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Record W2745816174 · doi:10.1186/s12974-017-0941-3

Responses of rat and mouse primary microglia to pro- and anti-inflammatory stimuli: molecular profiles, K+ channels and migration

2017· article· en· W2745816174 on OpenAlexafffund
Doris Lam, Starlee Lively, Lyanne C. Schlichter

Bibliographic record

VenueJournal of Neuroinflammation · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsKrembil FoundationUniversity of TorontoUniversity Health Network
FundersCanadian Institutes of Health ResearchCanadian Stroke Network
KeywordsMicrogliaNeurosciencePrimary (astronomy)NeurologyMedicineNeuroinflammationInflammationImmunologyBiology

Abstract

fetched live from OpenAlex

Acute CNS damage is commonly studied using rat and mouse models, but increasingly, molecular analysis is finding species differences that might affect the ability to translate findings to humans. Microglia can undergo complex molecular and functional changes, often studied by in vitro responses to discrete activating stimuli. There is considerable evidence that pro-inflammatory (M1) activation can exacerbate tissue damage, while anti-inflammatory (M2) states help resolve inflammation and promote tissue repair. However, in assessing potential therapeutic targets for controlling inflammation, it is crucial to determine whether rat and mouse microglia respond the same. Primary microglia from Sprague-Dawley rats and C57BL/6 mice were cultured, then stimulated with interferon-γ + tumor necrosis factor-α (I + T; M1 activation), interleukin (IL)-4 (M2a, alternative activation), or IL-10 (M2c, acquired deactivation). To profile their activation responses, NanoString was used to monitor messenger RNA (mRNA) expression of numerous pro- and anti-inflammatory mediators, microglial markers, immunomodulators, and other molecules. Western analysis was used to measure selected proteins. Two potential targets for controlling inflammation—inward- and outward-rectifier K + channels (Kir2.1, Kv1.3)—were examined (mRNA, currents) and specific channel blockers were applied to determine their contributions to microglial migration in the different activation states. Pro-inflammatory molecules increased after I + T treatment but there were several qualitative and quantitative differences between the species (e.g., iNOS and nitric oxide, COX-2). Several molecules commonly associated with an M2a state differed between species or they were induced in additional activation states (e.g., CD206, ARG1). Resting levels and/or responses of several microglial markers (Iba1, CD11b, CD68) differed with the activation state, species, or both. Transcripts for several Kir2 and Kv1 family members were detected in both species. However, the current amplitudes (mainly Kir2.1 and Kv1.3) depended on activation state and species. Treatment-induced changes in morphology and migratory capacity were similar between the species (migration reduced by I + T, increased by IL-4 or IL-10). In both species, Kir2.1 block reduced migration and Kv1.3 block increased it, regardless of activation state; thus, these channels might affect microglial migration to damage sites. Caution is recommended in generalizing molecular and functional responses of microglia to activating stimuli between species.

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)0.001
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 score0.006
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.034
GPT teacher head0.279
Teacher spread0.245 · 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

Citations72
Published2017
Admission routes2
Has abstractyes

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