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Record W3118300061 · doi:10.1038/s42003-020-01557-1

Age-related injury responses of human oligodendrocytes to metabolic insults: link to BCL-2 and autophagy pathways

2021· article· en· W3118300061 on OpenAlexaff
Milton Guilherme Forestieri Fernandes, Julia Xiao Xuan Luo, Qiao‐Ling Cui, Kelly Perlman, Florian Pernin, Moein Yaqubi, Jeffery A. Hall, Roy Dudley, Myriam Srour, Charles Couturier, Kevin Petrecca, Catherine Larochelle, Luke M. Healy, Jo Anne Stratton, Timothy E. Kennedy, Jack P. Antel

Bibliographic record

VenueCommunications Biology · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversité de MontréalMontreal Children's HospitalMcGill University Health CentreDouglas Mental Health University InstituteMcGill UniversityMontreal Neurological Institute and Hospital
FundersInternational Progressive MS Alliance
KeywordsAutophagyLink (geometry)Cell biologyOligodendrocyteNeuroscienceBiologyMedicineApoptosisCentral nervous systemGeneticsComputer scienceMyelin

Abstract

fetched live from OpenAlex

Myelin destruction and oligodendrocyte (OL) death consequent to metabolic stress is a feature of CNS disorders across the age spectrum. Using cells derived from surgically resected tissue, we demonstrate that young (<age 5) pediatric-aged sample OLs are more resistant to in-vitro metabolic injury than fetal O4+ progenitor cells, but more susceptible to cell death and apoptosis than adult-derived OLs. Pediatric but not adult OLs show measurable levels of TUNEL+ cells, a feature of the fetal cell response. The ratio of anti- vs pro-apoptotic BCL-2 family genes are increased in adult vs pediatric (<age 5) mature OLs and in more mature OL lineage cells. Lysosomal gene expression was increased in adult and pediatric compared to fetal OL lineage cells. Cell death of OLs was increased by inhibiting pro-apoptotic BCL-2 gene and autophagy activity. These distinct age-related injury responses should be considered in designing therapies aimed at reducing myelin injury.

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 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 score0.222
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.088
GPT teacher head0.347
Teacher spread0.260 · 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

Citations37
Published2021
Admission routes1
Has abstractyes

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