Irritability in disruptive mood dysregulation disorder (DMDD) may be associated with a biased tendency to judge ambiguous facial expressions as angry. We conducted three experiments to explore this ...bias as a treatment target. We tested: 1) whether youth with DMDD express this bias; 2) whether judgment of ambiguous faces can be altered in healthy youth by training; and 3) whether such training in youth with DMDD is associated with reduced irritability and associated changes in brain function.
Participants in all experiments made happy versus angry judgments of faces that varied along a happy to angry continuum. These judgments were used to quantify a "balance point," the facial expression at which a participant's judgment switches from predominantly happy to predominantly angry. We first compared balance points in youth with DMDD (n = 63) versus healthy youth (n = 26). We then conducted a double-blind, randomized controlled trial of active versus sham balance-point training in 19 healthy youth. Finally, we piloted open, active balance-point training in 14 youth with DMDD, with 10 completing an implicit functional MRI (fMRI) face-emotion processing task.
Relative to healthy youth, DMDD youth manifested a shifted balance point, expressed as a tendency to classify ambiguous faces as angry rather than happy. In both healthy and DMDD youth, active training is associated with a shift in balance point toward more happy judgments. In DMDD, evidence suggests that active training may be associated with decreased irritability and changes in activation in the lateral orbitofrontal cortex.
These results set the stage for further research on computer-based treatment targeting interpretation bias of angry faces in DMDD. Such treatment may decrease irritability and alter neural responses to subtle expressions of happiness and anger.
XNAT Central is a publicly accessible medical imaging data repository based on the XNAT open-source imaging informatics platform. It hosts a wide variety of research imaging data sets. The primary ...motivation for creating XNAT Central was to provide a central repository to host and provide access to a wide variety of neuroimaging data. In this capacity, XNAT Central hosts a number of data sets from research labs and investigative efforts from around the world, including the OASIS Brains imaging studies, the NUSDAST study of schizophrenia, and more. Over time, XNAT Central has expanded to include imaging data from many different fields of research, including oncology, orthopedics, cardiology, and animal studies, but continues to emphasize neuroimaging data. Through the use of XNAT's DICOM metadata extraction capabilities, XNAT Central provides a searchable repository of imaging data that can be referenced by groups, labs, or individuals working in many different areas of research. The future development of XNAT Central will be geared towards greater ease of use as a reference library of heterogeneous neuroimaging data and associated synthetic data. It will also become a tool for making data available supporting published research and academic articles.
•XNAT Central is a publicly accessible medical imaging data repository.•It runs on the widely used XNAT open-source imaging informatics platform.•It emphasizes neuroimaging data but includes imaging data from many different fields.•Research groups from around the world provide data on XNAT Central.•Future development will emphasize publishing and data management functions.
Update on neuroblastoma Newman, Erika A.; Abdessalam, Shahab; Aldrink, Jennifer H. ...
Journal of pediatric surgery,
March 2019, 2019-Mar, 2019-03-00, 20190301, Volume:
54, Issue:
3
Journal Article
Peer reviewed
Neuroblastoma is an embryonic cancer arising from neural crest stem cells. This cancer is the most common malignancy in infants and the most common extracranial solid tumor in children. The clinical ...course may be highly variable with the possibility of spontaneous regression in the youngest patients and increased risk of aggressive disease in older children. Clinical heterogeneity is a consequence of the diverse biologic characteristics that determine patient risk and survival. This review will focus on current progress in neuroblastoma staging, risk stratification, and treatment strategies based on advancing knowledge in tumor biology and genetic characterization.
Review article.
Level II.
Complex traits often involve interactions between different genetic loci. This can lead to sign epistasis, whereby mutations that are individually deleterious or neutral combine to confer a fitness ...benefit. In order to acquire the beneficial genotype, an asexual population must cross a fitness valley or plateau by first acquiring the deleterious or neutral intermediates. Here, we present a complete, intuitive theoretical description of the valley-crossing process across the full spectrum of possible parameter regimes. We calculate the rate at which a population crosses a fitness valley or plateau of arbitrary width, as a function of the mutation rates, the population size, and the fitnesses of the intermediates. We find that when intermediates are close to neutral, a large population can cross even wide fitness valleys remarkably quickly, so that valley-crossing dynamics may be common even when mutations that directly increase fitness are also possible. Thus the evolutionary dynamics of large populations can be sensitive to the structure of an extended region of the fitness landscape — the population may not take directly uphill paths in favor of paths across valleys and plateaus that lead eventually to fitter genotypes. In smaller populations, we find that below a threshold size, which depends on the width of the fitness valley and the strength of selection against intermediate genotypes, valley-crossing is much less likely and hence the evolutionary dynamics are less influenced by distant regions of the fitness landscape.
