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Record W4283034626 · doi:10.1021/acsnano.2c00327

Fluidity-Guided Assembly of Au@Pt on Liposomes as a Catalase-Powered Nanomotor for Effective Cell Uptake in Cancer Cells and Plant Leaves

2022· article· en· W4283034626 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACS Nano · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsUniversity of Waterloo
FundersAnhui Provincial Key Research and Development PlanMinistry of Education of the People's Republic of ChinaNational Natural Science Foundation of China
KeywordsLiposomeCatalaseCancer cellCancerNanotechnologyBiophysicsChemistryMaterials scienceBiochemistryMedicineBiologyEnzymeInternal medicine

Abstract

fetched live from OpenAlex

The fluidity of the liposomes is essential to nanoparticle–membrane interactions. We herein report a liposomal nanomotor system by controlling the self-assembly behavior of gold core–platinum shell nanoparticles (Au@Pt) on liposomes. Au@Pt can aggregate immediately on fluid-phase dioleoyl-sn-glycero-3-phosphocholine (DOPC) liposomes, forming an uneven distribution. By control of the lipid phase and fluidity, either using pure 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) above its phase transition temperature or adding cholesterol as an adjuvant to DPPC lipids, we precisely control the assembly of Au@Pt on liposomes. Au@Pt maintained high catalase-like activity on the liposomal surface, promoting the decomposition of H2O2 and the movement of the liposomal nanomotors. Finally, we demonstrate that liposomal nanomotors are biocompatible and they can speed up the cellular uptake in mammalian HepG2 cancer cells and Nicotiana tabacum (Nb) plant leaves. This liposomal nanomotor system is expected to be further investigated in biomedicine and plant nanotechnology.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.006
Threshold uncertainty score0.712

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.012
GPT teacher head0.255
Teacher spread0.243 · 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