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Record W4386126034 · doi:10.1016/j.bea.2023.100104

In situ synchrotron quantitative analysis of competitive adsorption tendency of human serum protein to different clinical hemodialysis membranes and assessment of potential impacts

2023· article· en· W4386126034 on OpenAlexafffundabout
Amira Abdelrasoul, Heloisa Westphalen, Denis Kalugin, Huu Doan, Ahmed Shoker

Bibliographic record

VenueBiomedical Engineering Advances · 2023
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsSt. Paul's HospitalToronto Metropolitan UniversityUniversity of Saskatchewan
FundersGovernment of SaskatchewanNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Research CouncilSaskatchewan Health Research FoundationCanada Foundation for InnovationUniversity of SaskatchewanCanadian Light Source
KeywordsAdsorptionMembraneProtein adsorptionHuman serum albuminPolyacrylonitrileChemistryDialysisChromatographyDialysis tubingChemical engineeringBiophysicsPolymerOrganic chemistryBiochemistryMedicineBiologySurgery

Abstract

fetched live from OpenAlex

Protein adsorption on hemodialysis (HD) membrane matrices and surfaces is a highly undesirable process, as it triggers complement activation and leads to severe health complications for HD patients. However, there is a lack of systematic research investigating the correlation between membrane characteristics and their performance in the dialysis process. This study aims to provide a comprehensive understanding of the competitive adsorption tendencies of three human serum proteins (albumin (HSA), fibrinogen (FB), and transferrin (TRF)) on clinical dialysis membranes composed of polyethersulfone (PES), polyacrylonitrile (PAN), and polyvinyl fluoride (PVDF) polymers. To assess membrane morphology across the membrane cross-section, in situ synchrotron radiation micro-computed tomography (SR-µCT) imaging was conducted at the Canadian Light Source (CLS). Protein adsorption was analyzed qualitatively and quantitatively using an innovative synchrotron-based X-ray tomography technique. To determine the mutual influence of protein species on overall protein adsorption, adsorption from single-protein solutions was compared to adsorption from a protein mixture. Regarding single-protein adsorption, the PVDF membrane exhibited 40% less adsorption of HSA compared to the PES membrane. Conversely, FB adsorption was approximately 25% higher on the PVDF membrane compared to the PES membrane. The PAN membrane showed similar levels of HSA adsorption as the PES membrane and similar levels of FB adsorption as the PVDF membrane. In the case of adsorption from the protein mixture, a suppression of HSA adsorption and replacement of HSA with FB were observed. Consequently, the initial solution with a HSA content of 92% resulted in an adsorbed layer containing approximately 75-80% HSA across all the studied membranes. TRF adsorption remained unaffected by the presence of other proteins, consistent across all three membranes. Notably, the PES membrane exhibited the most significant change in the adsorbed protein composition between single-protein and multi-protein adsorption. In addition, this study comprehensively assesses the impact of fibrinogen adsorption on dialysis, including its consequences, blood activation, and implications for quality of life.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0010.000
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 head0.023
GPT teacher head0.353
Teacher spread0.330 · 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

Citations5
Published2023
Admission routes3
Has abstractyes

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