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Record W2616494871 · doi:10.1186/s12896-017-0364-3

Ultrasound and microbubble induced release from intracellular compartments

2017· article· en· W2616494871 on OpenAlexafffund
Farah Hussein, Costin N. Antonescu, Raffi Karshafian

Bibliographic record

VenueBMC Biotechnology · 2017
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsSt. Michael's HospitalToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntracellularEndosomeExocytosisSonoporationEndocytosisCell biologyExtracellularBiologyCytoplasmLysosomeMicrobubblesCell membraneInternalizationCellBiophysicsMembraneBiochemistryUltrasound

Abstract

fetched live from OpenAlex

BACKGROUND: Ultrasound and microbubbles (USMB) have been shown to enhance the intracellular uptake of molecules, generally thought to occur as a result of sonoporation. The underlying mechanism associated with USMB-enhanced intracellular uptake such as membrane disruption and endocytosis may also be associated with USMB-induced release of cellular materials to the extracellular milieu. This study investigates USMB effects on the molecular release from cells through membrane-disruption and exocytosis. RESULTS: USMB induced the release of 19% and 67% of GFP from the cytoplasm in viable and non-viable cells, respectively. Tfn release from early/recycling endosomes increased by 23% in viable cells upon USMB treatment. In addition, the MFI of LAMP-1 antibody increased by 50% in viable cells, suggesting USMB-stimulated lysosome exocytosis. In non-viable cells, labeling of LAMP-1 intracellular structures in the absence of cell permeabilization by detergents suggests that USMB-induced cell death correlates with lysosomal permeabilization. CONCLUSIONS: In conclusion, USMB enhanced the molecular release from the cytoplasm, lysosomes, and early/recycling endosomes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2017
Admission routes2
Has abstractyes

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