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Record W4310593807 · doi:10.1212/nxi.0000000000200046

Single-Cell Transcriptomics Identifies Brain Endothelium Inflammatory Networks in Experimental Autoimmune Encephalomyelitis

2022· article· en· W4310593807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeurology Neuroimmunology & Neuroinflammation · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSingle-cell and spatial transcriptomics
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsNeuroinflammationExperimental autoimmune encephalomyelitisImmune systemBiologyMultiple sclerosisImmunologyMicrogliaTranscriptomeCell biologyPathologyInflammationGene expressionMedicineGene

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Multiple sclerosis (MS) is a neuroinflammatory and neurodegenerative disease characterized by infiltration of immune cells in multifocal areas of the CNS. The specific molecular processes allowing autoreactive immune cells to enter the CNS compartment through the blood-brain barrier remain elusive. METHODS: Using endothelial cell (EC) enrichment and single-cell RNA sequencing, we characterized the cells implicated in the neuroinflammatory processes in experimental autoimmune encephalomyelitis, an animal model of MS. Validations on human MS brain sections of the most differentially expressed genes in venous ECs were performed using immunohistochemistry and confocal microscopy. RESULTS: ) in MS lesions. DISCUSSION: In this study, we provide a landscape of the cellular heterogeneity associated with neuroinflammation. We also present important molecular insights for further exploration of specific cell processes that promote infiltration of immune cells inside the brain of experimental autoimmune encephalomyelitis mice.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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