Dual‐modality <i>in vivo</i> monitoring of subventricular zone stem cell migration and metabolism
Bibliographic record
Abstract
Rat subventricular zone (SVZ) stem cells were labeled with superparamagnetic iron oxide particles (SPIO) to follow their fate and migratory potential with magnetic resonance imaging (MRI) and positron emission tomography (PET). Labeled cells were transplanted into either the right rostral migratory stream (RMS) or striatum of normal adult Sprague-Dawley rats and serially followed for 3 months. Minimal migration of the cells implanted into the striatum was observed after 3 weeks whereas SVZ cells implanted into the RMS migrated toward the olfactory bulb at 1 week post-transplantation. PET studies of glucose metabolism using (18)F-FDG demonstrated enhanced glucose utilization in the striatum of transplanted animals. PET studies conducted 3 months after transplantation showed elevated accumulation of (11)C-raclopride (dopamine receptor type 2) and (11)C-CFT (dopamine transporter) binding in the striatal grafts. Implanted SVZ cells did not induce significant inflammation as identified by PET using (11)C-PK11195, a ligand detecting activated microglia. Histological analysis identified viable SPIO-labeled cells (some of which were nestin-positive) 7 weeks post-transplantation, suggesting a prolonged presence of undifferentiated neural stem cells within transplants. In addition, double immunostaining for neuronal and astrocytic markers (NeuN and GFAP) indicated that differentiation into neuronal and astrocytic phenotypes also occurred. Thus, combining MRI and PET enables monitoring of cell migration and metabolism non-invasively in vivo for extended periods of time.
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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) | 0.000 | 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".