Multicomponent Peak Modeling of Protein Secondary Structures: Comparison of Gaussian with Lorentzian Analytical Methods for Plant Feed and Seed Molecular Biology and Chemistry Research
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".