Intranasal Delivery of Neural Stem/Progenitor Cells: A Noninvasive Passage to Target Intracerebral Glioma
Bibliographic record
Abstract
Stem cell-based therapies for neurological disorders, including brain tumors, advance continuously toward clinical trials. Optimized cell delivery to the central nervous system remains a challenge since direct intracerebral injection is an invasive method with low transplantation efficiency. We investigated the feasibility of intranasal administration of neural stem/progenitor cells (NSPCs) as an alternative, noninvasive, and direct passage for the delivery of stem cells to target malignant gliomas. Tumor-targeting and migratory pathways of murine and human NSPCs were investigated by intravital magnetic resonance imaging and in histological time course analyses in the intracerebral U87, NCE-G55T2, and syngenic Gl261 glioblastoma models. Intranasally administered NSPCs displayed a rapid, targeted tumor tropism with significant numbers of NSPCs accumulating specifically at the intracerebral glioma site within 6 hours after intranasal delivery. Histological time series analysis revealed that NSPCs migrated within the first 24 hours mainly via olfactory pathways but also by systemic distribution via the microvasculature of the nasal mucosa. Intranasal application of NSPCs leads to a rapid, targeted migration of cells toward intracerebral gliomas. The directional distribution of cells accumulating intra- and peritumorally makes the intranasal delivery of NSPCs a promising noninvasive and convenient alternative delivery method for the treatment of malignant gliomas with the possibility of multiple dosing regimens.
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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) | 0.000 | 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 | 0.001 |
| 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".