Recent trauma and acute infection as risk factors for childhood arterial ischemic stroke.

ObjectiveTrauma and acute infection have been associated with stroke in adults, and are prevalent exposures in children. We hypothesized that these environmental factors are independently associated with childhood arterial ischemic stroke (AIS).MethodsIn a case-control study nested within a cohort of 2.5 million children (≤19 years old) enrolled in an integrated health care plan (1993-2007), childhood AIS cases (n = 126) were identified from electronic records and confirmed through chart review. Age- and facility-matched controls (n = 378) were randomly selected from the cohort. Exposures were determined from review of medical records prior to the stroke diagnosis, or the same date for the paired controls; time windows were defined a priori.ResultsA medical encounter for head or neck trauma within the prior 12 weeks was an independent risk factor for childhood AIS (odds ratio [OR], 7.5; 95% confidence interval [CI], 2.9-19.3), present in 12% of cases (1.6% of controls). Median time from trauma to stroke was 0.5 days (interquartile range, 0-2 days); post hoc redefinition of trauma exposure (prior 1 week) was more strongly associated with AIS: OR, 39; 95% CI, 5.1-298. A medical encounter for a minor acute infection (prior 4 weeks) was also an independent risk factor (OR, 4.6; 95% CI, 2.6-8.2), present in 33% of cases (13% of controls). No single infection type predominated. Only 2 cases had exposure to trauma and infection.InterpretationTrauma and acute infection are common independent risk factors for childhood AIS, and may be targets for stroke prevention strategies

Abnormal lateralization of functional connectivity between language and default mode regions in autism

Background: Lateralization of brain structure and function occurs in typical development, and abnormal lateralization is present in various neuropsychiatric disorders. Autism is characterized by a lack of left lateralization in structure and function of regions involved in language, such as Broca and Wernicke areas. Methods: Using functional connectivity magnetic resonance imaging from a large publicly available sample (n = 964), we tested whether abnormal functional lateralization in autism exists preferentially in language regions or in a more diffuse pattern across networks of lateralized brain regions. Results: The autism group exhibited significantly reduced left lateralization in a few connections involving language regions and regions from the default mode network, but results were not significant throughout left- and right-lateralized networks. There is a trend that suggests the lack of left lateralization in a connection involving Wernicke area and the posterior cingulate cortex associates with more severe autism. Conclusions: Abnormal language lateralization in autism may be due to abnormal language development rather than to a deficit in hemispheric specialization of the entire brain

Multisite functional connectivity MRI classification of autism: ABIDE results

Background:: Systematic differences in functional connectivity MRI metrics have been consistently observed in autism, with predominantly decreased cortico-cortical connectivity. Previous attempts at single subject classification in high-functioning autism using whole brain point-to-point functional connectivity have yielded about 80% accurate classification of autism vs. control subjects across a wide age range. We attempted to replicate the method and results using the Autism Brain Imaging Data Exchange (ABIDE) including resting state fMRI data obtained from 964 subjects and 16 separate international sites. Methods:: For each of 964 subjects, we obtained pairwise functional connectivity measurements from a lattice of 7266 regions of interest covering the gray matter (26.4 million “connections”) after preprocessing that included motion and slice timing correction, coregistration to an anatomic image, normalization to standard space, and voxelwise removal by regression of motion parameters, soft tissue, CSF, and white matter signals. Connections were grouped into multiple bins, and a leave-one-out classifier was evaluated on connections comprising each set of bins. Age, age-squared, gender, handedness, and site were included as covariates for the classifier. Results:: Classification accuracy significantly outperformed chance but was much lower for multisite prediction than for previous single site results. As high as 60% accuracy was obtained for whole brain classification, with the best accuracy from connections involving regions of the default mode network, parahippocampaland fusiform gyri, insula, Wernicke Area, and intraparietal sulcus. The classifier score was related to symptom severity, social function, daily living skills, and verbal IQ. Classification accuracy was significantly higher for sites with longer BOLD imaging times. Conclusions:: Multisite functional connectivity classification of autism outperformed chance using a simple leave-one-out classifier, but exhibited poorer accuracy than for single site results. Attempts to use multisite classifiers will likely require improved classification algorithms, longer BOLD imaging times, and standardized acquisition parameters for possible future clinical utility

