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Record W3119743018 · doi:10.1002/nbm.4456

Monitoring apoptosis in intact cells by high‐resolution magic angle spinning <sup>1</sup>H NMR spectroscopy

2021· article· en· W3119743018 on OpenAlexfundno aff
Marta Wylot, David Whittaker, Stephen Wren, John H. Bothwell, Leslie P. Hughes, Julian L. Griffin

Bibliographic record

VenueNMR in Biomedicine · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilMedical Research CouncilMedical Research Council Canada
KeywordsMagic angle spinningNuclear magnetic resonance spectroscopyChemistryLipid dropletApoptosisBiophysicsSpectroscopyAnalytical Chemistry (journal)BiochemistryChromatographyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Apoptosis maintains an equilibrium between cell proliferation and cell death. Many diseases, including cancer, develop because of defects in apoptosis. A known metabolic marker of apoptosis is a notable increase in 1H NMR‐observable resonances associated with lipids stored in lipid droplets. However, standard one‐dimensional NMR experiments allow the quantification of lipid concentration only, without providing information about physical characteristics such as the size of lipid droplets, viscosity of the cytosol, or cytoskeletal rigidity. This additional information can improve monitoring of apoptosis‐based cancer treatments in intact cells and provide us with mechanistic insight into why these changes occur. In this paper, we use high‐resolution magic angle spinning (HRMAS) 1H NMR spectroscopy to monitor lipid concentrations and apparent diffusion coefficients of mobile lipid in intact cells treated with the apoptotic agents cisplatin or etoposide. We also use solution‐state NMR spectroscopy to study changes in lipid profiles of organic solvent cell extracts. Both NMR techniques show an increase in the concentration of lipids but the relative changes are 10 times larger by HRMAS 1H NMR spectroscopy. Moreover, the apparent diffusion rates of lipids in apoptotic cells measured by HRMAS 1H NMR spectroscopy decrease significantly as compared with control cells. Slower diffusion rates of mobile lipids in apoptotic cells correlate well with the formation of larger lipid droplets as observed by microscopy. We also compared the mean lipid droplet displacement values calculated from the two methods. Both methods showed shorter displacements of lipid droplets in apoptotic cells. Our results demonstrate that the NMR‐based diffusion experiments on intact cells discriminate between control and apoptotic cells. Apparent diffusion measurements in conjunction with 1H NMR spectroscopy‐derived lipid signals provide a novel means of following apoptosis in intact cells. This method could have potential application in enhancing drug discovery by monitoring drug treatments in vitro, particularly for agents that cause portioning of lipids such as apoptosis.

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)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

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