Quantification of Leishmania (Viannia) Kinetoplast DNA in Ulcers of Cutaneous Leishmaniasis Reveals Inter-site and Inter-sampling Variability in Parasite Load
Bibliographic record
Abstract
Cutaneous leishmaniasis (CL) is a skin disease caused by the protozoan parasite Leishmania. Few studies have assessed the influence of the sample collection site within the ulcer and the sampling method on the sensitivity of parasitological and molecular diagnostic techniques for CL. Sensitivity of the technique can be dependent upon the load and distribution of Leishmania amastigotes in the lesion.We applied a quantitative real-time PCR (qPCR) assay for Leishmania (Viannia) minicircle kinetoplast DNA (kDNA) detection and parasite load quantification in biopsy and scraping samples obtained from 3 sites within each ulcer (border, base, and center) as well as in cytology brush specimens taken from the ulcer base and center. A total of 248 lesion samples from 31 patients with laboratory confirmed CL of recent onset (≤3 months) were evaluated. The kDNA-qPCR detected Leishmania DNA in 97.6% (242/248) of the examined samples. Median parasite loads were significantly higher in the ulcer base and center than in the border in biopsies (P<0.0001) and scrapings (P = 0.0002). There was no significant difference in parasite load between the ulcer base and center (P = 0.80, 0.43, and 0.07 for biopsy, scraping, and cytology brush specimens, respectively). The parasite load varied significantly by sampling method: in the ulcer base and center, the descending order for the parasite load levels in samples was: cytology brushes, scrapings, and biopsies (P<0.0001); in the ulcer border, scrapings had higher parasite load than biopsies (P<0.0001). There was no difference in parasite load according to L. braziliensis and L. peruviana infections (P = 0.4).Our results suggest an uneven distribution of Leishmania amastigotes in acute CL ulcers, with higher parasite loads in the ulcer base and center, which has implications for bedside collection of diagnostic specimens. The use of scrapings and cytology brushes is recommended instead of the more invasive biopsy.
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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 | 0.001 | 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".