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Record W2357032787

Comparison of Methods for the Extraction and Concentration Determination of Total Protein in Maize

2010· article· en· W2357032787 on OpenAlexvenueno aff
Wang Wei

Bibliographic record

VenueSeed · 2010
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsExtraction (chemistry)AcetoneChromatographyProtein purificationChemistryBradford protein assayPhosphate buffered salineTrisPlant proteinBiochemistryFood science
DOInot available

Abstract

fetched live from OpenAlex

The extraction and concentration determination of total protein in maize organs is a key step for proteomic research.In this study.Using maize leaves and silks as materials,6 methods for total protein extraction,i.e.Phosphate Buffer(PB),Tris,Improved Tris,TCA-acetone,Plant Total Protein Extraction Kit and its improved one were compared in respective extraction quantity and quality;simultaneously,3 methods of Bradford,2-D Quant Kit and UV were compared in accuracy of protein concentration determination.The results showed:1.the amount of total protein extracted by the above methods was Plant Total Protein Extraction KitImproved Plant Total Protein Extraction KitImproved TrisTrisTCA-acetone PB;2.The quality of total protein extracted was Plant Total Protein Extraction KitImproved Plant Total Protein Extraction KitTCA-acetone Improved TrisTrisPB;3.The protein concentrations determined by both methods of Bradford and 2-D Quant Kit were accurate and no significant difference,however the one determined by UV method was inaccurate.Taking one consideration with another,using Improved Tris for SDS-PAGE and Improved Plant Total Protein Extraction Kit for 2-DE analyses,and Bradford for concentration measurement would be efficient.It should be a good reference for proteomic research in maize.

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 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 score0.081
Threshold uncertainty score0.109

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 studies0.0000.000
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 head0.026
GPT teacher head0.417
Teacher spread0.390 · 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.

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

Citations1
Published2010
Admission routes1
Has abstractyes

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