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Record W4297266708 · doi:10.1002/cpz1.563

Using the HepaCometChip Assay for Broad‐Spectrum DNA Damage Analysis

2022· article· en· W4297266708 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.

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

VenueCurrent Protocols · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCarcinogens and Genotoxicity Assessment
Canadian institutionsnot available
FundersInstitute for Liberal StudiesNational Institute of Environmental Health Sciences
KeywordsDNA damageComet assayDNA repairGenotoxicityDNAXenobioticCarcinogenDNA adductComputational biologyBiologyChemistryBiochemistryCell biologyEnzymeToxicity

Abstract

fetched live from OpenAlex

Exposure to DNA damaging agents can lead to mutations that cause cancer. The liver is particularly vulnerable because it contains high levels of Cytochrome P450 enzymes that can convert xenobiotics into DNA reactive metabolites that form potentially carcinogenic bulky DNA adducts. As such, current requirements for preclinical testing include in vivo testing for DNA damage in the liver, which often requires many animals. Given that efforts are underway in many countries to reduce or eliminate the use of animals in research, there is a critical need for fast and robust in vitro tests to discern whether xenobiotics or potential pharmaceutical agents can damage the hepatocyte genome. One possible approach is to leverage the alkaline comet assay, which is used to assess genotoxicity based on the ability of damaged DNA to become free to migrate toward the anode during electrophoresis. The comet assay, however, has several limitations. The assay is (i) slow and (ii) vulnerable to experimental noise, (iii) it is difficult to detect bulky DNA adducts since they do not directly affect DNA migration, and (iv) cell types typically used do not have robust metabolic capacity. To address some of these concerns, we have developed the "HepaCometChip" (a.k.a. the HepaRG CometChip), wherein metabolically competent cells are incorporated into a higher throughput CometChip platform. Repair trapping is used to increase sensitivity for bulky lesions: undetectable bulky lesions are converted into repair intermediates (specifically, single-strand breaks) that can be detected with the assay. Here, we describe a protocol for performing the HepaCometChip assay that includes handling and dosing of HepaRG cells and performing the CometChip assay. With its higher throughput, ability to capture metabolic activation, and sensitivity to bulky lesions, the HepaCometChip offers a potential alternative to the use of animals for genotoxicity testing. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: HepaRG cell culturing and dosing Basic Protocol 2: CometChip assay.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.525

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 studies0.0010.000
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 head0.073
GPT teacher head0.394
Teacher spread0.321 · 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