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Record W2137126316 · doi:10.1039/c4nr06545j

Local pH tracking in living cells

2015· article· en· W2137126316 on OpenAlexaff
Chieh-Jui Tsou, Chih‐Hao Hsia, Jia-Yin Chu, Yann Hung, Yi‐Ping Chen, Fan‐Ching Chien, Keng C. Chou, Peilin Chen, Chung‐Yuan Mou

Bibliographic record

VenueNanoscale · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Fluorescence Microscopy Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEndocytosisFluorescenceNanoparticleTracking (education)ChemistryMesoporous silicaCondensationNanotechnologyEndocytic cycleParticle (ecology)Chemical engineeringMesoporous materialMaterials scienceCatalysisOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Continuous and simultaneous 3D single-particle movement and local pH detection in HeLa cells were demonstrated for the first time by combining fluorescent mesoporous silica nanoparticles (FMSNs) and a single-particle tracking (SPT) technique with a precision of ∼10 nm. FMSNs, synthesized by the co-condensation of both pH-sensitive and reference dyes with a silica/surfactant source, allow long-term reliable ratiometric pH measurements with a precision better than 0.3 pH unit because of their excellent brightness and stability. pH variation in the surrounding area of FMSNs during endocytosis was monitored in real-time. Acidification and low mobility of FMSNs were observed at the early endocytic stage, whereas basification and high mobility of FMSNs were observed at the late stage. Our results indicate that it is possible to monitor local pH changes in the environments surrounding nanoparticles during the cellular uptake process of FMSNs, which provides much needed information for designing an efficient drug delivery nanosystem.

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)0.000
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 score0.230
Threshold uncertainty score0.412

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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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