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Record W2892872231 · doi:10.15835/nbha47111133

The Proteome Response of Salt-Sensitive Rapeseed (Brassica napus L.) Genotype to Salt Stress

2018· article· en· W2892872231 on OpenAlexfundno aff
Nima Dolatabadi, Mahmoud Toorchi, Mostafa Valizadeh, Ali Bandehagh

Bibliographic record

VenueNotulae Botanicae Horti Agrobotanici Cluj-Napoca · 2018
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
FundersUniversity of Alberta
KeywordsRapeseedSeedlingBrassicaSpotsProlineProteomeShootHorticultureBiologyFood scienceEnzymeDry weightChemistryEnzyme assayBotanyAgronomyBiochemistryAmino acid

Abstract

fetched live from OpenAlex

Productivity of rapeseed (Brassica napus L.), the third most important oilseed crop, was reduced more than other crops under the salt stress higher than the threshold. Thus, breeding, especially at seedling stage, seems necessary. Plants under salt stress, by synthesis of essential metabolites, specific structural proteins or enzymes of metabolic pathways deal with the stress. To identify the molecular mechanisms of salt responsiveness in rapeseed, ‘Option500’ a salt-sensitive genotype was exposed to 0, 150, and 300mM NaCl during the seedling stage. An increase in proline and the Na+ content of leaf and a reduction in shoot dry weight, plant height, K+ content and K+/Na+ ratio were observed. Protein expression changes were examined by two-dimensional electrophoresis (2-DE). Out of 110 protein spots identified by 2-DE gels, 37 spots showed significant abundant changes based on induction factor (IF), and 7 spots were recognized significantly at 5% probability level, which 1 and 6 spots were up and down-regulated, respectively. By using LC-MS/MS mass spectrometry analysis, proteins were identified which are involved in energy production and photosynthesis. Activity of enzymes involved in energy production decreased under stress, while the abundance of Phosphoribulokinase (PRK) -an important enzyme in the pentose phosphate pathway- increased.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.022
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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