Angiogenic study in Graves’ disease treated with thyroid arterial embolization
Bibliographic record
Abstract
PURPOSE: To investigate angiogenesis in the thyroid of Graves' disease (GD) treated with thyroid arterial embolization through analysis of vascular endothelial growth factor (VEGF), basic fibroblast growth factor (bFGF) and microvessel density (MVD). MATERIALS AND METHODS: Forty-two GD patients were treated with thyroid arterial embolization and followed up for 1-68 months after embolization. Before embolization and at 7 days, 3, 6, 12, 36 and 48 months following embolization, TT3, TT4, FT3, FT4, TSH and thyroid stimulating antibody (TSAb) were tested respectively. Thyroid biopsy was performed under the guidance of computed tomography for immunohistochemical staining of VEGF and bFGF, and MVD within the thyroid gland was marked by CD34. RESULTS: VEGF and bFGF were mostly expressed in the cytoplasm and on the cell membrane. The expression of VEGF was increased (P < 0.05) at < or = 6 months compared with before embolization and decreased (P < 0.05) at > or = 1 year compared with either at < or = 6 months or before embolization. The expression of bFGF was not statistically different at < or = 6 months compared with before embolization but was decreased (P < 0.05) at > or = 1 year compared with either at ?6 months or before embolization. Thyroid MVD marked by CD34 had similar changes to those of the VEGF expression after embolization. There was a positive correlation between VEGF and bFGF (P < 0.05) and between VEGF or bFGF and MVD (P < 0.05). Thyroid hormones mostly returned to normal and TSAb was decreased in longer follow-up. CONCLUSION: Thyroid arterial embolization can decrease the expression of VEGF, bFGF and MVD. Consequently, angiogenesis within the GD thyroid will be decreased in the long term after embolization and may serve as the basis for reduced thyroid size and 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 | 0.000 | 0.001 |
| 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".