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Record W2065369277 · doi:10.1021/nn403760q

Dielectrophoretic Sorting of Membrane Protein Nanocrystals

2013· article· en· W2065369277 on OpenAlex
Bahige G. Abdallah, Tzu‐Chiao Chao, Christopher Kupitz, Petra Fromme, Alexandra Ros

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

VenueACS Nano · 2013
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Bio-sensing Technologies
Canadian institutionsUniversity of Regina
FundersNational Institute of General Medical SciencesUniversity of California, San FranciscoNational Institutes of Health
KeywordsProtein crystallizationDielectrophoresisMicrofluidicsMaterials scienceCrystallizationMembraneSortingFemtosecondCrystallinityNanotechnologyNanocrystalNanometreChemical engineeringChemistryComputer scienceOptics

Abstract

fetched live from OpenAlex

Structure elucidation of large membrane protein complexes is still a considerable challenge, yet is a key factor in drug development and disease combat. Femtosecond nanocrystallography is an emerging technique with which structural information of membrane proteins is obtained without the need to grow large crystals, thus overcoming the experimental riddle faced in traditional crystallography methods. Here, we demonstrate for the first time a microfluidic device capable of sorting membrane protein crystals based on size using dielectrophoresis. We demonstrate the excellent sorting power of this new approach with numerical simulations of selected submicrometer beads in excellent agreement with experimental observations. Crystals from batch crystallization broths of the huge membrane protein complex photosystem I were sorted without further treatment, resulting in a high degree of monodispersity and crystallinity in the ~100 nm size range. Microfluidic integration, continuous sorting, and nanometer-sized crystal fractions make this method ideal for direct coupling to femtosecond nanocrystallography.

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 score0.005
Threshold uncertainty score0.375

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 head0.006
GPT teacher head0.177
Teacher spread0.171 · 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