Investigating the Relationship between Transverse Relaxation Rate ( <i>R2</i> ) and Interecho Time in MagA-Expressing, Iron-Labeled Cells
Why this work is in the frame
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Bibliographic record
Abstract
Reporter gene-based labeling of cells with iron is an emerging method of providing magnetic resonance imaging contrast for long-term cell tracking and monitoring cellular activities. This report investigates 9.4 T nuclear magnetic resonance properties of mammalian cells overexpressing MagA, a putative iron transport protein from magnetotactic bacteria. MagA-expressing MDA-MB-435 cells were cultured in the presence and absence of iron supplementation and compared to the untransfected control. The relationship between the transverse relaxation rate (R2) and interecho time was investigated using the Carr-Purcell-Meiboom-Gill sequence. This relationship was analyzed using a model based on water diffusion in weak magnetic field inhomogeneities (Jensen-Chandra model) as well as a fast-exchange model (Luz-Meiboom model). Increases in R2 with increasing interecho time were larger in the iron-supplemented, MagA-expressing cells compared to other cells. The dependence of R2 on interecho time in these iron-supplemented, MagA-expressing cells was better represented by the Jensen-Chandra model compared to the Luz-Meiboom model, whereas the Luz-Meiboom model performed better for the remaining cell types. Our findings provide an estimate of the distance scale of microscopic magnetic field variations in MagA-expressing cells, which is thought to be related to the size of iron-containing vesicles.
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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 | 0.001 | 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 it