Microglial activation and TNFα production mediate altered CNS excitability following peripheral inflammation
Bibliographic record
Abstract
Peripheral inflammation leads to a number of centrally mediated physiological and behavioral changes. The underlying mechanisms and the signaling pathways involved in these phenomena are not yet well understood. We hypothesized that peripheral inflammation leads to increased neuronal excitability arising from a CNS immune response. We induced inflammation in the gut by intracolonic administration of 2,4,6-trinitrobenzene sulfonic acid (TNBS) to adult male rats. To examine the excitability of the brain in vivo, we administered pentylenetetrazole (PTZ; a GABAergic antagonist) intravenously to evoke clonic seizures. Rats treated with TNBS showed increased susceptibility to PTZ seizures that was strongly correlated with the severity and progression of intestinal inflammation. In vitro hippocampal slices from inflamed, TNBS-treated rats showed increased spontaneous interictal burst firing following application of 4-aminopyridine, indicating increased intrinsic excitability. The TNBS-treated rats exhibited a marked, reversible inflammatory response within the hippocampus, characterized by microglial activation and increases in tumor necrosis factor alpha (TNFalpha) levels. Central antagonism of TNFalpha using a monoclonal antibody or inhibition of microglial activation by i.c.v. injection of minocycline prevented the increase in seizure susceptibility. Moreover, i.c.v. infusion of TNFalpha in untreated rats for 4 days also increased seizure susceptibility and thus mimicked the changes in seizure threshold observed with intestinal inflammation. Our finding of a microglia-dependent TNFalpha-mediated increase in CNS excitability provides insight into potential mechanisms underlying the disparate neurological and behavioral changes associated with chronic 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) | 0.000 | 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".