Prolonged <i>In Vivo</i> Retention of a Cathepsin D Targeted Optical Contrast Agent in a Mouse Model of Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Cathepsin D (CatD) is a lysosomal protease that is elevated early in Alzheimer's disease (AD). We have previously developed a Targeted contrast agent (CA) to detect CatD activity in vivo, consisting of a magnetic resonance imaging/fluorescent moiety linked to a cell penetrating peptide (CPP) by means of a CatD cleavage site and have demonstrated its uptake in the brain of an AD mouse model. OBJECTIVE: The purpose of this study was to characterize the in vivo retention of a near infra-red fluorescent dye labeled version of this CA. METHODS: Six adult C57Bl/6 wild-type mice and six adult 5XFAD transgenic AD mice were studied using a small animal imaging system at five and twelve months of age using our novel Targeted CA, or two different control CAs; a Non-Targeted (lacking the CatD cleavage site) and a Non-Penetrating (lacking the CPP). Following intravenous CA administration, the optical signal was recorded within the brain and uptake and washout curves were measured and fitted to a one-phase exponential decay curve. RESULTS: In all wild-type and 5XFAD mice, the washout of the Targeted CA that included a CPP domain was significantly slower than the washout of the Non-Penetrating and Non-Targeted CA. Furthermore, the washout of the CatD Targeted CA was significantly slower in the 5XFAD mice compared to the age matched wild-type controls (p < 0.05) at 5 and 12 months of age. Control CAs showed no differences in washout. CONCLUSIONS: The prolonged retention of the CatD targeted CA in 5XFAD mice suggests this agent may be useful for AD detection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".