K+ absorption by locust gut and inhibition of ileal K+ and water transport by FGLamide allatostatins.
Bibliographic record
Abstract
The scanning ion-selective electrode technique (SIET) was utilized for the first time in Locusta migratoria to characterize K(+) transport along the digestive tract and to determine the effect of two locust FGLamide allatostatins (FGLa/ASTs) on K(+) transport: a previously sequenced FGLa/AST from Schistocerca gregaria (Scg-AST-6; ARPYSFGL-NH2) and a newly sequenced FGLa/AST from L. migratoria (Locmi-FGLa/AST-2; LPVYNFGL-NH2). Regional differences in K(+) fluxes along the gut were evident, where K(+) efflux in vitro (or absorption into the hemolymph in vivo) was greatest at the anterior ileum, and lowest at the colon. Ileal K(+) efflux was inhibited by both Scg-AST-6 and Locmi-FGLa/AST-2, with maximal inhibition at 10(-10) and 10(-11) mol l(-1), respectively. Both FGLa/ASTs also inhibited cAMP-stimulated K(+) efflux from the ileum. Locmi-FGLa/AST-2 also inhibited efflux of water across the ileum. Locusts are terrestrial insects living in dry climates, risking desiccation and making water conservation a necessity. The results suggest that FGLa/ASTs may be acting as diuretics by increasing K(+) excretion and therefore increasing water excretion. Thus it is likely that FGLa/ASTs are involved in the control of hemolymph water and ion levels during feeding and digestion, to help the locust deal with the excess K(+) load (and subsequently fluid) when the meal is processed.
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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 | 0.000 | 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 | 0.000 |
| 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".