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Record W4416592970 · doi:10.3390/biom15121650

Plasma Membrane Lipid Composition and Turnover in Human Midbrain Neurons Investigated by Time-of-Flight Mass Spectrometry

2025· article· en· W4416592970 on OpenAlexaff
Emmanuel Berlin, Alicia A. Lork, Carl Ernst, John S. Fletcher, Nhu T. N. Phan

Bibliographic record

VenueBiomolecules · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersHasselbladstiftelsenGöteborgs UniversitetVetenskapsrådet
KeywordsMidbrainMembraneLipid metabolismMass spectrometryMembrane proteinBiological membraneCell membraneMass spectrometry imaging

Abstract

fetched live from OpenAlex

The molecular structure and dynamics of the neuronal plasma membrane are essential for neuronal biology and function. We employed time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging to investigate the lipid composition and turnover at the plasma membrane of single human midbrain neurons. The results showed that the profile of lipid turnover was heavily influenced by the types of precursors incorporated into the membrane lipids. In addition, there was a high prevalence of phosphatidylcholines, phosphatidylserines, and ceramides in the human midbrain neurons, and a preference for incorporating stearic acid into membrane lipids compared to other precursors. These features indicate a direct link between the membrane lipids to the biological state and functions of midbrain neurons. This is among a very few studies using mass spectrometry imaging to provide an insight into the native membrane lipid organization and lipid turnover using various lipid precursors in human neurons at a single cell level, illustrating their biological relevance in neuronal functions.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.708

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
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 head0.005
GPT teacher head0.236
Teacher spread0.231 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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