pH Micro‐Environments Associated with Transport Activity of the Erythrocyte Membrane Cl <sup>−</sup> /HCO <sub>3</sub> <sup>−</sup> Exchanger, AE1
Bibliographic record
Abstract
Cl − /HCO 3 − exchange proteins (AEs) interact with carbonic anhydrases (CAs) to maximize HCO 3 − transport. CAs catalyse the hydration of CO 2 to HCO 3 − and H + . We hypothesize that rapid AE1‐mediated HCO 3 − transport causes differences in pH between the region around AE1 and the rest of the cell (pH micro‐environments). To examine this possibility we have measured intracellular pH during HCO 3 − transport using pH‐sensitive fluorescent proteins (FPs) localized to unique cellular locations. We have identified a FP, deGFP4, that reports on pH without interference from other ions; deGFP4 had a Stern‐Volmer (Ksv) quenching constant of 5×10 7 M −1 for H + and 0.5 M −1 for Cl − . We constructed deGFP4 fusion proteins to: AE1 N‐terminus (measures pH at the cytosolic surface of AE1), the nucleoside transporter hCNT3 (a spectator protein), calnexin C‐terminus (to probe pH at the cytosolic ER surface), a GPI‐linked construct (to probe pH at the extracellular surface), and deGFP4 alone (cytosolic pH). The AE1‐deGFP4 and cytosolic deGFP4 exhibit an average transport rate of 0.5 pH units/min with an overall change in pH of 0.8 pH units. A new pH‐sensitive red FP (RFP) was recently developed and has been used as a cytosolic pH sensor, and as a fusion to hCNT3. pH was measured simultaneously in distinct regions of the cell using both GFP and RFP fusion proteins. This research is supported by the Canadian Institutes of Health Research.
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 | 0.000 | 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) | 0.001 | 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".