Antigenic characterisation of lyssaviruses in South Africa
Bibliographic record
Abstract
There are at least six Lyssavirus species that have been isolated in Africa, which include classical rabies virus, Lagos bat virus, Mokola virus, Duvenhage virus, Shimoni bat virus and Ikoma lyssavirus. In this retrospective study, an analysis of the antigenic reactivity patterns of lyssaviruses in South Africa against a panel of 15 anti-nucleoprotein monoclonal antibodies was undertaken. A total of 624 brain specimens, collected between 2005 and 2009, confirmed as containing lyssavirus antigen by direct fluorescent antibody test, were subjected to antigenic differentiation. The lyssaviruses were differentiated into two species, namely rabies virus (99.5%) and Mokola virus (0.5%). Furthermore, rabies virus was further delineated into two common rabies biotypes in South Africa: canid and mongoose. Initially, it was found that the canid rabies biotype had two reactivity patterns; differential staining was observed with just one monoclonal antibody. This difference was likely to have been an artefact related to sample quality, as passage in cell culture restored staining. Mongoose rabies viruses were more heterogeneous, with seven antigenic reactivity patterns detected. Although Mokola viruses were identified in this study, prevalence and reservoir host species are yet to be established. These data demonstrate the usefulness of monoclonal antibody typing panels in lyssavirus surveillance with reference to emergence of new species or spread of rabies biotypes to new geographic zones.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".