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Biotechnological advances in the production of unusual fatty acids in transgenic plants and recombinant microorganisms

2024· review· en· W4401946460 on OpenAlex
Juli Wang, Stacy D. Singer, Guanqun Chen

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiotechnology Advances · 2024
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Alberta
Fundersnot available
KeywordsMicroorganismPolyunsaturated fatty acidBiologyFood industryFermentationBiotechnologyIndustrial microbiologyGenetically modified cropsFood scienceTransgeneGeneBacteriaBiochemistryFatty acidGenetics

Abstract

fetched live from OpenAlex

Certain plants and microorganisms can produce high amounts of unusual fatty acids (UFAs) such as hydroxy, conjugated, cyclic, and very long-chain polyunsaturated fatty acids, which have distinct physicochemical properties and significant applications in the food, feed, and oleochemical industries. Since many natural sources of UFAs are not ideal for large-scale agricultural production or fermentation, it is attractive to produce them through synthetic biology. Although several UFAs have been commercially or pre-commercially produced in transgenic plants and microorganisms, their contents in transgenic hosts are generally much lower than in natural sources. Moreover, reproducing this success for a wider spectrum of UFAs has remained challenging. This review discusses recent advancements in our understanding of the biosynthesis, accumulation, and heterologous production of UFAs, and addresses the challenges and potential strategies for achieving high UFA content in engineered plants and microorganisms.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.001
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 head0.016
GPT teacher head0.293
Teacher spread0.277 · 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