Intraspecies Polymorphisms in the Lipophosphoglycan of L. braziliensis Differentially Modulate Macrophage Activation via TLR4
Bibliographic record
Abstract
Lipophosphoglycan (LPG) is the major Leishmania surface glycoconjugate having importance during the host-parasite interface. Leishmania (Viannia) braziliensis displays a spectrum of clinical forms including: typical cutaneous leishmaniasis (TL), mucocutaneous (ML) and atypical lesions (AL). Those variations in the immunopathology may be a result of intraspecies polymorphisms in the parasite’s virulence factors. In this context, we evaluated the role of LPG of strains originated from patients with different clinical manifestations and the sandfly vector. Six isolates of L. braziliensis were used: M2903, RR051 and RR418 (TL), RR410 (AL), M15991 (ML) and M8401 (vector). LPGs were extracted and purified by hydrophobic interaction. Peritoneal macrophages from C57BL/6 and respective knock-outs (TLR2 -/- and TLR-4 -/-) were exposed to different LPGs for nitric oxide (NO) and cytokine production (IL-1beta, IL-6, IL-12 and TNF-alpha). LPGs differentially activated the production of NO and cytokines via TLR4. In order to confirm if such functional variations were related to intraspecies polymorphisms in the LPG, the purified glycoconjugates were subjected to western blot with CA7AE and LT22. Based on antibody reactivity preliminary variations in the repeat units were detected. To confirm these findings, LPGs were depolymerized for purification of repeat units. After thin layer chromatography, intraspecies polymorphisms were confirmed especially in the type and/size of sugars branching-off the repeat units motif. In conclusion, different isolates of L. braziliensis from different clinical forms and hosts can induce different responses in cells of the vertebrate host and this could be a result of LPG polymorphisms.
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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".