Molecular imaging of nestin in neuroinflammatory conditions reveals marked signal induction in activated microglia
Bibliographic record
Abstract
BACKGROUND: Nestin is a known marker of neuronal progenitor cells in the adult brain. Following neuro- and gliogenesis, nestin is replaced by cell type-specific intermediate filaments, e.g., neurofilaments for panneuronal expression and glial fibrillary acidic protein as a specific marker of mature astrocytes. While previous work have been mostly focused on the neuronal fate of nestin-positive progenitors, in the present study, we sought to investigate in real time how nestin signals and cellular expression patterns are controlled in the context of neuroinflammatory challenge and ischemic brain injury. METHODS: To visualize effects of neuroinflammation on neurogenesis/gliogenesis, we created a transgenic model bearing the dual reporter system luciferase and GFP under transcriptional control of the murine nestin promoter. In this model, transcriptional activation of nestin was visualized from the brains of living animals using biophotonic/bioluminescence molecular imaging and a high resolution charged coupled device camera. Nestin induction profiles in vivo and in tissue sections were analyzed in two different experimental paradigms: middle cerebral artery occlusion and lipopolysaccharide-induced innate immune stimuli. RESULTS: We report here a context- and injury-dependent induction and cellular expression profile of nestin. While in the baseline conditions the nestin signal and/or GFP expression was restricted to neuronal progenitors, the cellular expression patterns of nestin following innate immune challenge and after stroke markedly differed shifting the cellular expression patterns towards activated microglia/macrophages and astrocytes. CONCLUSIONS: Our results suggest that nestin may serve as a context-dependent biomarker of inflammatory response in glial cells including activated microglia/macrophages.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".