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Record W2474882389 · doi:10.1038/srep25494

Proteomic analyses bring new insights into the effect of a dark stress on lipid biosynthesis in Phaeodactylum tricornutum

2016· article· en· W2474882389 on OpenAlexaff
Xiaocui Bai, Hao Song, Michel Lavoie, Kun Yan Zhu, Yiyuan Su, Hanqi Ye, Si Chen, Zhengwei Fu, Haifeng Qian

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldEnergy
TopicAlgal biology and biofuel production
Canadian institutionsUniversité Laval
FundersProgram for Changjiang Scholars and Innovative Research Team in UniversityNatural Science Foundation of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsPhaeodactylum tricornutumBiosynthesisProteomicsChemistryBiochemistryCell biologyBiologyBotanyAlgaeGene

Abstract

fetched live from OpenAlex

Microalgae biosynthesize high amount of lipids and show high potential for renewable biodiesel production. However, the production cost of microalgae-derived biodiesel hampers large-scale biodiesel commercialization and new strategies for increasing lipid production efficiency from algae are urgently needed. Here we submitted the marine algae Phaeodactylum tricornutum to a 4-day dark stress, a condition increasing by 2.3-fold the total lipid cell quotas, and studied the cellular mechanisms leading to lipid accumulation using a combination of physiological, proteomic (iTRAQ) and genomic (qRT-PCR) approaches. Our results show that the expression of proteins in the biochemical pathways of glycolysis and the synthesis of fatty acids were induced in the dark, potentially using excess carbon and nitrogen produced from protein breakdown. Treatment of algae in the dark, which increased algal lipid cell quotas at low cost, combined with optimal growth treatment could help optimizing biodiesel 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.267
Teacher spread0.249 · 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 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

Citations80
Published2016
Admission routes1
Has abstractyes

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