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Record W2969911993 · doi:10.1038/s42003-019-0596-y

Quantitative comparative analysis of human erythrocyte surface proteins between individuals from two genetically distinct populations

2019· article· en· W2969911993 on OpenAlex
Benjamin J. Ravenhill, Usheer Kanjee, Ambroise D. Ahouidi, Luís Nobre, James C. Williamson, Jonathan M. Goldberg, Robin Antrobus, Tandakha Ndiaye Dièye, Manoj T. Duraisingh, Michael P. Weekes

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCommunications Biology · 2019
Typearticle
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsnot available
FundersNational Heart, Lung, and Blood InstituteCambridge Institute for Medical Research, University of CambridgeCanadian Institutes of Health ResearchNational Institutes of HealthEvelyn TrustNIHR Cambridge Biomedical Research CentreWellcome TrustWellcomeNational Institute of Allergy and Infectious DiseasesBill and Melinda Gates Foundation
KeywordsProteomeBiologyErythrocyte membraneMembrane proteinRed blood cellMalariaComputational biologyReceptorProteomicsCell biologyImmunologyGeneticsGeneMembrane

Abstract

fetched live from OpenAlex

Abstract Red blood cells (RBCs) play a critical role in oxygen transport, and are the focus of important diseases including malaria and the haemoglobinopathies. Proteins at the RBC surface can determine susceptibility to disease, however previous studies classifying the RBC proteome have not used specific strategies directed at enriching cell surface proteins. Furthermore, there has been no systematic analysis of variation in abundance of RBC surface proteins between genetically disparate human populations. These questions are important to inform not only basic RBC biology but additionally to identify novel candidate receptors for malarial parasites. Here, we use ‘plasma membrane profiling’ and tandem mass tag-based mass spectrometry to enrich and quantify primary RBC cell surface proteins from two sets of nine donors from the UK or Senegal. We define a RBC surface proteome and identify potential Plasmodium receptors based on either diminished protein abundance, or increased variation in RBCs from West African individuals.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.175
GPT teacher head0.430
Teacher spread0.254 · 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