Extracellular vesicles are present in mouse lymph and their level differs in atherosclerosis
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 lymphatic system works in close collaboration with the cardiovascular system to preserve fluid balance throughout the body and is essential for the trafficking of antigen-presenting cells and lymphocytes to lymphoid organs. Recent findings have associated lymphatic dysfunction with the pathogenesis of cardiovascular-related diseases such as atherosclerosis, inflammation and obesity. Whether lymphatic dysfunction is a cause or a consequence of these diseases, as well as how, is under intensive investigation. Extracellular vesicles (EVs) are submicron vesicles released by diverse cell types upon activation or apoptosis and are considered important biomarkers for several inflammatory diseases. Thus, it is critical to characterize the presence of EVs in various biological tissues and fluids to delineate their origins and, subsequently, their functions. In the past few years, new techniques allowing the quantitative and qualitative analysis of EVs have emerged, thus facilitating the onset of studies bridging these vesicles to the lymphatic system. Using several state-of-the-art approaches, this article reports the presence of diverse EVs inclusively derived from red blood cells and platelets in lymph of healthy animals. Our results suggest that lymph from atherosclerotic mice displays a higher concentration of EVs, bringing forward the concept that EVs contained in lymph could either be a biomarker for lymphatic dysfunction or, conversely, for inflammatory disease progression.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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