Catching Rabies by the Toe:: An Investigation into the Toehold Switch as a Sensor for Rabies virus
Bibliographic record
Abstract
Rabies is a disease of the central nervous system caused by the Rabies virus. Current methods to test for Rabies are costly, time consuming, and not sensitive enough to identify the disease early enough for treatment. A novel mechanism of virus identification that has shown promise for Ebola and Zika virus detection is the toehold switch. Toehold switches are RNA-based constructs that allow the visual identification of genomic targets of interest. They are composed of a switch RNA and a trigger RNA. In the presence of the trigger, a change in secondary structure causes the reporter gene following the switch to be expressed. When the trigger is not\npresent, the gene is repressed. This project designed a toehold switch for use as a Rabies virus sensor. First, a region of the Rabies genome was identified as a promising trigger sequence. From this sequence, a complementary switch was designed with GFP as a reporter gene. The designed switch was constructed and inserted into a pBluescript plasmid backbone. The next steps of this project would be to develop an assay to test the effectiveness of the switch to identify Rabies virus.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 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".