Exploitation of reproductive barriers between Macrobrachium species for responsible aquaculture and biocontrol of schistosomiasis in West Africa
Bibliographic record
Abstract
Macrobrachium prawns are voracious predators of the freshwater snails that host the flatworms responsible for bilharzia (schistosomiasis), a health burden in many African countries.A novel strategy to decrease the disease in Africa involves the use of prawns as biocontrol agents of the snails.Although the endemic African river prawn Macrobrachium vollenhovenii is a natural candidate for aquaculture and biocontrol, efforts to domesticate it have been unsuccessful to date, and it is not available in the large quantities required for aquaculture and biocontrol.The Asian giant prawn Macrobrachium rosenbergii has been cultured worldwide for decades.Recently, novel biotechnologies were developed to create monosex (all-male) non-breeding populations for aquaculture that we suggest are also ideal for biocontrol in Africa.Since the above 2 prawn species are of the same genus, exhibit similar sizes and require a female pre-mating molt prior to egg fertilization, the potential for cross-breeding between the 2 species must be tested.To assure that all-male populations of M. rosenbergii will not pose such an ecological threat, we carried out cross-breeding experiments with M. vollenhovenii.Both interspecies encounters and attempts at artificial insemination revealed that fertilization does not occur between the 2 species.Our results demonstrate both behavioral and physiological pre-zygotic reproductive barriers between these species.We suggest that all-male M. rosenbergii can be used as an aquaculture species and as a biocontrol agent in areas where M. vollenhovenii occurs without concern for hybridization.
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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".