Palmitoyl Acyltransferase zD17 Mediates Neuronal Responses in Acute Ischemic Brain Injury by Regulating JNK Activation in a Signaling Module
Bibliographic record
Abstract
Although the palmitoyl acyltransferase (PAT) zinc-finger DHHC containing 17 (zD17) has been implicated in genetic neurological disorders by regulating protein palmitoylation, the role of zD17 in acute brain injury remains unknown. Here, we report that zD17 contributes to acute ischemic brain injury via a mechanism independent of its PAT activity. We have found that zD17 directly interacts with c-Jun N terminus kinase (JNK) to form a signaling module for JNK activation. Pathological stressors induce the zD17-JNK interaction, which promotes downstream neuronal cell death signals. We have developed novel peptides targeting the JNK-interacting motif on zD17 to selectively block the enhancement of the zD17-JNK interaction and the activation of JNK isoforms 2 and 3. Application of these peptides successfully blocks JNK activation and neuronal cell death pathways, protects cultured neurons from excitotoxicity, and dramatically reduces brain damage and behavioral deficits in a rat model of focal ischemic stroke. Our findings indicate zD17 as a key player in ischemic stroke and suggest the potential therapeutic value of targeting the zD17-JNK interaction for acute brain injury.
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".