An Insulin-Like Growth Factor in Rhodnius prolixus Is Involved in Post-feeding Nutrient Balance and Growth
Bibliographic record
Abstract
Growth of organisms is modulated by the availability of nutrients and energy, and is mostly regulated by insulin-like growth factors (IGFs) through the insulin signaling system. In insects, IGFs produced by the fat body induce cell division during the molt cycle, regulate adult body size and have metabolic effects. Here we describe an IGF from the hematophagous hemipteran Rhodnius prolixus and show its activity in regulating growth and metabolism in the post-feeding period during the fifth, and last, nymphal instar. Rhopr-IGF transcript is present in a variety of tissues, with greatest expression in the fat body, the dorsal vessel and the CNS. We silenced the expression of the transcript using RNA interference, and at two weeks after feeding, insects with reduced Rhopr-IGF expression showed increased hemolymph lipid and carbohydrate levels when compared to controls, but no differences were observed in fat body lipid or carbohydrate content. In order to assess the role of Rhopr-IGF in post-feeding growth, double stranded IGF-injected insects were followed through ecdysis, and this treatment resulted in shorter adults, with shorter and narrower wings, when compared to controls. The results suggest that Rhopr-IGF modulates growth in R. prolixus most likely through altering the usage of nutrients that are available in the hemolymph.
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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".