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Expression and regulation of <i>Sclerotinia sclerotiorum</i> necrosis and ethylene‐inducing peptides (NEPs)

2009· article· en· W2071876335 on OpenAlexafffund
Zafer Dallal Bashi, Dwayne D. Hegedus, L. Buchwaldt, S. R. Rimmer, M. Hossein Borhan

Bibliographic record

VenueMolecular Plant Pathology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaSaskatchewan Canola Development CommissionMinistry of Agriculture - Saskatchewan
KeywordsSclerotinia sclerotiorumBiologyNecrosisGeneMicrobiologyTumor necrosis factor alphaGene expressionHost (biology)VirulenceProgrammed cell deathCell biologyBiochemistryBotanyGeneticsImmunologyApoptosis

Abstract

fetched live from OpenAlex

Successful host colonization by necrotrophic plant pathogens requires the induction of plant cell death to provide the nutrients needed for infection establishment and progression. We have cloned two genes encoding necrosis and ethylene-inducing peptides from Sclerotinia sclerotiorum, which we named SsNep1 and SsNep2. The peptides encoded by these genes induce necrosis when expressed transiently in tobacco leaves. SsNep1 is expressed at a very low level relative to SsNep2 during infection. The expression of SsNep2 was induced by contact with solid surfaces and occurred in both the necrotic zone and at the leading margin of the infection. SsNep2 expression was dependent on calcium and cyclic adenosine monophosphate signalling, as compounds affecting these pathways reduced or abolished SsNep2 expression coincident with a partial or total loss of virulence.

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)0.000
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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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 head0.011
GPT teacher head0.189
Teacher spread0.178 · 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

Citations82
Published2009
Admission routes2
Has abstractyes

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