Inflamm-ageing: the role of inflammation in age-dependent cardiovascular disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The ongoing worldwide increase in life expectancy portends a rising prevalence of age-related cardiovascular (CV) diseases in the coming decades that demands a deeper understanding of their molecular mechanisms. Inflammation has recently emerged as an important contributor for CV disease development. Indeed, a state of chronic sterile low-grade inflammation characterizes older organisms (also known as inflamm-ageing) and participates pivotally in the development of frailty, disability, and most chronic degenerative diseases including age-related CV and cerebrovascular afflictions. Due to chronic activation of inflammasomes and to reduced endogenous anti-inflammatory mechanisms, inflamm-ageing contributes to the activation of leucocytes, endothelial, and vascular smooth muscle cells, thus accelerating vascular ageing and atherosclerosis. Furthermore, inflamm-ageing promotes the development of catastrophic athero-thrombotic complications by enhancing platelet reactivity and predisposing to plaque rupture and erosion. Thus, inflamm-ageing and its contributors or molecular mediators might furnish targets for novel therapeutic strategies that could promote healthy ageing and conserve resources for health care systems worldwide. Here, we discuss recent findings in the pathophysiology of inflamm-ageing, the impact of these processes on the development of age-related CV diseases, results from clinical trials targeting its components and the potential implementation of these advances into daily clinical practice.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 it