De novo transcriptome analysis for examination of the nutrition metabolic system related to the evolutionary process through which stick insects gain the ability of flight (Phasmatodea)
Bibliographic record
Abstract
OBJECTIVE: Insects are the most evolutionarily successful groups of organisms, and this success is largely due to their flight ability. Interestingly, some stick insects have lost their flight ability despite having wings. To elucidate the shift from wingless to flying forms during insect evolution, we compared the nutritional metabolism system among flight-winged, flightless-winged, and flightless-wingless stick insect groups. RESULTS: Here, we report RNA sequencing of midgut transcriptome of Entoria okinawaensis, a prominent Japanese flightless-wingless stick insect, and the comparative analysis of its transcriptome in publicly available midgut transcriptomes obtained from seven stick insect species. A gene enrichment analysis for differentially expressed genes, including those obtained from winged vs wingless and flight vs flightless genes comparisons, revealed that carbohydrate metabolic process-related genes were highly expressed in the winged stick insect group. We also found that the expression of the mitochondrial enolase superfamily member 1 transcript was significantly higher in the winged stick insect group than in the wingless stick insect group. Our findings could indicate that carbohydrate metabolic processes are related to the evolutionary process through which stick insects gain the ability of flight.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".