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Isolating, Culturing, and Polarizing Primary Human Adult and Fetal Microglia

2013· article· en· W104113135 on OpenAlexaff
Bryce A. Durafourt, Craig S. Moore, Manon Blain, Jack P. Antel

Bibliographic record

VenueMethods in molecular biology · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMontreal Neurological Institute and HospitalMcGill University
Fundersnot available
KeywordsMicrogliaPrimary (astronomy)FetusPrimary cultureCell biologyNeuroscienceBiologyImmunologyPregnancyCell cultureGeneticsPhysicsInflammation

Abstract

fetched live from OpenAlex

Microglia are an important component of the innate immune system within the central nervous system (CNS). Isolation and in vitro culturing of microglia can provide insight towards the basic biology of these cells as well as their interactions with neurons, astrocytes, and oligodendrocytes. While studies of rodent microglia and microglial cell lines have provided a basis for our understanding of these cells, human adult microglia exhibit distinct properties when compared to rodent cells. Furthermore, the study of human fetal microglia provides a window into the developing CNS. This chapter describes the protocols used to isolate, purify, and culture both human adult and fetal microglia. Under basal culture conditions, human microglia survive for extended periods in the absence of growth factors, thus allowing their properties to be investigated under resting conditions. In addition, both human adult and fetal microglia can be used to study how they respond to different polarization conditions. As is the case with macrophages, it is also possible to polarize microglia towards the pro-inflammatory "M1" and the anti-inflammatory "M2" phenotypes, as described in this chapter.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.005

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 head0.025
GPT teacher head0.348
Teacher spread0.324 · 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
GenreMethods

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

Citations89
Published2013
Admission routes1
Has abstractyes

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