Introduction: Angiogenesis in the central nervous system is visible in animal models of neuroinflammation and bone cancer pain. However, whether spinal angiogenesis exists and contributes to central sensitization in neuropathic pain remains unclear. This study analyzes the impact of angiogenesis on spinal neuroinflammation in neuropathic pain. Methods: Rats with chronic constriction injury (CCI) to the sciatic nerve underwent the implantation of an intrathecal catheter. Fumagillin or vascular endothelial growth factor-A antibody (anti-VEGF-A) was administered intrathecally. Nociceptive behaviors, cytokine immunoassay, Western blot, and immunohistochemical analysis assessed the effect of angiogenesis inhibition on CCI-induced neuropathic pain. Results: VEGF, cluster of differentiation 31 (CD31), and von Willebrand factor (vWF) expressions increased after CCI in the ipsilateral lumbar spinal cord compared to that in the contralateral side of CCI and control rats from post-operative day (POD) 7 to 28, with a peak at POD 14. Tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and IL-6 concentrations, but not IL-10 levels, also increased in the ipsilateral spinal cord after CCI. Fumagillin and anti-VEGF-A reduced CCI-induced thermal hyperalgesia from POD 5 to 14 and mechanical allodynia from POD 3 to 14. Fumagillin reduced CCI-upregulated expressions of angiogenic factors and astrocytes. Furthermore, fumagillin decreased TNF-α and IL-6 amounts and increased IL-10 levels at POD 7 and 14, but not IL-1β concentrations. Conclusions: Fumagillin significantly ameliorates CCI-induced nociceptive sensitization, spinal angiogenesis, and astrocyte activation. Our results suggest that angiogenesis inhibitor treatment suppresses peripheral neuropathy-induced central angiogenesis, neuroinflammation, astrocyte activation, and neuropathic pain.

This study was undertaken within the framework of an ongoing prospective study on the prognosis of asymptomatic intracranial arterial disease in patients with hypertension. Patients were consecutively recruited either from the outpatient clinic or from the ward of the Department of Hypertension at Ruijin Hospital, a tertiary public general hospital in Shanghai, China, from January 2005 to December 2010. Patients with hypertension were invited to participate in the study if they had ≥2 cardiovascular risk factors defined according to the Chinese hypertension guidelines 18 and were willing to undergo an examination of brain using computerized

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This study developed a fault diagnosis meter based on a ZigBee wireless sensor network (WSN) for photovoltaic power generation systems. First, the Solar Pro software was used to simulate the 9-series, 2-parallel photovoltaic module array formed with the Sharp NT-R5E3E photovoltaic module as well as record the power generation data of the photovoltaic module array at different levels of solar radiation, module temperature, and fault conditions. The derived data were used to establish the weights of the extension neural network (ENN). The fault diagnosis in the photovoltaic power generation system required extracting the system's power generation data and real-time solar radiation and module temperatures; this study thus developed an acquisition circuit for measuring these characteristic values. This study implemented extension neural network theory using a PIC single chip microcontroller and incorporated the ZigBee wireless sensor network module to construct a portable fault diagnosis meter to assess the photovoltaic power generation system. The experimental results showed that the proposed portable fault diagnosis meter based on the extension neural network for the photovoltaic power generation system possessed a high level of accuracy in fault identification.