LPS-induced inflammation reduces GABAergic interneuron markers and brain-derived neurotrophic factor in mouse prefrontal cortex and hippocampus
Bibliographic record
Abstract
Inflammation, reduced gamma-aminobutyric acidergic (GABAergic) function and altered neuroplasticity are co-occurring pathophysiologies in major depressive disorder (MDD). However, the link between these biological changes remains unclear. We hypothesized that inflammation induces deficits in GABAergic interneuron markers and that this effect is mediated by brain-derived neurotrophic factor (BDNF). We report here that systemic inflammation induced by intraperitoneal injection of lipopolysaccharide (LPS) (0.125, 0.25, 0.5, 1, 2 mg/kg) in the first cohort of C57BL/6 mice (n = 72; 9–12 weeks; 50% female) resulted in increased interleukin 1-beta and interleukin-6 in prefrontal cortex (PFC) and hippocampus (HPC), as measured using enzyme-linked immunosorbent assay (ELISA). Quantitative real-time polymerase reaction (qPCR) was used to explore the effect of LPS on the expression of GABAergic interneuron markers. In the PFC of the second cohort (n = 39; 9–12 weeks; 50% female), 2 mg/kg of LPS decreased the expression of somatostatin (Sst) (p = 0.0014), parvalbumin (Pv) (p = 0.0257), cortistatin (Cort) (p = 0.0003), neuropeptide Y (Npy) (p = 0.0033) and cholecystokinin (Cck) (p = 0.0041), and did not affect corticotropin-releasing hormone (Crh) and vasoactive intestinal peptide (Vip) expression. In the HPC, 2 mg/kg of LPS decreased the expression of Sst (P = 0.0543), Cort (p = 0.0011), Npy (p = 0.0001), and Cck (p < 0.0001), and did not affect Crh, Pv, and Vip expression. LPS decreased the expression of Bdnf in the PFC (P < 0.0001) and HPC (P = 0.0003), which significantly correlated with affected markers (Sst, Pv, Cort, Cck, and Npy). Collectively, these results suggest that inflammation may causally contribute to cortical cell microcircuit GABAergic deficits observed in MDD.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".