Nanolitre real-time PCR detection of bacterial, parasitic, and viral agents from patients with diarrhoea in Nunavut, Canada
Bibliographic record
Abstract
BACKGROUND: Little is known about the microbiology of diarrhoeal disease in Canada's Arctic regions. There are a number of limitations of conventional microbiology testing techniques for diarrhoeal pathogens, and these may be further compromised in the Arctic, given the often long distances for specimen transport. OBJECTIVE: To develop a novel multiple-target nanolitre real-time reverse transcriptase (RT)-PCR platform to simultaneously test diarrhoeal specimens collected from residents of the Qikiqtani (Baffin Island) Region of Nunavut, Canada, for a wide range of bacterial, parasitic and viral agents. STUDY DESIGN/METHODS: Diarrhoeal stool samples submitted for bacterial culture to Qikiqtani General Hospital in Nunavut over an 18-month period were tested with a multiple-target nanolitre real-time PCR panel for major diarrhoeal pathogens including 8 bacterial, 6 viral and 2 parasitic targets. RESULTS: Among 86 stool specimens tested by PCR, a total of 50 pathogens were detected with 1 or more pathogens found in 40 (46.5%) stool specimens. The organisms detected comprised 17 Cryptosporidium spp., 5 Clostridium difficile with toxin B, 6 Campylobacter spp., 6 Salmonella spp., 4 astroviruses, 3 noroviruses, 1 rotavirus, 1 Shigella spp. and 1 Giardia spp. The frequency of detection by PCR and bacterial culture was similar for Salmonella spp., but discrepant for Campylobacter spp., as Campylobacter was detected by culture from only 1/86 specimens. Similarly, Cryptosporidium spp. was detected in multiple samples by PCR but was not detected by microscopy or enzyme immunoassay. CONCLUSIONS: Cryptosporidium spp., Campylobacter spp. and Clostridium difficile may be relatively common but possibly under-recognised pathogens in this region. Further study is needed to determine the regional epidemiology and clinical significance of these organisms. This method appears to be a useful tool for gastrointestinal pathogen research and may also be helpful for clinical diagnostics and outbreak investigation in remote regions where the yield of routine testing may be compromised.
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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 | 0.000 | 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 | 0.000 |
| 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".