MétaCan
Menu
Back to cohort
Record W2035618913 · doi:10.1080/00071668.2014.888397

Research note: methodology for high-quality RNA extraction from poultry whole blood for further gene expression analysis

2014· article· en· W2035618913 on OpenAlexafffund
J. L. Mewis, Xu Sun, M.J. Zuidhof, Le Luo Guan

Bibliographic record

VenueBritish Poultry Science · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMolecular Biology Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsTrizolRNA extractionWhole bloodRNAExtraction (chemistry)BiologyChromatographyChemistryGeneImmunologyBiochemistry

Abstract

fetched live from OpenAlex

1. There are no published methods for RNA isolation from avian whole blood where nucleated red blood cells prevent the use of established mammalian protocols. The aim of this study was therefore to develop a protocol for total RNA extraction using avian whole blood by defining the effect of anticoagulants and sample purification protocols on RNA yield and quality. 2. Blood collections from the cutaneous ulnar or medial metatarsal veins of birds yielded adequate blood volume (2-3 ml) draws. The experiment was a 2 × 2 × 3 factorial arrangement of treatments, with two levels of DNase (0 and TURBO DNA-free Kit), two levels of Cleanup (0 and RNeasy MinElute Cleanup Kit), and three anticoagulants (no anticoagulant, EDTA, or sodium citrate). 3. RNA was isolated successfully by adding TRIzol LS to 0.25 ml of chicken whole blood at 3:1 ratio. From 0.125 ml of avian whole blood, 2-3 µg of RNA with RNA integrity number values of 7.75 was successfully isolated with the TRIzol LS extraction and an RNeasy MinElute Cleanup Kit. 4. This reliable protocol can be used to extract high yield and quality of total RNA from a small amount of whole blood.

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)0.003
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.250
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.065
GPT teacher head0.434
Teacher spread0.370 · 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
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

Citations8
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueBritish Poultry ScienceSame topicMolecular Biology Techniques and ApplicationsFrench-language works237,207