Molecular characterization and diagnostic potential of serine proteinase inhibitors from Taenia solium
Bibliographic record
Abstract
Abstract Serine protease inhibitors (serpins) play essential physiological roles in a wide range of biological processes. Serpins are researched limited inTaenia solium, although some are considered to participate in host immune responses. Tsserpins were identified as typical serpins due to the primary structure of characteristic features: the serpin motif, serpin signature and reaction centre loop (RCL). RCLs of four serpin genes (TsB6, Ts4848, Ts12383 and Ts570) contained the conserved sequences of inhibitory serpins, which may involve in immune regulation. TsEP45 differed greatly from the patterns of representative serpins, suggesting that TsEP45 may be non-inhibitory. The bioinformatic analyses were supposed that Tsserpins might be a potential antigen for diagnosis. The five recombinant Tsserpin proteins were expressed and identified reacting withCysticercus cellulosae-positive serum samples. The indirect enzyme-linked immunosorbent assay (iELISAs) based on Tsserpins were developed and validated, one of the five Tsserpins, TsEP45, showed excellent diagnostic results with 93·33% sensitivity and 94·12% specificity, respectively. This performance was in perfect accordance with the results of the bioinformatic analysis. This study provided a comprehensive demonstration of sequences and structural-based analysis of Tsserpins. The iELISAs based on five Tsserpins were developed and compared.TsEP45 was the potential species-specific antigen for developing iELISA to detect porcine cysticercosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".