Faculty Bibliography

BACKGROUND AND PURPOSE/OBJECTIVE:Previous hippocampal proton MR spectroscopic imaging distinguished patients with schizophrenia from controls by elevated Cr levels and significantly more variable NAA and Cho concentrations. This goal of this study was to ascertain whether this metabolic variability is associated with clinical features of the syndrome, possibly reflecting heterogeneous hippocampal pathologies and perhaps variability in its "positive" (psychotic) and "negative" (social and emotional deficits) symptoms. MATERIALS AND METHODS/METHODS:, we examined the association of NAA and Cho levels with research diagnostic interviews and clinical symptom ratings of the patients. Metabolite concentrations were previously obtained with 3D proton MR spectroscopic imaging at 3T, a technique that facilitates complete coverage of this small, irregularly shaped, bilateral, temporal lobe structure. RESULTS: ≥  .055). CONCLUSIONS:These preliminary findings suggest that NAA and Cho variations reflect different pathophysiologic processes, consistent with microgliosis/astrogliosis and/or lower vitality (reduced NAA) and demyelination (elevated Cho). In particular, the active state-related symptoms, including psychosis and mania, were associated with demyelination. Consequently, their deviations from the means of healthy controls may be a marker that may benefit precision medicine in selection and monitoring of schizophrenia treatment.

This study derives normative prediction equations for respiratory impedance in a healthy asymptomatic urban population using an impulse oscillation system (IOS). In addition, this study uses body mass index (BMI) in the equations to describe the effect of obesity on respiratory impedance. Data from an urban population comprising 472 healthy asymptomatic subjects that resided or worked in lower Manhattan, New York City were retrospectively analysed. This population was the control group from a previously completed case-control study of the health effects of exposure to World Trade Center dust. Since all subjects underwent spirometry and oscillometry, these previously collected data allowed a unique opportunity to derive normative prediction equations for oscillometry in an urban, lifetime non-smoking, asymptomatic population without underlying respiratory disease. Normative prediction equations for men and women were successfully developed for a broad range of respiratory oscillometry variables with narrow confidence bands. Models that used BMI as an independent predictor of oscillometry variables (in addition to age and height) demonstrated equivalent or better fit when compared with models that used weight. With increasing BMI, resistance and reactance increased compatible with lung and airway compression from mass loading. This study represents the largest cohort of healthy urban subjects assessed with an IOS device. Normative prediction equations were derived that should facilitate application of IOS in the clinical setting. In addition, the data suggest that modelling of lung function may be best performed using height and BMI as independent variables rather than the traditional approach of using height and weight.

PURPOSE/OBJECTIVE:To develop and evaluate a neural network-based method for Gibbs artifact and noise removal. METHODS:A convolutional neural network (CNN) was designed for artifact removal in diffusion-weighted imaging data. Two implementations were considered: one for magnitude images and one for complex images. Both models were based on the same encoder-decoder structure and were trained by simulating MRI acquisitions on synthetic non-MRI images. RESULTS:Both machine learning methods were able to mitigate artifacts in diffusion-weighted images and diffusion parameter maps. The CNN for complex images was also able to reduce artifacts in partial Fourier acquisitions. CONCLUSIONS:The proposed CNNs extend the ability of artifact correction in diffusion MRI. The machine learning method described here can be applied on each imaging slice independently, allowing it to be used flexibly in clinical applications.

Deciphering how neuronal diversity is established and maintained requires a detailed knowledge of neuronal gene expression throughout development. In contrast to mammalian brains^1,2, the large neuronal diversity of the Drosophila optic lobe³ and its connectome^4-6 are almost completely characterized. However, a molecular characterization of this neuronal diversity, particularly during development, has been lacking. Here we present insights into brain development through a nearly complete description of the transcriptomic diversity of the optic lobes of Drosophila. We acquired the transcriptome of 275,000 single cells at adult and at five pupal stages, and built a machine-learning framework to assign them to almost 200 cell types at all time points during development. We discovered two large neuronal populations that wrap neuropils during development but die just before adulthood, as well as neuronal subtypes that partition dorsal and ventral visual circuits by differential Wnt signalling throughout development. Moreover, we show that the transcriptomes of neurons that are of the same type but are produced days apart become synchronized shortly after their production. During synaptogenesis we also resolved neuronal subtypes that, although differing greatly in morphology and connectivity, converge to indistinguishable transcriptomic profiles in adults. Our datasets almost completely account for the known neuronal diversity of the Drosophila optic lobes, and serve as a paradigm to understand brain development across species.

OBJECTIVE:We conducted a meta-analysis of resting state functional magnetic resonance imaging (R-fMRI) studies in children/adolescents and adults with ADHD to assess spatial convergence of findings from available studies. METHOD/METHODS:, 2019, with no language/type-of-document restrictions. Study authors were systematically contacted for additional unpublished information/data. R-fMRI studies using seed-based connectivity (SBC) or any other method (non-SBC) reporting whole-brain results of group comparisons between individuals with ADHD and typically developing controls were eligible. Voxel-wise meta-analysis via activation likelihood estimation with cluster-level Family Wise Error (FWE) (voxel-level: p < 0.001; cluster-level: p < 0.05) was used. The full dataset used for analyses will be freely available online in an open source platform (http://anima.fz-juelich.de/). RESULTS:30 studies (18 SBC and 12 non-SBC), including a total of 1978 participants (1094 ADHD; 884 controls) were retained. The meta-analysis focused on SBC studies found no significant spatial convergence of ADHD-related hyper- or hypo-connectivity across studies. This non-significant finding remained after integrating 12 non-SBC studies into the main-analysis and in sensitivity analyses limited to studies including only children or only non-medication naïve patients. CONCLUSION/CONCLUSIONS:The lack of significant spatial convergence may be accounted for by heterogeneity in study participants, experimental procedures and analytic flexibility, as well as in ADHD pathophysiology. Alongside other neuroimaging meta-analyses in other psychiatric conditions, our results should inform the conduct and publication of future neuroimaging studies of psychiatric disorders.

