Carbon nanotube based targeted drug delivery systems for breast cancer and other drug delivery applications
Bibliographic record
Abstract
Breast cancer is the most commonly diagnosed cancer in women and the second leading cause of death among all cancers. Surgical removal of breast tumour tissues is the primary treatment for breast cancer. However, this does not rule out relapse at local or distant sites, so, chemotherapy is widely used as an adjuvant therapy. Although effective, chemotherapy drugs often cause severe side effects due to their non-specificity to cancer cells. Nanotechnology for drug delivery is an emerging field focused on targeting drugs to the desirable sites, such as tumour tissues, while minimizing the unwanted side effects of chemotherapy drugs on other tissues. Discovery of a new type of nanomaterial opens more opportunities for drug delivery. The carbon nanotube (CNT) is a novel type of synthetic material that has shown great potential for targeted delivery of anti-cancer agents. The initial hurdle for biomedical applications of CNT has been its hydrophobicity. Proper surface modification of CNT, or CNT functionalization, so as to prepare well-dispersed and biocompatible CNT in biologically compatible solutions, is a primary step for its biomedical application. In this thesis, noncovalent functionalization of CNT using various polymers is first explored to make well-dispersed CNT. By identifying the problems of the existing CNT-based drug delivery systems, three novel schemes for CNT-based, targeted drug delivery systems are designed and developed for delivery of a potent breast cancer chemotherapy drug paclitaxel (PTX). The three CNT-PTX delivery systems are characterized and evaluated for their toxicity, drug-loading capacity, cell penetration and cancer cell growth inhibition in vitro. Of the three schemes, the CNT-drug carrier developed through a lipid-drug approach is the best delivery system in terms of drug loading capacity, targeted drug delivery features and potential multifunctional drug delivery. Hence, the CNT-lipid-drug delivery system has been selected for further evaluation for its in vivo tumour growth inhibition, safety and toxicity using a breast cancer xenograft mice model. The CNT-lipid-drug approach has shown good results in a breast cancer animal model. Overall, this thesis explores a new type of nanomaterial as a drug carrier to overcome major limitations of chemotherapy drugs. As a newly discovered nanomaterial, research on CNT as a drug carrier is still in its infancy. Each of these schemes offers a new route of drug loading on CNT, which contributes to our present knowledge on construction of CNT-based drug delivery systems.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".