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Record W1494364449 · doi:10.3233/jad-2009-1015

Dramatic Shifts in Circulating CD4 but not CD8 T Cell Subsets in Mild Alzheimer's Disease

2009· article· en· W1494364449 on OpenAlexafffund
Anis Larbi, Graham Pawelec, Jacek M. Witkowski, Hyman M. Schipper, Evelyna Derhovanessian, David Goldeck, Tamàs Fülöp

Bibliographic record

VenueJournal of Alzheimer s Disease · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversité de SherbrookeJewish General Hospital
FundersCanadian Institutes of Health ResearchEli Lilly and Company
KeywordsCD8CD28ImmunologyPhenotypeCytotoxic T cellBiologyIL-2 receptorAlzheimer's diseaseImmune systemMajor histocompatibility complexDiseaseT cellCell biologyMedicineInternal medicineIn vitroGeneticsGene

Abstract

fetched live from OpenAlex

The distribution of peripheral T cell subsets in young and healthy old people is markedly different, characterized by decreased numbers of naïve cells and increased numbers and clonal expansions of memory cells, predominantly in the CD8+ MHC class I-restricted subset. Here, however, we document dramatic alterations in naïve and memory subsets of CD4+ cells in patients with mild Alzheimer's disease (AD), with greatly decreased percentages of naïve cells, elevated memory cells, and increased proportions of CD4+ but not CD8+ cells lacking the important costimulatory receptor CD28. CD4+CD25(high) potentially T regulatory cells with a naïve phenotype are also reduced in AD patients. Together these data provide stronger evidence than hitherto presented for more highly differentiated CD4+ as well as CD8+ T cells in AD patients, consistent with an adaptive immune system undergoing persistent antigenic challenge and possibly manifesting dysregulation as a result.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.289
Teacher spread0.233 · 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 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

Citations207
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Alzheimer s DiseaseSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207