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Record W3199118106 · doi:10.1111/imm.13414

Do peripheral protein oligomers in neurodegenerative diseases shape T cell responses beyond the brain?

2021· editorial· en· W3199118106 on OpenAlexaff
A Ferguson, Simon Milling

Bibliographic record

VenueImmunology · 2021
Typeeditorial
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsInstitute of Infection and Immunity
FundersUniversity of Glasgow
KeywordsNeurodegenerationImmune systemPeripheralDiseaseNeuroscienceProtein aggregationOligomerMechanism (biology)BiologyCellImmunologyMedicineCell biologyChemistryPathologyBiochemistryInternal medicine

Abstract

fetched live from OpenAlex

Neurodegenerative diseases place a devastating burden on affected individuals and their families, and new treatments are desperately needed for these common immune-mediated inflammatory conditions. While large aggregates of abnormal proteins in the brain cause significant damage, it is becoming clear that smaller soluble protein aggregates can also contribute to disease, by both direct and indirect mechanisms. These soluble protein oligomers can be found in patients' serum. Here, we describe recent research that identifies effects of model oligomer molecules on peripheral blood T cells, therefore providing an additional mechanism by which neurodegeneration may be worsened through amplification of peripheral adaptive immune responses.

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)0.002
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.308
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.014
GPT teacher head0.308
Teacher spread0.294 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations0
Published2021
Admission routes1
Has abstractyes

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