Hollow microshell through layer-by-layer self-assembly of chitosan/alginate on «E.coli»
Bibliographic record
Abstract
Hollow microspheres prepared via layer-by-layer (LbL) self-assembled polymers have become a growing interest for developing biocompatible delivery systems for drugs, imaging probes and other macromolecules.The development of these capsules benefits from ease of fabrication, versatility of materials being used and its ability to be tuned to the application by incorporating pH-sensitivity as well as targeting molecules.The LbL method has been used to construct capsules for delivering anti-cancer drugs, insulin and other therapeutics.Furthermore, previous work done in the lab has exploited this technique to obtain polyelectrolyte-coated E. coli for use as a bio-recognition element and discovered that a hollow polyelectrolyte capsule can be formed by spontaneous cell lysis.Following that observation, the current project aims to develop a protocol for making hollow capsules by LbL assembly of natural polyelectrolytes onto E. coli, subsequently lysing the cells and evaluating their efficacy using quantum dots as cargo.The study found that four bilayers of chitosan/alginate can be produced on the surface of the E. coli cells with good stability/minimal aggregation as verified by zeta-potential measurements.TEM and confocal microscopy were also used to characterize the capsule formation, thickness and morphology.Cell lysis was performed using 1% Triton-X buffer with EDTA and lysozyme, which resulted in empty vesicles with a wall thickness of ~50 nm and similar dimensions as the cell template.The design of a tunable and biocompatible delivery system is crucial in controlling the biodistribution of imaging probes to enhance efficacy in the targeted site as well as lower toxicity.ii ABSTRACT (FRENCH) Les microsphères creuses formées par auto-assemblage couche par couche (LBL) de polymère présentent un intérêt grandissant pour le développement de système biocompatibles de délivrance de médicaments, de sonde d'imagerie ainsi que d'autres types de macromolécules.Le développement de ces capsules bénéficie de procédés de fabrication simples, d'une large variété de matériaux disponibles, ainsi que d'une bonne adaptabilité à leurs applications par l'incorporation une sensibilité au pH et des molécules pour le ciblage.La méthode LBL a été employée pour construire des capsules pour la délivrance de médicaments anticancéreux, d'insuline et d'autres thérapies.De plus, les travaux antérieurs du laboratoire ont utilisé cette technique pour obtenir une bactérie E Coli revêtue de polyélectrolyte utilisée comme élément de bioreconnaissance et ont abouti à l'obtention d'une capsule creuse de polyélectrolyte par lyse cellulaire spontanée.Suite de ces observations, le projet actuel vise à développer un protocole pour la fabrication de capsules creuses par assemblage LBL de polyélectrolytes naturels sur E coli et lyse cellulaire ainsi que l'évaluation de leurs capacités par encapsulation de points quantiques.L'étude démontre que 4 bicouches de chitosan / alginate peuvent être assemblés à la surface de E. Coli et présentant une bonne stabilité comme le confirme les mesures de potentiel zeta.Les microscopies TEM et confocales ont aussi été employées pour caractériser la formation des capsules, leur épaisseur et leur morphologie.La lyse cellulaire a été effectuée en employant un tampon 1% Triton-X contenant de l'EDTA et du lisozyme, résultant en la formation de vésicules vides de 50 nm d'épaisseur et des dimensions similaires à la cellule modèle.La conception d'un système de délivrance sur mesure et biocompatible est crucial dans le contrôle de la biodistribution de sondes d'imagerie pour améliorer l'efficacité de ciblage et diminuer la toxicité.iii ACKNOWLEDGEMENT I would like to thank my supervisor Prof. Maryam Tabrizian for her support, advice and guidance throughout this project.Working with her has been an invaluable learning experience and I am extremely grateful to have had such an opportunity.I would also like to thank my labmates at Biomat'X laboratories for all their help and support throughout this endeavor.Specifically, I would like to thank Brandon Paylis for answering my questions regarding E. coli culture and spectrophotometry measurements; Saadia Shoaib, who helped me with fluorescence microscopy; Rafael Castiello for answering my questions regarding layer-by-layer assembly; and Kaushar Jahan for her expertise on everything chitosan related.I also extend my gratitude to the rest of our current lab members as well as ex-
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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) | 0.000 | 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 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".