Plant tissue-based scaffolds filled with oil function as adipose tissue mimetics
Bibliographic record
Abstract
Cellulosic scaffolds filled with oil were designed to replicate animal adipose tissues. Many plants are structured as polysaccharide-based cellular solids. They maintain their integrity after drying, can serve as a scaffold for incorporating fat, and do not lose integrity upon heating, thus resembling native adipose tissue. Carrots, broccoli, and asparagus were freeze-dried and subsequently filled with peanut oil, its glycerolysis product (GP), and the oleogel of this GP. Oleogel-filled scaffolds displayed high oil binding capacity (≥95%), and an oil loss resembling that of adipose tissue. In addition, the texture of oleogel-filled asparagus and broccoli tissue closely resembled that of beef and pork adipose tissues, respectively. Plant scaffolds closely emulated the temperature-dependent rheological behavior of adipose tissue. These new materials could significantly improve the quality of plant-based meat analogues, such as burgers and sausages, by preventing the thermal softening of the material upon cooking and excessive oil loss. • Oil-filled freeze dried whole tissue plant tissue retain oil and remain intact upon heating to cooking temperatures • Mechanical properties and oil binding and release from oil-filled plant tissue resemble those of animal adipose tissue • Different plant tissues bind and retain oil differently due to their pore and wall structure • Glycerolysis oil and their oleogels bind more tightly in the plant tissue and resemble adipose tissue more than regular oil • Oil-filled plant tissue is an inexpensive, natural and practical solution to creating adipose tissue mimetics
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".