Crosstalk between Nutrition, Insulin, Juvenile Hormone, and Ecdysteroid Signaling in the Classical Insect Model, Rhodnius prolixus
Bibliographic record
Abstract
The rigorous balance of endocrine signals that control insect reproductive physiology is crucial for the success of egg production. Rhodnius prolixus, a blood-feeding insect and main vector of Chagas disease, has been used over the last century as a model to unravel aspects of insect metabolism and physiology. Our recent work has shown that nutrition, insulin signaling, and two main types of insect lipophilic hormones, juvenile hormone (JH) and ecdysteroids, are essential for successful reproduction in R. prolixus; however, the interplay behind these endocrine signals has not been established. We used a combination of hormone treatments, gene expression analyses, hormone measurements, and ex vivo experiments using the corpus allatum or the ovary, to investigate how the interaction of these endocrine signals might define the hormone environment for egg production. The results show that after a blood meal, circulating JH levels increase, a process mainly driven through insulin and allatoregulatory neuropeptides. In turn, JH feeds back to provide some control over its own biosynthesis by regulating the expression of critical biosynthetic enzymes in the corpus allatum. Interestingly, insulin also stimulates the synthesis and release of ecdysteroids from the ovary. This study highlights the complex network of endocrine signals that, together, coordinate a successful reproductive cycle.
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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".