A novel TaqMan qPCR assay for rapid detection and quantification of pro-inflammatory microalgae <i>Prototheca</i> spp. in milk samples
Bibliographic record
Abstract
Animal or human protothecosis belongs to rather rare, endemic, pro-inflammatory infections. It is caused by achlorophyllous algae of the genus Prototheca. Especially, P. bovis (formerly P. zopfii genotype 2) is often inflected as a non-bacterial causative agent of dairy cattle mastitis. In this study, we present a multiplex real-time PCR (qPCR) system for rapid and exact Prototheca spp. detection and quantification. Limit of detection, diagnostic sensitivity, and specificity were determined. For the first time, specific sequences of AccD (encoding acetyl CoA reductase) for P. bovis, cox1 (encoding cytochrome C oxidase subunit 1) for P. wickerhamii, cytB (encoding cytochrome B) for P. blashkeae and atp6 (encoding transporting ATPase F0 subunit 6) for P. ciferrii (formerly P. zopfii genotype 1) were used for species identification and quantification together with 28S rRNA sequence detecting genus Prototheca. The developed qPCR assay was applied to 55 individual cow milk samples from a herd suspected of protothecosis, 41 bulk milk samples from different Czech farms, 16 boxed milk samples purchased in supermarkets and 21 environmental samples originating from a farm suspected of protothecosis. Our work thus offers the possibility to diagnose protothecosis in the samples, where bacterial mastitis is the most commonly presumed and thereby assisting adequate corrective measures to be taken.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".