<scp>GSK</scp>‐3β inhibitor <scp>TDZD</scp>‐8 reduces neonatal hypoxic‐ischemic brain injury in mice
Bibliographic record
Abstract
AIMS: Glycogen synthase kinase 3β (GSK-3β) is activated following hypoxic-ischemic (HI) brain injury. TDZD-8 is a specific GSK-3β inhibitor. Currently, the impact of inhibiting GSK-3β in neonatal HI injury is unknown. We aimed to investigate the effect of TDZD-8 following neonatal HI brain injury. METHODS: Unilateral common carotid artery ligation followed by hypoxia was used to induce HI injury in postnatal day 7 mouse pups pretreated with TDZD-8 or vehicle. The infarct volume, whole-brain imaging, Nissl staining, and behavioral tests were used to evaluate the protective effect of TDZD-8 on the neonatal brain and assess functional recovery after injury. Western blot was used to evaluate protein levels of phosphorylated protein kinase B (Akt), GSK-3β, and cleaved caspase-3. Protein levels of cleaved caspase-3, neuronal marker, and glial fibrillary acidic protein were detected through immunohistochemistry. RESULTS: Pretreatment with TDZD-8 significantly reduced brain damage and improved neurobehavioral outcomes following HI injury. TDZD-8 reversed the reduction of phosphorylated Akt and GSK-3β, and the activation of caspase-3 induced by hypoxia-ischemia. In addition, TDZD-8 suppressed apoptotic cell death and reduced reactive astrogliosis. CONCLUSION: TDZD-8 has the therapeutic potential for hypoxic-ischemic brain injury in neonates. The neuroprotective effect of TDZD-8 appears to be mediated through its antiapoptotic activity and by reducing astrogliosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".