Frontiers in stroke最新文献

{"title":"Trans-Spinal Direct Current Stimulation in Spasticity: A Literature Mini-Review","authors":"M. A. Estudillo-Guerra, I. Mesia-Toledo, Noga Rogel, N. Yaghoubi, Z. Ahmed, R. Black-Schaffer, L. Morales-Quezada","doi":"10.3389/fstro.2022.921450","DOIUrl":"https://doi.org/10.3389/fstro.2022.921450","url":null,"abstract":"Spasticity is common after a stroke and has a negative impact on functional and quality-of-life measures. There is an unmet medical need to provide safe and effective treatment using non-pharmacological approaches. Trans-spinal direct current stimulation (tsDCS) is an emerging modality for non-invasive neuromodulation that induces reduction of spinal excitability leading to a decrease in spasticity. We describe current treatment options for spasticity, including a literature review about the use of tsDCS in patients with spasticity. We found four clinical studies that used tsDCS to treat spasticity for different neurological conditions including hereditary spastic paraplegia, upper extremity spasticity following stroke, multiple sclerosis, and incomplete chronic spinal cord injury. Spasticity was the primary outcome in three of the studies and a secondary outcome in the final study. The three studies that addressed spasticity as the primary outcome found that active tsDCS decreased spasticity compared to sham. These studies suggest that tsDCS can modulate spinal motor and sensory spinal pathways through the use of specific electrode montages and stimulation parameters. This therapy can improve motor functions and may represent a viable treatment option for spasticity.","PeriodicalId":73108,"journal":{"name":"Frontiers in stroke","volume":"195 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79582801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The profile of inflammatory extracellular vesicles in intracerebral hemorrhage patients.","authors":"Harshal Sawant, Trevor Bihl, Doan Nguyen, Ifeanyi Iwuchukwu, Ji Bihl","doi":"10.3389/fstro.2022.988081","DOIUrl":"10.3389/fstro.2022.988081","url":null,"abstract":"<p><strong>Background: </strong>Intracerebral hemorrhage (ICH) is one of the leading life-threatening types of strokes with high mortality. A prominent feature of ICH is neuroinflammation involving leukocytes, such as neutrophils and macrophages. Large extracellular vesicles (lEV) and small extracellular vesicles (sEV) released from various cells are used as biomarkers for different diseases. Here, we aimed to determine the concentration/population of lEV and sEV from different leukocytes in ICH patients and analyze the correlation of these lEV/sEV with clinical parameters.</p><p><strong>Methods: </strong>lEV and sEV were isolated from the plasma of ICH patients (n = 39) by using the serial centrifuge methods. Nanoparticle tracking analysis (NTA, NS300) was used to determine the type and concentration of different leukocytes-released lEV/sEV. Specific antibodies, CD66b, P2RY12, and CD80 were used for different leukocyte types.</p><p><strong>Results: </strong>A predictive relationship between both hospital length of stay (<i>R</i> ² = 0.83) and Intensive care units (ICU) length of stay (<i>R</i> ² = 0.88) was found with lEV and sEV and patient data [including low-density lipoprotein (LDL), ICH volume, etc.]. Further predictive-multiple linear regression relationship was seen between lEV and sEV concentrations and MRSV3 (Modified Rankin Scale at 90 days) (<i>R</i> ² = 0.46) and MRSV5 (modified Rankin Scale at 180 days) (<i>R</i> ² = 0.51). Additionally, a slight, but statistically significant (<i>p</i> = 0.0151), multiple linear regression relationship was seen between lEV and sEV concentrations and ICU length of stay (<i>R</i> ² = 0.26).</p><p><strong>Conclusion: </strong>This study found predictive relationships between patient outcomes and lEV and sEV. When combined with generally collected patient data (LDL, etc.), measurements of lEV and sEV are strongly predictive of overall patient outcome. Further, larger studies should investigate these effects.</p>","PeriodicalId":73108,"journal":{"name":"Frontiers in stroke","volume":"320 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11932702/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77784578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gut microbial dysbiosis correlates with stroke severity markers in aged rats.","authors":"Tyler C Hammond, Sarah Messmer, Jacqueline A Frank, Doug Lukins, Rita Colwell, Ai-Ling Lin, Keith R Pennypacker","doi":"10.3389/fstro.2022.1026066","DOIUrl":"10.3389/fstro.2022.1026066","url":null,"abstract":"<p><strong>Background: </strong>An imbalanced gut microbial community, or dysbiosis, has been shown to occur following stroke. It is possible that this dysbiosis negatively impacts stroke recovery and rehabilitation. Species level resolution measurements of the gut microbiome following stroke are needed to develop and test precision interventions such as probiotic or fecal microbiota transplant therapies that target the gut microbiome. Previous studies have used 16S rRNA amplicon sequencing in young male mice to obtain broad profiling of the gut microbiome at the genus level following stroke, but further investigations will be needed with whole genome shotgun sequencing in aged rats of both sexes to obtain species level resolution in a model which will better translate to the demographics of human stroke patients.</p><p><strong>Methods: </strong>Thirty-nine aged male and female rats underwent middle cerebral artery occlusion. Fecal samples were collected before stroke and 3 days post stroke to measure gut microbiome. Machine learning was used to identify the top ranked bacteria which were changed following stroke. MRI imaging was used to obtain infarct and edema size and cerebral blood flow (CBF). ELISA was used to obtain inflammatory markers.</p><p><strong>Results: </strong>Dysbiosis was demonstrated by an increase in pathogenic bacteria such as <i>Butyricimonas virosa</i> (15.52 fold change, <i>p</i> < 0.0001), <i>Bacteroides vulgatus</i> (7.36 fold change, <i>p</i> < 0.0001), and <i>Escherichia coli</i> (47.67 fold change, <i>p</i> < 0.0001). These bacteria were positively associated with infarct and edema size and with the inflammatory markers Ccl19, Ccl24, IL17a, IL3, and complement C5; they were negatively correlated with CBF. Conversely, beneficial bacteria such as <i>Ruminococcus flavefaciens</i> (0.14 fold change, <i>p</i> < 0.0001), <i>Akkermansia muciniphila</i> (0.78 fold change, <i>p</i> < 0.0001), and <i>Lactobacillus murinus</i> (0.40 fold change, <i>p</i> < 0.0001) were decreased following stroke and associated with all the previous parameters in the opposite direction of the pathogenic species. There were not significant microbiome differences between the sexes.</p><p><strong>Conclusion: </strong>The species level resolution measurements found here can be used as a foundation to develop and test precision interventions targeting the gut microbiome following stroke. Probiotics that include <i>Ruminococcus flavefaciens, Akkermansia muciniphila, and Lactobacillus murinus</i> should be developed to target the deficit following stroke to measure the impact on stroke severity.</p>","PeriodicalId":73108,"journal":{"name":"Frontiers in stroke","volume":"1 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10800047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}