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Pitfalls associated with the use of molecular diagnostic panels in the diagnosis of cryptococcal meningitis

Abstract We report the case of a kidney transplantation patient on chronic immunosuppressive therapy presenting with subacute meningitis. The final diagnosis of cryptococcal meningitis was delayed due to 2 false-negative cryptococcal results on a molecular diagnostic panel. Caution with such platforms in suspected cryptococcal meningitis is needed.</jats:p

Epidemiology, clinical characteristics, and antimicrobial susceptibility profiles of human clinical isolates of Staphylococcus intermedius group

ABSTRACT The veterinary pathogens in the Staphylococcus intermedius group (SIG) are increasingly recognized as causes of human infection. Shared features between SIG and Staphylococcus aureus may result in the misidentification of SIG in human clinical cultures. This study examined the clinical and microbiological characteristics of isolates recovered at a tertiary-care academic medical center. From 2013 to 2015, 81 SIG isolates were recovered from 62 patients. Patients were commonly ≥50 years old, diabetic, and/or immunocompromised. Documentation of dog exposure in the electronic medical record was not common. Of the 81 SIG isolates, common sites of isolation included 37 (46%) isolates from wound cultures and 17 (21%) isolates from respiratory specimens. Although less common, 10 (12%) bloodstream infections were documented in 7 unique patients. The majority of SIG (65%) isolates were obtained from polymicrobial cultures. In comparison to S. aureus isolates from the same time period, significant differences were noted in proportion of SIG isolates that were susceptible to doxycycline (74% versus 97%, respectively; P &lt; 0.001), trimethoprim-sulfamethoxazole (65% versus 97%, respectively; P &lt; 0.001), and ciprofloxacin (78% versus 59%, respectively; P &lt; 0.01). Methicillin resistance (MR) was detected in 12 (15%) of 81 SIG isolates. All MR isolates detected by an oxacillin disk diffusion test would have been misclassified as methicillin susceptible using a cefoxitin disk diffusion test. Thus, SIG is recovered from human clinical specimens, and distinction of SIG from S. aureus is critical for the accurate characterization of MR status in these isolates. </jats:p

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

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

Homing Behavior in Response to Displacement and Orientation of the Northern Diamondback Terrapin (Malaclemys terrapin terrapin) in Barnegat Bay, New Jersey

Increasing urbanization of the Barnegat Bayestuary in New Jersey has subjected northern diamondback terrapins to substantial habitat loss. Understanding whether terrapins have homing behavior, and determining the types of orientation cues they use to aid in this behavior, is important for conservation management. To test their homing behavior, nine non-gravid female terrapins were outfitted with biotelemetry tracking devices and data loggers and were displaced 4 km north and/or south. Eight of nine terrapins successfully returned home; the one terrapin that did not return home was inadvertently captured in a crab pot. Urbanization and shoreline development of the north displacement location may be causing terrapins to make quicker movements home compared to the ‘natural’ south displacement location. A terrestrial arena that blocked terrapins from perceiving visual landmarks was used to test orientation in both male and female terrapins that had been captured to the south or east of the testing site. Only male terrapins captured from the east exhibited apparent homeward orientation, suggesting that terrapins orient toward water rather than home. Terrapins from the south tested under overcast skies and during the afternoon, and females captured from the south, tested separately, had easterly orientation, suggesting there was orientation toward open water as well within these groups. While displaced terrapins were able to return home, terrapins tested in the arena appeared to orient toward water, suggesting that the orientation cues used in homing may not be available to the terrapins on land, within the arena. Understanding both homing behavior and orientation will give managers insight into how terrapin home ranges might be protected. Since terrapins are able to return home after displacement, protection measures will be needed for all potential home ranges of the terrapins and relocation efforts may require the displacement of terrapins to more distant areas

Multivariate characterization of white matter heterogeneity in autism spectrum disorder

The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders

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