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Record W7048608840

Lipid droplets under stressful conditions

2013· dissertation· en· W7048608840 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchConcordia UniversityNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsOxidative stressReactive oxygen speciesLipid dropletOrganellep38 mitogen-activated protein kinasesIntracellularLipotoxicityPhospholipidAntioxidantProtein kinase A
DOInot available

Abstract

fetched live from OpenAlex

Lipid droplets (LDs) are phylogenetically conserved and ubiquitous organelles with many cellular functions.In the last two decades, our understanding of LD biology and of their roles in physiological processes has increased dramatically.In addition, increasing evidence suggests that LDs are highly involved in inflammatory processes, and in metabolic disorders such as type 2 diabetes mellitus (T2DM).Despite such advancement, many aspects of LD biology and of their roles in health and disease remain unknown.The core of LDs is highly enriched with neutral lipids and these can be mobilized to provide metabolic energy.The phospholipid monolayer surrounding the LD core is associated with a wide variety of proteins, including structural and signaling proteins, as well as metabolic enzymes.While LDs may be induced by physiological stimuli such as dietary fatty acids, they can also be formed under stressful conditions, in the absence of such fatty acids.However, exactly how cellular stress leads to LD accumulation remains unclear.Our main objective is to understand the regulation of LD formation under stressful conditions, specifically oxidative stress, inflammation, and metabolic stress.We first investigated LDs in cells exposed to environmental stressors, namely cytotoxic metallic nanoparticles (e.g cadmium telluride nanocrystals) and reactive oxygen species (hydrogen peroxide).LD formation and expression of perilipin-2, a key structural LD protein, were highly increased in rodent cells exposed to these stress agents.Interestingly, supplementation with antioxidant N-acetyl cysteine or pharmacological inhibition of p38 mitogen activated protein kinase (MAPK) reduced stress-induced LD accumulation, suggesting that oxidative stress and p38 MAPK activation play a role in the induction of LD formation.Stimulation of LD formation by oleic acid, a dietary fatty acid, reduced stressor-induced cell death, suggesting that LDs may exert protective functions against oxidative stress.Inflammatory leukocytes and macrophages contain a large number of LDs.While this phenomenon has been widely investigated in peripheral immune cells, its explanation remains elusive in immune cells of the central nervous system.We therefore investigated LD dynamics and regulation in microglia, the resident immune cells in the brain.We

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.263
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2013
Admission routes1
Has abstractyes

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