Blocking Notch signal pathway suppresses the activation of neurotoxic A1 astrocytes after spinal cord injury
Bibliographic record
Abstract
Spinal cord injury (SCI) is a catastrophic disease which has complicated pathogenesis including inflammation, oxidative stress and glial scar formation. Astrocytes are the most abundant cells in central nervous system and fulfill homeostatic functions. Recent studies have described a new reactive phenotype of astrocytes, A1, induced by inflammation, which may have negative effects in SCI. As the Notch signaling pathway has been linked to cell differentiation and inflammation, we aimed to investigate its potential role in the differentiation of astrocytes in SCI. Contusive SCI rat model showed elevated A1 astrocyte numbers at the damage site 28 days after SCI and the expression levels of Notch signaling and its downstream genes were upregulated parallelly. Western blotting, RT-qPCR and immunofluorescence revealed that blocking of Notch pathway using γ-secretase blocker (DAPT) suppressed the differentiation of A1 astrocytes. Flow cytometry, and TUNEL staining indicated that DAPT alleviated neuronal apoptosis and axonal damage caused by A1 astrocytes likely through the Notch-dependent release of pro-inflammatory factors. CO-IP and western blotting revealed an interaction between Notch pathway and signal transducer and activator of transcription 3 (Stat3), which played a vital role in differentiation of A1 astrocytes. We conclude that phenotypic transition of A1 astrocytes and their neurotoxity were controlled by the Notch-Stat3 axis and that Notch pathway in astrocytes may serve as a promising therapeutic target for SCI.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.083 | 0.002 |
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; both teacher heads agree on what is shown here.
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".