MétaCan
Menu
Back to cohort
Record W2271765889 · doi:10.1039/c6cc00099a

Direct water-phase synthesis of lead sulfide quantum dots encapsulated by β-lactoglobulin for in vivo second near infrared window imaging with reduced toxicity

2016· article· en· W2271765889 on OpenAlexaff
Jun Chen, Yifei Kong, Wei Wang, Hongwei Fang, Yan Wo, Dejian Zhou, Ziying Wu, Yunxia Li, Shiyi Chen

Bibliographic record

VenueChemical Communications · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsASTER
FundersEngineering and Physical Sciences Research CouncilChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsBiocompatibilityLead sulfideQuantum yieldFluorescenceQuantum dotNear-infrared spectroscopyMaterials scienceTwo-photon excitation microscopyFluorescence-lifetime imaging microscopyPreclinical imagingNanotechnologyIn vivoPhotochemistryChemistryOptics

Abstract

fetched live from OpenAlex

Compared to conventional fluorescence imaging in the visible (400-700 nm) and NIR-I regions (700-900 nm), optical fluorescence imaging in the second near infrared window (NIR-II, 1000-1400 nm) offers reduced photon scattering, deeper tissue penetration and lower auto-fluorescence. Despite excellent imaging capabilities, current NIR-II probes have not yet reached their full potential due to weak quantum yield, low water solubility and suboptimal biocompatibility. To address these problems, we report herein a new NIR-II fluorescent PbS quantum dots (QDs) that are fabricated in water using β-lactoglobulin (LG) as a biological template. The LG-PbS QDs exhibit satisfactory dispersibility, relatively high quantum yield and favorable biocompatibility, and therefore are suitable for high-resolution in vivo imaging applications.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.505

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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.

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".

Quick stats

Citations51
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueChemical CommunicationsSame topicQuantum Dots Synthesis And PropertiesFrench-language works237,207