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Record W2980187415 · doi:10.1016/j.trci.2019.09.001

A single systemic inflammatory insult causes acute motor deficits and accelerates disease progression in a mouse model of human tauopathy

2019· article· en· W2980187415 on OpenAlexaff
Megan Torvell, David W. Hampton, Peter Connick, Alasdair M. J. MacLullich, Colm Cunningham, Siddharthan Chandran

Bibliographic record

VenueAlzheimer s & Dementia Translational Research & Clinical Interventions · 2019
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsTrinity College
FundersBiotechnology and Biological Sciences Research CouncilNational Centre for the Replacement, Refinement and Reduction of Animals in ResearchMedical Research CouncilUniversity of Edinburgh
KeywordsTauopathyNeurodegenerationNeuroinflammationMedicineInflammationNeuroscienceSystemic inflammationDiseaseDementiaImmunologyPathologyPsychology

Abstract

fetched live from OpenAlex

INTRODUCTION: Neuroinflammation, which contributes to neurodegeneration, is a consistent hallmark of dementia. Emerging evidence suggests that systemic inflammation also contributes to disease progression. METHODS: The ability of systemically administered lipopolysaccharide (LPS - 500 μg/kg) to effect acute and chronic behavioural changes in C57BL/6 and P301S tauopathy mice was assessed. Markers of pathology were assessed in the brain and spinal cord. RESULTS: P301S mice display regional microgliosis. Systemic LPS treatment induced exaggerated acute sickness behaviour and motor dysfunction in P301S mice compared with wild-type controls and advanced the onset and accelerated chronic decline. LPS treatment was associated with increased tau pathology 24 hours after LPS injection and spinal cord microgliosis at the end stage. DISCUSSION: This is the first demonstration that a single systemic inflammatory episode causes exaggerated acute functional impairments and accelerates the long-term trajectory of functional decline associated with neurodegeneration in a mouse model of human tauopathy. The findings have relevance to management of human dementias.

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)0.002
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 score0.049
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.236
GPT teacher head0.481
Teacher spread0.245 · 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

Citations21
Published2019
Admission routes1
Has abstractyes

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