scMRI Reveals Large-Scale Brain Network Abnormalities in Autism

Autism is a complex neurological condition characterized by childhood onset of dysfunction in multiple cognitive domains including socio-emotional function, speech and language, and processing of internally versus externally directed stimuli. Although gross brain anatomic differences in autism are well established, recent studies investigating regional differences in brain structure and function have yielded divergent and seemingly contradictory results. How regional abnormalities relate to the autistic phenotype remains unclear. We hypothesized that autism exhibits distinct perturbations in network-level brain architecture, and that cognitive dysfunction may be reflected by abnormal network structure. Network-level anatomic abnormalities in autism have not been previously described. We used structural covariance MRI to investigate network-level differences in gray matter structure within two large-scale networks strongly implicated in autism, the salience network and the default mode network, in autistic subjects and age-, gender-, and IQ-matched controls. We report specific perturbations in brain network architecture in the salience and default-mode networks consistent with clinical manifestations of autism. Extent and distribution of the salience network, involved in social-emotional regulation of environmental stimuli, is restricted in autism. In contrast, posterior elements of the default mode network have increased spatial distribution, suggesting a ‘posteriorization’ of this network. These findings are consistent with a network-based model of autism, and suggest a unifying interpretation of previous work. Moreover, we provide evidence of specific abnormalities in brain network architecture underlying autism that are quantifiable using standard clinical MRI

Tamm Review: Management of mixed-severity fire regime forests in Oregon, Washington, and Northern California

Increasingly, objectives for forests with moderate- or mixed-severity fire regimes are to restore successionally diverse landscapes that are resistant and resilient to current and future stressors. Maintaining native species and characteristic processes requires this successional diversity, but methods to achieve it are poorly explained in the literature. In the Inland Pacific US, large, old, early seral trees were a key historical feature of many young and old forest successional patches, especially where fires frequently occurred. Large, old trees are naturally fire-tolerant, but today are often threatened by dense understory cohorts that create fuel ladders that alter likely post-fire successional pathways. Reducing these understories can contribute to resistance by creating conditions where canopy trees will survive disturbances and climatic stressors; these survivors are important seed sources, soil protectors, and critical habitat elements. Historical timber harvesting has skewed tree size and age class distributions, created hard edges, and altered native patch sizes. Manipulating these altered forests to promote development of larger patches of older, larger, and more widely-spaced trees with diverse understories will increase landscape resistance to severe fires, and enhance wildlife habitat for underrepresented conditions. Closed-canopy, multi-layered patches that develop in hot, dry summer environments are vulnerable to droughts, and they increase landscape vulnerability to insect outbreaks and severe wildfires. These same patches provide habitat for species such as the northern spotted owl, which has benefited from increased habitat area. Regional and local planning will be critical for gauging risks, evaluating trade-offs, and restoring dynamics that can support these and other species. The goal will be to manage for heterogeneous landscapes that include variably-sized patches of (1) young, middle-aged, and old, closed canopy forests growing in upper montane, northerly aspect, and valley bottom settings, (2) a similar diversity of open-canopy, fire-tolerant patches growing on ridgetops, southerly aspects, and lower montane settings, and (3) significant montane chaparral and grassland areas. Tools to achieve this goal include managed wildfire, prescribed burning, and variable density thinning at small to large scales. Specifics on ‘‘how much and where?” will vary according to physiographic, topographic and historical templates, and regulatory requirements, and be determined by means of a socio-ecological process

Tamm Review: Management of mixed-severity fire regime forests in Oregon, Washington, and Northern California

Increasingly, objectives for forests with moderate- or mixed-severity fire regimes are to restore successionally diverse landscapes that are resistant and resilient to current and future stressors. Maintaining native species and characteristic processes requires this successional diversity, but methods to achieve it are poorly explained in the literature. In the Inland Pacific US, large, old, early seral trees were a key historical feature of many young and old forest successional patches, especially where fires frequently occurred. Large, old trees are naturally fire-tolerant, but today are often threatened by dense understory cohorts that create fuel ladders that alter likely post-fire successional pathways. Reducing these understories can contribute to resistance by creating conditions where canopy trees will survive disturbances and climatic stressors; these survivors are important seed sources, soil protectors, and critical habitat elements. Historical timber harvesting has skewed tree size and age class distributions, created hard edges, and altered native patch sizes. Manipulating these altered forests to promote development of larger patches of older, larger, and more widely-spaced trees with diverse understories will increase landscape resistance to severe fires, and enhance wildlife habitat for underrepresented conditions. Closed-canopy, multi-layered patches that develop in hot, dry summer environments are vulnerable to droughts, and they increase landscape vulnerability to insect outbreaks and severe wildfires. These same patches provide habitat for species such as the northern spotted owl, which has benefited from increased habitat area. Regional and local planning will be critical for gauging risks, evaluating trade-offs, and restoring dynamics that can support these and other species. The goal will be to manage for heterogeneous landscapes that include variably-sized patches of (1) young, middle-aged, and old, closed canopy forests growing in upper montane, northerly aspect, and valley bottom settings, (2) a similar diversity of open-canopy, fire-tolerant patches growing on ridgetops, southerly aspects, and lower montane settings, and (3) significant montane chaparral and grassland areas. Tools to achieve this goal include managed wildfire, prescribed burning, and variable density thinning at small to large scales. Specifics on ‘‘how much and where?” will vary according to physiographic, topographic and historical templates, and regulatory requirements, and be determined by means of a socio-ecological process

