Comparison of agar plate and real-time PCR on enumeration of Lactobacillus, Clostridium perfringens and total anaerobic bacteria in dog faeces
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Bibliographic record
Abstract
AIMS: To compare agar plate and real-time PCR methods on enumeration of total anaerobic bacteria, Lactobacillus and Clostridium perfringens in dog faeces. METHODS AND RESULTS: Thirty-two faecal specimens from Labrador retriever dogs were used to compare agar plate and real-time PCR enumeration methods for Lactobacillus, C. perfringens and total anaerobic bacteria. Total anaerobic bacteria, C. perfringens and Lactobacillus of faeces were counted (as CFU g(-1) faeces) for 48-h incubation at 37 degrees C in an anaerobic gas chamber on genus-selective media. Total genomic DNA from samples was extracted by the QIAamp DNA stool mini kit. The quantification of DNA (as DNA copy per gram faeces) by real-time PCR was performed with a LightCycler system with the QuantiTect SYBR green PCR kit for PCR amplification. The results indicated that there was a significant correlation between CFU and DNA copy of Lactobacillus (R2 = 0.78, P < 0.01) and total anaerobic bacteria (R2 = 0.21, P < 0.05); but no correlation was found between CFU and DNA copy of C. perfringens. The regression equations for Lactobacillus and total anaerobic bacteria were log(DNA copy) = 0.83 x log(CFU) + 1.43 and log(DNA copy) = 1.62 x log(CFU) - 6.32 respectively. CONCLUSIONS: The real-time PCR method could be used to enumerate Lactobacillus within 2 days when compared with plating method which requires 5-6 days. SIGNIFICANCE AND IMPACT OF THE STUDY: The real-time PCR method and the primer set for Lactobacillus spp. harboured in the dog intestine can be used for rapid enumeration of lactobacilli and monitoring of the faecal Lactobacillus community.
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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 it