Determining rates of epithelial solute transport by optical measurement of fluorochrome concentration gradients in the unstirred layer
Bibliographic record
Abstract
We describe a method for calculating rates of fluorochrome transport from unstirred layer (USL) concentration gradients measured using confocal microscopy. Isolated Malpighian tubules or guts of Drosophila melanogaster were secured to depression slides and bathed in saline containing a fluorescent compound. By measuring the concentration gradient of fluorescent organic anions (fluorescein, Texas Red) or the P-glycoprotein substrate daunorubicin in the USL adjacent to the epithelium we were able to calculate the transepithelial flux of the fluorochrome using Fick's equation. Dose-response curves for fluorescein and Texas Red based on USL concentration gradients near the surface of the Malpighian tubule were comparable to those based on collection and analysis of secreted fluid droplets. Rates of Texas Red and daunorubicin secretion were also calculated for the gut of second instar D. melanogaster larvae, a tissue that is too small for measurement of transport rates by other in vitro techniques such as cannulation and perfusion. Our results suggest that measurement of USL concentration gradients by confocal microscopy may be applicable to any fluorescent indicator of rapidly transported compounds.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".