Construction of a Complementary DNA Library of Parelaphostrongylus tenuis and Identification of a Potentially Sero-Diagnostic Recombinant Antigen
Bibliographic record
Abstract
Newly developed serological tests for diagnosing parelaphostrongylosis in cervids, using the excretory-secretory products (ES) of the infective larvae of Parelaphostrongylus tenuis in enzyme-linked immunosorbent assays (ELISAs), have demonstrable superiority over the traditional method of larval recovery and microscopic identification. To generate a source of ELISA antigen by genetic engineering, we created a complementary DNA (cDNA) expression library by the reverse transcription of mRNA of P. tenuis adult worms, and ligation with the vector lambda-ZAP II. The library was screened using antisera produced in mice by immunization with a somatic antigen preparation of adult worms. Seventeen clones were isolated, sequenced, and checked for similarity to other DNA sequences in GenBank. A previously identified parasite gene encoding an aspartyl protease inhibitor (API) was isolated from the cDNA library, subcloned and expressed using the pET expression vector to produce a glutathione S transferase (GST)-His-S.Tag-P. tenuis API fusion protein (molecular weight = 63 kDa). An enzyme-linked immunosorbent assay utilizing the API fusion protein as the coating antigen was used to serologically diagnose all white-tailed deer (WTD, 10 out of 10) that had been inoculated with 6 - 150 L3 P. tenuis, indicating that the antigen may be a useful serodiagnostic antigen for P. tenuis infection in this cervid species.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".