Molecular imaging application of radioiodinated anti-EGFR human Fab to EGFR-overexpressing tumor xenografts.
Bibliographic record
Abstract
BACKGROUND: Suitable diagnostics could identify patients who might benefit from targeted therapies. Molecular imaging is a promising method estimating the expression of specific molecules in vivo, and the goal of this study was to evaluate a radioiodinated anti-epidermal growth factor receptor (EGFR) human Fab as a molecular imaging agent for diagnosis. MATERIALS AND METHODS: Three human tumor cell lines representing tumors with different levels of EGFR expression were selected and their corresponding xenografts produced. (125)I was conjugated to a human anti-EGFR Fab that recognizes the native extracellular domain of EGFR evidenced by immunoprecipitation (IP) and fluorescence-activated cell sorting (FACS) assays. Single-photon-emission computed tomography (SPECT) imaging of (125)I-Fab being administered to nude mice bearing xenografts were obtained, and further analyzed by region of interest (ROI) assay. RESULTS: The (125)I-Fab was achieved successfully without losing its immunoreactivity. The scintigrams as well as ROI assay showed that (125)I-Fab was able to clearly quantitatively distinguish the different expression levels of EGFR in vivo. CONCLUSION: (125)I-Fab is a potential molecular imaging agent for clinical diagnosis of EGFR-overexpressing tumors.
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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".