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Record W4399922107 · doi:10.1101/2024.06.20.599976

Engineering <i>Rhodosporidium toruloides</i> for sustainable production of value-added punicic acid from glucose and wood residues

2024· preprint· en· W4399922107 on OpenAlexaff
Juli Wang, Dagem Zekaryas Haddis, Qiong Xiao, David C. Bressler, Guanqun Chen

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryFood scienceSustainable productionProduction (economics)Pulp and paper industryEngineeringEconomics

Abstract

fetched live from OpenAlex

Abstract Rhodosporidium toruloides has emerged as a prominent candidate for producing single-cell oil from cost-effective feedstocks. In this study, the capability of R. toruloides to produce punicic acid (PuA), a representative plant unusual fatty acid, was investigated. The introduction of acyl lipid desaturase and conjugase (PgFADX) allowed R. toruloides to accumulate 3.7% of total fatty acids as PuA. Delta-12 acyl lipid desaturase (PgFAD2) and diacylglycerol acyltransferase 2 were shown to benefit PuA production. The strain with PgFADX and PgFAD2 coexpression accumulated 12% of its lipids as PuA from glucose, which translated into a PuA titer of 451.6 mg/L in shake flask condition. Utilizing wood hydrolysate as the feedstock, this strain produced 6.4% PuA with a titer of 310 mg/L. Taken together, the results demonstrated that R. toruloides could serve as an ideal platform for the production of plant-derived high-value conjugated fatty acid using agricultural and forestry waste as feedstock.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.187
Teacher spread0.180 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2024
Admission routes1
Has abstractyes

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