Atypical development of white matter microstructure of the corpus callosum in males with autism: a longitudinal investigation

Background: The corpus callosum is the largest white matter structure in the brain, and it is the most consistently reported to be atypical in diffusion tensor imaging studies of autism spectrum disorder. In individuals with typical development, the corpus callosum is known to undergo a protracted development from childhood through young adulthood. However, no study has longitudinally examined the developmental trajectory of corpus callosum in autism past early childhood. Methods: The present study used a cohort sequential design over 9 years to examine age-related changes of the corpus callosum in 100 males with autism and 56 age-matched males with typical development from early childhood (when autism can first be reliably diagnosed) to mid-adulthood (after development of the corpus callosum has been completed) (3 to 41 years of age). Results: The group with autism demonstrated a different developmental trajectory of white matter microstructure in the anterior corpus callosum’s (genu and body) fractional anisotropy, which suggests atypical brain maturation in these regions in autism. When analyses were broken down by age group, atypical developmental trajectories were present only in the youngest participants (10 years of age and younger). Significant main effects for group were found in terms of decreased fractional anisotropy across all three subregions of the corpus callosum (genu, body, and splenium) and increased mean diffusivity, radial diffusivity, and axial diffusivity in the posterior corpus callosum. Conclusions: These longitudinal results suggest atypical early childhood development of the corpus callosum microstructure in autism that transitions into sustained group differences in adolescence and adulthood. This pattern of results provides longitudinal evidence consistent with a growing number of published studies and hypotheses regarding abnormal brain connectivity across the life span in autism. Electronic supplementary material The online version of this article (doi:10.1186/s13229-015-0001-8) contains supplementary material, which is available to authorized users

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Polarization and Spectral Energy Distribution in OJ 287 during the 2016/17 Outbursts

We report optical photometric and polarimetric observations of the blazar OJ 287 gathered during 2016/17. The high level of activity, noticed after the General Relativity Centenary flare, is argued to be part of the follow-up flares that exhibited high levels of polarization and originated in the primary black hole jet. We propose that the follow-up flares were induced as a result of accretion disk perturbations, traveling from the site of impact towards the primary SMBH. The timings inferred from our observations allowed us to estimate the propagation speed of these perturbations. Additionally, we make predictions for the future brightness of OJ 287.</p

An evaluation of the left-brain vs. right-brain hypothesis with resting state functional connectivity magnetic resonance imaging.

Lateralized brain regions subserve functions such as language and visuospatial processing. It has been conjectured that individuals may be left-brain dominant or right-brain dominant based on personality and cognitive style, but neuroimaging data has not provided clear evidence whether such phenotypic differences in the strength of left-dominant or right-dominant networks exist. We evaluated whether strongly lateralized connections covaried within the same individuals. Data were analyzed from publicly available resting state scans for 1011 individuals between the ages of 7 and 29. For each subject, functional lateralization was measured for each pair of 7266 regions covering the gray matter at 5-mm resolution as a difference in correlation before and after inverting images across the midsagittal plane. The difference in gray matter density between homotopic coordinates was used as a regressor to reduce the effect of structural asymmetries on functional lateralization. Nine left- and 11 right-lateralized hubs were identified as peaks in the degree map from the graph of significantly lateralized connections. The left-lateralized hubs included regions from the default mode network (medial prefrontal cortex, posterior cingulate cortex, and temporoparietal junction) and language regions (e.g., Broca Area and Wernicke Area), whereas the right-lateralized hubs included regions from the attention control network (e.g., lateral intraparietal sulcus, anterior insula, area MT, and frontal eye fields). Left- and right-lateralized hubs formed two separable networks of mutually lateralized regions. Connections involving only left- or only right-lateralized hubs showed positive correlation across subjects, but only for connections sharing a node. Lateralization of brain connections appears to be a local rather than global property of brain networks, and our data are not consistent with a whole-brain phenotype of greater "left-brained" or greater "right-brained" network strength across individuals. Small increases in lateralization with age were seen, but no differences in gender were observed