Peroxynitrite (PN, ONOO−) is a potent oxidant and nitrating agent that contributes to pain through peripheral and spinal mechanisms, but its supraspinal role is unknown. We present evidence here that PN in the rostral ventromedial medulla (RVM) is essential for descending nociceptive modulation in rats during inflammatory and neuropathic pain through PN-mediated suppression of opioid signaling. Carrageenan-induced thermal hyperalgesia was associated with increased 3-nitrotyrosine (NT), a PN biomarker, in the RVM. Furthermore, intra-RVM microinjections of the PN decomposition catalyst (PNDC), Fe(III)-5,10,15,20-tetrakis(N-methyl-pyridinium-4-yl)porphyrin (FeTMPyP5+) dose-dependently reversed this thermal hyperalgesia. These effects of FeTMPyP5+ were abrogated by intra-RVM naloxone, implicating potential interplay between PN and opioids. In support, we identified NT co-localization with the endogenous opioid, enkephalin (ENK), in the RVM during thermal hyperalgesia, suggesting potential in situ interactions. To address the functional significance of such interactions, we exposed methionine-enkephalin (MENK) to PN and identified the major metabolite, 3-nitrotyrosine-methionine-sulfoxide (NSO-MENK), using liquid chromatography-mass spectrometry (LCMS). Next, we isolated, purified, and tested NSO-MENK for opioid receptor binding affinity and analgesic effects. Compared to MENK, this NSO-MENK metabolite lacked appreciable binding affinity for δ, µ, and κ opioid receptors. Intrathecal injection of NSO-MENK in rats did not evoke antinociception suggesting that PN-mediated chemical modifications of ENK suppress opioid signaling. When extended to chronic pain, intra-RVM FeTMPyP5+ produced naloxone-sensitive reversal of mechanical allodynia in rats following chronic constriction injury (CCI) of the sciatic nerve. Collectively, our data reveal the central role of PN in RVM descending facilitation during inflammatory and neuropathic pain potentially through anti-opioid activity.

In this paper, we present a novel technique for automatic parametric mesh generation of subject-specific cerebral arterial trees. This technique generates high-quality and anatomically accurate computational meshes for fast blood flow simulations extending the scope of 3D vascular modeling to a large portion of cerebral arterial trees. For this purpose, a parametric meshing procedure was developed to automatically decompose the vascular skeleton, extract geometric features and generate hexahedral meshes using a body-fitted coordinate system that optimally follows the vascular network topology. To validate the anatomical accuracy of the reconstructed vasculature, we performed statistical analysis to quantify the alignment between parametric meshes and raw vascular images using receiver operating characteristic curve. Geometric accuracy evaluation showed an agreement with area under the curves value of 0.87 between the constructed mesh and raw MRA data sets. Parametric meshing yielded on-average, 36.6% and 21.7% orthogonal and equiangular skew quality improvement over the unstructured tetrahedral meshes. The parametric meshing and processing pipeline constitutes an automated technique to reconstruct and simulate blood flow throughout a large portion of the cerebral arterial tree down to the level of pial vessels. This study is the first step towards fast large-scale subject-specific hemodynamic analysis for clinical applications.

Redox-active metalloporphyrins represent the most well characterized class of catalysts capable of attenuating oxidative stress in vivo through the direct interception and decomposition of superoxide and peroxynitrite. While many interesting pharmacological probes have emerged from these studies, few catalysts have been developed with pharmaceutical properties in mind. Herein we describe our efforts to identify new Mn(III)-porphyrin systems with enhanced membrane solubilizing properties. To this end seven new Mn(III)-tetracyclohexenylporphyin (TCHP) analogues 7, 10, 12, 15, 16a–c have been prepared in which the beta-fused cyclohexenyl rings provide a means to shield the charged metal center from the membrane during passive transport. Compounds 7, 15, and 16a–c have been shown to be orally active and potent analgesics in a model of carrageenan-induced thermal hyperalgesia. In addition oral administration of compound 7 (10–100 mg/kg, n = 5) has been shown to dose dependently reverse mechano-allodynia in the CCI model of chronic neuropathic pain.

Current image processing techniques capture large vessels reliably but often fail to preserve connectivity in bifurcations and small vessels. Imaging artifacts and noise can create gaps and discontinuity of intensity that hinders segmentation of vascular trees. However, topological analysis of vascular trees require proper connectivity without gaps, loops or dangling segments. Proper tree connectivity is also important for high quality rendering of surface meshes for scientific visualization or 3D printing. We present a fully automated vessel enhancement pipeline with automated parameter settings for vessel enhancement of tree-like structures from customary imaging sources, including 3D rotational angiography, magnetic resonance angiography, magnetic resonance venography, and computed tomography angiography. The output of the filter pipeline is a vessel-enhanced image which is ideal for generating anatomical consistent network representations of the cerebral angioarchitecture for further topological or statistical analysis. The filter pipeline combined with computational modeling can potentially improve computer-aided diagnosis of cerebrovascular diseases by delivering biometrics and anatomy of the vasculature. It may serve as the first step in fully automatic epidemiological analysis of large clinical datasets. The automatic analysis would enable rigorous statistical comparison of biometrics in subject-specific vascular trees. The robust and accurate image segmentation using a validated filter pipeline would also eliminate operator dependency that has been observed in manual segmentation. Moreover, manual segmentation is time prohibitive given that vascular trees have more than thousands of segments and bifurcations so that interactive segmentation consumes excessive human resources. Subject-specific trees are a first step toward patient-specific hemodynamic simulations for assessing treatment outcomes.

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