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Record W4413801833 · doi:10.1016/j.xpro.2025.104049

Protocol for plasma membrane enrichment by ultracentrifugation for mass spectrometry of cell lines, xenografts, and patient tumors

2025· article· en· W4413801833 on OpenAlexafffund
Amber K Hamilton, Brian Mooney, Tina Glisovic‐Aplenc, Alexander B. Radaoui, Karina L. Conkrite, Caitlyn de Jong, Simone Sidoli, Poul H. Sorensen, Benjamin A. Garcia, Richard Aplenc, John M. Maris, Gregg B. Morin, Sharon J. Diskin

Bibliographic record

VenueSTAR Protocols · 2025
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsCanada's Michael Smith Genome Sciences Centre
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentHyundai Hope On WheelsNational Cancer InstituteStand Up To CancerNational Institutes of HealthBC Cancer FoundationFoundation for the National Institutes of HealthCancer Research UKMichael Smith Health Research BCMark Foundation For Cancer ResearchAlex's Lemonade Stand Foundation for Childhood CancerW. W. Smith Charitable TrustOsteosarcoma InstituteSt. Baldrick's Foundation
KeywordsUltracentrifugeMass spectrometryChemistryChromatographyMembranePlasmaBiochemistryPhysics

Abstract

fetched live from OpenAlex

The success of immunotherapies hinges on identifying targetable cell surface proteins expressed in the cancer of interest. Here, we present a protocol for enriching plasma membrane proteins for mass spectrometry analysis using a density gradient ultracentrifugation approach. We describe steps for cell lysis, membrane isolation, and preparation for downstream analysis. This protocol is applicable to cell lines, cell-/patient-derived xenografts (CDX/PDX), and primary tissues. For complete details on the use and execution of this protocol, please refer to Glisovic-Aplenc et al., 1 Hamilton et al., 2 and Mooney et al. 3

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)0.000
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.194
Threshold uncertainty score0.874

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 head0.013
GPT teacher head0.307
Teacher spread0.294 · 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
GenreProtocol

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

Citations1
Published2025
Admission routes2
Has abstractyes

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