DNA Fingerprinting of Cryptosporidium parvum Isolates Using Amplified Fragment Length Polymorphism (AFLP)
Bibliographic record
Abstract
The genetic variability of 10 Cryptosporidium parvum isolates of human and animal origin was investigated using amplified fragment length polymorphism (AFLP). Analysis of fluorescent dye-labeled amplified products was carried out using an ABI PRISMS 377 DNA sequencer and ABI PRISMS GeneScan software. One-hundred and twelve primer combinations were evaluated using a single C. parvum isolate. The patterns generated were highly reproducible. For subsequent study, a subset of 9 primer pairs that yielded 30-90 DNA fragments after the polymerase chain reaction, within the size range of 50-500 bp, was used to screen the 10 C. parvum isolates, including 7 bovine, 1 equine, and 2 of human origin. The animal isolates produced identical fingerprint patterns with every primer combination tested. Of the 2 human isolates tested, 1 of the isolates, passaged in calves, generated the same AFLP DNA banding patterns as the animal isolates, whereas the other isolate, obtained directly from human feces, produced unique patterns. Polymorphism, detected by comparison of the fingerprint patterns of the latter human isolate with the common pattern shared by all other isolates, ranged from 17 to 35% for the 9 primer pairs. The results show that AFLP is a useful method for differentiating C. parvum isolates into 2 distinct genotypes.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".