What biologists want from their chloride reporters – a conversation between chemists and biologists
Bibliographic record
Abstract
Impaired chloride transport affects diverse processes ranging from neuron excitability to water secretion, which underlie epilepsy and cystic fibrosis, respectively. The ability to image chloride fluxes with fluorescent probes has been essential for the investigation of the roles of chloride channels and transporters in health and disease. Therefore, developing effective fluorescent chloride reporters is critical to characterizing chloride transporters and discovering new ones. However, each chloride channel or transporter has a unique functional context that demands a suite of chloride probes with appropriate sensing characteristics. This Review seeks to juxtapose the biology of chloride transport with the chemistries underlying chloride sensors by exploring the various biological roles of chloride and highlighting the insights delivered by studies using chloride reporters. We then delineate the evolution of small-molecule sensors and genetically encoded chloride reporters. Finally, we analyze discussions with chloride biologists to identify the advantages and limitations of sensors in each biological context, as well as to recognize the key design challenges that must be overcome for developing the next generation of chloride sensors.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.008 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".