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Record W2968728008 · doi:10.1186/s13104-019-4562-z

Comparable type I interferon score determination from PAXgene and Tempus whole blood RNA collection and isolation systems

2019· article· en· W2968728008 on OpenAlexafffund
Lovro Lamot, Iwona Niemietz, Kelly L. Brown

Bibliographic record

VenueBMC Research Notes · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
Topicinterferon and immune responses
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersRare Disease Foundation
KeywordsTEMPUSInterferonWhole bloodMolecular biologyGene expressionRNARecombinant DNARNA-SeqGeneBiologyImmunologyGeneticsTranscriptome

Abstract

fetched live from OpenAlex

OBJECTIVE: Type I interferons (IFN) have important roles in many immune-mediated inflammatory diseases (IMIDs) and are a relatively new therapeutic target. Direct detection of type I IFNs has proved challenging, thus their presence is often inferred from the expression of interferon-stimulated genes (ISGs) and calculation of an interferon score (IS). The objective of this research was to determine if the expression of six common ISGs and subsequent IS were comparable when RNA was derived from the Tempus and PAXgene whole blood RNA collection systems. RESULTS: Whole blood was obtained from ten healthy adults, incubated ex vivo in the absence and presence of recombinant human IFNα then divided into PAXgene and Tempus tubes. Despite reports of tube-specific patterns of gene expression, quantitative PCR (qPCR) analysis revealed no significant differences between PAXgene and Tempus tubes in either the homeostatic or IFNα-induced expression of six ISGs (IFI27, IFI44L, IFIT1, ISG15, RSAD2, SIGLEC1). Overall there was a strong correlation in the IS between unstimulated (r = 0.92, p = 0.0005) and IFNα-stimulated (r = 0.71, p = 0.0268) samples derived from the PAXgene and Tempus tubes.

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)0.001
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 score0.150
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.091
GPT teacher head0.342
Teacher spread0.251 · 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
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

Citations12
Published2019
Admission routes2
Has abstractyes

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