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Record W2517473991 · doi:10.1038/srep31652

Laquinimod rescues striatal, cortical and white matter pathology and results in modest behavioural improvements in the YAC128 model of Huntington disease

2016· article· en· W2517473991 on OpenAlexaff
Marta Garcia‐Miralles, Xin Hong, Liang Tan, Nicholas S. Caron, Yihui Huang, Xuan Vinh To, Rachel Yanping Lin, Sonia Franciosi, Spyros Papapetropoulos, Liat Hayardeny, Michael R. Hayden, Kai‐Hsiang Chuang, Mahmoud A. Pouladi

Bibliographic record

VenueScientific Reports · 2016
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersNational University of SingaporeTeva Pharmaceutical Industries
KeywordsCorpus callosumWhite matterStriatumHuntington's diseaseAtrophyNeuroscienceMedicineImmune systemPathogenesisNeurodegenerationNeuroinflammationDiseasePathologyPsychologyImmunologyMagnetic resonance imagingDopamine

Abstract

fetched live from OpenAlex

Increasing evidence supports a role for abnormal immune activation and inflammatory responses in Huntington disease (HD). In this study, we evaluated the therapeutic potential of laquinimod (1 and 10 mg/kg), a novel immunomodulatory agent shown to be protective in a number of neuroinflammatory conditions, in the YAC128 mouse model of HD. Treatment with laquinimod for 6 months rescued atrophy in the striatum, in certain cortical regions, and in the corpus callosum of YAC128 HD mice. Diffusion tensor imaging showed that white matter microstructural abnormalities in the posterior corpus callosum were improved following treatment with low dose (1 mg/kg) laquinimod, and were paralleled by reduced levels of interleukin-6 in the periphery of YAC128 HD mice. Functionally, treatment with laquinimod (1 and 10 mg/kg) led to modest improvements in motor function and in depressive-like behaviour. Taken together, these results suggest that laquinimod may improve some features of pathology in HD, and provides support for the role of immune activation in the pathogenesis of HD.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.300
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.040
GPT teacher head0.277
Teacher spread0.236 · 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

Citations67
Published2016
Admission routes1
Has abstractyes

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