Aptamer-Targeted Plasmonic Photothermal Therapy of Cancer
Bibliographic record
Abstract
Novel nanoscale bioconjugates combining unique plasmonic photothermal properties of gold nanoparticles (AuNPs) with targeted delivery using cell-specific DNA aptamers have a tremendous potential for medical diagnostics and therapy of many cell-based diseases. In this study, we demonstrate the high anti-cancer activity of aptamer-conjugated, 37-nm spherical gold nanoparticles toward Ehrlich carcinoma in tumor-bearing mice after photothermal treatment. The synthetic anti-tumor aptamers bring the nanoparticles precisely to the desired cells and selectively eliminate cancer cells after the subsequent laser treatment. To prove tumor eradication, we used positron emission tomography (PET) utilizing radioactive glucose and computer tomography, followed by histological analysis of cancer tissue. Three injections of aptamer-conjugated AuNPs and 5 min of laser irradiations are enough to make the tumor undetectable by PET. Histological analysis proves PET results and shows lower damage of healthy tissue in addition to a higher treatment efficiency and selectivity of the gold nanoparticles functionalized with aptamers in comparison to control experiments using free unconjugated nanoparticles.
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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 | 0.000 | 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) | 0.001 | 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".