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Record W3025732903 · doi:10.1149/ma2020-01251425mtgabs

One-Pot Synthesis of Theranostic Nanocapsules with Lanthanide Doped Nanoparticles

2020· article· en· W3025732903 on OpenAlexaff
Miao Wang, Yu Zhang, Michael Ng, Artiom Skripka, Ting Cheng, Xu Li, Kishore Bhakoo, Alex Y. Chang, Federico Rosei, Fiorenzo Vetrone

Bibliographic record

VenueECS Meeting Abstracts · 2020
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsNanocapsulesSilanolMaterials scienceNanoparticleMicelleChemical engineeringMesoporous silicaHydrophobeDispersityMesoporous materialCopolymerMiniemulsionHydrophobic silicaNanotechnologyAqueous solutionChemistryOrganic chemistryPolymerizationPolymer chemistryPolymerCatalysis

Abstract

fetched live from OpenAlex

In this work, we have established a one-pot synthesis strategy to develop a new theranostic nanoplatform by simultaneously encapsulating Er3+, Yb3+ doped NaGdF4 upconverting nanoparticles (UCNPs) and photosensitizer zinc phthalocyanine (ZnPc) into polymeric micelle/silica nanocapsules. This approach consisted of interfacial templating condensation, using triblock copolymers, ethylene oxide)106(propylene oxide)70(ethylene oxide)106 (PEO-PPO-PEO), as the templating and protecting agent. The encapsulation followed a straightforward microemulsion mechanism in an aqueous environment of a near neutral pH. The surface hydrophobic nature of UCNPs is crucial for the success of encapsulation. To prevent the interaction between the hydrophobic OA ligands of UCNPs and the silanol groups of hydrated tetramethoxysilane (TMOS), we modified the previous procedure by tuning the addition sequence of TMOS. It allowed first to encapsulate UCNPs in PEO-PPO-PEO micelles, and then grow the silica shell within the micellar PPO core and PEO corona interface. The silica shell is incorporated for its chemical and mechanical stability, while the PEO corona confers additional steric stability to the nanocapsule. Using the modified strategy we successfully co-encapsulated UCNPs and ZnPc in one-pot, and minimized the distance between the two payloads to facilitate the energy transfer from UCNPs to ZnPc, as compared to conventional PS loading in the mesoporous silica coating. The integrated nanocapsule has an average hydrodynamic size of 85 nm with a low polydispersity index of 0.1, and demonstrates excellent colloidal stability, biocompatibility, as well as enhanced negative contrast for T2-weighted imaging and photodynamic therapy. The latter is obtained through indirect excitation of co-encapsulated ZnPc by UCNPs, resulting in singlet oxygen generation and in vitro eradication of BT474 breast cancer cells. Overall, the presented one-pot approach shined light on the co-encapsulation of OA capped inorganic UCNPs with hydrophobic photosensitizers, constituting an important step forward in the surface engineering of UCNPs, as well as upconversion based photodynamic therapy delivery systems.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.017
GPT teacher head0.200
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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