Programmed death-ligand 1 (PD-L1) expression on tumor cells (TCs) by immunohistochemistry is rapidly gaining importance as a diagnostic for the selection or stratification of patients with non-small ...cell lung cancer (NSCLC) most likely to respond to single-agent checkpoint inhibitors. However, at least two distinct patterns of PD-L1 expression have been observed with potential biological and clinical relevance in NSCLC: expression on TC or on tumor-infiltrating immune cells (ICs). We investigated the molecular and cellular characteristics associated with PD-L1 expression in these distinct cell compartments in 4,549 cases of NSCLC. PD-L1 expression on IC was more prevalent and likely reflected IFN-γ–induced adaptive regulation accompanied by increased tumor-infiltrating lymphocytes and effector T cells. High PD-L1 expression on TC, however, reflected an epigenetic dysregulation of the PD-L1 gene and was associated with a distinct histology described by poor immune infiltration, sclerotic/desmoplastic stroma, and mesenchymal molecular features. Importantly, durable clinical responses to atezolizumab (anti–PD-L1) were observed in patients with tumors expressing high PD-L1 levels on either TC alone 40% objective response rate (ORR) or IC alone (22% ORR). Thus, PD-L1 expression on TC or IC can independently attenuate anticancer immunity and emphasizes the functional importance of IC in regulating the antitumor T cell response.
ConnectomeDB is a database for housing and disseminating data about human brain structure, function, and connectivity, along with associated behavioral and demographic data. It is the main archive ...and dissemination platform for data collected under the WU-Minn consortium Human Connectome Project. Additional connectome-style study data is and will be made available in the database under current and future projects, including the Connectome Coordination Facility. The database currently includes multiple modalities of magnetic resonance imaging (MRI) and magnetoencephalograpy (MEG) data along with associated behavioral data. MRI modalities include structural, task, resting state and diffusion. MEG modalities include resting state and task. Imaging data includes unprocessed, minimally preprocessed and analysis data. Imaging data and much of the behavioral data are publicly available, subject to acceptance of data use terms, while access to some sensitive behavioral data is restricted to qualified investigators under a more stringent set of terms. ConnectomeDB is the public side of the WU-Minn HCP database platform. As such, it is geared towards public distribution, with a web-based user interface designed to guide users to the optimal set of data for their needs and a robust backend mechanism based on the commercial Aspera fasp service to enable high speed downloads. HCP data is also available via direct shipment of hard drives and Amazon S3.
Update on Wilms tumor Aldrink, Jennifer H.; Heaton, Todd E.; Dasgupta, Roshni ...
Journal of pediatric surgery,
March 2019, 2019-Mar, 2019-03-00, 20190301, Volume:
54, Issue:
3
Journal Article
Peer reviewed
Open access
This article reviews of the current evidence-based treatment standards for children with Wilms tumor. In this article, a summary of recently completed clinical trials by the Children's Oncology Group ...is provided, the current diagnostic evaluation and surgical standards are discussed, and the surgical impact on current risk stratification for patients with Wilms tumor is highlighted.
This is a review article of previously published and referenced LEVEL 1 studies, but also includes expert opinion LEVEL V, represented by the American Pediatric Surgical Association Cancer Committee.
Pathologic myopia is a severe form of myopia that can lead to permanent visual impairment. The recent global increase in the prevalence of myopia has been projected to lead to a higher incidence of ...pathologic myopia in the future. Thus, imaging myopic eyes to detect early pathological changes, or predict myopia progression to allow for early intervention, has become a key priority. Recent advances in optical coherence tomography (OCT) have contributed to the new grading system for myopic maculopathy and myopic traction maculopathy, which may improve phenotyping and thus, clinical management. Widefield fundus and OCT imaging has improved the detection of posterior staphyloma. Non-invasive OCT angiography has enabled depth-resolved imaging for myopic choroidal neovascularisation. Artificial intelligence (AI) has shown great performance in detecting pathologic myopia and the identification of myopia-associated complications. These advances in imaging with adjunctive AI analysis may lead to improvements in monitoring disease progression or guiding treatments. In this review, we provide an update on the classification of pathologic myopia, how imaging has improved clinical evaluation and management of myopia-associated complications, and the recent development of AI algorithms to aid the detection and classification of pathologic myopia.
