Detecting molecular changes in Vimy flaxseed protein structure using synchrotron FTIRM and DRIFT spectroscopic techniques: Structural and biochemical characterization
Bibliographic record
Abstract
Mid-IR techniques were used to characterize any changes that occurred on a molecular level in flaxseed that had been heated using an autoclave. The objectives were to investigate the effects of autoclave heating on differences in diffuse reflectance infrared Fourier transform (DRIFT) and synchrotron-based Fourier transform infrared microspectroscopy (SFTIRM) based measurements of the proteinα-helix toβ-sheet ratio for flaxseed (Linum usitatissimum), cv. Vimy. Hierarchical cluster analysis (CLA) and principal components analysis (PCA) were also conducted to identify molecular differences in the DRIFT spectra. Flaxseed samples were kept raw for the control or autoclaved in batches at 120°C for 20, 40 or 60 min for treatments 1, 2 and 3, respectively. DRIFT analysis of protein secondary structure ratios showed a decrease (P< 0.05) in theα-helix toβ-sheet ratio for the whole seed while the results from synchrotron SFTIRM spot data from the endosperm tissue in flaxseed showed autoclaving had the opposite effect (P> 0.05). CLA and PCA were successfully used to make distinctions between the different treatment spectra and showed enhanced sensitivity upon selection of a smaller spectral window to include only the amide I and II portion of the IR spectrum. Our results indicated that autoclaving had a great enough effect on the mid-IR spectrum of flaxseed to identify the alteredα-helix toβ-sheet ratio and subsequently differentiated between the treatments using PCA and CLA suggesting greater sensitivity of mid-IR spectral methods in identifying the effect of heat treatment on protein secondary structure. Future study is needed to quantify the relationship between protein secondary structure and protein functionality.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".