Toll-Like Receptor 9 Signaling Delays Neutrophil Apoptosis by Increasing Transcription of Mcl-1
Bibliographic record
Abstract
Neutrophils detect bacterial constituents, including bacterial DNA (CpG DNA), which elicits innate immunity and prolongs the functional life span of neutrophils through suppression of apoptosis. Both the anti-apoptotic protein Mcl-1 and activation of NF-κB have been implicated in neutrophil survival, but there is no evidence that these are linked in neutrophils. We hypothesized that CpG DNA could simultaneously activate these pathways. High purity CpG DNA (0.4-3.2 µg/ml) extended the life span of human neutrophils in vitro by delaying apoptosis through altering the rate of Mcl-1 turnover. CpG DNA slightly decreased Mcl-1 protein level in the presence of cyclohexmide and the proteasome inhibitor MG132 had little effect on Mcl-1 expression in CpG DNA-treated neutrophils. In contrast, CpG DNA evoked rapid increases in DNA binding by NF-κB/p65 and Mcl-1 mRNA. NF-κB inhibitors and the telomere-derived TLR9 inhibitory oligonucleotide 5'-TTT AGG GTT AGG GTT AGG G-3' markedly reduced Mcl-1 protein levels and subsequently abrogated suppression of apoptosis by CpG DNA. Furthermore, CpG DNA attenuated the decreases in Mcl-1 in both cell lysate and nucleus of neutrophils undergoing spontaneous apoptosis and increased Mcl-1 translocation to the mitochondria, leading to preservation of mitochondrial transmembrane potential. These results demonstrate that CpG DNA through toll-like receptor 9 links two survival signaling pathways by delaying apoptosis through induction of NF-κB-mediated Mcl-1 gene transcription and promoting Mcl-1 translocation to the mitochondria.
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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".