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Record W4399929864 · doi:10.1101/2024.06.21.599412

Metabolic analysis in intact human-derived cerebral organoids by high-resolution magic-angle spinning NMR spectroscopy

2024· preprint· en· W4399929864 on OpenAlexaff
María Alejandra Castilla Bolaños, Vorapin Chinchalongporn, Rajshree Ghosh Biswas, Colleen Bailey, Maggie Wu, Ronald Soong, Fermisk Saleh, André J. Simpson, Carol Schuurmans, Jamie Near

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsMagic angle spinningMAGIC (telescope)Nuclear magnetic resonance spectroscopySpectroscopyResolution (logic)OrganoidNuclear magnetic resonanceMagic angleChemistryHigh resolutionMaterials scienceAnalytical Chemistry (journal)PhysicsBiologyChromatographyComputer scienceNeuroscience

Abstract

fetched live from OpenAlex

Abstract Human-derived cerebral organoids (COs) are an emerging model system for the study of human neural development and physiology. Here, we describe the assessment of metabolism in human-derived CO’s using high-resolution magic-angle spinning (HR-MAS) NMR spectroscopy. Metabolic changes during development are assessed by studying COs at various stages of maturity. Our results suggest that COs exhibit a metabolic profile similar to in vivo human brain metabolism, albeit with a few notable metabolic differences.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.012
GPT teacher head0.253
Teacher spread0.240 · 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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

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