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RNA Isolation and Real-Time Quantitative RT-PCR

2008· article· en· W122810863 on OpenAlexaff
Haiyan Guan, Kaiping Yang

Bibliographic record

VenueMethods in molecular biology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsChildren’s Health Research InstituteLawson Health Research InstituteWestern University
Fundersnot available
KeywordsReal-time polymerase chain reactionIsolation (microbiology)Computational biologyRNARNA extractionBiologyComputer scienceMicrobiologyGeneticsGene

Abstract

fetched live from OpenAlex

Adipose tissue has emerged as a major endocrine organ producing a wide spectrum of hormones and factors that play crucial roles in regulating cell turnover and function, not only locally within the adipose tissue but also in the brain and other key metabolic organ systems. It is known that gene activity is controlled at both transcriptional and post-transcriptional levels. Consequently, one of the most important means by which the activity of a gene is assessed is through the determination of levels of the corresponding messenger ribonucleic acid (mRNA). This process involves the isolation of total cellular RNA and subsequent analysis of the mRNA of interest. Given the unique nature of adipose tissue and adipocytes (i.e., containing high amounts of lipid), special RNA isolation techniques that have been tested in both white adipose tissue and isolated mature adipocytes from rats and mice will be presented. Although several methods are available for mRNA quantitation, we will describe a real-time quantitative reverse transcription polymerase chain reaction protocol because of its superior sensitivity and reliability.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.221
Threshold uncertainty score0.884

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 head0.026
GPT teacher head0.402
Teacher spread0.376 · 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
GenreMethods

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

Citations26
Published2008
Admission routes1
Has abstractyes

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