Stereological Analysis on Migration of Human Neural Stem Cells in the Brain of Rats Bearing Glioma
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to determine the rate and pattern of NSC migration in the brain and its time course after NSC transplantation. METHODS: We investigated the tropism of HB1.F3 (F3) immortalized human NSCs in rats bearing U373 human glioma in the brain. Rats received an injection of human U373MG malignant glioma cells into the striatum followed by an injection of F3 cells into the contralateral hemisphere 7 days later. We analyzed the numbers, distribution, and migration rate of NSCs using unbiased stereology. RESULTS: Approximately 10% of the injected NSCs migrated into the tumor region by 50 minutes after NSC injection. The number of NSCs in the tumor region increased slowly up to 5 days post-injection and increased significantly up to 15 days post-injection. Changes in tumor volume showed similar patterns. The rate of NSC migration was approximately 175 microm/min. NSCs increased in number approximately 1.7-fold during day 1 in the absence of tumor cell inoculation in vivo. However, the proliferation of NSCs began to decline after 5 days after injection. CONCLUSION: We identified for the first time the rate and pattern of NSC migration to the tumor mass in vivo. These findings may provide useful information with respect to preclinical research of gene therapy for malignant gliomas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".