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TNFα exposure induces neuroinflammation and insulin resistance in a rat‐derived hypothalamic cell model, rHypoE‐7

2017· article· en· W4389022897 on OpenAlexafffund
Matthew N. Clemenzi, Makram E. Aljghami, Leigh Wellhauser, Denise D. Belsham

Bibliographic record

VenueThe FASEB Journal · 2017
Typearticle
Languageen
FieldNeuroscience
TopicRegulation of Appetite and Obesity
Canadian institutionsUniversity of Toronto
FundersBanting and Best Diabetes Centre, University of TorontoNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchWeatherhead Center for International Affairs, Harvard UniversityChesapeake Research ConsortiumAnesthesia Patient Safety Foundation
KeywordsNeuroinflammationInsulin resistanceEndocrinologyInternal medicineTumor necrosis factor alphaInsulinBiologyInsulin receptorProinflammatory cytokineCytokineInflammationMedicine

Abstract

fetched live from OpenAlex

Obesity is approaching epidemic levels. One of the main characteristics of obesity is the development of insulin resistance, leading to other comorbidities, such as type 2 diabetes mellitus (T2DM) and cardiovascular disease. Insulin resistance has been shown to be induced with obesity in peripheral tissues, such as liver, muscle, and adipocytes, by the pro‐inflammatory cytokine tumor necrosis factor alpha (TNFα). In the hypothalamus, the main brain region for energy regulation, neuroinflammation‐induced insulin resistance has been demonstrated to occur upon prolonged treatment with high levels of insulin and palmitate, and we are exploring whether TNFα, a downstream surrogate for palmitate, has similar effects. We hypothesized that TNFα‐treated rat hypothalamic neurons would exhibit cellular neuroinflammation and insulin resistance as evidenced by increased expression of pro‐inflammatory genes and attenuated phosphorylation of Akt (pAkt) in the insulin signaling pathway. Using an immortalized rat hypothalamic cell line (rHypoE‐7), a well‐characterized NPY‐expressing neuronal line derived from male embryonic hypothalamii, we studied changes in pAkt and inflammatory gene marker mRNA expression after TNFα treatment by Western blot and quantitative real‐time PCR, respectively. A qPCR array of 84 inflammatory markers (receptors, chemokines, and cytokines) demonstrated an increase in the expression of a number of genes encoding inflammatory markers, including Tollip and Caspase‐1 , upon exposure to 100 ng/mL TNFα for 4 h. Neurons pre‐exposed to TNFα (50 ng/mL) for 6 or 16 h exhibited a significant reduction in pAkt compared to control after insulin treatment. TNFα also significantly increased mRNA expression of TNF , IK‐κB , Tollip , Tnfrsf1a , and IL6 at 4 h. In conclusion, pre‐treatment with the inflammatory cytokine TNFα causes cellular insulin resistance in the rHypoE‐7 neurons, consistent with effects seen with TNFα in peripheral tissues. It also mimics insulin‐ and palmitate‐induced insulin resistance in hypothalamic neurons. Further, these results demonstrate that components of the IKK‐β/NF‐κB pathway appear to be activated upon exposure to TNFα, providing a putative target to reverse neuroinflammation and insulin resistance with anti‐inflammatory agents. Support or Funding Information This research was supported by grants from the CIHR, CRC, CFI, NSERC, APS and BBDC.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.247
Teacher spread0.213 · 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
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

Citations0
Published2017
Admission routes2
Has abstractyes

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