Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Ataxia is a neurodegenerative disease resulting from brainstem, cerebellar, and/or spinocerebellar tracts impairments. Symptoms onset could vary widely from childhood to late-adulthood. Autosomal cerebellar ataxias are considered as one of the most complex group in neurogenetics. In addition to their genetic heterogeneity, there is an important phenotypic variability in the expression of cerebellar impairment, complicating the genetic mutation research. A pattern recognition approach using brain MRI measures of atrophy, hyperintensities and iron-induced hypointensity of the dentate nuclei, could be therefore helpful in guiding genetic research. This review will discuss a pattern recognition approach that, associated with the age at disease onset, and clinical manifestations, may help neuroradiologists differentiate the most frequent profiles of ataxia.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.neurad.2018.05.005 | DOI Listing |
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