Quantifying Interactions Within the NADP(H) Enzyme Network in <i>Drosophila melanogaster</i>
Bibliographic record
Abstract
In this report, we use synthetic, activity-variant alleles in Drosophila melanogaster to quantify interactions across the enzyme network that reduces nicotinamide adenine dinucleotide phosphate (NADP) to NADPH. We examine the effects of large-scale variation in isocitrate dehydrogenase (IDH) or glucose-6-phosphate dehydrogenase (G6PD) activity in a single genetic background and of smaller-scale variation in IDH, G6PD, and malic enzyme across 10 different genetic backgrounds. We find significant interactions among all three enzymes in adults; changes in the activity of any one source of a reduced cofactor generally result in changes in the other two, although the magnitude and directionality of change differs depending on the gene and the genetic background. Observed interactions are presumably through cellular mechanisms that maintain a homeostatic balance of NADPH/NADP, and the magnitude of change in response to modification of one source of reduced cofactor likely reflects the relative contribution of that enzyme to the cofactor pool. Our results suggest that malic enzyme makes the largest single contribution to the NADPH pool, consistent with the results from earlier experiments in larval D. melanogaster using naturally occurring alleles. The interactions between all three enzymes indicate functional interdependence and underscore the importance of examining enzymes as components of a network.
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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) | 0.000 | 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".