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Recent studies have shown that white–gray contrast (WGC) of either cortical or subcortical gray matter provides for accurate predictions of age in typically developing (TD) children, and that, at least for the cortex, it changes differently with age in subjects with autism spectrum disorder (ASD) compared to their TD peers. Our previous study showed different patterns of contrast change between ASD and TD in sensorimotor and association cortices. While that study was confined to the cortex, we hypothesized that subcortical structures, particularly the thalamus, were involved in the observed cortical dichotomy between lower and higher processing. The current paper investigates that hypothesis using the WGC measures from the thalamus in addition to those from the cortex. We compared age‐related WGC changes in the thalamus to those in the cortex. To capture the simultaneity of this change across the two structures, we devised a metric capturing the co‐development of the thalamus and cortex (CoDevTC), proportional to the magnitude of cortical and thalamic age‐related WGC change. We calculated this metric for each of the subjects in a large homogeneous sample taken from the Autism Brain Imaging Data Exchange (ABIDE) (N = 434). We used structural MRI data from the largest high‐quality cross‐sectional sample (NYU) as well as two other large high‐quality sites, GU and OHSU, all three using Siemens 3T scanners. We observed that the co‐development features in ASD and TD exhibit contrasting patterns; specifically, some higher‐order thalamic nuclei, such as the lateral dorsal nucleus, exhibited reduction in codevelopment with most of the cortex in ASD compared to TD. Moreover, this difference in the CoDevTC pattern correlates with a number of behavioral measures across multiple cognitive and physiological domains. The results support previous notions of altered connectivity in autism, but add more specific evidence about the heterogeneity in thalamocortical development that elucidates the mechanisms underlying the clinical features of ASD. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) has been used to study the developing brain in early childhood, infants and in utero studies. In infants, number of used diffusion encoding directions has traditionally been smaller in earlier studies down to the minimum of 6 orthogonal directions. Whereas the more recent studies often involve more directions, number of used directions remain an issue when acquisition time is optimized without compromising on data quality and in retrospective studies. Variability in the number of used directions may introduce bias and uncertainties to the DTI scalar estimates that affect cross‐sectional and longitudinal study of the brain. We analysed DTI images of 133 neonates, each data having 54 directions after quality control, to evaluate the effect of number of diffusion weighting directions from 6 to 54 with interval of 6 to the DTI scalars with Tract‐Based Spatial Statistics (TBSS) analysis. The TBSS analysis was applied to DTI scalar maps, and the mean region of interest (ROI) values were extracted using JHU atlas. We found significant bias in ROI mean values when only 6 directions were used (positive in fractional anisotropy [FA] and negative in fractional anisotropy [MD], axial diffusivity [AD] and fractional anisotropy [RD]), while when using 24 directions and above, the difference to scalar values calculated from 54 direction DTI was negligible. In repeated measures voxel‐wise analysis, notable differences to 54 direction DTI were observed with 6, 12 and 18 directions. DTI measurements from data with at least 24 directions may be used in comparisons with DTI measurements from data with higher numbers of directions. [ABSTRACT FROM AUTHOR]

Blood‐flow artifacts present a serious challenge for most, if not all, volumetric analytical approaches. We utilize T1‐weighted data with prominent blood‐flow artifacts from the Autism Brain Imaging Data Exchange (ABIDE) multisite agglomerative dataset to assess the impact that such blood‐flow artifacts have on registration of T1‐weighted data to a template. We use a heuristic approach to identify the blood‐flow artifacts in these data; we use the resulting blood masks to turn the underlying voxels to the intensity of the cerebro‐spinal fluid, thus mimicking the effect of blood suppression. We then register both the original data and the deblooded data to a common T1‐weighted template, and compare the quality of those registrations to the template in terms of similarity to the template. The registrations to the template based on the deblooded data yield significantly higher similarity values compared with those based on the original data. Additionally, we measure the nonlinear deformations needed to transform the data from the position achieved by registering the original data to the template to the position achieved by registering the deblooded data to the template. The results indicate that blood‐flow artifacts may seriously impact data processing that depends on registration to a template, that is, most all data processing. [ABSTRACT FROM AUTHOR]

