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Record W2976763038 · doi:10.1139/cjps-2019-0057

PlWRKY70: a <i>Paeonia lactiflora</i> transcription factor that sensitively responds to low-temperature, salt, and waterlogging stresses

2019· article· en· W2976763038 on OpenAlexvenueno aff
Caiyun Han, Junjie Li, Yan Ma, Jing Guo, Xianfeng Guo, Jinguang Xu

Bibliographic record

VenueCanadian Journal of Plant Science · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPaeonia lactifloraWRKY protein domainAbiotic stressBiologyGeneGene familyPaeonia suffruticosaAbiotic componentBotanyHorticultureGene expressionGeneticsTranscriptomeEcologyMedicine

Abstract

fetched live from OpenAlex

The WRKY family is a specific super gene family in plants that plays a significant regulatory role in abiotic stress in plants. In this paper, the PlWRKY70 gene was cloned by RT-PCR from Paeonia lactiflora ‘Da Fugui’ buds (GenBank accession no. KU891819). The open reading frame of the gene was 936 bp in length, encoding 311 amino acids. The PlWRKY70 gene contained a WRKY domain in its coding region that belonged to the group III WRKY family and was evolutionarily the closest to Paeonia suffruticosa. PlWRKY70 was widely expressed and found at an extremely high level in buds. Moreover, the PlWRKY70 protein was mostly detected in the nucleus. The expression of PlWRKY70 was remarkably influenced by different abiotic stresses with completely different patterns. It could be significantly induced by low-temperature and salt stress, rapidly reaching peak levels after the initial 4 or 8 h of the stress treatment, whereas under waterlogging stress, it was considerably suppressed, dramatically dropping to minimum levels after 2 h of treatment. These profiles suggested that PlWRKY70 was sensitive to low-temperature, salt, and waterlogging stresses in P. lactiflora.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.421

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.008
GPT teacher head0.212
Teacher spread0.204 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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