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Record W2694472030 · doi:10.1093/jnen/nlx001

Immune Cell Infiltrates in Hippocampal Sclerosis: Correlation With Neuronal Loss

2017· article· en· W2694472030 on OpenAlexaff
Jian‐Qiang Lu, Trevor A. Steve, Matt Wheatley, Donald Gross

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2017
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHippocampal sclerosisPathogenesisCD8Immune systemMicrogliaInfiltration (HVAC)Cytotoxic T cellCD68EpilepsyImmunologyPathologyMedicineBiologyImmunohistochemistryInflammationNeuroscienceTemporal lobeGenetics

Abstract

fetched live from OpenAlex

Immune mechanisms have been increasingly recognized in the pathogenesis of hippocampal sclerosis (HS), but infiltration of cytotoxic T-cells and its pathological significance in patients with HS has not been explored. We examined 30 cases of surgically resected hippocampi, including 16 International League Against Epilepsy (ILAE) type 1, 9 ILAE type 2, 1 ILAE type 3 HS, and 4 ILAE No-HS, as well as 6 autopsy No-HS hippocampi. The HS hippocampi showed sparse to scattered CD8-positive T-cells, rare CD4-positive T-cells, and a modest increase in CD68-positive microglia/macrophages, which were significantly more numerous than those in the No-HS controls. The infiltration of CD8-positive T-cells was significantly greater in the CA1 subfield than other subfields of type 1 and type 2 HS. The numbers of CD8-positive T-cells positively correlated with those of CD4-positive T-cells; there was a lower ratio of CD4/CD8-positive T-cells. There were positive correlations between these cells and scores of neuronal loss but no significant correlation between the infiltration of these cells and epilepsy disease duration or age of epilepsy onset. These findings suggest that an autoimmune process may be involved in the pathogenesis of HS and infiltration of immune cells, particularly CD8-positive cytotoxic T-cells, may contribute to neuronal loss in HS.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.254
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
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 head0.024
GPT teacher head0.293
Teacher spread0.269 · 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 designObservational
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

Citations29
Published2017
Admission routes1
Has abstractyes

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