Integrative Approach for the Reliable Detection and Specific Identification of the Microsporidium <i>Loma morhua</i> in Atlantic Cod (<i>Gadus morhua</i>)
Bibliographic record
Abstract
Microsporidia are fungal parasites that infect diverse invertebrate and vertebrate hosts. Finfish aquaculture supports epizootics due to high host density and the high biotic potential of these parasites. Reliable methods for parasite detection and identification are a necessary precursor to empirical assessment of strategies to mitigate the effects of these pathogens during aquaculture. We developed an integrative approach to detect and identify Loma morhua infecting Atlantic cod. We show that the spleen is more reliable than the commonly presumed gills as best organ for parasite detection in spite of substantial morphological plasticity in xenoma complexes. We developed rDNA primers with 100% sensitivity in detecting L. morhua and with utility in distinguishing some congeneric Loma species. ITS sequencing is necessary to distinguish L. morhua from other congeneric microsporidia due to intraspecific nucleotide variation. 64% of L. morhua ITS variants from Atlantic cod have a 9-nucleotide motif that distinguishes it from Loma spp. infecting non-Gadus hosts. The remaining 36% of ITS variants from Atlantic cod are distinguished from currently represented Loma spp., particularly those infecting Gadus hosts, based on a 14-nucleotide motif. This research approach is amenable to developing templates in support of reliable detection and identification of other microsporidian parasites in fishes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".