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Record W4394688709 · doi:10.1080/10408398.2024.2331566

Unveiling the applications of membrane proteins from oil bodies: leading the way in artificial oil body technology and other biotechnological advancements

2024· review· en· W4394688709 on OpenAlexaff
Yi Liao, Zhenxiao Wang, Yukun Pei, Shizhang Yan, Tianyao Chen, Baokun Qi, Yang Li

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsScience North
Fundersnot available
KeywordsOleosinOrganelleMembraneMembrane proteinPhospholipidFunction (biology)BiologyChemistryNanotechnologyBiochemistryCell biologyMaterials science

Abstract

fetched live from OpenAlex

Oil bodies (OBs) function as organelles that store lipids in plant seeds. An oil body (OB) is encased by a membrane composed of proteins (e.g., oleosins, caleosins, and steroleosins) and a phospholipid monolayer. The distinctive protein-phospholipid membrane architecture of OBs imparts exceptional stability even in extreme environments, thereby sparking increasing interest in their structure and properties. However, a comprehensive understanding of the structure-activity relationships determining the stability and properties of oil bodies requires a more profound exploration of the associated membrane proteins, an aspect that remains relatively unexplored. In this review, we aim to summarize and discuss the structural attributes, biological functions, and properties of OB membrane proteins. From a commercial perspective, an in-depth understanding of the structural and functional properties of OBs is important for the expansion of their applications by producing artificial oil bodies (AOB). Besides exploring their structural intricacies, we describe various methods that are used for purifying and isolating OB membrane proteins. These insights may provide a foundational framework for the practical utilization of OB membrane proteins in diverse applications within the realm of AOB technology, including biological and probiotic delivery, protein purification, enzyme immobilization, astringency detection, and antibody production.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.052
GPT teacher head0.357
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations21
Published2024
Admission routes1
Has abstractyes

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