Consistency, distinction, and potential metabolic crosstalk of nitrogen mobilization-related genes in silk production and silk gland biology
Bibliographic record
Abstract
The domesticated silkworm (Bombyx mori) has evolved a highly efficient nitrogen utilization system to support silk production. The silk glands play a pleiotropic role in sequestering nitrogen resources for silk synthesis, mitigating aminoacidemia by assimilating free amino acids, and reallocating nitrogen during metamorphosis through programmed cell death. However, the specific functions of nitrogen metabolism-related genes in this process remain unclear. Using CRISPR/Cas9-based gene editing, mutations were generated in glutamine synthetase (GS), glutamate synthetase (GOGAT), asparagine synthetase (AS), glutamate dehydrogenase (GDH) and glutamate oxaloacetate transaminase 1 (GOT1). Disruption of GS, GOGAT, and AS consistently reduced silkworm cocoon and pupal weight and significantly down-regulated silk protein gene transcription, whereas GOT1 mutation had no such effect. GOGAT mutants exhibited abnormally enlarged silk glands, whereas GS and AS mutants showed delayed programmed cell death in the silk glands. In contrast, GOT1 mutants displayed normal silk gland morphology but were consistently smaller. Disruption of GS, GOGAT, and AS led to more extensive transcriptional changes, including altered expression of transcription factors in the silk glands, compared with GOT1 mutants. Both GS and GOGAT mutants exhibited up-regulation of AS and GDH, while only GOGAT mutants displayed elevated AS enzymatic activity, suggesting that GOGAT may compete with AS for glutamine in the silk glands to support silk protein synthesis. AS mutants showed significantly elevated GOT activity and up-regulation of several metabolic pathways, indicating that AS may functionally interact with GOT in regulating both silk gland development and programmed cell death during metamorphosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".