Ibrutinib alleviated LPS-induced neuroinflammation and synaptic defects in a mouse model of depression
Bibliographic record
Abstract
Abstract Background Previous studies indicate a close association between the altered immune system and major depressive disorders. and inhibition of neuroinflammation may represent an alternative mechanism to treat depression. Recently, the anti-inflammatory activity of ibrutinib has been reported, however, the effect of ibrutinib on neuroinflammation allied depression and its underlying mechanism has not been comprehensively studied. Therefore, we aimed to elucidate the potential anti-depressive role and mechanism of ibrutinib against neuroinflammation induced depression as well as synaptic defects. Methods Adult C57BL/6J male mice weighing 25–30 g (age 7–8 weeks) were treated with LPS (2 mg/kg BW i.p) and 50 mg/kg BW ibrutinib, orally. Depressive-like behaviors were assessed by FST and SPT, cytokine levels were determined by ELISA, ROS, TBARs, and Nitric oxides were measured via biochemical assays, Iba-1 and GFAP expression were determined by immunofluorescence. Further, spine density was measured by Golgi staining, while NF-kB, Nrf2, SOD2, HO-1, NLRP3, P38, Caspase-1, BDNF, PSD95, and synaptophysin were measured by immunoblotting. Results Our results showed that ibrutinib treatment significantly reduced LPS induced depressive-like behaviors and neuroinflammation via inhibiting NF-kB activation, decreasing pro-inflammatory cytokines level, normalizing redox signaling and it’s a downstream component including Nrf2, HO-1, and SOD2 as well as glial cells activation markers such as Iba-1 and GFAP expression. Further, ibrutinib treatment inhibited LPS activated inflammasome activation by targeting NLRP3/P38/Caspase-1 signaling. Interestingly, LPS reduced dendritic spines numbers, expression of BDNF and synaptic related markers including PSD95, snap25, and synaptophysin were improved by ibrutinib treatment in the hippocampal area of the mice brain. Conclusion In conclusion, our finding suggested that ibrutinib could alleviate neuroinflammation and synaptic defects, rendering its antidepressant potential against LPS induced neuroinflammation and depression.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".