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Record W4387333855 · doi:10.3390/biology12101307

Microglia and Astrocytes in Amyotrophic Lateral Sclerosis: Disease-Associated States, Pathological Roles, and Therapeutic Potential

2023· review· en· W4387333855 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBiology · 2023
Typereview
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersCanadian Institutes of Health ResearchUniversity of TorontoFondation Brain Canada
KeywordsMicrogliaAmyotrophic lateral sclerosisBiologyPathogenesisNeuroscienceNeuroprotectionDiseaseAstrocyteMultiple sclerosisNeuroinflammationPathologicalGliosisCentral nervous systemImmunologyPathologyInflammationMedicine

Abstract

fetched live from OpenAlex

Microglial and astrocytic reactivity is a prominent feature of amyotrophic lateral sclerosis (ALS). Microglia and astrocytes have been increasingly appreciated to play pivotal roles in disease pathogenesis. These cells can adopt distinct states characterized by a specific molecular profile or function depending on the different contexts of development, health, aging, and disease. Accumulating evidence from ALS rodent and cell models has demonstrated neuroprotective and neurotoxic functions from microglia and astrocytes. In this review, we focused on the recent advancements of knowledge in microglial and astrocytic states and nomenclature, the landmark discoveries demonstrating a clear contribution of microglia and astrocytes to ALS pathogenesis, and novel therapeutic candidates leveraging these cells that are currently undergoing clinical trials.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.091
GPT teacher head0.349
Teacher spread0.258 · 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