Effects of mating on female reproductive physiology in the insect model, Rhodnius prolixus, a vector of the causative parasite of Chagas disease
Bibliographic record
Abstract
The blood-sucking hemipteran Rhodnius prolixus is one of the main vectors of Chagas disease, a neglected tropical disease that affects several million people worldwide. Consuming a blood meal and mating are events with a high epidemiological impact since after each meal, mated females can lay fertile eggs that result in hundreds of offspring. Thus, a better knowledge of the control of R. prolixus reproductive capacity may provide targets for developing novel strategies to control vector populations, thereby reducing vector-host contacts and disease transmission. Here, we have used a combination of gene transcript expression analysis, biochemical assays, hormone measurements and studies of locomotory activity to investigate how mating influences egg development and egg laying rates in R. prolixus females. The results demonstrate that a blood meal increases egg production capacity and leads to earlier egg laying in mated females compared to virgins. Virgin females, however, have increased survival rate over mated females. Circulating juvenile hormone (JH) and ecdysteroid titers are increased in mated females, a process mainly driven through an upregulation of the transcripts for their biosynthetic enzymes in the corpus allatum and ovaries, respectively. Mated females display weaker locomotory activity compared to virgin females, mainly during the photophase. In essence, this study shows how reproductive output and behaviour are profoundly influenced by mating, highlighting molecular, biochemical, endocrine and behavioral features differentially expressed in mated and virgin R. prolixus females.
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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".