Mycobacterium avium Subspecies paratuberculosis Infects and Replicates within Human Monocyte-Derived Dendritic Cells
Bibliographic record
Abstract
BACKGROUND: (MAP), a member of the mycobacteriaceae family, causes Johne's disease in ruminants, which resembles Crohn's disease (CD) in humans. MAP was proposed to be one of the causes of human CD, but the evidence remains elusive. Macrophages were reported to be the only cell where MAP proliferates in ruminants and humans and is likely the major producer of TNFα-associated inflammation. However, whether human dendritic cells (DCs), another major antigen-presenting cell (APC), have the ability to harbor MAP and disseminate infection, remains unknown. METHODS: Human monocyte-derived dendritic cells (moDCs) were infected with MAP and phagocytosis and intracellular survival were quantified by immunofluorescence (IF) and colony counts, respectively. MoDC cytokine expression was measured via ELISA and their activation state was measured via flow cytometry. RESULTS: We showed that MAP can infect and replicate in human moDCs as means to evade the immune system for successful infection, through inhibition of the phago-lysosome fusion via the secretion of protein tyrosine phosphatase PtpA. This mechanism initially led to a state of tolerance in moDCs and then subsequently caused a pro-inflammatory response as infection persisted, characterized by the upregulation of IL-6 and TNFα, and downregulation of IL-10. Moreover, we showed that moDCs have the ability to phagocytose up to 18% of MAP, when exposed at a multiplicity of infection of 1:1. CONCLUSION: Infection and subsequent proliferation of MAP within moDCs could provide a unique means for the dissemination of MAP to lymphoid tissue, while altering immune responses to facilitate the persistence of infection of host tissues in CD.
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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 | 0.001 |
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".