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Record W1983091747 · doi:10.1139/b2012-099

Construction and analysis of a SSH cDNA library of <i>Eucalyptus grandis</i> × <i>Eucalyptus urophylla</i> 9224 induced by <i>Cylindrocladium quinqueseptatum</i>

2012· article· en· W1983091747 on OpenAlexvenueno aff
Lizhen Feng, Wenshuo Guo, Wanfeng Xie, Quanzhu Chen, Xiaozhen Ye

Bibliographic record

VenueBotany · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Gene Expression Analysis
Canadian institutionsnot available
FundersDirectorate for Biological SciencesFujian Agriculture and Forestry University
KeywordsBiologyEucalyptusSuppression subtractive hybridizationcDNA libraryBotanyBlightPlant disease resistanceCultivarComplementary DNAGeneHorticultureGenetics

Abstract

fetched live from OpenAlex

Leaf blight caused by Cylindrocladium quinqueseptatum Boedijn &amp; Reitsma is a major disease occurring in Eucalyptus plantlets and saplings worldwide. Current studies on the resistance to this disease in eucalypti have focused primarily on analyzing the relationship between the disease and the metabolic products from the anatomic structure of Eucalyptus leaves and their physiological responses to pathogen invasion. There have been no reports on the mechanisms of molecular responses. Previous research suggests that Eucalyptus grandis × Eucalyptus urophylla 9224 is the highest resistant cultivar among the 11 ones planted in Fujian Province. Therefore, in this study, the molecular responses of E. grandis × E. urophylla 9224 to C. quinqueseptatum were investigated by means of suppression subtractive hybridization (SSH). In total, 928 clones were obtained from the forward SSH cDNA library of E. grandis × E. urophylla 9224, and 25 up-regulated genes were identified by screening the library using the method of reverse northern hybridization. The results show that among these, 23 up-regulated genes with known functions were involved in signal transduction, plant resistance response, photosynthesis, energy transfer, protein metabolism, and plant growth.

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 categoriesMeta-epidemiology (narrow)
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 score0.035
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.006
GPT teacher head0.222
Teacher spread0.216 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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