Hepcidin and Ferroportin Expression in Breast Cancer Tissue and Serum and Their Relationship with Anemia
Bibliographic record
Abstract
OBJECTIVE: Our correlation study investigated the relationships of the expression of hepcidin and ferroportin (fpn) in tissues and serum from breast cancer (bca) patients and the relationships of hepcidin and fpn with anemia. METHODS: We used elisa and immunohistochemistry to detect the expression of hepcidin and fpn in tissue and serum from 62 individuals with bca, and we analyzed correlations between hepcidin and fpn expression in tissue and in serum. At the same time, we evaluated the relationships between hepcidin, fpn, and anemia. RESULTS: Mean serum hepcidin was 8.18 ± 3.75 μg/L in bca patients with anemia and 4.53 ± 2.07μg/L in those without anemia, a statistically significant difference (t = 3.7090, p < 0.01). Mean serum fpn was obviously lower in the anemia group than in the non-anemia group (1.77 ± 0.51 μg/L vs. 2.46 ± 0.52 μg/L, t = 3.5115, p < 0.01). Serum hepcidin and hemoglobin were negatively correlated (r = -0.502, p < 0.01); however, serum fpn was positively correlated with hemoglobin, and serum hepcidin was negatively correlated with fpn. The rates of hepcidin and fpn expression in bca tissues were 50.0% and 61.2% respectively, but no association with anemia was observed. We also observed no relationship between expression of hepcidin and fpn in serum and in tissue. CONCLUSIONS: In bca patients, expression of hepcidin in serum was high, but expression of fpn was low, suggesting that serum hepcidin plays a major role in anemia in those patients. Expression of hepcidin and fpn in bca tissue showed no correlation with their expression in serum and no clear relationship with anemia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".