Comparison of Computed Tomography– and Optical Image–Based Assessment of Liposome Distribution
Bibliographic record
Abstract
The use of multimodal imaging as a tool to assess the in vivo pharmacokinetics and biodistribution of nanocarriers is important in understanding the nature of their in vivo transport. The current study reports the development of a nano-sized liposomal computed tomographic (CT)/optical imaging probe carrying iohexol and Cy5.5 and its use in micro-CT and optical imaging to quantitatively assess the whole-body (macroscopic), intratumoral, and microscopic distribution over a period of 8 days. These multimodal liposomes have a vascular half-life of 30.3 ± 8.9 hours in mice bearing subcutaneous H520 non-small cell lung cancer tumors, with the maximum liposome accumulation in tumor achieved 48 hours postinjection. The in vivo liposome distribution and stability were quantitatively assessed using both micro-CT and fluorescence molecular tomography. The combination of CT and optical imaging enables visualization of the liposomes at the whole-body, tumor, and cellular scales with high sensitivity. Such noninvasive tracking of therapeutic vehicles at the macro- and microscale is important for informed and rational development of novel nanocarrier systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".