Optimization of flow cytometry assays for extracellular vesicles (EVs) often fail to include appropriate reagent titrations – the most critically antibody titration is either not performed or is incomplete. Using nonoptimal antibody concentration is one of the main sources of error leading to a lack of reproducible data. Antibody titration for the analysis of antigens on the surface of EVs is challenging for a variety of technical reasons. Using platelets as surrogates for cells and platelet‐derived particles as surrogates for EV populations, we demonstrate our process for antibody titration, highlighting some of the key analysis parameters that may confound and surprise new researchers moving into the field of EV research. Additional care must be exercised to ensure instrument and reagent controls are utilized appropriately. Complete graphical analysis of positive and negative signal intensities, concentration, and separation or stain index data is highly beneficial when paired with visual analysis of the cytometry data. Using analytical flow cytometry procedures optimized for cells for EV analysis can lead to misleading and nonreproducible results. [ABSTRACT FROM AUTHOR]

Background: There is an unmet clinical need for minimally invasive diagnostic tests to improve the detection of grade group (GG) ≥3 prostate cancer relative to prostate antigen‐specific risk calculators. We determined the accuracy of the blood‐based extracellular vesicle (EV) biomarker assay (EV Fingerprint test) at the point of a prostate biopsy decision to predict GG ≥3 from GG ≤2 and avoid unnecessary biopsies. Methods: This study analyzed 415 men referred to urology clinics and scheduled for a prostate biopsy, were recruited to the APCaRI 01 prospective cohort study. The EV machine learning analysis platform was used to generate predictive EV models from microflow data. Logistic regression was then used to analyze the combined EV models and patient clinical data and generate the patients' risk score for GG ≥3 prostate cancer. Results: The EV‐Fingerprint test was evaluated using the area under the curve (AUC) in discrimination of GG ≥3 from GG ≤2 and benign disease on initial biopsy. EV‐Fingerprint identified GG ≥3 cancer patients with high accuracy (0.81 AUC) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cutoff, 95% of men with GG ≥3 would have been recommended a biopsy while avoiding 144 unnecessary biopsies (35%) and missing four GG ≥3 cancers (5%). Conversely, a 5% cutoff would have avoided 31 unnecessary biopsies (7%), missing no GG ≥3 cancers (0%). Conclusions: EV‐Fingerprint accurately predicted GG ≥3 prostate cancer and would have significantly reduced unnecessary prostate biopsies. [ABSTRACT FROM AUTHOR]

Exposures to prenatal maternal depressive symptoms (PMDS) may lead to neurodevelopmental changes in the offspring in a sex‐dependent way. Although a connection between PMDS and infant brain development has been established by earlier studies, the relationship between PMDS exposures measured at various prenatal stages and microstructural alterations in fundamental subcortical structures such as the amygdala remains unknown. In this study, we investigated the associations between PMDS measured during gestational weeks 14, 24 and 34 and infant amygdala microstructural properties using diffusion tensor imaging. We explored amygdala mean diffusivity (MD) alterations in response to PMDS in infants aged 11 to 54 days from birth. PMDS had no significant main effect on the amygdala MD metrics. However, there was a significant interaction effect for PMDS and infant sex in the left amygdala MD. Compared with girls, boys exposed to greater PMDS during gestational week 14 showed significantly higher left amygdala MD. These results indicate that PMDS are linked to infants' amygdala microstructure in boys. These associations may be relevant to later neuropsychiatric outcomes in the offspring. Further research is required to better understand the mechanisms underlying these associations and to develop effective interventions to counteract any potential adverse consequences. [ABSTRACT FROM AUTHOR]

The rapid white matter (WM) maturation of first years of life is followed by slower yet long‐lasting development, accompanied by learning of more elaborate skills. By the age of 5 years, behavioural and cognitive differences between females and males, and functions associated with brain lateralization such as language skills are appearing. Diffusion tensor imaging (DTI) can be used to quantify fractional anisotropy (FA) within the WM and increasing values correspond to advancing brain development. To investigate the normal features of WM development during early childhood, we gathered a DTI data set of 166 healthy infants (mean 3.8 wk, range 2–5 wk; 89 males; born on gestational week 36 or later) and 144 healthy children (mean 5.4 years, range 5.1–5.8 years; 76 males). The sex differences, lateralization patterns and age‐dependent changes were examined using tract‐based spatial statistics (TBSS). In 5‐year‐olds, females showed higher FA in wide‐spread regions in the posterior and the temporal WM and more so in the right hemisphere, while sex differences were not detected in infants. Gestational age showed stronger association with FA values compared to age after birth in infants. Additionally, child age at scan associated positively with FA around the age of 5 years in the body of corpus callosum, the connections of which are important especially for sensory and motor functions. Lastly, asymmetry of WM microstructure was detected already in infants, yet significant changes in lateralization pattern seem to occur during early childhood, and in 5‐year‐olds the pattern already resembles adult‐like WM asymmetry. [ABSTRACT FROM AUTHOR]

