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Record W4411001395 · doi:10.1093/jas/skaf188

Reducing dextran sodium sulfate interference with gene expression quantification in a mouse model of colitis

2025· article· en· W4411001395 on OpenAlexafffund
Drake Hechter, Sara V. Good

Bibliographic record

VenueJournal of Animal Science · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversity of WinnipegUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaWinnipeg Foundation
KeywordsColitisDextranGene expressionChemistryInterference (communication)GeneBiologyBiochemistryComputer scienceImmunologyTelecommunications

Abstract

fetched live from OpenAlex

Gene expression analysis via reverse transcription quantitative real-time polymerase chain reaction (qPCR) can be inhibited by various substances, including dextran sodium sulfate (DSS), a chemical commonly used to induce intestinal inflammation in animal models. Ensuring elimination and reduction of qPCR interference in tissues from laboratory animals following oral administration of DSS is critical and may improve the power of experimental tests. While methods for DSS removal have been reported, their effectiveness varies depending on the animal model, extraction techniques, DSS concentration, and treatment duration. We compared the effectiveness of the commonly used RNeasy Plus Universal Mini Kit with and without further lithium chloride (LiCl) precipitation at eliminating or reducing qPCR interference from RNA isolated from the colons of DSS-treated mice with histologically confirmed intestinal damage. The RNeasy Plus Universal Mini Kit alone was insufficient to eliminate interference in colonic tissue, as evidenced by increased quantification cycle (Cq) values and variation in the reference gene expression in DSS-treated distal colons (P adj. = 0.04). LiCl precipitation restored Cq values to control levels and reduced variation. DSS treatment did not lead to interference in non-enteric tissues, including the spleen and cortex. LiCl precipitation not only restored reference gene expression but also improved the detection of changes in inflammatory markers, Il-6 and Tnf, in colonic tissue. In proximal colons, Il-6 was upregulated 2.97-fold in DSS-treated (non-LiCl precipitated, P adj. = 0.007), and 4.00-fold following LiCl precipitation (P adj. = 0.0004), compared to control mice. In distal colons, Il-6 was upregulated 3.95-fold in DSS-treated (non-LiCl precipitated, P adj. = 0.014) and 5.57-fold after LiCl precipitation (P adj. = 0.001) compared to control. Tnf was upregulated 2.05-fold in DSS-treated (non-LiCl precipitated, P adj. = 0.04), and 2.44 (P adj. = 0.009) after LiCl precipitation compared to controls in proximal colons. In distal colons, Tnf was 3.47-fold higher in DSS-treated (non-LiCl precipitated, P adj. = 0.009) and 4.41-fold higher after LiCl precipitation (P adj. = 0.002) compared to control. These findings demonstrate that the combined use of the RNeasy Plus Universal Mini Kit and LiCl precipitation enhances qPCR performance, ensuring reliable gene expression analysis in colonic tissue following acute DSS treatment in a murine model.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2025
Admission routes2
Has abstractyes

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