Selective peroxisome proliferator‐activated receptor‐gamma modulator, INT131 exhibits anti‐inflammatory effects in an EcoHIV mouse model
Bibliographic record
Abstract
Despite the use of antiretroviral therapy for the treatment of HIV-1 infection, cognitive impairments, that is, HIV-1-associated neurocognitive disorders remain prevalent potentially due to persistent viral replication, production of viral proteins, associated brain inflammation or in certain instances, antiretroviral neurotoxicity. Cellular targets in the brain include microglia which in response to infection release inflammatory markers and viral proteins. Evidence suggests that PPARγ agonists exert anti-inflammatory properties in neurological disorders. However, these agonists namely, thiazolidinediones have limited use in the clinic due to reported adverse side effects. INT131 is a novel non-thiazolidinedione compound that belongs to a new class of drugs known as selective PPARγ modulators. INT131 is considered to have a safer profile; however, its neuroprotective role in vivo is not known.The goal of this study was to examine the effect of INT131 in the context of EcoHIV-induced inflammation in vitro, in primary cultures of mouse glial cells and in vivo, in a mouse model of EcoHIV-associated brain inflammation, as well as characterize its pharmacokinetic properties and brain penetration. In primary cultures of glial cells and in the in vivo mouse model, EcoHIV exposure resulted in a significant elevation of inflammatory markers such as TNFα, IL-1β, CCL3, and C3 which were attenuated with INT131 treatment. Pharmacokinetic analyses revealed that INT131 penetrates into the brain with a brain to blood partition ratio Kp value of 8.5%. Overall, this is the first report to demonstrate that INT131 could be a potential candidate for the treatment of HIV-1-associated brain inflammation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".