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Record W2305318049 · doi:10.1186/s12974-016-0531-9

Complex molecular and functional outcomes of single versus sequential cytokine stimulation of rat microglia

2016· article· en· W2305318049 on OpenAlexafffund
Tamjeed Siddiqui, Starlee Lively, Lyanne C. Schlichter

Bibliographic record

VenueJournal of Neuroinflammation · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsKrembil FoundationUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchHeart and Stroke Foundation of Canada
KeywordsMicrogliaNeuroscienceCytokineStimulationNeurologyMedicineNeuroinflammationPsychologyImmunologyInflammation

Abstract

fetched live from OpenAlex

BACKGROUND: Microglia are the "professional" phagocytes of the CNS. Phagocytosis is crucial for normal CNS development and maintenance, but it can be either beneficial or detrimental after injury or disease. For instance, white matter damage releases myelin debris that must be cleared by microglia in order for re-myelination to occur. However, phagocytosis can also produce damaging reactive oxygen species (ROS). Furthermore, microglia can acquire pro-inflammatory (M1) or anti-inflammatory (M2) activation states that affect cell functions. Although microglia are exposed to a changing cytokine environment after injury or disease, little is known about the molecular and functional consequences. Therefore, we applied several microglial activation paradigms, with or without myelin debris. We assessed (i) gene expression changes reflecting microglial activation and inflammatory states, and receptors and enzymes related to phagocytosis and ROS production, (ii) myelin phagocytosis and production of ROS, and (iii) expression and contributions of several ion channels that are considered potential targets for regulating microglial behavior. METHODS: Primary rat microglia were exposed to cytokines, individually or sequentially. First, responses to individual M1 or M2 stimuli were compared: IFN-γ plus TNF-α ("I + T"; M1 activation), interleukin-4 (M2a/alternative activation), and interleukin-10 (M2c/acquired deactivation). Second, sequential cytokine addition was used to assess microglia repolarization and cell functions. The paradigms were M2a→M1, M2c→M1, M1→M2a, and M1→M2c. RESULTS: M1 stimulation increased pro-inflammatory genes, phagocytosis, and ROS, as well as expression of Kv1.3, KCa3.1, and Kir2.1 channels. M2a stimulation increased anti-inflammatory genes, ROS production, and Kv1.3 and KCa3.1 expression. Myelin phagocytosis enhanced the M1 profile and dampened the M2a profile, and both phagocytosis and ROS production were dependent on NOX enzymes and Kir2.1 and CRAC channels. Importantly, microglia showed some capacity for re-polarization between M1 and M2a states, based on gene expression changes, myelin phagocytosis, and ROS production. CONCLUSIONS: In response to polarizing and re-polarizing cytokine treatments, microglia display complex changes in gene transcription profiles, phagocytic capacity, NOX-mediated ROS production, and in ion channels involved in microglial activation. Because these changes might affect microglia-mediated CNS inflammation, they should be considered in future experimental, pre-clinical studies.

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)0.001
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 score0.015
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.074
GPT teacher head0.282
Teacher spread0.207 · 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

Citations60
Published2016
Admission routes2
Has abstractyes

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