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Record W2348272922

Construction and Identification of Yeast Two-hybrid cDNA Library of Porcine Intestinal Epithelial Cells

2014· article· en· W2348272922 on OpenAlexaff
XU Tia

Bibliographic record

VenueChina Animal Husbandry & Veterinary Medicine · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsScience North
Fundersnot available
KeywordscDNA libraryComplementary DNABiologyYeastMolecular biologyTwo-hybrid screeningTiterLibraryReverse transcriptaseVirusHomologous recombinationDNARNAGeneVirologyGenetics
DOInot available

Abstract

fetched live from OpenAlex

In order to study the molecular mechanism of invasion and virulence of the swine intestinal virus systematically,we constructed a porcine intestinal epithelial cells(IEC)cDNA yeast two-hybrid library.Taking advantage of RNeasy Min Kit,total cellular RNA was extracted from cultured porcine IEC,after reverse transcription,synthetise double stranded cDNA by the SMART technology,porcine IEC yeast cDNA library were constructed with homologous recombination.The results showed,library titer was 8.4×108 CFU/mL,the inserted fragment of ds-cDNA was 0.5to 2.0kb,the average length up to1.1kb with a high library recombination rate.This library could be used for screening intestinal host proteins which were interacted with virus proteins,provide reference for the further study of the pathogenesis of the virus,and provide basement for the development of effective drug or vaccine.

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)0.001
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.238
Teacher spread0.219 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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