The Development of Theranostic Agents for Photoacoustic Detection and Laser-activated Anti-HER2 Breast Cancer Therapy
Bibliographic record
Abstract
Breast cancer is one of the most common malignancies among women. Mammography and ultrasound imaging modalities are routinely used as breast cancer screening procedures. The sensitivity of those modalities decreases significantly in patients with dense tissues and advanced stage breast cancer. Photoacoustic (PA) imaging, as a non-invasive modality, may offer increased sensitivity for screening breast tumors. To probe additional, specific structural and molecular information, targeted exogenous contrast agents are often introduced. Gold nanorods (GNRs) are effective contrast agents in PA imaging due to their high optical absorption at the near-infrared band and superior biocompatibility. The high spatial localization of GNRs provides significant increases in signal amplitude within the target tissue and assists nanoparticle-mediated cancer therapy. I proposed using targeted theranostic agents containing GNRs for breast tumour detection using a photoacoustic method and laser-activated therapy. In this work, I have developed polymeric nanoparticles (NPs) for the imaging and treatment of breast cancer over-expressing human epidermal growth factor receptor 2 (HER2). These NPs contain a perfluorohexane liquid and gold nanorods (GNRs) interior stabilized by biodegradable and biocompatible copolymer PLGA-PEG. Water-insoluble therapeutic drug Paclitaxel (PAC) and fluorescent dye are encapsulated into the PLGA shell. The NP surfaces are conjugated to the HER2-binding antibody Herceptin to target HER2-positive cancer cells actively. The NP uptake by tumor is evaluated using multi-spectral PA imaging. The effectiveness of cancer cell treatment by laser-induced particle vaporization and stimulated drug release are investigated in vitro. The therapeutic efficacy on tumours is also performed using a xenograft mouse bilateral tumor model. PA quantitative analysis demonstrates that these NPs actively target HER2 positive cells with high efficiency. The laser-induced vaporization causes more damage to the targeted cells versus PAC-only and negative controls. The relative concentrations of GNRs in the tumour with peak signal at 6 hours are quantified using a linear spectral unmixing technique. The therapeutic efficacy of these nanoparticles is evaluated using tissue immunofluorescence and histology. In this dissertation, PLGA-PEG-GNRs as theranostic agents for anti-HER2 breast cancer therapy are developed. They may provide better diagnostic imaging and therapeutic potential than current methods for treating HER2-positive breast cancer.
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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 | 0.001 | 0.001 |
| 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".