Designing ligands for conjugation to gold nanoshells for multitasking
Bibliographic record
Abstract
Completing this thesis and earning an M. Sc.In chemistry at McGill is certainly the most difficult task I have ever set out to accomplish.It would have been very easy (and more than very tempting) to give up at any time, the easy option is almost never the right one.This thesis was worth all of the time and effort that was needed to complete it.I would like to take a little bit of the page count to thank all the people that have helped me along this journey.The first person that I would like to thank is my supervising professor Dr.Ashok Kakkar.Without his help, knowledge and support I would not have been able to complete this degree.My labmates deserve a very big cheer and a very big thank you for all of their invaluable help and advice they have given me, but also for enduring my antics and making this experience all the better.I would like to thank Yu-Chen Wang for her immense heart, loving personality and joyous smile.I have never met a kinder or sweeter person than Yu-Chen.More than once she checked on an over-weekend reaction for me or closed my pump when I forgot to do so.Her perpetually bubbly personality and good mood are quite contagious.And she gives the best hugs.I would like to thank Tina Lam for her immeasurable amount of help and advice.Anytime I would have any insecurity about a new reaction (especially a potentially hazardous one) she would be by my side AbstractGold nanoshells integrate non-cytotoxicity of gold, surface plasmon resonance properties and high-contrast imaging, yielding an efficient and ideal platform for biological imaging.For example, a probe that could detect atherosclerotic plaque, its composition, and its rupture behaviour, could lead to understanding and treating this high mobility disease.Gold nanoshells, due to their characteristic properties, especially upon conjugation of appropriate ligands, offer an exciting venue.This thesis presents a methodology for the development of multitasking gold nanoshell-based probes using carefully designed ligands to incorporate diversifying functions.Hollow gold nanoshells were synthesized using a sacrificial template method which has been optimized to produce nanoshells of the desired properties, with a plasmon absorption between 650 and 900 nm (the biological window).Monofunctional linear and dendritic ligands were designed and constructed to introduce multiple functions onto gold nanoshells including solubility and stealth (TEG), and dual imaging using fluorescence (BODIPY, Cy5.5).These ligands were covalently linked to the surface of gold nanoshells by exploiting the strong Au-S interaction, through a ligand exchange reaction.The dendritic ligands incorporating TEG were found to rupture nanoshells, a phenomenon attributed to the size difference between the dendritic ligand and the displaced citrate, where a void leads to compromised shell integrity.The ligands incorporating a dye linked at the optimum distance from the surface of gold nanoshells lead to fluorescence quenching.The conditions to optimize the latter
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".