Peptidergic control of food intake and digestion in insects<sup>1</sup>This review is part of a virtual symposium on recent advances in understanding a variety of complex regulatory processes in insect physiology and endocrinology, including development, metabolism, cold hardiness, food intake and digestion, and diuresis, through the use of omics technologies in the postgenomic era.
Bibliographic record
Abstract
Like all heterotrophic organisms, insects require a strict control of food intake and efficient digestion of food into nutrients to maintain homeostasis and to fulfill physiological tasks. Feeding and digestion are steered by both external and internal signals that are transduced by a multitude of regulatory factors, delivered either by neurons innervating the gut or mouthparts, or by midgut endocrine cells. The present review gives an overview of peptide regulators known to control feeding and digestion in insects. We describe the discovery and functional role in these processes for insect allatoregulatory peptides, diuretic hormones, FMRFamide-related peptides, (short) neuropeptide F, proctolin, saliva production stimulating peptides, kinins, and tachykinins. These peptides control either gut myoactivity, food intake, and (or) release of digestive enzymes. Some peptides exert their action at multiple levels, possibly having a biological function that depends on their site of delivery. Many regulatory peptides have been physically extracted from different insect species. However, multiple peptidomics, proteomics, transcriptomics, and genome sequencing projects have led to increased discovery and prediction of peptide (precursor) and receptor sequences. In combination with physiological experiments, these large-scale projects have already led to important steps forward in unraveling the physiology of feeding and digestion in insects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".