Atractaspis aterrima Toxins: The First Insight into the Molecular Evolution of Venom in Side-Stabbers
Why this work is in the frame
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Bibliographic record
Abstract
Although snake venoms have been the subject of intense research, primarily because of their tremendous potential as a bioresource for design and development of therapeutic compounds, some specific groups of snakes, such as the genus Atractaspis, have been completely neglected. To date only limited number of toxins, such as sarafotoxins have been well characterized from this lineage. In order to investigate the molecular diversity of venom from Atractaspis aterrima-the slender burrowing asp, we utilized a high-throughput transcriptomic approach completed with an original bioinformatics analysis pipeline. Surprisingly, we found that Sarafotoxins do not constitute the major ingredient of the transcriptomic cocktail; rather a large number of previously well-characterized snake venom-components were identified. Notably, we recovered a large diversity of three-finger toxins (3FTxs), which were found to have evolved under the significant influence of positive selection. From the normalized and non-normalized transcriptome libraries, we were able to evaluate the relative abundance of the different toxin groups, uncover rare transcripts, and gain new insight into the transcriptomic machinery. In addition to previously characterized toxin families, we were able to detect numerous highly-transcribed compounds that possess all the key features of venom-components and may constitute new classes of toxins.
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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) | 0.000 | 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) | 0.000 | 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 it