Background
Magnetic resonance imaging (MRI) scans are known to suffer from a variety of acquisition artifacts as well as equipment‐based variations that impact image appearance and segmentation ...performance. It is still unclear whether a direct relationship exists between magnetic resonance (MR) image quality metrics (IQMs) (e.g., signal‐to‐noise, contrast‐to‐noise) and segmentation accuracy.
Purpose
Deep learning (DL) approaches have shown significant promise for automated segmentation of brain tumors on MRI but depend on the quality of input training images. We sought to evaluate the relationship between IQMs of input training images and DL‐based brain tumor segmentation accuracy toward developing more generalizable models for multi‐institutional data.
Methods
We trained a 3D DenseNet model on the BraTS 2020 cohorts for segmentation of tumor subregions enhancing tumor (ET), peritumoral edematous, and necrotic and non‐ET on MRI; with performance quantified via a 5‐fold cross‐validated Dice coefficient. MRI scans were evaluated through the open‐source quality control tool MRQy, to yield 13 IQMs per scan. The Pearson correlation coefficient was computed between whole tumor (WT) dice values and IQM measures in the training cohorts to identify quality measures most correlated with segmentation performance. Each selected IQM was used to group MRI scans as “better” quality (BQ) or “worse” quality (WQ), via relative thresholding. Segmentation performance was re‐evaluated for the DenseNet model when (i) training on BQ MRI images with validation on WQ images, as well as (ii) training on WQ images, and validation on BQ images. Trends were further validated on independent test sets derived from the BraTS 2021 training cohorts.
Results
For this study, multimodal MRI scans from the BraTS 2020 training cohorts were used to train the segmentation model and validated on independent test sets derived from the BraTS 2021 cohort. Among the selected IQMs, models trained on BQ images based on inhomogeneity measurements (coefficient of variance, coefficient of joint variation, coefficient of variation of the foreground patch) and the models trained on WQ images based on noise measurement peak signal‐to‐noise ratio (SNR) yielded significantly improved tumor segmentation accuracy compared to their inverse models.
Conclusions
Our results suggest that a significant correlation may exist between specific MR IQMs and DenseNet‐based brain tumor segmentation performance. The selection of MRI scans for model training based on IQMs may yield more accurate and generalizable models in unseen validation.
Objective
Individuals with posttraumatic stress disorder (PTSD) exhibit heightened amygdala reactivity and atypical activation patterns in the medial prefrontal cortex (mPFC) in response to negative ...emotional information. It is unknown whether these aspects of neural function are risk factors for PTSD or consequences of either trauma exposure or onset of the disorder. We had a unique opportunity to investigate this issue following the terrorist attacks at the 2013 Boston Marathon and the ensuing manhunt and shelter in place order. We examined associations of neural function measured prior to the attack with PTSD symptom onset related to these events.
Methods
A sample of 15 adolescents (mean age = 16.5 years) who previously participated in a neuroimaging study completed a survey assessing posttraumatic symptoms related to the terrorist attack. We examined blood oxygen level dependent (BOLD) response to viewing and actively down‐regulating emotional responses to negative stimuli in regions previously associated with PTSD, including the amygdala, hippocampus, and mPFC, as prospective predictors of posttraumatic symptom onset.
Results
Increased BOLD signal to negative emotional stimuli in the left amygdala was strongly associated with posttraumatic symptoms following the attack. Reduced bilateral hippocampal activation during effortful attempts to down‐regulate emotional responses to negative stimuli was also associated with greater posttraumatic symptoms. Associations of amygdala reactivity with posttraumatic symptoms were robust to controls for pre‐existing depression, anxiety, and PTSD symptoms and prior exposure to violence.
Conclusions
Amygdala reactivity to negative emotional information might represent a neurobiological marker of vulnerability to traumatic stress and, potentially, a risk factor for PTSD.
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