<i>Brucella</i>discriminates between mouse dendritic cell subsets upon<i>in vitro</i>infection
Why this work is in the frame
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Bibliographic record
Abstract
Brucella is a Gram-negative bacterium responsible for brucellosis, a worldwide re-emerging zoonosis. Brucella has been shown to infect and replicate within Granulocyte macrophage colony-stimulating factor (GMCSF) in vitro grown bone marrow-derived dendritic cells (BMDC). In this cell model, Brucella can efficiently control BMDC maturation. However, it has been shown that Brucella infection in vivo induces spleen dendritic cells (DC) migration and maturation. As DCs form a complex network composed by several subpopulations, differences observed may be due to different interactions between Brucella and DC subsets. Here, we compare Brucella interaction with several in vitro BMDC models. The present study shows that Brucella is capable of replicating in all the BMDC models tested with a high infection rate at early time points in GMCSF-IL15 DCs and Flt3l DCs. GMCSF-IL15 DCs and Flt3l DCs are more activated than the other studied DC models and consequently intracellular bacteria are not efficiently targeted to the ER replicative niche. Interestingly, GMCSF-DC and GMCSF-Flt3l DC response to infection is comparable. However, the key difference between these 2 models concerns IL10 secretion by GMCSF DCs observed at 48 h post-infection. IL10 secretion can explain the weak secretion of IL12p70 and TNFα in the GMCSF-DC model and the low level of maturation observed when compared to GMCSF-IL15 DCs and Flt3l DCs. These models provide good tools to understand how Brucella induce DC maturation in vivo and may lead to new therapeutic design using DCs as cellular vaccines capable of enhancing immune response against pathogens.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 0.003 |
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