J1‐31 protein expression in astrocytes and astrocytomas
Bibliographic record
Abstract
J1-31 is one of the astrocytic proteins, the expression of which has not been evaluated in astrocytomas. In the present study, we studied the expression of J1-31 protein in astrocytes and astrocytomas in comparison with GFAP, p53 and Ki-67. Materials consisted of formalin-fixed paraffin-embedded tissue specimens that included five cases of normal brain, 17 of gliosis, 15 of pilocytic astrocytoma (WHO grade I), 26 of low-grade diffuse astrocytoma (WHO grade II), four of anaplastic astrocytoma (WHO grade III), and eight of glioblastoma (WHO grade IV). GFAP was highly expressed in all specimens examined. The anti-J1-31 antibody exhibited strong cytoplasmic staining of reactive gliosis in 17/17 (100%) cases with a higher intensity of staining than that observed in the adjacent normal astrocytes. The antibody showed reactivity with tumor cells in 12/15 (80%) cases of pilocytic astrocytoma, although intensity of staining was generally weaker and more focal than observed in reactive gliosis. J1-31-positive tumor cells were detected in only 9/26 (35%) cases of the low-grade diffuse astrocytoma and none of the cases of anaplastic astrocytoma and glioblastoma. Increasing Ki-67 indices paralleled advancing tumor grades. p53 protein was expressed more commonly in infiltrating astrocytomas compared to pilocytic astrocytoma. In conclusion, down-regulation of J1-31 expression correlates with advancing grade of astrocytomas. The result suggests this protein plays some role in astrocytes that is progressively lost in malignant progression. The anti-J1-31 antibody may help further our understanding of astrocytes in disease and may be useful as an aid in the pathologic diagnosis of astrocytic lesions.
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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) | 0.000 | 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 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".