MétaCan
Menu
Back to cohort
Record W2098657179 · doi:10.1177/1087057110394181

A High-Content Screening (HCS) Assay for the Identification of Chemical Inducers of PML Oncogenic Domains (PODs)

2011· article· en· W2098657179 on OpenAlex

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

VenueSLAS DISCOVERY · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of HealthU.S. Department of Defense
KeywordsHigh-content screeningInducerIdentification (biology)ChemistryComputational biologyCancer researchBiochemistryCell biologyBiologyBotanyCellGene

Abstract

fetched live from OpenAlex

PML is a multi-functional protein with roles in tumor suppression and host defense against viruses. When active, PML localizes to subnuclear structures named PML oncogenic domains (PODs) or PML nuclear bodies (PML-NBs), whereas inactive PML is located diffusely throughout the nucleus of cells. The objective of the current study was to develop a high content screening (HCS) assay for the identification of chemical activators of PML. We describe methods for automated analysis of POD formation using high throughput microscopy (HTM) to localize PML immunofluorescence in conjunction with image analysis software for POD quantification. Using this HCS assay in 384 well format, we performed pilot screens of a small synthetic chemical library and mixture-based combinatorial libraries, demonstrating the robust performance of the assay. HCS counter-screening assays were also developed for hit characterization, based on immunofluorescence analyses of the subcellular location of phosphorylated H2AX or phosphorylated CHK1, which increase in a punctate nuclear pattern in response to DNA damage. Thus, the HCS assay devised here represents a high throughput screen that can be utilized to discover POD-inducing compounds that may restore the tumor suppressor activity of PML in cancers or possibly promote anti-viral states. PML is a multi-functional protein with roles in tumor suppression and host defense against viruses. When active, PML localizes to subnuclear structures named PML oncogenic domains (PODs) or PML nuclear bodies (PML-NBs), whereas inactive PML is located diffusely throughout the nucleus of cells. The objective of the current study was to develop a high content screening (HCS) assay for the identification of chemical activators of PML. We describe methods for automated analysis of POD formation using high throughput microscopy (HTM) to localize PML immunofluorescence in conjunction with image analysis software for POD quantification. Using this HCS assay in 384 well format, we performed pilot screens of a small synthetic chemical library and mixture-based combinatorial libraries, demonstrating the robust performance of the assay. HCS counter-screening assays were also developed for hit characterization, based on immunofluorescence analyses of the subcellular location of phosphorylated H2AX or phosphorylated CHK1, which increase in a punctate nuclear pattern in response to DNA damage. Thus, the HCS assay devised here represents a high throughput screen that can be utilized to discover POD-inducing compounds that may restore the tumor suppressor activity of PML in cancers or possibly promote anti-viral states.

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 score0.063
Threshold uncertainty score0.345

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 head0.034
GPT teacher head0.250
Teacher spread0.216 · 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