Exosomal microRNA and stroke: A review
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
Blood vessels rupture or occlusion in brain results in stroke. Stroke is the major reason for mortality and dysfunction worldwide. Despite several attempts, there are no any approved therapeutic approaches for stroke subjects. The most neuroprotective agents showed the positive effects in preclinical reports, while there are no significant therapeutic impacts in the clinical trials. MicroRNAs (miRNAs) are small noncoding RNAs which involved in the modulation of a variety of cellular and molecular pathways. Given that deregulation of these molecules is related to initiation and progression of stroke. Exosomes are nano-carriers which are able to transfer different cargos such as miRNAs to recipient cells. Increasing evidence revealed that exosomal miRNAs are one of very important factors which are involved in the pathogenesis of stroke. Hence, more understanding about the role of exosomal miRNAs in stroke pathogenesis could contribute in discovering and developing new therapeutic approaches. Moreover, it has been proved the exosomal miRNAs could be used as noninvasive biomarkers in diagnosis and monitoring response to therapy in subjects with stroke. Herein for first time, we summarized different exosomal miRNAs involved in pathogenesis of stroke.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 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