Edible oleogels for the oral delivery of lipid soluble molecules: Composition and structural design considerations
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.
Bibliographic record
Abstract
Edible oleogels, oils structured by non-triglyceride networks, can be used for the delivery of lipid-soluble molecules due to their composition, functional properties, and structure. Different oleogelators exist, including small molecules that crystallize to form colloidal or fibrillar networks and hydrophobic polymers that self-assemble under specific processing conditions. Several types of edible oleogels have been characterized, but only select systems have been used in oral delivery applications. This review covers the potential for use of edible oleogels for lipophilic molecular delivery. Factors affecting lipolysis relevant to oil gelation will be discussed, as well as the relationship between lipolysis and bioaccessibility. The use of lipid-based delivery systems to increase the bioaccessibility of poorly water-soluble molecules is emphasized, and oleogels are introduced as a delivery material. The review then discusses different methods of oleogelation, and addresses properties of oleogels that may be beneficial for delivery. Oleogel structure, mechanical strength, composition, and gelator type are factors that may affect the rate and extent of lipolysis of the material. These in turn affect the delivery of lipid-soluble molecules from the oleogel. Crystalline oleogels used in oral delivery formulations have been shown to offer increased bioaccessibility, prevention against bioactive recrystallization, and targeted or delayed bioactive release. In addition, the ability to manipulate oleogel physicochemical properties with gelator type, formulation, and processing parameters is beneficial for tailoring the material functionality. Ethylcellulose oleogels are unique food-grade polymer oleogels that could be used for delivery, similar to other crystalline oleogel systems.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it