The Notch pathway is highly active in almost all patients with T-cell acute lymphoblastic leukemia (T-ALL), but the implication of Notch ligands in T-ALL remains underexplored. Methods: We used a genetic mouse model of Notch ligand delta like 4 (DLL4)-driven T-ALL and performed thymectomies and splenectomies in those animals. We also used several patient-derived T-ALL (PDTALL) models, including one with DLL4 expression on the membrane and we treated PDTALL cells in vitro and in vivo with demcizumab, a blocking antibody against human DLL4 currently being tested in clinical trials in patients with solid cancer. Results: We show that surgical removal of the spleen abrogated T-ALL development in our preclinical DLL4-driven T-ALL mouse model. Mechanistically, we found that the spleen, and not the thymus, promoted the accumulation of circulating CD4⁺CD8⁺ T cells before T-ALL onset, suggesting that DLL4-driven T-ALL derives from these cells. Then, we identified a small subset of T-ALL patients showing higher levels of DLL4 expression. Moreover, in mice xenografted with a DLL4-positive PDTALL model, treatment with demcizumab had the same therapeutic effect as global Notch pathway inhibition using the potent γ-secretase inhibitor dibenzazepine. This result demonstrates that, in this PDTALL model, Notch pathway activity depends on DLL4 signaling, thus validating our preclinical mouse model. Conclusion: DLL4 expression in human leukemic cells can be a source of Notch activity in T-ALL, and the spleen plays a major role in a genetic mouse model of DLL4-driven T-ALL.

Down syndrome (DS) is the primary genetic cause of intellectual disability (ID), which is due to the triplication of human chromosome 21 (HSA21). In addition to ID, HSA21 trisomy results in a number of neurological and physiological pathologies in individuals with DS, including progressive cognitive dysfunction and learning and memory deficits which worsen with age. Further exacerbating neurological dysfunction associated with DS is the concomitant basal forebrain cholinergic neuron (BFCN) degeneration and onset of Alzheimer's disease (AD) pathology in early mid-life. Recent single population RNA sequencing (RNA-seq) analysis in the Ts65Dn mouse model of DS, specifically the medial septal cholinergic neurons of the basal forebrain (BF), revealed the mitochondrial oxidative phosphorylation pathway was significantly impacted, with a large subset of genes within this pathway being downregulated. We further queried oxidative phosphorylation pathway dysregulation in Ts65Dn mice by examining genes and encoded proteins within brain regions comprising the basocortical system at the start of BFCN degeneration (6 months of age). In select Ts65Dn mice we demonstrate significant deficits in gene and/or encoded protein levels of Complex I-V of the mitochondrial oxidative phosphorylation pathway in the BF. In the frontal cortex (Fr Ctx) these complexes had concomitant alterations in select gene expression but not of the proteins queried from Complex I-V, suggesting that defects at this time point in the BF are more severe and occur prior to cortical dysfunction within the basocortical circuit. We propose dysregulation within mitochondrial oxidative phosphorylation complexes is an early marker of cognitive decline onset and specifically linked to BFCN degeneration that may propagate pathology throughout cortical memory and executive function circuits in DS and AD.

Flipping through social media feeds, viewing exhibitions in a museum, or walking through the botanical gardens, people consistently choose to engage with and disengage from visual content. Yet, in most laboratory settings, the visual stimuli, their presentation duration, and the task at hand are all controlled by the researcher. Such settings largely overlook the spontaneous nature of human visual experience, in which perception takes place independently from specific task constraints and its time course is determined by the observer as a self-governing agent. Currently, much remains unknown about how spontaneous perceptual experiences unfold in the brain. Are all perceptual categories extracted during spontaneous perception? Does spontaneous perception inherently involve volition? Is spontaneous perception segmented into discrete episodes? How do different neural networks interact over time during spontaneous perception? These questions are imperative to understand our conscious visual experience in daily life. In this article we propose a framework for spontaneous perception. We first define spontaneous perception as a task-free and self-paced experience. We propose that spontaneous perception is guided by four organizing principles that grant it temporal and spatial structures. These principles include coarse-to-fine processing, continuity and segmentation, agency and volition, and associative processing. We provide key suggestions illustrating how these principles may interact with one another in guiding the multifaceted experience of spontaneous perception. We point to testable predictions derived from this framework, including (but not limited to) the roles of the default-mode network and slow cortical potentials in underlying spontaneous perception. We conclude by suggesting several outstanding questions for future research, extending the relevance of this framework to consciousness and spontaneous brain activity. In conclusion, the spontaneous perception framework proposed herein integrates components in human perception and cognition, which have been traditionally studied in isolation, and opens the door to understand how visual perception unfolds in its most natural context.