Congenital Malformations in Sea Turtles: Puzzling Interplay between Genes and Environment
Bibliographic record
Abstract
The completion of embryonic development depends, in part, on the interplay between genetic factors and environmental conditions, and any alteration during development may affect embryonic genetic and epigenetic regulatory pathways leading to congenital malformations, which are mostly incompatible with life. Oviparous reptiles, such as sea turtles, that produce numerous eggs in a clutch that is buried on the beach provide an opportunity to study embryonic mortality associated with malformations that occur at different times during development, or that prevent the hatchling from emerging from the nest. In sea turtles, the presence of congenital malformations frequently leads to mortality. A few years ago, a detailed study was performed on external congenital malformations in three species of sea turtles from the Mexican Pacific and Caribbean coasts, the hawksbill turtle, Eretmochelys imbricata (n = 23,559 eggs), the green turtle, Chelonia mydas (n = 17,690 eggs), and the olive ridley, Lepidochelys olivacea (n = 20,257 eggs), finding 63 types of congenital malformations, of which 38 were new reports. Of the three species, the olive ridley showed a higher incidence of severe anomalies in the craniofacial region (49%), indicating alterations of early developmental pathways; however, several malformations were also observed in the body, including defects in the carapace (45%) and limbs (33%), as well as pigmentation disorders (20%), indicating that deviations occurred during the middle and later stages of development. Although intrinsic factors (i.e., genetic mutations or epigenetic modifications) are difficult to monitor in the field, some environmental factors (such as the incubation temperature, humidity, and probably the status of feeding areas) are, to some extent, less difficult to monitor and/or control. In this review, we describe the aetiology of different malformations observed in sea turtle embryos, and provide some actions that can reduce embryonic mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".