Mating behaviour and cholesterol nutritional strategies promoted ovarian development of female swimming crab (<i>Portunus trituberculatus</i>)
Bibliographic record
Abstract
Abstract Female crabs enter a stage of rapid ovarian development after mating, and cholesterol is a substrate for steroid hormone synthesis. Therefore, in this experiment, an 8-week feeding trial was conducted to investigate the effects of mating treatments (mated crab and unmated crab) and three dietary cholesterol levels (0·09 %, 0·79 % and 1·40 %) on ovarian development, cholesterol metabolism and steroid hormones metabolism of adult female swimming crab (Portunus trituberculatus). The results indicated that crabs fed the diet with 0·79 % cholesterol significantly increased gonadosomatic index (GSI) and vitellogenin (VTG) content than other treatments in the same mating status. Moreover, mated crabs had markedly increased GSI and VTG content in the ovary and hepatopancreas than unmated crabs. The histological observation found that exogenous vitellogenic oocytes appeared in the mated crabs, while previtellogenic oocytes and endogenous vitellogenic oocytes were the primary oocytes in unmated crabs. The transmission electron microscopy analysis showed that when fed diet with 0·79 % cholesterol, the unmated crabs contained more rough endoplasmic reticulum and mated crabs had higher yolk content than other treatments. Furthermore, mating treatment and dietary 0·79 % cholesterol level both promoted cholesterol deposition by up-regulation of the mRNA and protein expression levels of class B scavenger receptors 1 (Srb1), while stimulating the secretion of steroid hormones by up-regulation of the mRNA and protein expression of steroidogenic acute regulatory protein (Star). Overall, the present results indicated that mating behaviour plays a leading role in promoting ovarian development, and dietary 0·79 % cholesterol level can further promote ovarian development after mating.
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 | 0.000 | 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".