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The dual-functional memantine nitrate MN-08 alleviates cerebral vasospasm and brain injury in experimental subarachnoid haemorrhage models.

ABSTRACT: BACKGROUND AND PURPOSE:Cerebral vasospasm and neuronal apoptosis after subarachnoid haemorrhage (SAH) is the major cause of morbidity and mortality in SAH patients. So far, single-target agents have not prevented its occurrence. Memantine, a non-competitive NMDA re3ceptor antagonist, is known to alleviate brain injury and vasospasm in experimental models of SAH. Impairment of NO availability also contributes to vasospasm. Recently, we designed and synthesized a memantine nitrate MN-08, which has potent dual functions: neuroprotection and vasodilation. Here, we have tested the therapeutic effects of MN-08 in animal models of SAH. EXPERIMENTAL APPROACH:Binding to NMDA receptors (expressed in HEK293 cells), NO release and vasodilator effects of MN-08 were assessed in vitro. Therapeutic effects of MN-08 were investigated in vivo, using rat and rabbit SAH models. KEY RESULTS:MN-08 bound to the NMDA receptor, slowly releasing NO in vitro and in vivo. Consequently, MN-08 relaxed the pre-contracted middle cerebral artery ex vivo and increased blood flow velocity in small vessels of the mouse cerebral cortex. It did not, however, lower systemic blood pressure. In an endovascular perforation rat model of SAH, MN-08 improved the neurological scores and ameliorated cerebral vasospasm. Moreover, MN-08 also alleviated cerebral vasospasm in a cisterna magna single-injection model in rabbits. MN-08 attenuated neural cell apoptosis in both rat and rabbit models of SAH. Importantly, the therapeutic benefit of MN-08 was greater than that of memantine. CONCLUSION AND IMPLICATIONS:MN-08 has neuroprotective potential and can ameliorate vasospasm in experimental SAH models.

SUBMITTER: Luo F

PROVIDER: S-EPMC6692588 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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The dual-functional memantine nitrate MN-08 alleviates cerebral vasospasm and brain injury in experimental subarachnoid haemorrhage models.

Luo Fangcheng F Wu Liangmiao L Zhang Zhixiang Z Zhu Zeyu Z Liu Zheng Z Guo Baojian B Li Ning N Ju Jun J Zhou Qiang Q Li Shupeng S Yang Xifei X Mak Shinghung S Han Yifan Y Sun Yewei Y Wang Yuqiang Y Zhang Gaoxiao G Zhang Zaijun Z

British journal of pharmacology 20190731 17

<h4>Background and purpose</h4>Cerebral vasospasm and neuronal apoptosis after subarachnoid haemorrhage (SAH) is the major cause of morbidity and mortality in SAH patients. So far, single-target agents have not prevented its occurrence. Memantine, a non-competitive NMDA re3ceptor antagonist, is known to alleviate brain injury and vasospasm in experimental models of SAH. Impairment of NO availability also contributes to vasospasm. Recently, we designed and synthesized a memantine nitrate MN-08, w ...[more]

PMID: 31180578

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Project description:BackgroundCerebral vasospasm (CV) is a feared complication which occurs after 20-40% of subarachnoid haemorrhage (SAH). It is standard practice to admit patients with SAH to intensive care for an extended period of resource-intensive monitoring. We used machine learning to predict CV requiring verapamil (CVRV) in the largest and only multi-center study to date.MethodsPatients with SAH admitted to UCLA from 2013 to 2022 and a validation cohort from VUMC from 2018 to 2023 were included. For each patient, 172 unique intensive care unit (ICU) variables were extracted through the primary endpoint, namely first verapamil administration or no verapamil. At each institution, a light gradient boosting machine (LightGBM) was trained using five-fold cross validation to predict the primary endpoint at various hospitalization timepoints.FindingsA total of 1750 patients were included from UCLA, 125 receiving verapamil. LightGBM achieved an area under the ROC (AUC) of 0.88 > 1 week in advance and ruled out 8% of non-verapamil patients with zero false negatives. Our models predicted "no CVRV" vs "CVRV within three days" vs "CVRV after three days" with AUCs = 0.88, 0.83, and 0.88, respectively. From VUMC, 1654 patients were included, 75 receiving verapamil. VUMC predictions averaged within 0.01 AUC points of UCLA predictions.InterpretationWe present an accurate and early predictor of CVRV using machine learning with multi-center validation. This represents a significant step towards optimized clinical management and resource allocation in patients with SAH.FundingRobert E. Freundlich is supported by National Center for Advancing Translational Sciences federal grant UL1TR002243 and National Heart, Lung, and Blood Institute federal grant K23HL148640; these funders did not play any role in this study. The National Institutes of Health supports Vanderbilt University Medical Center which indirectly supported these research efforts. Neither this study nor any other authors personally received financial support for the research presented in this manuscript. No support from pharmaceutical companies was received.

Project description:The diagnosis of cerebral vasospasm after Subarachnoid-Hemorrhage is currently very difficult, additional tools such as blood biomarkers are necessary. We tested the ability of gene expression profiles of blood cells to predict vasospasm. 32 patients suffering subarachnoid-hemorrhage were included in this prospective monocentre study. They were grouped according to have a complicated cerebral vasospasm (Vasospasm) or not (Control) and Paired according to age (+/- 10 years), sex, Fisher grade (+/- 1), location, smoking (at least 3 first parameters). Gene expression profiles of blood cells were determined using 25,000~gene microarray. Blood sample: 2.5 mL harvested in PAXgene® Blood RNA tubes (PreAnalytix) RNA extraction: PAXgene® Blood RNA kit (Qiagen). We used a Universel Reference RNA (Stratagene). RNA amplification and labelling: kit Amino Allyl MessageAmp II (Ambion). We hybridized 4 microarrays per patient using pangenomic microarrays from the "Réseau National des Génopôles" (Illkirch, France). 2 slides were hybridized with reference RNA labelled Cy3 and patient RNA labelled Cy5, and 2 slides were hybridized with reference RNA labelled Cy5 and patient RNA labelled Cy3. Hybridation : Agilent protocol with few modifications : 750 ng of each labelled RNA were hubriddized at 60°C during 17 hours in an Aglient hybridization oven. After washings, Slides were scanned with a GenePix 4000B scanner (Molecular Devices). Image intensity data were extracted with GenePix Pro 6.0 analysis software. Quantification of Cy3 and Cy5 and selection of good spots were performed using the MAIA software (Novikov E and Barillot E. Software package for automatic microarray image analysis (MAIA). The ACUITY software was then used to normalize log ratios Cy3/Cy5 with Lowess non linear normalization, to filter out genes not present in at least 3 slides out of 4, to evaluate the reproducibility of the 4 microarrays of each patient (hierarchical clustering, Self Organizing Maps). Statistical analyses to insure reproducibility was performed using Excel (correlation coefficients, ANOVA). Only slides that passed all reprocubility tests were validated.

Dataset Information

The dual-functional memantine nitrate MN-08 alleviates cerebral vasospasm and brain injury in experimental subarachnoid haemorrhage models.

Publications

The dual-functional memantine nitrate MN-08 alleviates cerebral vasospasm and brain injury in experimental subarachnoid haemorrhage models.

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