Leishmania braziliensis: Strain-Specific Modulation of Phagosome Maturation
Bibliographic record
Abstract
Leishmania (Viannia) braziliensis is responsible for the largest number of American tegumentary leishmaniasis in Brazil (ATL). ATL can present several clinical forms including typical (TL) and atypical (AL) cutaneous and mucocutaneous (ML) lesions. To identify parasite and host factors potentially associated with these diverse clinical manifestations, we first surveyed the expression of two virulence-associated glycoconjugates, lipophosphoglycan (LPG) and the metalloprotease GP63 by a panel of promastigotes of L. braziliensis strains isolated from patients with different clinical manifestations of ATL and from the sand fly vector. We observed a diversity of expression patterns for both LPG and GP63, which may be related to strain-specific polymorphisms. Interestingly, we noted that GP63 activity varies from strain to strain, including the ability to cleave host cell molecules. We next evaluated the ability of promastigotes from these L. braziliensis strains to modulate phagolysosome biogenesis in bone marrow-derived macrophages, by assessing phagosomal recruitment of the lysosome-associated membrane protein 1 (LAMP-1) and intraphagosomal acidification. Whereas three out of six L. braziliensis strains impaired the phagosomal recruitment of LAMP-1, only the ML strain inhibited phagosome acidification to the same extent as the L. donovani strain that was used as a positive control. While decreased phagosomal recruitment of LAMP-1 correlated with higher LPG levels, decreased phagosomal acidification correlated with higher GP63 levels. Finally, we observed that the ability infect and replicate within host cells did not fully correlate with the inhibition of phagosome maturation. Collectively, our results revealed a diversity of strain-specific phenotypes among L. braziliensis isolates, consistent with the high genetic diversity within Leishmania populations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".