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
Increasing rates of addiction behavior have motivated mental health researchers and clinicians alike to understand antireward and recovery. This shift away from reward and commencement necessitates novel perspectives, paradigms, and hypotheses along with an expansion of the methods applied to investigate addiction. Here, we provide an example: A systems biology approach to investigate antireward that combines laser capture microdissection (LCM) and high-throughput microfluidic reverse transcription quantitative polymerase chain reactions (RT-qPCR). Gene expression network dynamics were measured and a key driver of neurovisceral dysregulation in alcohol and opioid withdrawal, neuroinflammation, was identified. This combination of technologies provides anatomic and phenotypic specificity at single-cell resolution with high-throughput sensitivity and specific gene expression measures yielding both hypothesis-generating datasets and mechanistic possibilities that generate opportunities for novel insights and treatments.
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Source |
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http://dx.doi.org/10.3791/64014 | DOI Listing |
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