Electron microscopy of antibody-conjugated, lutetium-177 lanthanide gold-coated nanoparticles: Proof of concept of targeted loci—A potential theranostic agent
Bibliographic record
Abstract
Following murine injection, the ultrastructural loci of nanoparticles (NPs) containing lutetium-177 (Lu-177) conjugated to an anti-thrombomodulin antibody (mAb-201b) were determined. The results confirmed prior work localizing NPs using Single Photon Emission Computed Tomography (SPECT) scans. The in vivo pharmacokinetics of these NPs were also identified. mAb-201b antibodies are primarily attracted to the thrombomodulin, a membrane protein in the endothelium of the lung vasculature. SPECT images demonstrated NPs in the lungs, liver, spleen, and proximal small bowel. Prior injection of clodronate liposomes reduced the number of circulating macrophages, which, in turn, reduced NP phagocytosis. At 24 h after injection of NPs and after final SPECT imaging, the lungs, liver, spleen, and kidneys were harvested for transmission electron microscopy. Although some NPs were found in all four organs, 85% of the injected dose was localized in type I and type II pneumocytes. Small concentrations were found in secondary lysosomes in hepatocytes, in splenic macrophages, and in an intravascular macrophage in a kidney. Importantly, there was no apoptosis or necrosis in any of the tissues, highlighting the relative safety of the radionuclide NP, whose primary interaction with non-targeted organs/tissues is in the filtration process. In addition to validating the biodistribution results of the SPECT scans carried out in our prior work, this study is proof of principle that NPs conjugated with appropriate antibodies can target specific antigens in vivo. From a theranostic perspective, these results suggest that radioactive nanoconjugates labeled with proper antigens should be able to target and destroy a variety of cancers with minimal harm to the surrounding healthy cells.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".