Leveraging sex determination systems for genetic biocontrol of dipteran pests
Bibliographic record
Abstract
Genetic biocontrol is an increasingly important way to suppress insect pest populations and to mitigate their economic and health impact. One key advantage is that it is species-specific, as it relies on the mating of released males with wild females to either suppress or modify populations. The latter is through rendering females incompetent at disease transmission. Sex separation is critical to ensure the efficiency of these control programs, and it is essential in the case of vector control to avoid releasing females that can transmit pathogens. Modern genetic methods provide the opportunity to target or manipulate components of the sex determination systems to facilitate genetic biocontrol with new means to effectively accomplish sex-specific selection, lethality, or sterility. For example, sex-specific splicing elements in genes in the sex determination pathway are used to produce sex-specific markers. Sex-linked recessive lethal alleles are used to differentially eliminate the transgene-marked sex chromosome from males to produce nontransgenic males. Knocking out or knocking down sex-specific isoforms of genes in the sex determination pathway is employed to confer female-specific lethality or sterility. Sex determination pathways and sex chromosomes are also targeted for gene drives that suppress pest populations by introducing extreme sex ratio biases. Here, we review these and other recent advances in genetic technologies for pest control that have benefited from knowledge of sex determination systems in Diptera.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".