Use of Discriminatory Probes for Strain Typing of Formalin-Fixed, Rabies Virus-Infected Tissues by In Situ Hybridization
Bibliographic record
Abstract
An in situ hybridization (ISH) method has been developed to overcome difficulties encountered in the viral typing of formalin-fixed rabies virus-infected brain tissue. Rabies viruses representative of all strains normally encountered in diagnostic submissions throughout Canada, including 3 strains of terrestrial hosts (arctic fox, western skunk, mid-Atlantic raccoon), 10 strains circulating in several bat reservoirs (BBCAN1 to BBCAN7, LACAN, SHCAN, and MYCAN), and the Evelyn-Rokitniki-Abelseth (ERA) strain, used as an oral vaccine for fox rabies control in Ontario, were targeted. Partial phosphoprotein gene fragments generated from reverse transcription (RT)-PCR products of specimens of each viral type were molecularly cloned and used to produce negative-sense digoxigenin-labeled RNA transcripts. Conditions permitting the use of these transcripts as strain-specific probes were optimized by blotting analyses with RT-PCR amplicons generated with representative rabies viruses and by ISH applied to mouse brains inoculated with these strains. The successful application of this methodology to two rabies virus-positive specimens that were also identified by traditional methods and the retrospective typing of two archival rabies virus-positive equine specimens is described. This technique provides a typing regimen for rabies virus isolates submitted in a form that is normally recalcitrant to alternate typing strategies.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".