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Record W4385295365 · doi:10.1002/jmv.28967

The interplay between lipid droplets and virus infection

2023· review· en· W4385295365 on OpenAlexaff
Yafei Qu, Weili Wang, Maggie Z. X. Xiao, Yuejuan Zheng, Qiming Liang

Bibliographic record

VenueJournal of Medical Virology · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid metabolism and biosynthesis
Canadian institutionsUniversity of Toronto
FundersProgram of Shanghai Academic Research LeaderFundamental Research Funds for the Central UniversitiesScience and Technology Commission of Shanghai MunicipalityNational Natural Science Foundation of China
KeywordsLipid dropletDengue virusBiologyVirusVirologyLipid metabolismViral replicationBiogenesisIntracellularHepatitis C virusCell biologyOrganelleIntracellular parasiteDengue feverBiochemistry

Abstract

fetched live from OpenAlex

As an intracellular parasite, the virus usurps cellular machinery and modulates cellular metabolism pathways to replicate itself in cells. Lipid droplets (LDs) are universally conserved energy storage organelles that not only play vital roles in maintaining lipid homeostasis but are also involved in viral replication. Increasing evidence has demonstrated that viruses take advantage of cellular lipid metabolism by targeting the biogenesis, hydrolysis, and lipophagy of LD during viral infection. In this review, we summarize the current knowledge about the modulation of cellular LD by different viruses, with a special emphasis on the Hepatitis C virus, Dengue virus, and SARS-CoV-2.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.995
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.028
GPT teacher head0.365
Teacher spread0.337 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

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