Drug resistance analysis by next generation sequencing in Leishmania
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The use of next generation sequencing has the power to expedite the identification of drug resistance determinants and biomarkers and was applied successfully to drug resistance studies in Leishmania. This allowed the identification of modulation in gene expression, gene dosage alterations, changes in chromosome copy numbers and single nucleotide polymorphisms that correlated with resistance in Leishmania strains derived from the laboratory and from the field. An impressive heterogeneity at the population level was also observed, individual clones within populations often differing in both genotypes and phenotypes, hence complicating the elucidation of resistance mechanisms. This review summarizes the most recent highlights that whole genome sequencing brought to our understanding of Leishmania drug resistance and likely new directions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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