Telomere-Mediated Chromosomal Instability Triggers TLR4 Induced Inflammation and Death in Mice
Bibliographic record
Abstract
BACKGROUND: Telomeres are essential to maintain chromosomal stability. Cells derived from mice lacking telomerase RNA component (mTERC-/- mice) display elevated telomere-mediated chromosome instability. Age-dependent telomere shortening and associated chromosome instability reduce the capacity to respond to cellular stress occurring during inflammation and cancer. Inflammation is one of the important risk factors in cancer progression. Controlled innate immune responses mediated by Toll-like receptors (TLR) are required for host defense against infection. Our aim was to understand the role of chromosome/genome instability in the initiation and maintenance of inflammation. METHODOLOGY/PRINCIPAL FINDINGS: We examined the function of TLR4 in telomerase deficient mTERC-/- mice harbouring chromosome instability which did not develop any overt immunological disorder in pathogen-free condition or any form of cancers at this stage. Chromosome instability was measured in metaphase spreads prepared from wildtype (mTERC+/+), mTERC+/- and mTERC-/- mouse splenocytes. Peritoneal and/or bone marrow-derived macrophages were used to examine the responses of TLR4 by their ability to produce inflammatory mediators TNFalpha and IL6. Our results demonstrate that TLR4 is highly up-regulated in the immune cells derived from telomerase-null (mTERC-/-) mice and lipopolysaccharide, a natural ligand for TLR4 stabilises NF-kappaB binding to its promoter by down-regulating ATF-3 in mTERC-/- macrophages. CONCLUSIONS/SIGNIFICANCE: Our findings implied that background chromosome instability in the cellular level stabilises the action of TLR4-induced NF-kappaB action and sensitises cells to produce excess pro-inflammatory mediators. Chromosome/genomic instability data raises optimism for controlling inflammation by non-toxic TLR antagonists among high-risk groups.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".