Faculty Bibliography

OBJECTIVE:Global Maxwell Tomography (GMT) is a recently introduced volumetric technique for noninvasive estimation of electrical properties (EP) from magnetic resonance measurements. Previous work evaluated GMT using ideal radiofrequency (RF) excitations. The aim of this simulation study was to assess GMT performance with a realistic RF coil. METHODS:) inside heterogeneous head models for different RF shimming approaches, and used them as input for GMT to reconstruct EP for all voxels. RESULTS:) and absorbed power could be predicted with less than 0.5% error over the entire head. GMT could accurately detect a numerically inserted tumor. CONCLUSION/CONCLUSIONS:This work demonstrates that GMT can reliably reconstruct EP in realistic simulated scenarios using a tailored 8-channel RF coil design at 7T. Future work will focus on construction of the coil and optimization of GMT's robustness to noise, to enable in vivo GMT experiments. SIGNIFICANCE/CONCLUSIONS:GMT could provide accurate estimations of tissue EP, which could be used as biomarkers and could enable patient-specific estimation of RF power deposition, which is an unsolved problem for ultra-high-field magnetic resonance imaging.

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.

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.

Perturbed neuronal Ca²⁺ homeostasis is implicated in Alzheimer's disease, which has primarily been demonstrated in mice with amyloid-β deposits but to a lesser and more variable extent in tauopathy models. In this study, we injected AAV to express Ca²⁺ indicator in layer II/III motor cortex neurons and measured neuronal Ca²⁺ activity by two photon imaging in awake transgenic JNPL3 tauopathy and wild-type mice. Various biochemical measurements were conducted in postmortem mouse brains for mechanistic insight and a group of animals received two intravenous injections of a tau monoclonal antibody spaced by four days to test whether the Ca²⁺ dyshomeostasis was related to pathological tau protein. Under running conditions, we found abnormal neuronal Ca²⁺ activity in tauopathy mice compared to age-matched wild-type mice with higher frequency of Ca²⁺ transients, lower amplitude of peak Ca²⁺ transients and lower total Ca²⁺ activity in layer II/III motor cortex neurons. While at resting conditions, only Ca²⁺ frequency was increased. Brain levels of soluble pathological tau correlated better than insoluble tau levels with the degree of Ca²⁺ dysfunction in tauopathy mice. Furthermore, tau monoclonal antibody 4E6 partially rescued Ca²⁺ activity abnormalities in tauopathy mice after two intravenous injections and decreased soluble pathological tau protein within the brain. This correlation and antibody effects strongly suggest that the neuronal Ca²⁺ dyshomeostasis is causally linked to pathological tau protein. These findings also reveal more pronounced neuronal Ca²⁺ dysregulation in tauopathy mice than previously reported by two-photon imaging that can be partially corrected with an acute tau antibody treatment.

Angelman syndrome (AS), a genetic disorder that primarily affects the nervous system, is characterized by delayed development, intellectual disability, severe speech impairment, and problems with movement and balance (ataxia). Most affected children also have recurrent seizures (epilepsy). No existing therapies are capable of comprehensively treating the deficits in AS; hence, there is an urgent need to identify new treatments. Here we show that insulin-like growth factor 2 (IGF-2) and mannose-6-phosphate (M6P), ligands of two independent binding sites of the cation-independent M6P/IGF-2 receptor (CIM6P/IGF-2R), reverse most major deficits of AS modeled in mice. Subcutaneous injection of IGF-2 or M6P in mice modeling AS restored cognitive impairments as assessed by measurements of contextual and recognition memories, motor deficits assessed by rotarod and hindlimb clasping, and working memory/flexibility measured by Y-maze. IGF-2 also corrected deficits in marble burying and significantly attenuated acoustically induced seizures. An observational battery of tests confirmed that neither ligand changed basic functions including physical characteristics, general behavioral responses, and sensory reflexes, indicating that they are relatively safe. Our data provide strong preclinical evidence that targeting CIM6P/IGF-2R is a promising approach for developing novel therapeutics for AS. LAY SUMMARY: There is no effective treatment for the neurodevelopmental disorder Angelman syndrome (AS). Using a validated AS mouse model, the Ube3a^m-/p+ , in this study we show that systemic administration of ligands of the cation independent mannose-6-phosphate receptor, also known as insulin-like growth factor 2 receptor (CIM6P/IGF-2R) reverses cognitive impairment, motor deficits, as well as seizures associated with AS. Thus, ligands that activate the CIM6P/IGF-2R may represent novel, potential therapeutic targets for AS.

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.

The immune microenvironment of tumors can play a critical role in promoting or inhibiting tumor progression depending on the context. We present evidence that tumor-associated macrophages/microglia (TAMs) can promote tumor progression in the sonic hedgehog subgroup of medulloblastoma (SHH-MB). By combining longitudinal manganese-enhanced magnetic resonance imaging (MEMRI) and immune profiling of a sporadic mouse model of SHH-MB, we found the density of TAMs is higher in the ~50% of tumors that progress to lethal disease. Furthermore, reducing regulatory T cells or eliminating B and T cells in Rag1 mutants does not alter SHH-MB tumor progression. As TAMs are a dominant immune component in tumors and are normally dependent on colony-stimulating factor 1 receptor (CSF1R), we treated mice with a CSF1R inhibitor, PLX5622. Significantly, PLX5622 reduces a subset of TAMs, prolongs mouse survival, and reduces the volume of most tumors within 4 weeks of treatment. Moreover, concomitant with a reduction in TAMs the percentage of infiltrating cytotoxic T cells is increased, indicating a change in the tumor environment. Our studies in an immunocompetent preclinical mouse model demonstrate TAMs can have a functional role in promoting SHH-MB progression. Thus, CSF1R inhibition could have therapeutic potential for a subset of SHH-MB patients.

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.