Extracellular vesicles (EVs) are highly abundant in human biofluids, containing a repertoire of macromolecules and biomarkers representative of the tissue of origin. EVs released by tumours can communicate key signals both locally and to distant sites to promote growth and survival or impact invasive and metastatic progression. Microscale flow cytometry of circulating EVs is an emerging technology that is a promising alternative to biopsy for disease diagnosis. However, biofluid‐derived EVs are highly heterogeneous in size and composition, making their analysis complex. To address this, we developed a machine learning approach combined with EV microscale cytometry using tissue‐ and disease‐specific biomarkers to generate predictive models. We demonstrate the utility of this novel extracellular vesicle machine learning analysis platform (EVMAP) to predict disease from patient samples by developing a blood test to identify high‐grade prostate cancer and validate its performance in a prospective 215 patient cohort. Models generated using the EVMAP approach significantly improved the prediction of high‐risk prostate cancer, highlighting the clinical utility of this diagnostic platform for improved cancer prediction from a blood test. [ABSTRACT FROM AUTHOR]

Diffusion tensor imaging (DTI) has provided great insights into the microstructural features of the developing brain. However, DTI images are prone to several artifacts and the reliability of DTI scalars is of paramount importance for interpreting and generalizing the findings of DTI studies, especially in the younger population. In this study, we investigated the intrascan test–retest repeatability of four DTI scalars: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) in 5‐year‐old children (N = 67) with two different data preprocessing approaches: a volume censoring pipeline and an outlier replacement pipeline. We applied a region of interest (ROI) and a voxelwise analysis after careful quality control, tensor fitting and tract‐based spatial statistics. The data had three subsets and each subset included 31, 32, or 33 directions thus a total of 96 unique uniformly distributed diffusion encoding directions per subject. The repeatability of DTI scalars was evaluated with intraclass correlation coefficient (ICC(3,1)) and the variability between test and retest subsets. The results of both pipelines yielded good to excellent (ICC(3,1) > 0.75) reliability for most of the ROIs and an overall low variability (<10%). In the voxelwise analysis, FA and RD had higher ICC(3,1) values compared to AD and MD and the variability remained low (<12%) across all scalars. Our results suggest high intrascan repeatability in pediatric DTI and lend confidence to the use of the data in future cross‐sectional and longitudinal studies. [ABSTRACT FROM AUTHOR]

The corpus callosum (CC) is the largest fiber tract in the human brain, allowing interhemispheric communication by connecting homologous areas of the two cerebral hemispheres. In adults, CC size shows a robust allometric relationship with brain size, with larger brains having larger callosa, but smaller brains having larger callosa relative to brain size. Such an allometric relationship has been shown in both males and females, with no significant difference between the sexes. But there is some evidence that there are alterations in these allometric relationships during development. However, it is currently not known whether there is sexual dimorphism in these allometric relationships from birth, or if it only develops later. We study this in neonate data. Our results indicate that there are already sex differences in these allometric relationships in neonates: male neonates show the adult‐like allometric relationship between CC size and brain size; however female neonates show a significantly more positive allometry between CC size and brain size than either male neonates or female adults. The underlying cause of this sexual dimorphism is unclear; but the existence of this sexual dimorphism in neonates suggests that sex‐differences in lateralization have prenatal origins. [ABSTRACT FROM AUTHOR]

