Molecular dissection of cobra venom highlights heparinoids as an antidote for spitting cobra envenoming
Bibliographic record
Abstract
Snakebites affect about 1.8 million people annually. The current standard of care involves antibody-based antivenoms, which can be difficult to access and are generally not effective against local tissue injury, the primary cause of morbidity. Here, we used a pooled whole-genome CRISPR knockout screen to define human genes that, when targeted, modify cell responses to spitting cobra venoms. A large portion of modifying genes that conferred resistance to venom cytotoxicity was found to control proteoglycan biosynthesis, including EXT1 , B4GALT7 , EXT2 , EXTL3 , XYLT2 , NDST1 , and SLC35B2 , which we validated independently. This finding suggested heparinoids as possible inhibitors. Heparinoids prevented venom cytotoxicity through binding to three-finger cytotoxins, and the US Food and Drug Administration–approved heparinoid tinzaparin was found to reduce tissue damage in mice when given via a medically relevant route and dose. Overall, our systematic molecular dissection of cobra venom cytotoxicity provides insight into how we can better treat cobra snakebite envenoming.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".