PHAIR: a biosensor for pH measurement in air–liquid interface cell culture
Bibliographic record
Abstract
In many biological systems, pH can be used as a parameter to understand and study cell dynamics. However, measuring pH in live cell culture is limited by the sensor ion specificity, proximity to the cell surface, and scalability. Commercially available pH sensors are difficult to integrate into a small-scale cell culture system due to their size and are not cost-effective for disposable use. We made PHAIR-a new pH sensor that uses a micro-wire format to measure pH in vitro human airway cell culture. Tungsten micro-wires were used as the working electrodes, and silver micro-wires with a silver/silver chloride coating were used as a pseudo reference electrode. pH sensitivity, in a wide and narrow range, and stability of these sensors were tested in common standard buffer solutions as well as in culture media of human airway epithelial cells grown at the air-liquid interface in a 24 well cell culture plate. When measuring the pH of cells grown under basal and challenge conditions using PHAIR, cell viability and cytokine responses were not affected. Our results confirm that micro-wire-based sensors have the capacity for miniaturization and detection of diverse ions while maintaining sensitivity. This suggests the broad application of PHAIR in various biological experimental settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".