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Record W2739265498 · doi:10.5539/apr.v9n4p23

Biomechanical and Physiological Conditions Influence Erythrocytes - Erythrocyte Adhesion. An in vitro Study

2017· article· en· W2739265498 on OpenAlexvenueno aff
Mohamed A. Elblbesy

Bibliographic record

VenueApplied Physics Research · 2017
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsnot available
Fundersnot available
KeywordsAdhesionErythrocyte aggregationBiophysicsErythrocyte deformabilityChemistryCell adhesionAlbuminIn vitroFibrinogenRed blood cellBiochemistryBiology

Abstract

fetched live from OpenAlex

Erythrocyte - erythrocyte adhesion (EEA) is of the large interest since it will effect directly on its function and interaction with other organs. Also, erythrocytes adhesion may arise erythrocytes aggregation which has a significant effect on the hemodynamic mechanism. The present study is aimed at examining the effect of erythrocytes mechanical properties on their adhesion. In addition, the impact of the physiological conditions around erythrocytes on their adhesion will be evaluated. A simple flow compartment technique built on inverted microscope was used to calculate adhesion number (AN) of erythrocytes which reflects the ability of erythrocytes to adhere to each other. AN was correlated strongly to shear rate and erythrocyte deformation index. Shape parameters of erythrocytes (Radius and volume) were found to play a major role in EEA. The concentration of the main plasma proteins (fibrinogen and albumin) were determined to have a significant effect on EEA. The results obtained in this study give the attention that other factors rather than particle diameter and work of adhesion may effect on erythrocytes adhesion.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.836

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.150
GPT teacher head0.423
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

Citations0
Published2017
Admission routes1
Has abstractyes

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