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Record W2114163781 · doi:10.1186/1477-5956-11-2

Comparisons of protein profiles of beech bark disease resistant and susceptible American beech (Fagus grandifolia)

2013· article· en· W2114163781 on OpenAlex
Mary E. Mason, Jennifer Koch, M. J. Krasowski, Judy Loo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueProteome Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPlant Pathogens and Fungal Diseases
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of New Brunswick
Fundersnot available
KeywordsBeechBark (sound)Scale insectBiologyBotanyFagus sylvaticaEcology

Abstract

fetched live from OpenAlex

BACKGROUND: Beech bark disease is an insect-fungus complex that damages and often kills American beech trees and has major ecological and economic impacts on forests of the northeastern United States and southeastern Canadian forests. The disease begins when exotic beech scale insects feed on the bark of trees, and is followed by infection of damaged bark tissues by one of the Neonectria species of fungi. Proteomic analysis was conducted of beech bark proteins from diseased trees and healthy trees in areas heavily infested with beech bark disease. All of the diseased trees had signs of Neonectria infection such as cankers or fruiting bodies. In previous tests reported elsewhere, all of the diseased trees were demonstrated to be susceptible to the scale insect and all of the healthy trees were demonstrated to be resistant to the scale insect. Sixteen trees were sampled from eight geographically isolated stands, the sample consisting of 10 healthy (scale-resistant) and 6 diseased/infested (scale-susceptible) trees. RESULTS: Proteins were extracted from each tree and analysed in triplicate by isoelectric focusing followed by denaturing gel electrophoresis. Gels were stained and protein spots identified and intensity quantified, then a statistical model was fit to identify significant differences between trees. A subset of BBD differential proteins were analysed by mass spectrometry and matched to known protein sequences for identification. Identified proteins had homology to stress, insect, and pathogen related proteins in other plant systems. Protein spots significantly different in diseased and healthy trees having no stand or disease-by-stand interaction effects were identified. CONCLUSIONS: Further study of these proteins should help to understand processes critical to resistance to beech bark disease and to develop biomarkers for use in tree breeding programs and for the selection of resistant trees prior to or in early stages of BBD development in stands. Early identification of resistant trees (prior to the full disease development in an area) will allow forest management through the removal of susceptible trees and their root-sprouts prior to the onset of disease, allowing management and mitigation of costs, economic impact, and impacts on ecological systems and services.

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.

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 score0.306
Threshold uncertainty score0.460

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 studies0.0000.001
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 head0.009
GPT teacher head0.236
Teacher spread0.228 · 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