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Peroxisome Injury in Multiple Sclerosis: Protective Effects of 4-Phenylbutyrate in CNS-Associated Macrophages

2022· article· en· W4290667613 on OpenAlexafffund
Andrej Roczkowsky, Matthew A. L. Doan, Brittyne A. Hlavay, Manmeet K. Mamik, William G. Branton, Brienne McKenzie, Leina B. Saito, Laura Schmitt, Gary Eitzen, Francesca Di Cara, Melinda Wuest, Frank Wuest, Richard A. Rachubinski, Christopher Power

Bibliographic record

VenueJournal of Neuroscience · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPeroxisome Proliferator-Activated Receptors
Canadian institutionsDalhousie UniversityWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsMultiple sclerosisAdrenoleukodystrophyNeuroinflammationImmunolabelingPeroxisomeMicrogliaBiologyProteolipid protein 1ChemistryMyelinEndocrinologyMyelin basic proteinImmunologyInflammationCentral nervous systemImmunohistochemistryBiochemistry

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is a progressive and inflammatory demyelinating disease of the CNS. Peroxisomes perform critical functions that contribute to CNS homeostasis. We investigated peroxisome injury and mitigating effects of peroxisome-restorative therapy on inflammatory demyelination in models of MS. Human autopsied CNS tissues (male and female), human cell cultures, and cuprizone-mediated demyelination mice (female) were examined by RT-PCR, Western blotting, and immunolabeling. The therapeutic peroxisome proliferator, 4-phenylbutyrate (4-PBA) was investigated in vitro and in vivo. White matter from MS patients showed reduced peroxisomal transcript and protein levels, including PMP70, compared with non-MS controls. Cultured human neural cells revealed that human microglia contained abundant peroxisomal proteins. TNF-α-exposed microglia displayed reduced immunolabeling of peroxisomal proteins, PMP70 and PEX11β, which was prevented with 4-PBA. In human myeloid cells exposed to TNF-α or nigericin, suppression of PEX11β and catalase protein levels were observed to be dependent on NLRP3 expression. Hindbrains from cuprizone-exposed mice showed reduced Abcd1, Cat, and Pex5l transcript levels, with concurrent increased Nlrp3 and Il1b transcript levels, which was abrogated by 4-PBA. In the central corpus callosum, Iba-1 in CNS-associated macrophages and peroxisomal thiolase immunostaining after cuprizone exposure was increased by 4-PBA. 4-PBA prevented decreased myelin basic protein and neurofilament heavy chain immunoreactivity caused by cuprizone exposure. Cuprizone-induced neurobehavioral deficits were improved by 4-PBA treatment. Peroxisome injury in CNS-associated macrophages contributed to neuroinflammation and demyelination that was prevented by 4-PBA treatment. A peroxisome-targeted therapy might be valuable for treating inflammatory demyelination and neurodegeneration in MS. SIGNIFICANCE STATEMENT Multiple sclerosis (MS) is a common and disabling disorder of the CNS with no curative therapies for its progressive form. The present studies implicate peroxisome impairment in CNS-associated macrophages (CAMs), which include resident microglia and blood-derived macrophages, as an important contributor to inflammatory demyelination and neuroaxonal injury in MS. We also show that the inflammasome molecule NLRP3 is associated with peroxisome injury in vitro and in vivo, especially in CAMs. Treatment with the peroxisome proliferator 4-phenylbutyrate exerted protective effects with improved molecular, morphologic, and neurobehavioral outcomes that were associated with a neuroprotective CAM phenotype. These findings offer novel insights into the contribution of peroxisome injury in MS together with preclinical testing of a rational therapy for MS.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.016
GPT teacher head0.241
Teacher spread0.224 · 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 designBench or experimental
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".

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Citations35
Published2022
Admission routes2
Has abstractyes

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