Positron Emission Tomographic Imaging of Iodine 124 Anti–Prostate Stem Cell Antigen–Engineered Antibody Fragments in LAPC-9 Tumor–Bearing Severe Combined Immunodeficiency Mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The humanized antibody (hu1G8) has been shown to localize to prostate stem cell antigen (PSCA) and image PSCA-positive xenografts. We previously constructed hu1G8 anti-PSCA antibody fragments and tested them for tumor targeting and the ability to image prostate cancer at early and late time points postinjection by positron emission tomography (PET). We now then compare the PET imaging and the radioactivity accumulation properties in prostate cancer tumors and nontarget tissues to determine the superior 124I-labeled hu1G8 antibody format. 124I-labeled diabody, minibody, scFv-Fc, scFv-Fc double mutant (DM), and parental IgG were administered into severe combined immunodeficiency (SCID) mice bearing LAPC-9 xenografts and followed by whole-body PET imaging of mice at preselected time points. Regions of interest were manually drawn around tumor and nontarget tissues and evaluated for radioactivity accumulation. The 124I-hu1G8 IgG has its best time point for tumor high-contrast imaging at 168 hours postinjection. The 124I-hu1G8 minibody at 44 hours postinjection results in superior tumor high-contrast imaging compared to the other antibody formats. The 124I-hu1G8 minibody at 44 hours postinjection also has comparable percent tumor radioactivity compared to 124I-hu1G8 IgG at 168 hours postinjection. The 124I-hu1G8 minibody is the best engineered hu1G8 antibody format for imaging prostate cancer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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