Peer influence and social contagion are key denominators in the adoption and participation of information spreading, such as news propagation, word-of-mouth or viral marketing. In this study, we argue that it is biase...
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Recent years have witnessed an explosive growth of mobile devices. Mobile devices are permeating every aspect of our daily lives. With the increasing usage of mobile devices and intelligent applications, there is a so...
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BACKGROUND:Structural brain differences in the thalamus and the cortex have been widely reported in schizophrenia (SCZ) relative to neurotypical controls (NC). Most prior studies examined the thalamus as a whole, sing...
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BACKGROUND:Structural brain differences in the thalamus and the cortex have been widely reported in schizophrenia (SCZ) relative to neurotypical controls (NC). Most prior studies examined the thalamus as a whole, single region-of-interest. Additionally, findings in individuals at familial high-risk for schizophrenia (FHR) remain inconclusive. Here, we investigated whether local and network-wide thalamic-related structural alterations vary as a function of familial risk for schizophrenia.
METHODS:Structural MRI scans were obtained from 5,197 participants (3,409 NC, 257 FHR, 1,531 SCZ) across 32 cross-sectional samples within the ENIGMA Consortium. Random-effects meta-analyses, and network analyses were conducted on (i) local thalamic alterations (volume estimates of seven thalamic subdivisions), and (ii) network-wide thalamic alterations (thickness and surface-related thalamo-cortical/cortico-cortical co-variation patterns) across groups (NC, FHR, SCZ).
RESULTS:Individuals with SCZ showed significantly lower gray matter volume estimates in the anterior, pulvinar, medial, posterior, and ventral thalamic subdivisions compared to NC (q<0.05). FHR did not differ from NC. At the network-wide level, thalamo-cortical co-variations discriminated FHR from NC (q<0.05), with FHR showing intermediate co-variation between SCZ and NC. Cortico-cortical co-variation patterns revealed that SCZ and FHR shared similarly disconnected clustering configurations, distinct from NC (q<0.05).
CONCLUSIONS:Results revealed lower thalamic volume estimates in SCZ but not in FHR, hence yielding no evidence of a familial risk trait, whereas thalamo-cortical and cortico-cortical co-variation estimates were associated with familial risk for SCZ These findings suggest that, once the thalamus is parsed into subdivisions, network-wide thalamo-cortical features may identify trait-dependent, neurobiological correlates of genetic risk for SCZ.
We report the first > 99% confidence detection of X-ray polarization in BL Lacertae. During a recent X-ray/γ-ray outburst, a 287 ksec observation (2022 November 27-30) was taken using the Imaging X-ray Polarimetry...
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Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is prevalent worldwide and is caused by an ...
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Accumulating evidence indicates that biological aging can be accelerated by environmental exposures, collectively called the ‘exposome’. The skin, as the largest and most exposed organ, can be viewed as a ‘window’...
Randomized experiments have been used to assist decision-making in many areas. They help people select the optimal treatment for the test population with certain statistical guarantee. However, subjects can show signi...
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The magnetic field conditions in astrophysical relativistic jets can be probed by multiwavelength polarimetry, which has been recently extended to X-rays. For example, one can track how the magnetic field changes in t...
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Urban income segregation is a widespread phenomenon that challenges societies across the globe. Classical studies on segregation have largely focused on the geographic distribution of residential neighborhoods rather ...
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We analyze five big data sets from a variety of online social networking (OSN) systems and find that the growth dynamics of meme popularity exhibit characteristically different behaviors. For example, there is linear ...
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