully reversible alkalinization that was restricted to the lysosomal lumen, without measurably affecting the pH of endosomes or of the cytosol. The acute alkalinization induced by urease-urea impaired the activity of pH-dependent lysosomal enzymes, including cathepsins C and L, without altering endosomal function. This approach, which can be extended to other organelles, enables the analysis of the role of pH in selected compartments, without the confounding effects of global disturbances in pH or vesicular traffic.
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How this classification was reachedexpand
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) | 0.000 | 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 teacher head, 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".