Extracellular vesicles on the move: Traversing the complex matrix of tissues
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
Extracellular vesicles are small particles involved in intercellular signaling. They are produced by virtually all cell types, transport biological molecules, and are released into the extracellular space. Studies on extracellular vesicles have become more numerous in recent years, leading to promising research on their potential impact on health and disease. Despite significant progress in understanding the bioactivity of extracellular vesicles, most in vitro and in vivo studies overlook their transport through the extracellular matrix in tissues. The interaction or free diffusion of extracellular vesicles in their environment can provide valuable insights into their efficacy and function. Therefore, understanding the factors that influence the transport of extracellular vesicles in the extracellular matrix is essential for the development of new therapeutic approaches that involve the use of these extracellular vesicles. This review discusses the importance of the interaction between extracellular vesicles and the extracellular matrix and the different factors that influence their diffusion. In addition, we evaluate their role in tissue homeostasis, pathophysiology, and potential clinical applications. Understanding the complex interaction between extracellular vesicles and the extracellular matrix is critical in order to develop effective strategies to target specific cells and tissues in a wide range of clinical applications.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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