Immunofluorescence Assay and PCR Analysis of Cryptosporidium Oocysts and Species From Human Fcal Specimens
Bibliographic record
Abstract
BACKGROUND: Cryptosporidium spp. is a widespread protozoan parasite involving humans and animals. OBJECTIVES: This study was carried out to evaluate the immunofluorescence assay (IFA) and PCR results for more accurate diagnosis of faecal specimens. PATIENTS AND METHODS: Forty six faecal human specimens of Cryptosporidium oocysts were examined by PCR and IFA in Calgary, Canada. In statistical analysis, sensitivity and positive predictive value were detected by IFA. RESULTS: Among 46 faecal samples, 9 (19.6%) were IFA-positive and 10 (21.7%) PCR-positive. Faecal smears of both PCR- and IFA-positive shown that the reproducibility was 90.9% for PCR-DNA and 81.8% for IFA. In Our findings, PCR -DNA showed that diagnosis cryptosporidiosis 2.1% was more sensitive than IFA. Two different oocysts sizes were visualized by IF microscopy which belonged to different species. Furthermore, PCR analysis with primers against the 18S rRNA gene indicated two genotypes of C. hominis and C. parvum, 500-650 base pairs (bp). In this study, the golden standard was the PCR. In statistical analyses, IFA had positive predictive value (PPV) of 81.8% with 81.8% sensitivity, whereas negative predictive value (NPV) was 1% with 0.97% specificity. CONCLUSIONS: PCR showed more sensitivity than IFA for tracking Cryptosporidium oocysts as well as detection of species in faecal human specimens.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.001 | 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".