Time Dependent Distribution of MicroRNA 144 after Intravenous Delivery
Bibliographic record
Abstract
BACKGROUND: miR-144 has potential benefits in protecting against myocardial ischemia and suppression of tumor growth. We have previously shown that a single intravenous injection of miR-144 provides potent cardioprotection, but its kinetics and distribution are not known. METHODS: Single stranded mature miR-144 or Cy3-labelled-miR-144 was delivered into C57/B6 mice by tail vein injection. RESULTS: After intravenous injection, the signal of Cy3-labelled-miR-144 in the kidney, brain, heart and liver peaks at 60 minutes, and is predominantly localised to the endothelium at that stage. In the kidney and heart, Cy3-labelled-miR-144 signal is detectable within the parenchymal tissues for at least 3 days, after which it starts to decrease, but brain Cy3-miR-144 signal rapidly decreases after 1 hour, and is lost at day 1, with no parenchymal uptake detected. Cy3-miR-144 signal can be detected until day 28 in the liver. Stem loop RTPCR confirmed the temporal pattern shown by miR-144 in kidney, brain and heart, but in liver there was a continuous rise following the initial injection until day 28 with no signs of decrease, suggesting de-novo synthesis. CONCLUSION: There is early endothelial uptake of injected miR-144 followed by organ-specific distribution and kinetics. In the liver, there appears to be a positive feedback process that leads to continued accumulation of miR-144 that persists for at least 28 days. These observations should be taken into account when designing experiments utilizing parenteral miR-144 and assessing the biology of its actions.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".