Active transport of brilliant blue FCF across the <i>Drosophila</i> midgut and Malpighian tubule epithelia
Bibliographic record
Abstract
Abstract Under conditions of stress, many animals suffer from epithelial barrier disruption that can cause molecules to leak down their concentration gradients, potentially causing a loss of organismal homeostasis, further injury or death. Drosophila is a common insect model, used to study barrier disruption related to aging, traumatic injury, or environmental stress. Net leak of a non-toxic dye (Brilliant blue FCF) from the gut lumen to the hemolymph is often used to identify barrier failure under these conditions, but Drosophila are capable of actively transporting structurally-similar compounds. Here, we examined whether cold stress (like other stresses) causes Brilliant blue FCF (BB-FCF) to appear in the hemolymph of flies fed the dye, and if so whether Drosophila are capable of clearing this dye from their body following chilling. Using in situ midgut leak and transport assays as well as Ramsay assays of Malpighian tubule transport, we tested whether these ionoregulatory epithelia can actively transport BB-FCF. In doing so, we found that the Drosophila midgut and Malpighian tubules can mobilize BB-FCF via an active transcellular pathway, suggesting that elevated concentrations of the dye in the hemolymph may occur from increased paracellular permeability, reduced transcellular clearance, or both. Summary Statement Drosophila are able to actively secrete Brilliant blue FCF, a commonly used marker of barrier dysfunction
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 | 0.001 |
| 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".