Methodological aspects and effects of different imaging parameters on DTI (diffusion tensor imaging) results and their reproducibility have been recently studied comprehensively in adult populations. Although MR imaging of children's brains has become common, less interest has been focussed on researching whether adult‐based optimised parameters and pre‐processing protocols can be reliably applied to paediatric populations. Furthermore, DTI scalar values of preschool aged children are rarely reported. We gathered a DTI dataset from 5‐year‐old children (N = 49) to study the effect of the number of diffusion‐encoding directions on the reliability of resultant scalar values with TBSS (tract‐based spatial statistics) method. Additionally, the potential effect of within‐scan head motion on DTI scalars was evaluated. Reducing the number of diffusion‐encoding directions deteriorated both the accuracy and the precision of all DTI scalar values. To obtain reliable scalar values, a minimum of 18 directions for TBSS was required. For TBSS fractional anisotropy values, the intraclass correlation coefficient with two‐way random‐effects model (ICC[2,1]) for the subsets of 6 to 66 directions ranged between 0.136 [95%CI 0.0767;0.227] and 0.639 [0.542;0.740], whereas the corresponding values for subsets of 18 to 66 directions were 0.868 [0.815;0.913] and 0.995 [0.993;0.997]. Following the exclusion of motion‐corrupted volumes, minor residual motion did not associate with the scalar values. A minimum of 18 diffusion directions is recommended to result in reliable DTI scalar results with TBSS. We suggest gathering extra directions in paediatric DTI to enable exclusion of volumes with motion artefacts and simultaneously preserve the overall data quality. [ABSTRACT FROM AUTHOR]

Both cortical and subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with bringing results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface‐based approaches fare substantially better, but have thus far been used only for cortical parcellation, leaving subcortical parcellation in volumetric space. We extend the surface‐based approach to include also the subcortical deep gray‐matter structures, thus achieving a uniform representation across both cortex and subcortex, suitable for use with surface‐based metrics that span these structures, for example, white/gray contrast. Using data from the Enhanced Nathan Klein Institute—Rockland Sample, limited to individuals between 19 and 69 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that (a) our parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels; (b) our parcels align with known cortical and subcortical architecture; and (c) our extended functional parcellation provides an improved fit to the complexity of life‐span (6–85 years) changes in white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels, supporting its use with surface‐based measures. We provide our extended functional parcellation for the use of the neuroimaging community. [ABSTRACT FROM AUTHOR]

Hippocampal circuitry has been posited to be fundamental to positive symptoms in psychosis, but its contributions to other factors important for outcome remains unclear. We hypothesized that longitudinal changes in the hippocampal circuit and concomitant changes of intracortical microstructure are altered in first episode psychosis (FEP) patients and that such changes are associated with negative symptoms and verbal memory. Longitudinal brain scans (2–4 visits over 3–15 months) were acquired for 27 FEP and 29 age‐ and sex‐matched healthy controls. Quantitative T1 maps, sensitive to myelin content, were used to sample the microstructure of the hippocampal subfields and output circuitry (fimbria, alveus, fornix, mammillary bodies), and intracortical regions. Dynamic anatomical covariance in pair‐wise regional trajectories were assessed for each subject, and graph theory was used to calculate a participation coefficient metric that quantifies the similarity/divergence between hippocampal and intracortical microstructure. The mean participation coefficient of the hippocampus was significantly reduced in FEP patients compared with controls, reflecting differences in output hippocampal regions. Importantly, lower participation coefficient of the hippocampal circuit was associated with worse negative symptoms, a relationship that was mediated by changes in verbal memory. This study provides evidence for reduced hippocampal centrality in FEP and concomitant changes in intracortical anatomy. Myelin‐rich output regions of the hippocampus may be an important biological trigger in early psychosis, with cascading effects on broader cortical networks and resultant clinical profiles. [ABSTRACT FROM AUTHOR]

