<i>In vivo</i> Detection of Amyloid Plaques in the Mouse Brain using the Near-Infrared Fluorescence Probe THK-265
Bibliographic record
Abstract
Noninvasive detection of amyloid-β (Aβ) deposits in the brain would be beneficial for an early and presymptomatic diagnosis of Alzheimer's disease (AD). We developed THK-265 as a candidate near-infrared fluorescence (NIRF) probe for the in vivo detection of amyloid deposits in the brain. The maximal emission wavelength of THK-265 was greater than 650nm and it showed high quantum yield and molar absorption coefficients. A fluorescence binding assay showed its high binding affinity to Aβ fibrils (Kd = 97 nM). THK-265 clearly stained amyloid plaques in AD neocortical brain sections and showed a moderate log p value (1.8). After intravenous administration of THK-265 in amyloid-β protein precursor (AβPP) transgenic mice, amyloid deposits in the brain were clearly labeled with THK-265. Furthermore, in vivo NIRF imaging demonstrated significantly higher fluorescence intensity in the brains of AβPP transgenic mice than in those of wild-type mice. As THK-265 showed profound hyperchromic effect upon binding to Aβ fibrils, good discrimination between AβPP transgenic and wild-type mice was demonstrated even early after THK-265 administration. Furthermore, the fluorescence intensity of THK-265 correlated with amyloid plaque burden in the brains of AβPP transgenic mice. These findings strongly support the usefulness of THK-265 as an NIRF imaging probe for the noninvasive measurement of brain amyloid load.
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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 | 0.001 | 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".