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Record W6949019038 · doi:10.5281/zenodo.10528545

Extended supplementary data for manuscript: A single dose of cocaine rewires the 3D genome structure of midbrain dopamine neurons

2024· dataset· en· W6949019038 on OpenAlexaff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2024
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMidbrainGenomeDopamineTranscriptomeAddictionVentral tegmental area

Abstract

fetched live from OpenAlex

Cocaine, and other addictive drugs, can induce long-term synaptic modifications in midbrain dopamine neurons (DNs) which play key roles in the development of addiction, but the cellular basis of these long-term changes are not well understood. In this work, we applied Genome Architecture Mapping and single nucleus transcriptomic analyses in mouse midbrain DNs and found extensive rewiring of 3D genome architecture lasting 1 and 14 days upon a single cocaine exposure. The affected genes have major roles in cocaine responses and are preferentially expressed in a DN sub-type that projects to secondary reward-pathway regions. These results reveal an unexpected role for 3D genome remodelling in the long-term memory of a single cocaine exposure, providing new insights about the inception of drug addiction and 3D genome plasticity.

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)0.001
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.220
Threshold uncertainty score0.736

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.003
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.2200.166

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 head0.059
GPT teacher head0.280
Teacher spread0.221 · 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
GenreDataset

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
Published2024
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→French-language works237,207→