Assembly pattern of multicomponent supramolecular oleogel composed of ceramide and lecithin in sunflower oil: self-assembly or self-sorting?
Bibliographic record
Abstract
Ceramide (CER) is a novel food-grade organogelator with beneficial health effects. Lecithin (LEC) is not an effective gelator; however, it may alter the crystal morphology of the host gelator in a multicomponent system. In this paper, LEC and CER were mixed at various molar ratios in sunflower oil leading to different gelation behaviors. It was interesting since in this multicomponent system, gels formed when there was more less-effective gelator (LEC), while gels hardly formed when there was more effective gelator (CER). This drew our attention since there might not be only one kind of assembly mode between the LEC and the CER. A comprehensive rheological investigation was conducted. It was found that at specific ratios (6L4C and 5L5C), strong gels (G' > 1.0 × 105 Pa) formed with superior oil binding capacity (up to 99.84%). Meanwhile, these gels exhibited higher tolerance level to permanent deformation than the monocomponent gel. However, weak gels were observed off the optimal ratio (8L2C, 7L3C, 4L6C and 3L7C). The crystal morphology of gels drastically changed with change in gelator proportion. Short needle-like crystals and small rosette crystals were observed in 6L4C and 5L5C, respectively, while other samples exhibited spherulite-shaped crystals (8L2C, 7L3C, 4L6C, and 3L7C), which differed from any of the monocomponent gel structures (10L0C and 0L10C). Results from differential scanning calorimetry and polarized light microscopy suggested that the macroscopic properties are determined by the morphology and distribution of crystals rather than the crystallinity of the matrix. Fourier transform infrared spectroscopy results indicated the presence of van der Waals forces and the formation of hydrogen bonding between the phosphate of the LEC and the amide group of the CER. The above results indicated that the LEC and CER co-assembled at approximately equal molar ratio, and the redundant LEC or CER at other ratios self-sorted to combine with the co-assembled fibers by lateral association, leading to potentially different underlying microstructures. These multicomponent supramolecular oleogels with high tunability may further broaden their applicability in various healthy lipid-based product formats.
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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".