Spatial distribution, Leishmania species and clinical traits of Cutaneous Leishmaniasis cases in the Colombian army
Bibliographic record
Abstract
In Colombia, the cutaneous leishmaniasis (CL) is the most common manifestation across the army personnel.Hence, it is mandatory to determine the species associated with the disease as well as the association with the clinical traits.A total of 273 samples of male patients with CL were included in the study and clinical data of the patients was studied.PCR and sequencing analyses (Cytb and HSP70 genes) were performed to identify the species and the intra-specific genetic variability.A georeferenced database was constructed to identify the spatial distribution of Leishmania species isolated.The identification of five species of Leishmania that circulate in the areas where army personnel are deployed is described.Predominant infecting Leishmania species corresponds to L. braziliensis (61.1%), followed by Leishmania panamensis (33.5%), with a high distribution of both species at geographical and municipal level.The species L. guyanensis, L. mexicana and L. lainsoni were also detected at lower frequency.We also showed the identification of different genotypes within L. braziliensis and L. panamensis.In conclusion, we identified the Leishmania species circulating in the areas where Colombian army personnel are deployed, as well as the high intraspecific genetic variability of L. braziliensis and L. panamensis and how these genotypes are distributed at the geographic level. Author summaryColombia is one of the countries with the highest incidence of Cutaneous Leishmaniasis in the world and the army population is the most vulnerable population.Herein, we identified the infecting Leishmania species (L.braziliensis, L. panamensis, L. guyanensis, L. mexicana and L. lainsoni).We also showed the high intra-specific genetic variability of L. braziliensis and L. panamensis and how these genotypes are distributed at the geographic level.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".