Identification and Characterization of Novel Bone Marrow Myeloid DEC205+Gr-1+ Cell Subsets That Differentially Express Chemokine and TLRs
Bibliographic record
Abstract
Bone marrow-derived immunomodulatory cytokines impart a critical function in the regulation of innate immune responses and hemopoiesis. However, the source of immunomodulatory cytokines in murine bone marrow and the cellular immune mechanisms that control local cytokine secretion remain poorly defined. Herein, we identified a population of resident murine bone marrow myeloid DEC205(+)CD11c(-)B220(-)Gr1(+)CD8alpha(-)CD11b(+) cells that respond to TLR2, TLR4, TLR7, TLR8, and TLR9 agonists as measured by the secretion of proinflammatory and anti-inflammatory cytokines in vitro. Phenotypic and functional analyses revealed that DEC205(+)CD11b(+)Gr-1(+) bone marrow cells consist of heterogeneous populations of myeloid cells that can be divided into two main cell subsets based on chemokine and TLR gene expression profile. The DEC205(+)CD11b(+)Gr-1(low) cell subset expresses high levels of TLR7 and TLR9 and was the predominant source of IL-6, TNF-alpha, and IL-12 p70 production following stimulation with the TLR7 and TLR9 agonists CpG and R848, respectively. In contrast, the DEC205(+)CD11b(+)Gr-1(high) cell subset did not respond to CpG and R848 stimulation, which correlated with their lack of TLR7 and TLR9 expression. Similarly, a differential chemokine receptor expression profile was observed with higher expression of CCR1 and CXCR2 found in the DEC205(+)CD11(+)Gr-1(high) cell subset. Thus, we identified a previously uncharacterized population of resident bone marrow cells that may be implicated in the regulation of local immune responses in the bone marrow.
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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".