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Record W2006762949 · doi:10.1366/000370205774783151

Multicomponent Peak Modeling of Protein Secondary Structures: Comparison of Gaussian with Lorentzian Analytical Methods for Plant Feed and Seed Molecular Biology and Chemistry Research

2005· article· en· W2006762949 on OpenAlex

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.

Bibliographic record

VenueApplied Spectroscopy · 2005
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsGaussianPlant biologyChemistryStatistical physicsAnalytical Chemistry (journal)Biological systemPhysicsComputational chemistryBotanyBiologyChromatography

Abstract

fetched live from OpenAlex

The objective of this study was to compare Gaussian and Lorentzian multicomponent peak modeling methods in quantification of protein secondary structures of various plant seed and feed tissues within intact tissue at a cellular and subcellular level using the advanced synchrotron light sourced Fourier transform infrared (FT-IR) microspectroscopy (S-FTIR). This experiment was performed at the beamline U10B at the National Synchrotron Light Source (NSLS) in Brookhaven National Laboratory (BNL), U.S. Dept of Energy (NSLS-BNL, NY). The results show that in the comparison of the Gaussian and Lorentzian multi-peak modeling methods, the Gaussian method is more accurate for fitting multi-peak curves of protein secondary structures than the Lorentzian method, with higher modeling R(2) values (0.92 versus 0.89, P < 0.05). There were no large differences (P > 0.05) in the quantification of the relative percentage alpha-helices, beta-sheets, and others in protein secondary structures of the plant seed tissues, with averages of 30.2%, 40.4%, and 29.4%, respectively. However, there are significant differences (P < 0.05) in the quantification of the ratios of sheet alpha-helix (1.42 versus 1.60; SEM = 0.058) in protein secondary structures of the plant seed tissues. With synchrotron FT-IR microspectroscopy, the ultrastructural-chemical makeup and nutritive characteristics could be revealed at a high spatial resolution. Synchrotron-based FT-IR microspectroscopy revealed that the secondary structure of protein differed between the plant seed tissues in terms of relative percentage and ratio of protein secondary structures (alpha-helix and beta-sheet) within cellular dimensions. The results also show that the flaxseed tissues contained higher (P < 0.05) percentage alpha-helix (38.6 versus 24.0%) beta-sheet (45.3 versus 36.9%), lower (P < 0.05) percentage of other secondary structures (16.1% versus 39.0%), and higher (P < 0.05) ratios alpha-helix beta-sheet (0.90 versus 0.69) than the winterfat seed tissues. It must be mentioned that the relative percentages of protein secondary structure may not reflect the true secondary structure. However, the purpose of modeling the relative percentage of secondary structure was to detect the variety of differences among seed/feed/plant tissues and their relation to nutritive value and digestive behavior. The results demonstrate the potential of highly spatially resolved synchrotron-based FT-IR microspectroscopy to reveal protein secondary structures of the plant seed/feed tissues. Further study is needed to quantify the relationship between protein secondary structures and nutrient availability and digestive behavior of various varieties of plant seed tissues. Information from the infrared probing of protein secondary structures can be valuable as a guide to maintaining protein nutritive value and quality for animal and human use.

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 score0.096
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.039
GPT teacher head0.414
Teacher spread0.375 · 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