The serine protease Brachyuran is highly expressed in the posterior midgut of the black soldier fly, Hermetia illucens, during the processing of horse droppings
Bibliographic record
Abstract
Abstract Objective Livestock droppings cause some environmental problems, but they have the potential to be used as effective biomass resources. The black soldier fly (BSF), Hermetia illucens (Diptera: Stratiomyidae), is suitable for the efficient processing of livestock droppings. By using BSF larvae for the disposal of livestock droppings, we can obtain two valuable products: protein resources and organic fertilizer. However, there is not enough research on the digestive enzymes suitable for processing livestock droppings. Here, we aimed to construct an efficient BSF processing system using livestock droppings, and we explored the digestive enzymes involved in this process. Results First, we investigated the characteristics of transcripts expressed in the midgut of H. illucens and found that immune response-related genes were expressed in the midgut. Then, we investigated digestive enzymes and identified a novel serine protease, HiBrachyuran , whose mRNA was highly expressed in the posterior midgut when H. illucens larvae fed on horse droppings. Despite the low protein content of horse droppings, larvae that fed on horse droppings accumulated more protein than did those in the other groups. Therefore, HiBrachyuran may contribute to digestibility in the early stage of protein degradation in H. illucens larvae fed on horse droppings.
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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) | 0.001 | 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".