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Abstract Background Secreted phospholipase A2-IIA (sPLA2-IIA) is an inducible enzyme released under several inflammatory conditions. It has been shown that sPLA2-IIA is released from rat brain astrocytes after inflammatory stimulus, and lipopolysaccharide (LPS) and nitric oxide (NO) have been implicated in regulation of this release. Here, brain microvascular endothelial cells (BMVECs) were treated with LPS to uncover whether sPLA2-IIA was released, whether nitric oxide regulated this release, and any related signal mechanisms. Methods Supernatants were collected from primary cultures of BMVECs. The release of sPLA2-IIA, and the expression of inducible nitric oxide synthase (iNOS), phospho-JAK3, phospho-STAT1, total JAK3 and STAT1, β-actin, and bovine serum albumin (BSA) were analyzed by Western blot or ELISA. NO production was calculated by the Griess reaction. sPLA2 enzyme activity was measured with a fluorometric assay. Specific inhibitors of NO (L-NAME and aminoguanidine, AG), JAK3 (WHI-P154,WHI), STAT1 (fludarabine, Flu), and STAT1 siRNA were used to determine the involvement of these molecules in the LPS-induced release of sPLA2-IIA from BMVECs. Nuclear STAT1 activation was tested with the EMSA method. The monolayer permeability of BMVECs was measured with a diffusion assay using biotinylated BSA. Results Treatment of BMVECs with LPS increased the release of sPLA2-IIA and nitrite into the cell culture medium up to 24 h. Pretreatment with an NO donor, sodium nitroprusside, decreased LPS-induced sPLA2-IIA release and sPLA2 enzyme activity, and enhanced the expression of iNOS and nitrite generation after LPS treatment. Pretreatment with L-NAME, AG, WHI-P154, or Flu notably reduced the expression of iNOS and nitrite, but increased sPLA2-IIA protein levels and sPLA2 enzyme activity. In addition, pretreatment of the cells with STAT1 siRNA inhibited the phosphorylation of STAT1, iNOS expression, and nitrite production, and enhanced the release of sPLA2-IIA. Pretreatment with the specific inhibitors of NOS, JAK2, and STAT3 decreased the permeability of BMVECs. In contrast, inhibition of sPLA2-IIA release increased cell permeability. These results suggest that sPLA2-IIA expression is regulated by the NO-JAK3-STAT1 pathway. Importantly, sPLA2-IIA augmentation could protect the LPS-induced permeability of BMVECs. Conclusion Our results demonstrate the important action of sPLA2-IIA in the permeability of microvascular endothelial cells during brain inflammatory events. The sPLA2 and NO pathways can be potential targets for the management of brain MVEC injuries and related inflammation.

Abstract Background TIR-domain-containing adapter-inducing interferon-β (TRIF) is the sole downstream adaptor of Toll-like receptor (TLR)3, which is one of the major signaling pathways in immune cells leading to neuroinflammation in the central nervous system. Overexpression of TRIF may lead to activation of inflammatory responses, and contribute to pathophysiological progression in both acute and chronic neurodegenerative retinal diseases. In the present study, was aimed to elucidate the contributions of TRIF to optic nerve (ON) regeneration and retinal ganglion cell (RGC) survival following injury to the ON, a widely studied model of central nervous system injury and of degenerative diseases such as glaucoma. Methods We used retrograde labeling with a fluorochrome, hydroxystilbamidine (Fluorogold) to evaluate RGC survival, and immunostaining with growth-associated protein-43 to evaluate axon regeneration in an ON crush model. Changes in microglial cytokines following RGC injury was examined with ELISA and real-time PCR. In vivo studies were carried out in wild-type and trif-/- mice. A Transwell co-culture system and migration test were used to mimic the crosstalk between microglia and RGCs. TRIF-associated downstream adaptors were determined by western blotting. Results Compared with wild-type (WT) mice, TRIF knockout (KO) mice displayed a robust ability to regenerate axons 3 or 7 days after nerve injury. In addition, RGC survival was considerably higher in trif-/- than in WT mice. ON lesion induced less microglial activation in trif-/- than in WT mice. and more WT microglia distorted and migrated toward the foramen opticum. In the transwell system, few trif-/- microglia migrated through the membrane when stimulated by the performed lesion on RGC axons in a transwell system. Inactivation of microglial cells in trif-/- mice was associated with reduced production of inflammatory cytokines, as detected with real-time RT-PCR and ELISA. Furthermore western blot analysis showed that activation of known downstream effectors of TRIF, including TBK1, IKKε and NF-κB, were significantly inhibited by TRIF deficiency. Conclusion Our results indicate that TRIF deficiency promotes ON axon regeneration by attenuating microglial activation and consequently reducing the release of harmful cytokines via NF-κB inactivation.

Punishment is a common tactic to sustain cooperation and has been extensively studied for a long time. While most of previous game-theoretic work adopt the imitation learning framework where players imitate the strategies of those who are better off, the learning logic in the real world is often much more complex. In this work, we turn to the reinforcement learning paradigm, where individuals make their decisions based upon their experience and long-term returns. Specifically, we investigate the prisoners' dilemma game with a Q-learning algorithm, and cooperators probabilistically pose punishment on defectors in their neighborhood. Unexpectedly, we find that punishment could lead to either continuous or discontinuous cooperation phase transitions, and the nucleation process of cooperation clusters is reminiscent of the liquid–gas transition. The analysis of a Q-table reveals the evolution of the underlying "psychologic" changes, which explains the nucleation process and different levels of cooperation. The uncovered first-order phase transition indicates that great care needs to be taken when implementing the punishment compared to the continuous scenario. [ABSTRACT FROM AUTHOR]

While network science has become an indispensable tool for studying complex systems, the conventional use of pairwise links often shows limitations in describing high-order interactions properly. Hypergraphs, where each edge can connect more than two nodes, have thus become a new paradigm in network science. Yet, we are still in lack of models linking network growth and hyperedge expansion, both of which are commonly observable in the real world. Here, we propose a generative hypergraph model by employing the preferential attachment mechanism in both nodes and hyperedge formation. The model can produce bi-heterogeneity, exhibiting scale-free distributions in both hyperdegree and hyperedge size. We provide a mean-field treatment that gives the expression of the two scaling exponents, which agree with the numerical simulations. Our model may help to understand the networked systems showing both types of heterogeneity and facilitate the study of complex dynamics thereon. [ABSTRACT FROM AUTHOR]