Activation of the TLR4 signaling pathway and abnormal cholesterol efflux lead to emphysema in ApoE-deficient mice
Bibliographic record
Abstract
Smokers with airflow obstruction have an increased risk of atherosclerosis, but the relationship between the pathogenesis of these diseases is not well understood. To determine whether hypercholesterolemia alters lung inflammation and emphysema formation, we examined the lung phenotype of two hypercholesterolemic murine models of atherosclerosis at baseline and on a high-fat diet. Airspace enlargement developed in the lungs of apolipoprotein E-deficient (Apoe(-/-)) mice exposed to a Western-type diet for 10 wk. An elevated number of macrophages and lymphocytes accompanied by an increase in matrix metalloproteinase-9 (MMP-9) activity and MMP-12 expression was observed in the lungs of Apoe(-/-) mice on a Western-type diet. In contrast, low-density lipoprotein receptor-deficient (Ldlr(-/-)) mice did not exhibit lung destruction or inflammatory changes. Most importantly, we revealed augmented expression of the downstream targets of the Toll-like receptor (TLR) pathway, interleukin-1 receptor-associated kinase 1, and granulocyte colony-stimulating factor, in the lungs of Apoe(-/-) mice fed with a Western-type diet. In addition, we demonstrated overexpression of MMP-9 in Apoe(-/-) macrophages treated with TLR4 ligand, augmented with the addition of oxidized LDL, suggesting that emphysema in these mice results from the activation of the TLR pathway secondary to known abnormal cholesterol efflux. Our findings indicate that, in Apoe(-/-) mice fed with an atherogenic diet, abnormal cholesterol efflux leads to increased systemic inflammation with subsequent lung damage and emphysema formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".