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Record W2007217012 · doi:10.1016/j.febslet.2011.04.066

How do immune cells overcome the blood–brain barrier in multiple sclerosis?

2011· review· en· W2007217012 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueFEBS Letters · 2011
Typereview
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsUniversité de MontréalHôpital Notre-Dame
FundersCanadian Institutes of Health ResearchMultiple Sclerosis SocietyMultiple Sclerosis Society of Canada
KeywordsBlood–brain barrierMultiple sclerosisImmune systemCentral nervous systemInflammationImmunologyInfiltration (HVAC)NeuroinflammationBiologyLeukocyte TraffickingNeuroscienceChemokine

Abstract

fetched live from OpenAlex

The presence of the blood-brain barrier (BBB) restricts the movement of soluble mediators and leukocytes from the periphery to the central nervous system (CNS). Leukocyte entry into the CNS is nonetheless an early event in multiple sclerosis (MS), an inflammatory disorder of the CNS. Whether BBB dysfunction precedes immune cell infiltration or is the consequence of perivascular leukocyte accumulation remains enigmatic, but leukocyte migration modifies BBB permeability. Immune cells of MS subjects express inflammatory cytokines, reactive oxygen species (ROS) and enzymes that can facilitate their migration to the CNS by influencing BBB function, either directly or indirectly. In this review, we describe how immune cells from the peripheral blood overcome the BBB and promote CNS inflammation in MS through BBB disruption.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.914
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.097
GPT teacher head0.253
Teacher spread0.156 · 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