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Record W2546457044 · doi:10.1109/ultsym.2016.7728865

High frequency photoacoustic spectral analysis of erythrocyte programmed cell death (eryptosis)

2016· article· en· W2546457044 on OpenAlexafffund
Muhannad N. Fadhel, Eric M. Strohm, Michael C. Kolios

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsSt. Michael's Hospital
FundersNatural Sciences and Engineering Research Council of CanadaTerry Fox Foundation
KeywordsPhosphatidylserineMaterials scienceHemolysisPhotoacoustic imaging in biomedicineSphingomyelinPhotoacoustic effectBiophysicsOpticsChemistryMembraneBiochemistryBiologyPhospholipid

Abstract

fetched live from OpenAlex

Prior to hemolysis, erythrocytes undergo programmed cell death called eryptosis. Eryptosis is characterized by cell shrinkage, membrane blebbing and phosphatidylserine exposure. The high optical absorption of erythrocytes enables their photoacoustic (PA) detection and characterization. PA spectral analysis has been used to assess morphological changes of erythrocytes (e.g. size/shape). Normal and eryptotic RBCs (induced using sphingomyelinase (SMase)) were suspended on a substrate covered with 1% agarose. The PA signals of individual RBCs illuminated with a 532 nm laser were acquired using three ultrasound transducers with center frequencies of 200, 375 and 900 MHz. Frequency analysis of PA signals were applied to quantify the changes between normal and eryptotic RBCs. The results demonstrated significant changes in the spectral parameters. These parameters correlated to change in the RBC shape from the biconcave to spherical. This study also addressed examined the effects of ultrasound transducer focus on measured spectral parameters.

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: Observational · Consensus signal: none
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
Bibliometrics0.0010.000
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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 designObservational
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

Citations2
Published2016
Admission routes2
Has abstractyes

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