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Record W2029259824 · doi:10.1159/000350613

In vitro Clearance and Hemocompatibility Assessment of Ultrathin Nanoporous Silicon Membranes for Hemodialysis Applications Using Human Whole Blood

2013· article· en· W2029259824 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBlood Purification · 2013
Typearticle
Languageen
FieldEngineering
TopicNanopore and Nanochannel Transport Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMembraneNanoporousNanoporeMaterials scienceSiliconChemistryNanotechnologyBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Recent advances in nanotechnology have made it possible to mass-produce ultrathin silicon membranes with pore sizes in the range of nanometers. In this study, we investigate the possibility of employing ultrathin nanoporous silicon membranes with pore diameters of 5 and 20 nm for dialysis of human whole blood by performing in vitro clearance and hemocompatibility assessments. METHODS: A mini blood dialyzer is fabricated by mounting nanoporous silicon membranes on a Teflon structure. Clearance is calculated based on the concentration of sodium, chloride, ionized calcium, total CO2, glucose, creatinine and hematocrit measured before and after dialysis. Blood activation is assessed by flow cytometry. RESULTS: Blood contact with the nanoporous membranes induces considerable leukocyte activation. Coating of the membranes with polyethylene glycol significantly improves hemocompatibility without blocking the nanopores. CONCLUSION: Silicon nanoporous membranes are potential candidates for fabrication of miniaturized blood dialyzers. Their mechanical strength and hemocompatibility can be further improved.

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.

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 score0.030
Threshold uncertainty score0.656

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 head0.015
GPT teacher head0.256
Teacher spread0.242 · 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