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Record W3015749612 · doi:10.1007/s12274-020-2736-6

Super-assembled core-shell mesoporous silica-metal-phenolic network nanoparticles for combinatorial photothermal therapy and chemotherapy

2020· article· en· W3015749612 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

VenueNano Research · 2020
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPhotothermal therapyBiocompatibilityMesoporous silicaDrug deliveryMaterials scienceNanotechnologyNanoparticleCancer therapyMesoporous materialCoatingChemistryCancerMedicine

Abstract

fetched live from OpenAlex

Multimodal combinatorial therapy merges different modes of therapies in one platform, which can overcome several clinical challenges such as premature drug loss during blood circulation and significantly improve treatment efficiency. Here we report a combinatorial therapy nanoplatform that enables dual photothermal therapy and pH-stimulus-responsive chemotherapy. By super-assembly of mesoporous silica nanoparticles (MSN) with metal-phenolic networks (MPN), anti-cancer drugs can be loaded in the MSN matrix, while the outer MPN coating allows dual photothermal and pH-responsive properties. Upon near-infrared light irradiation, the MSN@MPN nanoplatform exhibits excellent photothermal effect, and demonstrates outstanding pH-triggered drug release property. In vitro cell experiments suggest the MSN@MPN system exhibits superior biocompatibility and can effectively kill tumor cells after loading anti-cancer drugs. Consequently, the MSN@MPN system shows promising prospects in clinical application for tumor therapy.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.107
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.316
Teacher spread0.212 · 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