Increasingly frequent urban floods strain the traditional grey infrastructure, overwhelming the capacity of drainage networks and causing challenges in managing stormwater. The heavy precipitation leads to flooding and damage to drainage systems. Consequently, efficient mitigation strategies for flooding have been researched deeply. Green infrastructure (GI) has proved to be effective in responding the increasing risk of flood and alleviate pressure on drainage systems. However, as the primary infrastructure of stormwater management, there is still a lack of attention to the dynamic operation feature of urban sewer systems during precipitation events. To fill this gap, we proposed a novel approach that integrates hydraulic characteristics and the topological structure of a sewer network system. This approach aims to identify influential nodes, which contribute to the connectivity of the sewer network amidst dynamic changes in inflow during precipitation events. Furthermore, we adopted rain barrels to serve as exemplars of GI, and 14 GI layout schemes are produced based on the different ranks of influential nodes. Implementing GI measures on both poorly performing and well-performing nodes can yield distinct benefits in mitigating node flooding. This approach provides a new perspective for stormwater management, establishing effective synergy between GI and the drainage system.

BACKGROUND: Panic disorder (PD) is a common disabling condition characterized by recurrent panic attacks. Emotional and behavioral impairments are associated with functional connectivity (FC) and network abnormalities. We used the whole brain FC, modular networks, and graph-theory analysis to investigate extensive network profiles in PD.
METHODS: The functional MRI data from 82 PD and 97 controls were included. Intrinsic FC between each pair of 160 regions, 6 intra-networks, and 15 inter-networks were analyzed. The topological properties were explored.
RESULTS: PD patients showed altered FCs within the right insula, between frontal cortex-posterior cingulate cortex (PCC), frontal cortex-cerebellum, and PCC-occipital cortex (corrected P values < 0.001). Lower connections within the Sensorimotor Network (SMN) and SMN-Occipital Network (OCN) were detected (P values < 0.05). Various decreased global and local network features were found in PD (P values < 0.05). In addition, significant correlations were found between PD symptoms and nodal efficiency (Ne) in the insula (r = -0.273, P = 0.016), and the FC of the intra-insula (r = -0.226, P = 0.041).
CONCLUSIONS: PD patients present with abnormal functional brain networks, especially the decreased FC and Ne within insula, suggesting that dysfunction of information integration plays an important role in PD.

The oncogenesis and progression of gastric cancer are closely correlated with the complex regulatory relationships among messenger RNA (mRNA), long noncoding RNA (lncRNA), and microRNA (miRNA). After constructing the gastric cancer lncRNA-miRNA-mRNA regulatory network, we analyzed the network topology properties and found that lncRNA ADAMTS9-AS2 and C20orf166-AS1 and miRNA hsa-mir-204 are key nodes. Further functional enrichment analysis and survival analysis were performed on these key nodes and the RNAs interacting with them. We found that CHRM2, ANGPT2, and COL1A1 interacting with ADAMTS9-AS2 are enriched in the PI3K-Akt signaling pathway, and low expression of the ADAMTS9-AS2 is closely related to the prognosis of patients. Abnormal expression of CACNA1H, FLNA, and FLNC interacting with lncRNA C20orf166-AS1 is associated with MAPK signaling pathway in gastric cancer. In addition, the downregulated miRNA hsa-mir-204 promotes invasion and proliferation of gastric cancer cells by regulating the abnormal expression of mRNAs (CHRDL1 and NPTX1) and lncRNAs (ADAMTS9-AS2, NKX2-1-AS1, TLR8-AS1, and VCAN-AS1). This study systematically analyzed the lncRNA-miRNA-mRNA regulatory network of gastric cancer, which not only has a new understanding of the pathogenesis of gastric cancer, but also provides new insights for the early diagnosis and treatment of gastric cancer.

Research on brain function after brachial plexus injury focuses on local cortical functional reorganization, and few studies have focused on brain networks after brachial plexus injury. Changes in brain networks may help understanding of brain plasticity at the global level. We hypothesized that topology of the global cerebral resting-state functional network changes after unilateral brachial plexus injury. Thus, in this cross-sectional study, we recruited eight male patients with unilateral brachial plexus injury (right handedness, mean age of 27.9 ± 5.4 years old) and eight male healthy controls (right handedness, mean age of 28.6 ± 3.2). After acquiring and preprocessing resting-state magnetic resonance imaging data, the cerebrum was divided into 90 regions and Pearson\'s correlation coefficient calculated between regions. These correlation matrices were then converted into a binary matrix with affixed sparsity values of 0.1-0.46. Under sparsity conditions, both groups satisfied this small-world property. The clustering coefficient was markedly lower, while average shortest path remarkably higher in patients compared with healthy controls. These findings confirm that cerebral functional networks in patients still show small-world characteristics, which are highly effective in information transmission in the brain, as well as normal controls. Alternatively, varied small-worldness suggests that capacity of information transmission and integration in different brain regions in brachial plexus injury patients is damaged.