A Quantitative Assay for Ca2+ Uptake through Normal and Pathological Hemichannels
Bibliographic record
Abstract
Connexin (Cx) hemichannels (HCs) are large pore hexameric structures that allow the exchange of ions, metabolites and a variety of other molecules between the cell cytoplasm and extracellular milieu. HC inhibitors are attracting growing interest as drug candidates because deregulated fluxes through HCs have been implicated in a plethora of genetic conditions and other diseases. HC activity has been mainly investigated by electrophysiological methods and/or using HC-permeable dye uptake measurements. Here, we present an all-optical assay based on fluorometric measurements of ionized calcium (Ca2+) uptake with a Ca2+-selective genetically encoded indicator (GCaMP6s) that permits the optical tracking of cytosolic Ca2+ concentration ([Ca2+]cyt) changes with high sensitivity. We exemplify use of the assay in stable pools of HaCaT cells overexpressing human Cx26, Cx46, or the pathological mutant Cx26G45E, under control of a tetracycline (Tet) responsive element (TRE) promoter (Tet-on). We demonstrate the usefulness of the assay for the characterization of new monoclonal antibodies (mAbs) targeting the extracellular domain of the HCs. Although we developed the assay on a spinning disk confocal fluorescence microscope, the same methodology can be extended seamlessly to high-throughput high-content platforms to screen other kinds of inhibitors and/or to probe HCs expressed in primary cells and microtissues.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".