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Record W3046949617 · doi:10.4236/ajps.2020.118082

Expression of Genes Associated with Nickel Resistance in White Spruce (<i>Picea glauca</i>) under Nickel Stress: Analysis of AT2G16800 and <i>NRAMP</i> Genes

2020· article· en· W3046949617 on OpenAlexafffund
Meagan Boyd, K. K. Nkongolo

Bibliographic record

VenueAmerican Journal of Plant Sciences · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Stress Responses and Tolerance
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNickelChemistryGene expressionGeneToxicityNitrateEnzymeMolecular biologyBiochemistryBiology

Abstract

fetched live from OpenAlex

Heavy metals such nickel (Ni) can cause toxicity by 1) displacing essential components in the biomolecules, 2) blocking the functional group of molecules, or 3) modifying enzymes, proteins, the plasma membrane, and membrane transporters. The main objective of the present study was to investigate the effect of nickel (Ni) on gene expression of nitrate on gene expression with a focus on the genes coding for the high affinity Ni transporter family protein AT2G16800, and natural resistance-associated macrophage protein (NRAMP). Ni toxicity was assessed by treating seedlings with an aqueous solution of nickel nitrate salt [Ni(NO3)2] at the concentrations of 150 mg, 800 mg, and 1600 mg of nickel per 1 kg of dry soil. RT-qPCR was used to measure the expression of AT2G16800, and NRAMP genes in samples treated with nickel nitrates and controls. The results revealed that P. glauca is resistant to Ni based on lack of plant damage at all nickel concentrations. Ni has no effect on the expression of the AT2G16800 gene in needles or roots. However, it induced an upregulation of the NRAMP genes in roots at all the doses tested (150 mg/kg, 800 mg/kg, and 1600 mg/kg). On the other hand, Ni has no effect on the expression of the NRAMP gene in needle but the lowest dose of potassium (150 mg/kg) upregulated this gene in needle tissues.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.007
Science and technology studies0.0010.003
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.248
Teacher spread0.212 · 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 designObservational
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

Citations7
Published2020
Admission routes2
Has abstractyes

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