Microglia/macrophage-specific deletion of TLR-4 protects against neural effects of diet-induced obesity in a sexually dimorphic manner
Bibliographic record
Abstract
Obesity is associated with numerous adverse neural effects, including reduced neurogenesis, cognitive impairment, and increased risks for developing Alzheimer's disease (AD) and vascular dementia. Obesity is also characterized by chronic, low-grade inflammation that is implicated in mediating negative consequences body-wide. Toll-like receptor 4 (TLR4) signaling from peripheral macrophages is implicated as an essential regulator of the systemic inflammatory effects of obesity. In the brain, obesity drives chronic neuroinflammation that involves microglial activation, however the contributions of microglia-derived TLR4 signaling to the consequences of obesity are poorly understood. To investigate this issue, we first generated mice that carry an inducible, microglia/macrophage-specific deletion of TLR4 that yields long-term TLR4 knockout only in brain indicating microglial specificity. Next, we analyzed the effects of microglia/macrophage TLR4 deletion on systemic and neural effects of a 16-week of exposure to control versus obesogenic high-fat diets. In male mice, TLR4 deletion generally yielded limited effects on diet-induced systemic metabolic dysfunction but significantly reduced neuroinflammation and impairments in neurogenesis and cognitive performance. In female mice maintained on obesogenic diet, TLR4 deletion partially protected against weight gain, adiposity, and metabolic impairments. Compared to males, females showed milder diet-induced neural consequences, against which TLR4 deletion was protective. Collectively, these findings demonstrate a central role of microglia/macrophage TLR4 signaling in mediating the neural effects of obesogenic diet and highlight sexual dimorphic responses to both diet and TLR4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".