Molecular recognition and phylogenetic tree analysis of Cystoisospora canis in stray dogs in Diwaniyah city, Iraq
Bibliographic record
Abstract
Cystoisospora spp. are Apicomplexa parasites, protozoan parasites with a global prevalence of 1-5% in dogs. The current study aimed at finding out about the presence and molecular features of Cystoisospora among homeless dogs in Al-Diwaniyah province in Iraq. The 200 fecal samples from street dogs from various regions were floated, sedimented and then tested by direct smear. We identified molecularly using PCR from the 18S rRNA gene and sequenced and phylogenetic. A 19% prevalence of Cystoisospora spp. was observed under microscope, the province’s first known case of the parasite. In our infection dogs, the infection rates were higher in females 22.34% than males 16.03%. Younger dogs (puppies) were much more common with prevalence at 38.02%, compared with 8.52% for the older dogs. Cystoisospora DNA was found in 56% (17/30) of the specimens by PCR. Sequence alignment of the 511 bp region of the 18S rRNA gene identified 100% identity with Cystoisospora canis strains already in GenBank from Canada. The strains in locality were identified as Cystoisospora canis by phylogenetic recognition including Unweighted Pair Group Method with Arithmetic Mean (UPGMA). The molecular phylogenetic data from this research on Cystoisospora canis in Iraqi street dogs represents the first such molecular phylogenetic data on this parasite in Iraq and adds to the epidemiology of this parasite in Iraq.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".