Targeting MAPK phosphorylation of Connexin43 provides neuroprotection in stroke
Bibliographic record
Abstract
Connexin43 (Cx43) function is influenced by kinases that phosphorylate specific serine sites located near its C-terminus. Stroke is a powerful inducer of kinase activity, but its effect on Cx43 is unknown. We investigated the impact of wild-type (WT) and knock-in Cx43 with serine to alanine mutations at the protein kinase C (PKC) site Cx43S368A, the casein kinase 1 (CK1) sites Cx43S325A/328Y/330A, and the mitogen-activated protein kinase (MAPK) sites Cx43S255/262/279/282A (MK4) on a permanent middle cerebral artery occlusion (pMCAO) stroke model. We demonstrate that MK4 transgenic animals exhibit a significant decrease in infarct volume that was associated with improvement in behavioral performance. An increase in astrocyte reactivity with a concomitant decrease in microglial reactivity was observed in MK4 mice. In contrast to WT, MK4 astrocytes displayed reduced Cx43 hemichannel activity. Pharmacological blockade of Cx43 hemichannels with TAT-Gap19 also significantly decreased infarct volume in WT animals. This study provides novel molecular insights and charts new avenues for therapeutic intervention associated with Cx43 function.
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.
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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".