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Record W2148891872 · doi:10.1039/c4tb01794c

pH- and redox-triggered synergistic controlled release of a ZnO-gated hollow mesoporous silica drug delivery system

2014· article· en· W2148891872 on OpenAlexaff
Shanshan Wu, Xuan Huang, Xuezhong Du

Bibliographic record

VenueJournal of Materials Chemistry B · 2014
Typearticle
Languageen
FieldMaterials Science
TopicMesoporous Materials and Catalysis
Canadian institutionsMinistry of Education and Child Care
FundersNanjing UniversityNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsRedoxMesoporous materialDrug deliveryMaterials scienceMesoporous silicaChemical engineeringNanotechnologyChemistryOrganic chemistryCatalysisMetallurgy

Abstract

fetched live from OpenAlex

Hollow mesoporous silica spheres (HMSS) have a hierarchical mesoporous structure composed of a hollow cavity and mesoporous shell available for high capacity drug storage. The covalent attachment of ZnO quantum dots (QDs) to the HMSS outer surface as gatekeepers via disulfide-conjugated two amide linkages encapsulated the anticancer drugs doxorubicin (DOX) within the HMSS cavities and pores, and minimized premature release of the drug. The controlled release of the drug from the ZnO-gated HMSS delivery system was realized by the dissolution of ZnO QDs upon a decrease in pH and cleavage of the disulfide bonds, which indicates that the pH- and redox-responsive controlled release of the drugs could be synergically stimulated by tumor cells with weakly acidic environments and high-expressed glutathione. The constructed ZnO-gated HMSS delivery system has promising applications in site-specific drug release for tumor chemotherapy.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.004
GPT teacher head0.194
Teacher spread0.190 · 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 teacher head, not a consensus.

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".

Quick stats

Citations84
Published2014
Admission routes1
Has abstractyes

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