Multicomponent Peak Modeling of Protein Secondary Structures: Comparison of Gaussian with Lorentzian Analytical Methods for Plant Feed and Seed Molecular Biology and Chemistry Research
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Notice bibliographique
Résumé
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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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle