Bibliographic record
Abstract
Malignant glioma are the most common brain tumors in adults.These tumors are composed of complex cellular microenvironments of rapidly proliferating cells expanding around a highly necrotic center, as well as a smaller subpopulation of rapidly migrating cells that invade the surrounding tissues.The high rate of tumor recurrence following surgical removal of the main tumor mass is due to the failure to control those malignant cells.In order to understand the mechanisms of this uncontrolled migration, we have targeted the protein tyrosine kinase Src, a proto-oncogene whose roles in normal tissues involve migration, adhesion and proliferation, and found that disruption of its activity impaired both glioma cell division and invasion.Rat and human glioma cell lines (C6 and U251, respectively) were cultured in DMEM medium supplemented with 10% FBS.To obtain spheroids, these cells were seeded into spinner culture flasks at 10 4 cells/ml and spun at 180 RPM for 3 to 6 weeks.The spheroids were then implanted in a three-dimensional collagen type I matrix, and the invasion was then followed at different time points.During this time, the medium was supplemented with the PP2 inhibitor to target Src kinase signaling.To express different exogenous proteins in the cells, the spheroids were incubated for 2 hours with recombinant
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.097 | 0.024 |
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".