Sex Steroid and Growth Factor Profile of a Meningioma Associated with Pregnancy
Bibliographic record
Abstract
BACKGROUND: Increased growth of meningiomas during pregnancy as well as postpartum clinical regression of symptoms have been reported but remain poorly understood. A better understanding of the factors that contribute to these observations, including potential factors associated with pregnancy, could enable design of more effective adjuvant therapies. METHODS: We describe the presentation of a meningioma during the immediate postpartum period. Serial imaging demonstrated subsequent rapid decrease in size of the tumour prior to any intervention. The lesion was resected, and the tissue was subjected to immunostaining for gene products associated with pregnancy, including estrogen receptor (ER), progesterone receptor (PR), platelet-derived growth factor receptor B (PDGFRB), fibroblastic growth factor receptor 2 (FGFR-2), epidermal growth factor receptor (EGFR) and human placental lactogen (hPL). RESULTS: The lesion proved to be an atypical fibroblastic meningioma grade II (WHO). Immunostaining demonstrated significant staining for PR, PDGFRB, and FGFR-2. No specific staining for ER, EGFR, or hPL was identified. CONCLUSION: Although clinical regression of meningioma following pregnancy is well-recognized, imaging data are much less abundant. This report provides clear clinical and imaging documentation of a meningioma associated with pregnancy. In addition, the growth factor profile of this tumour suggests the importance of PR, PDGFRB, and FGFR-2 as potential therapeutic targets.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".