MétaCan
Menu
Back to cohort
Record W4403983063 · doi:10.1186/s12974-024-03278-2

Senolytic treatment diminishes microglia and decreases severity of experimental autoimmune encephalomyelitis

2024· article· en· W4403983063 on OpenAlexafffund
Sienna Drake, Aliyah Zaman, Christine Gianfelice, Elizabeth M.-L. Hua, Kali Heale, Elia Afanasiev, Wendy Klément, Jo Anne Stratton, Alexandre Prat, Stéphanie Zandee, Alyson E. Fournier

Bibliographic record

VenueJournal of Neuroinflammation · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsCentre Hospitalier de l’Université de MontréalMcGill UniversityMontreal Neurological Institute and Hospital
FundersCanadian Institutes of Health ResearchMultiple Sclerosis Society of Canada
KeywordsMicrogliaExperimental autoimmune encephalomyelitisMedicineNeurologyMultiple sclerosisEncephalomyelitisImmunologyNeuroscienceInflammationPsychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The role of senescence in disease contexts is complex, however there is considerable evidence that depletion of senescent cells improves outcomes in a variety of contexts particularly related to aging, cognition, and neurodegeneration. Much research has shown previously that inflammation can promote cellular senescence. Microglia are a central nervous system innate immune cell that undergo senescence with aging and during neurodegeneration. The contribution of senescent microglia to multiple sclerosis, an inflammatory neurodegenerative disease, is not clear, but microglia are strongly implicated in chronic active lesion pathology, tissue injury, and disease progression. Drugs that could specifically eliminate dysregulated microglia in multiple sclerosis are therefore of great interest to the field. RESULTS: A single-cell analysis of brain tissue from mice subjected to experimental autoimmune encephalomyelitis (EAE), a mouse model of CNS inflammation that models aspects of multiple sclerosis (MS), identified microglia with a strong transcriptional signature of senescence including the presence of BCL2-family gene transcripts. Microglia expressing Bcl2l1 had higher expression of pro-inflammatory and senescence associated genes than their Bcl2l1 negative counterparts in EAE, suggesting they may exacerbate inflammation. Notably, in human single-nucleus sequencing from MS, BCL2L1 positive microglia were enriched in lesions with active inflammatory pathology, and likewise demonstrated increased expression of immune genes suggesting they may be proinflammatory and contribute to disease processes in chronic active lesions. Employing a small molecule BCL2-family inhibitor, Navitoclax (ABT-263), significantly reduced the presence of microglia and macrophages in the EAE spinal cord, suggesting that these cells can be targeted by senolytic treatment. ABT-263 treatment had a profound effect on EAE mice: decreasing motor symptom severity, improving visual acuity, promoting neuronal survival, and decreasing white matter inflammation. CONCLUSION: These results support the hypothesis that microglia and macrophages exhibit transcriptional features of cellular senescence in EAE and MS, and that microglia expressing Bcl2l1 demonstrate a proinflammatory signature that may exacerbate inflammation resulting in negative outcomes in neuroinflammatory disease. Depleting microglia and macrophages using a senolytic results in robust improvement in EAE disease severity, including across measures of neurodegeneration, inflammation, and demyelination, and may therefore represent a novel strategy to address disease progression in multiple sclerosis.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.009
Threshold uncertainty score0.653

Codex and Gemma teacher scores by category

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 communication0.0000.001
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 head0.030
GPT teacher head0.279
Teacher spread0.249 · 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 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".

Quick stats

Citations28
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueJournal of NeuroinflammationSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207