Quantitative Evaluation of Proliferative Potential Using Flow Cytometry Reveals Intratumoral Heterogeneity and Its Relevance to Tumor Characteristics in Vestibular Schwannomas
Bibliographic record
Abstract
This study sought to explore the existence and clinical significance of intratumoral heterogeneity of proliferative potential in vestibular schwannoma (VS). Rapid intraoperative flow cytometry was utilized with raw samples to measure the proliferative ability of VS. The proliferation index (PI) was defined as the ratio of the number of cells with greater than normal DNA content to the total number of cells. A total of 66 specimens (26 from the intrameatal portion and 40 from the cisternal portion) were obtained from 34 patients with VS. There was a moderate correlation between the PI and MIB-1 labelling index values (R = 0.57, p < 0.0001). In contrast, the patterns of heterogeneity, represented by the proportion of intrameatal PI to cisternal PI, were associated with tumor size (p = 0.03). In addition, preoperative hearing tended to be poor in cases where the intrameatal PI was higher than the cisternal PI (p = 0.06). Our data demonstrated the presence of intratumoral heterogeneity of proliferative potential in VS and its relationship with tumor characteristics. The results of this study may advocate the resection of the intrameatal portion of large VSs treated with planned subtotal resection, especially in cases of poor preoperative hearing function.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".