Immunomagnetic Separation Significantly Improves the Sensitivity of Polymerase Chain Reaction in Detecting <i>Giavdia Duodenalis</i> and <i>Cryptosporidium</i> spp. in Dairy Cattle
Bibliographic record
Abstract
The effectiveness of molecular methods for the detection of species of Giardia and Cryptosporidium in fecal samples is often reduced by low or intermittent cyst and oocyst shedding, and/or the presence of polymerase chain reaction (PCR) inhibitors. The present study investigates the use of immunomagnetic separation (IMS) as an additional concentration step before PCR in the detection of these common protozoan parasites in dairy cattle. The IMS-PCR assays were optimized for amplifying fragments of the 16S ribosomal RNA (rRNA), β-giardin, and glutamate dehydrogenase (GDH) genes of Giardia duodenalis, as well as fragments of the 18S rRNA, heat shock protein (HSP)-70, and Cryptosporidium oocyst wall protein (COWP) genes of Cryptosporidium spp. In all cases, IMS-PCR was more sensitive than PCR alone. A significantly greater number of Giardia-positive samples were identified using IMS-PCR of the 16S rRNA gene (P < 0.01) and of the GDH gene (P < 0.01), as compared with PCR without any additional concentration step. In the case of Cryptosporidium, IMS-PCR of the COWP gene (P = 0.02) resulted in a significantly greater number of positives than did PCR without the IMS concentration step. The greatest number of positives, however, was obtained using IMS-PCR to amplify a portion of the 16S rRNA gene of Giardia and a portion of the HSP-70 gene of Cryptosporidium. A further comparison of the optimized IMS-PCR assays to immunofluorescence microscopy suggested that the IMS-PCR assays were considerably more sensitive than microscopy was in the detection of Giardia cysts and Cryptosporidium oocysts in fecal samples.
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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 | 0.002 | 0.002 |
| 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 | 0.000 |
| 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 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".