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Record W2321214963 · doi:10.1093/jnen/nlw017

Complement and Humoral Adaptive Immunity in the Human Choroid Plexus: Roles for Stromal Concretions, Basement Membranes, and Epithelium

2016· article· en· W2321214963 on OpenAlexaff
George R. Moore, Cornelia Laule, Esther Leung, V Pavlova, B. Paul Morgan, Margaret M. Esiri

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesVancouver Coastal Health
FundersMedical Research Council
KeywordsChoroid plexusImmunoglobulin DBasement membraneImmunologyStromal cellBiologyComplement systemHumoral immunityAntibodyPathologyAcquired immune systemCerebrospinal fluidEpitheliumImmune systemCell biologyCentral nervous systemMedicineB cellNeuroscience

Abstract

fetched live from OpenAlex

The choroid plexus (CP) provides a barrier to entry of toxic molecules from the blood into the brain and transports vital molecules into the cerebrospinal fluid. While a great deal is known about CP physiology, relatively little is known about its immunology. Here, we show immunohistochemical data that help define the role of the CP in innate and adaptive humoral immunity. The results show that complement, in the form of C1q, C3d, C9, or C9neo, is preferentially deposited in stromal concretions. In contrast, immunoglobulin (Ig) G (IgG) and IgA are more often found in CP epithelial cells, and IgM is found in either locale. C4d, IgD, and IgE are rarely, if ever, seen in the CP. In multiple sclerosis CP, basement membrane C9 or stromal IgA patterns were common but were not specific for the disease. These findings indicate that the CP may orchestrate the clearance of complement, particularly by deposition in its concretions, IgA and IgG preferentially via its epithelium, and IgM by either mechanism.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.855
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.293
Teacher spread0.263 · 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 teacher head, 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

Citations27
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Neuropathology & Experimental NeurologySame topicComplement system in diseasesFrench-language works237,207