The determination of zinc, copper and iron oxidation state in invasive ductal carcinoma of breast tissue and normal surrounding tissue using XANES
Bibliographic record
Abstract
Abstract X‐ray absorption near‐edge structure (XANES) spectroscopy was used to examine the oxidation state of Zn, Fe and Cu in 22 normal and 23 tumour regions spread over 30 formalin‐fixed, paraffin‐embedded tissue samples of human primary invasive breast cancer. A micro‐mapping analysis of the metal distribution in the tissue was performed prior to the XANES analysis to identify and localise the metals in the tumour and normal tissue regions. The aim of this study was to identify the oxidation state of Zn, Fe and Cu in normal and tumour tissues of the breast, in order to correlate the oxidation state of these elements with the carcinogenesis process. The position of the Zn K‐edge in normal and tumour tissues suggests that Zn exists in a bounded form. The shape of the Cu K‐edge XANES spectra and the first derivative spectra of normal and tumour tissues shows that a significant portion of the total copper is present as Cu (I). Nevertheless, the position of the edges in the normal and tumour tissue spectra does not exclude the presence of Cu (II). The shape and position of both normal and tumour regions of the tissue suggest that they contain mixtures of Fe (II) and Fe (III) ions with a significant fraction being Fe (III). However, normal tissue regions were found to have a higher fraction of Fe (II) compared to the tumour tissues. In order to estimate the best target for therapy, more information is required about the relative abundance of Zn, Fe and Cu binding proteins, their oxidation state and their localisation at the subcellular level. Copyright © 2010 John Wiley & Sons, Ltd.
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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".