The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter , and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of , resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real networks. The discrepancy suggests that there are further relevant factors that are not yet captured here.

We study a modified prisoner's dilemma game taking place on two-dimensional disordered square lattices. The players are pure strategists and can either cooperate or defect with their immediate neighbors. In the generations each player updates its strategy by following one of the neighboring strategies with a probability dependent on the payoff difference. The neighbor selection obeys a dynamic preferential rule, i.e., the more frequently a neighbor's strategy was adopted by the focal player in the previous rounds, the larger probability it will be chosen to refer to in the subsequent rounds. It is found that cooperation is substantially promoted due to this simple selection mechanism. Corresponding analysis is provided by the investigation of the distribution of the players' impact weights, persistence, and correlation function.

The primate connectome, possessing a characteristic global topology and specific regional connectivity profiles, is well organized to support both segregated and integrated brain function. However, the organization mechanisms shaping the characteristic connectivity and its relationship to functional requirements remain unclear. The primate brain connectome is shaped by metabolic economy as well as functional values. Here, we explored the influence of two competing factors and additional advanced functional requirements on the primate connectome employing an optimal trade-off model between neural wiring cost and the representative functional requirement of processing efficiency. Moreover, we compared this model with a generative model combining spatial distance and topological similarity, with the objective of statistically reproducing multiple topological features of the network. The primate connectome indeed displays a cost-efficiency trade-off and that up to 67% of the connections were recovered by optimal combination of the two basic factors of wiring economy and processing efficiency, clearly higher than the proportion of connections (56%) explained by the generative model. While not explicitly aimed for, the trade-off model captured several key topological features of the real connectome as the generative model, yet better explained the connectivity of most regions. The majority of the remaining 33% of connections unexplained by the best trade-off model were long-distance links, which are concentrated on few cortical areas, termed long-distance connectors (LDCs). The LDCs are mainly non-hubs, but form a densely connected group overlapping on spatially segregated functional modalities. LDCs are crucial for both functional segregation and integration across different scales. These organization features revealed by the optimization analysis provide evidence that the demands of advanced functional segregation and integration among spatially distributed regions may play a significant role in shaping the cortical connectome, in addition to the basic cost-efficiency trade-off. These findings also shed light on inherent vulnerabilities of brain networks in diseases. Author summaryThe intricate primate structural connectome, as the network substrate for distributed and integrated brain function, is shaped by fundamental physical factors and functional requirements. We addressed a trade-off between two competing basic factors of wiring cost and processing efficiency as well as additional requirements of functional segregation and integration on regional structural connectivity profiles by applying cost-efficiency trade-off model to reconstruct the macaque cortical network. We also compared this model with a generative model combining spatial distance and topological similarity. The trade-off model balancing the two basic factors recovered the main topological features that were explicitly specified as the objective functions in the generative model. Moreover, 67% of all connections and most regional connectiv...

Poly (ADP-ribose) polymerase (PARP) has been proposed to play an important role in the pathogenesis of heart ischaemia/reperfusion (I/R) injury. However, the mechanisms of PARP-mediated heart I/R injury in vivo are still not thoroughly understood. Therefore, in this study, we investigate the effect of PARP inhibition on heart I/R injury and try to elucidate the underlying mechanisms. Studies were performed with I/R rats' hearts in vivo. Ischaemia followed by reperfusion caused a significant increase in Poly (ADP-ribose) (PAR), c-Jun NH2-terminal kinase (JNK) and apoptosis-inducing factor (AIF) activity. Administration of 3,4-dihydro-5-[4-(1-piperidinyl)butoxy]-1(2H)-isoquinolinone (DPQ), an inhibitor of PARP, decreased myocardial infarction size from 61.11±7.46%[0] to 38.83±5.67% (P<0.05) and cells apoptosis from 35±5.3% to 20±4.1% (P<0.05) and simultaneously improved the cardiac function. Western blot analysis showed that administration of DPQ reduced the activation of JNK and attenuated mitochondrial-nuclear translocation of AIF. Additionally, administration of SP600125, an inhibitor of JNK, attenuated mitochondrial-nuclear translocation of AIF. The results of the present study demonstrated that the inhibition of PARP was able to reduce heart I/R injury in vivo. Our results also suggested that JNK may be downstream of PARP activation and be required for PARP-mediated AIF translocation. Inhibition of the activity of PARP may reduce heart I/R injury via suppressing AIF translocation mediated by JNK.

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Myeloid-derived suppressor cells (MDSCs) have strong immunosuppressive functions and contribute to the formation of the tumor microenvironment. Long non-coding (Lnc) RNAs are highly important factors associated with tumors and may be used as markers for tumor diagnosis, which is valuable for targeted therapy. LncRNA MALAT1 is expressed in various tissues and plays a critical role in cell proliferation, including tumorigenesis and metastasis. However, the role of MALAT1 in MDSCs is unclear. In this study, we observed an increased proportion of MDSCs and elevated levels of the related molecule arginase-1 (ARG-1) in peripheral blood mononuclear cells (PBMCs) obtained from lung cancer patients. The proportion of CD8+ cytotoxic T lymphocyte (CTL) was significantly decreased in PBMCs from lung cancer patients. Moreover, the proportion of CTL cells was negatively correlated with the proportion of MDSCs. Furthermore, MALAT1 levels were decreased in PBMCs from lung cancer patients. The relative expression of MALAT1 was moderate negatively correlated with the proportion of MDSCs. In vitro results indicate that the knockdown of MALAT1 significantly increased the proportion of MDSCs. Our data provide the first evidence that lncRNA MALAT1 negatively regulates MDSCs and is decreased in PBMCs from lung cancer patients.

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Approximately 20-30% of patients with epilepsy continue to have seizures despite carefully monitored treatment with antiepileptic drugs. The mechanisms that underlie why some patients are responsive and others prove resistant to antiepileptic drugs are poorly understood. Increasing evidence supports a role for altered mitochondrial function in the pathogenesis of epilepsy. To gain greater molecular insight in the pathogenesis of intractable epilepsy, we undertook a global analysis of protein expressions in a pharmacoresistant epileptic model selected by phenytoin in electrical amygdala-kindled rats by using two-dimensional gel electrophoresis coupled with matrix-assisted laser desorption/ionization time of flight (MALDI-TOF-TOF). We identified five increased proteins and 14 decreased proteins including voltage-dependent anion channel 1 (VDAC1) with a 2.82-fold increased level (P < 0.05) and voltage-dependent anion channel 2 (VDAC2) with a 3.97-fold decreased level (P < 0.05) in hippocampus of pharmacoresistant rats. The increased VDAC1 and decreased VDAC2 were confirmed by Western blot analysis and immunohistochemistry. Vascular mitochondria and apoptosis neurons were observed through electron microscopy. Energy contents, the adenine nucleotides, were measured by high-performance liquid chromatography (HPLC). The correlation analyses were carried out between VDAC and the energy charge. These findings indicate that the increase of VDAC1 and the decrease of VDAC2 play an important role during the process and provide new molecular evidence in understanding mechanism of refractory epilepsy.