Profilin 1 knockdown prevents ischemic brain damage by promoting M2 microglial polarization associated with the RhoA/ROCK pathway
Bibliographic record
Abstract
Microglial polarization to the anti-inflammatory M2 phenotype is essential in resolving neuroinflammation, making it a promising therapeutic strategy for stroke intervention. The actin cytoskeleton is known to be important for the physiological functions of microglia, including migration and phagocytosis. Profilin 1 (PFN1), an actin-binding protein, is involved in the dynamic transformation and reorganization of actin. However, the role of PFN1 in microglial polarization and ischemia/reperfusion injury is unclear. The role of PFN1 on microglial polarization was examined in vitro in BV2 microglial cells subjected to oxygen-glucose deprivation/reoxygenation (OGDR) and in vivo in male mice after transient middle cerebral artery occlusion (MCAO). Knockdown of PFN1 inhibited M1 microglial polarization and promoted M2 microglia polarization 48 hr after OGDR stimulation in BV2 cells and 7 days after MCAO-induced injury in male mice. RhoA/ROCK pathway was involved in the regulation of PFN1 during microglial polarization. Knockdown of PFN1 also significantly attenuated brain infarcts and edema, improved cerebral blood flow and neurological deficits in MCAO-injured mice. Inhibition of PFN1 effectively protected the brain against ischemia/reperfusion injuries by promoting M2 microglial polarization in vitro and in vivo.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".