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Record W3153673529 · doi:10.1016/j.xpro.2021.100436

Detecting single cell interferon-beta production using a fluorescent reporter telomerase-immortalized human fibroblast cell line

2021· article· en· W3153673529 on OpenAlexafffund
David N. Hare, Minomi Subapanditha, Karen Mossman

Bibliographic record

VenueSTAR Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsSendai virusFlow cytometryCell cultureInterferonVirologyPopulationBiologyFibroblastImmunofluorescenceCellVirusMolecular biologyChemistryImmunologyMedicineAntibodyGenetics

Abstract

fetched live from OpenAlex

Recent data suggest that cells respond to infection by upregulating the antiviral cytokine interferon-beta (IFN-ß) in a fraction of infected cells. Approaches are thus needed to study these responses on a single-cell level rather than bulk population. Here, we describe a protocol to analyze the IFN-ß response of individual cells using flow cytometry and immunofluorescence microscopy. We show the heterogeneous IFN-ß response to inactivated Sendai virus and human cytomegalovirus, but this protocol can be adapted to other viruses. For complete details on the use and execution of this protocol, please refer to Hare et al. (2020).

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.036
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.094
GPT teacher head0.376
Teacher spread0.282 · 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.

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

Citations0
Published2021
Admission routes2
Has abstractyes

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