Abstract 411: The Development Of New Therapies Targeting Pneumonia-Accelerated Atherosclerosis
Bibliographic record
Abstract
Background: Pneumonia is inflammation of the lungs caused by a bacterial or viral infection. Recent studies show an association between pneumonia and an increased risk of a heart attack. It is proposed that inflammatory pathways are left uncontrolled, which exacerbates atherosclerotic vascular disease. As a result, there is a need to develop therapeutics for attenuating pneumonia-associated inflammation to reduce atherosclerotic plaque build-up and improve concomitant cardiac complications. A normal course of inflammation begins with an initial pro-inflammatory phase and ends with a resolution phase, which is marked by tissue return to homeostasis. During pneumonia, resolution pathways are impaired. Returning resolution processes to normal function may prove to be an effective strategy to attenuate prolonged pneumonia-associated inflammation. Resolution pathways are mediated by fatty acid derivatives termed specialized pro-resolving lipid mediators (SPMs), the metabolites of poly-unsaturated fatty acids such as eicosapentaenoic acid (EPA). EPA is used locally by cells and readily degraded in the body. To overcome this barrier, EPA can be encapsulated in nanoparticle carriers to increase bioavailability and therapeutic delivery. We hypothesize that delivery of EPA nanoparticles into the lungs may control the persistent inflammatory response following pneumonia and reduce atherosclerotic burden. Results: In vitro in mouse bone-marrow derived macrophages stimulated with gram-negative or gram-positive toxins, EPA nanoparticles reduced the production of pro-inflammatory markers including IL-6 and TNFa measured using western blot, qPCR and ELISA. To test the efficacy of EPA-nanoparticles in vivo , we have developed a mouse model of atherosclerosis combined with S. pneumoniae lung infection. We are currently evaluating the impact of infection with S.pneumoniae on atherosclerosis progression and will determine whether EPA-nanoparticles can be used to prevent atherosclerotic inflammation and plaque progression. Clinical Impact: The nanoparticles used are already FDA approved, and regular consumption of EPA has well supported benefits. As such, it is possible that this project may translate into a clinical setting more readily.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".