Bladder cancer has a recurrence rate of up to 80% and many patients require multiple treatments that often fail, eventually leading to disease progression. In particular, standard of care for high-grade disease, Bacillus Calmette-Guérin ( BCG), fails in 30% of patients. We have generated a novel oncolytic vaccinia virus ( VACV) by mutating the F4L gene that encodes the virus homolog of the cell-cycle-regulated small subunit of ribonucleotide reductase ( RRM2). The F4L-deleted VACVs are highly attenuated in normal tissues, and since cancer cells commonly express elevated RRM2 levels, have tumor-selective replication and cell killing. These F4L-deleted VACVs replicated selectively in immune-competent rat AY-27 and xenografted human RT112-luc orthotopic bladder cancer models, causing significant tumor regression or complete ablation with no toxicity. It was also observed that rats cured of AY-27 tumors by VACV treatment developed anti-tumor immunity as evidenced by tumor rejection upon challenge and by ex vivo cytotoxic T-lymphocyte assays. Finally, F4L-deleted VACVs replicated in primary human bladder cancer explants. Our findings demonstrate the enhanced safety and selectivity of F4L-deleted VACVs, with application as a promising therapy for patients with BCG-refractory cancers and immune dysregulation. [ABSTRACT FROM AUTHOR]

A long and productive history in biomedical research defines the chick as a model for human biology. Fundamental discoveries, including the description of directional circulation propelled by the heart and the link between oncogenes and the formation of cancer, indicate its utility in cardiac biology and cancer. Despite the more recent arrival of several vertebrate and invertebrate animal models during the last century, the chick embryo remains a commonly used model for vertebrate biology and provides a tractable biological template. With new molecular and genetic tools applied to the avian genome, the chick embryo is accelerating the discovery of normal development and elusive disease processes. Moreover, progress in imaging and chick culture technologies is advancing real-time visualization of dynamic biological events, such as tissue morphogenesis, angiogenesis, and cancer metastasis. A rich background of information, coupled with new technologies and relative ease of maintenance, suggest an expanding utility for the chick embryo in cardiac biology and cancer research. Developmental Dynamics 243:216-228, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Typical adults show an inverse relation between callosal fiber length and degree of interhemispheric connectivity. This has been hypothesized to be a consequence of the influence of conduction delays and cellular costs during development on axonal pruning, both of which increase with fiber length. Autism spectrum disorder (ASD) provides a test of this hypothesis: Children with ASD are known to have enlarged brains; thus, adults with ASD should show reductions in interhemispheric connectivity proportional to their degree of brain overgrowth during development. This prediction was tested by assessing the relation between both the size and structure of the corpus callosum and callosal fiber length, adjusting for intracranial volume, which is thought to reflect maximum brain size achieved during development. Using tractography to estimate the length of callosal fibers emanating from all areas of cortex, and through which region of the corpus callosum they pass, we show that adults with ASD show an inverse relation between callosal fiber length, adjusted for intracranial volume, and callosum size, and a positive relation between adjusted callosal fiber length and radial diffusivity. The results provide support for the hypothesized impact of fiber length during development. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Theoretical considerations, and findings from computational modeling, comparative neuroanatomy and developmental neuroscience, motivate the hypothesis that a deviant brain growth trajectory will lead to deviant patterns of change in cortico-cortical connectivity. Differences in brain size during development will alter the relative cost and effectiveness of short- and long-distance connections, and should thus impact the growth and retention of connections. Reduced brain size should favor long-distance connectivity; brain overgrowth should favor short-distance connectivity; and inconsistent deviations from the normal growth trajectory – as occurs in autism – should result in potentially disruptive changes to established patterns of functional and physical connectivity during development. To explore this hypothesis, neural networks which modeled inter-hemispheric interaction were grown at the rate of either typically developing children or children with autism. The influence of the length of the inter-hemispheric connections was analyzed at multiple developmental time-points. The networks that modeled autistic growth were less affected by removal of the inter-hemispheric connections than those that modeled normal growth – indicating a reduced reliance on long-distance connections – for short response times, and this difference increased substantially at approximately 24 simulated months of age. The performance of the networks showed a corresponding decline during development. And direct analysis of the connection weights showed a parallel reduction in connectivity. These modeling results support the hypothesis that the deviant growth trajectory in autism spectrum disorders may lead to a disruption of established patterns of functional connectivity during development, with potentially negative behavioral consequences, and a subsequent reduction in physical connectivity. The results are discussed in relation to the growing body of evidence of reduced functional and structural connectivity in autism, and in relation to the behavioral phenotype, particularly the developmental aspects. [ABSTRACT FROM AUTHOR]

Presents information on a study that examined histone ubiquitination. Abundance of ubiquitinated histones; Enzymes involved in histone ubiquitination; Role of histone ubiquitination.