Faculty Bibliography
Searched for:
school:SOM
Department/Unit:Neuroscience Institute
Total Results:
13474
Multimodal Hippocampal Subfield Grading For Alzheimer's Disease Classification
ISI:000487586600036
ISSN: 2045-2322
CID: 4155602
Don Summers Memorial MSA Travel Award: Baseline characteristics of patients with multiple system atrophy enrolled in the Natural History Study of the Synucleinopathies [Meeting Abstract]
Background: Multiple system atrophy (MSA) is a fatal and poorly understood rare neurodegenerative disorder. Here we describe the baseline characteristics of patients with MSA enrolled in a prospective multicenter and multinational NIH-sponsored Natural History Study of the Synucleinopathies.
Method(s): Patients with a clinical diagnosis of probable or possible MSA were prospectively enrolled at 11 participating centers. Demographic data, clinical variables, and autonomic testing results were included.
Result(s): 293 patients with MSA (125 women) have been enrolled. MSA-C was predominant (154 patients, 52.6%). Mean age at symptom onset was 57.6+/-8.4 (mean+/-SD) and at enrollment was 62.0+/-7.8 years old. UMSARS-1 was 21.1+/-7.6 and UMSARS-2 was 21.2+/-9.1. MoCA score was 26.3+/-4.4 indicating normal cognition. In the supine position, blood pressure (systolic BP/diastolic BP) was 143.0+/-25.2/84.0+/-14.5 mmHg, and heart rate was 75.0+/-11.5 bpm. After 3-min head-up tilt, BP fell to 113.1+/-25.5/69.6+/-15.9 mmHg and HR increased to 82.9+/-12.7 bpm. Supine plasma norepinephrine levels were 365.4+/-408.5 pg/ml and increased only to 449.8+/-277.2 pg/ml upon head-up tilt indicating impaired baroreflex-mediated sympathetic activation. The University of Pennsylvania Smell Identification Test (UPSIT) score was 28.5+/-8.1 indicating preserved olfaction. Probable rapid eye movement (REM) sleep behavior disorder was reported by 85%.
Conclusion(s): This is the largest cross-sectional sample of patients with MSA recruited consecutively reported so far. Our results confirm that: i) symptom onset in MSA is remarkable consistent at 57 years; ii) overt cognitive impairment is not a typical feature; iii) sympathetic and cardiovagal deficits are present; iv) olfaction is preserved, and; v) probable REM behavior disorder is very frequent. The prospective follow-up of these patients will provide additional information on the natural history of the disease
Method(s): Patients with a clinical diagnosis of probable or possible MSA were prospectively enrolled at 11 participating centers. Demographic data, clinical variables, and autonomic testing results were included.
Result(s): 293 patients with MSA (125 women) have been enrolled. MSA-C was predominant (154 patients, 52.6%). Mean age at symptom onset was 57.6+/-8.4 (mean+/-SD) and at enrollment was 62.0+/-7.8 years old. UMSARS-1 was 21.1+/-7.6 and UMSARS-2 was 21.2+/-9.1. MoCA score was 26.3+/-4.4 indicating normal cognition. In the supine position, blood pressure (systolic BP/diastolic BP) was 143.0+/-25.2/84.0+/-14.5 mmHg, and heart rate was 75.0+/-11.5 bpm. After 3-min head-up tilt, BP fell to 113.1+/-25.5/69.6+/-15.9 mmHg and HR increased to 82.9+/-12.7 bpm. Supine plasma norepinephrine levels were 365.4+/-408.5 pg/ml and increased only to 449.8+/-277.2 pg/ml upon head-up tilt indicating impaired baroreflex-mediated sympathetic activation. The University of Pennsylvania Smell Identification Test (UPSIT) score was 28.5+/-8.1 indicating preserved olfaction. Probable rapid eye movement (REM) sleep behavior disorder was reported by 85%.
Conclusion(s): This is the largest cross-sectional sample of patients with MSA recruited consecutively reported so far. Our results confirm that: i) symptom onset in MSA is remarkable consistent at 57 years; ii) overt cognitive impairment is not a typical feature; iii) sympathetic and cardiovagal deficits are present; iv) olfaction is preserved, and; v) probable REM behavior disorder is very frequent. The prospective follow-up of these patients will provide additional information on the natural history of the disease
EMBASE:632812914
ISSN: 1619-1560
CID: 4597902
Mechanistic investigation of Ca2+ alternans in human heart failure and its modulation by fibroblasts
BACKGROUND:Heart failure (HF) is characterized, among other factors, by a progressive loss of contractile function and by the formation of an arrhythmogenic substrate, both aspects partially related to intracellular Ca2+ cycling disorders. In failing hearts both electrophysiological and structural remodeling, including fibroblast proliferation, contribute to changes in Ca2+ handling which promote the appearance of Ca2+ alternans (Ca-alt). Ca-alt in turn give rise to repolarization alternans, which promote dispersion of repolarization and contribute to reentrant activity. The computational analysis of the incidence of Ca2+ and/or repolarization alternans under HF conditions in the presence of fibroblasts could provide a better understanding of the mechanisms leading to HF arrhythmias and contractile function disorders. METHODS AND FINDINGS/RESULTS:The goal of the present study was to investigate in silico the mechanisms leading to the formation of Ca-alt in failing human ventricular myocytes and tissues with disperse fibroblast distributions. The contribution of ionic currents variability to alternans formation at the cellular level was analyzed and the results show that in normal ventricular tissue, altered Ca2+ dynamics lead to Ca-alt, which precede APD alternans and can be aggravated by the presence of fibroblasts. Electrophysiological remodeling of failing tissue alone is sufficient to develop alternans. The incidence of alternans is reduced when fibroblasts are present in failing tissue due to significantly depressed Ca2+ transients. The analysis of the underlying ionic mechanisms suggests that Ca-alt are driven by Ca2+-handling protein and Ca2+ cycling dysfunctions in the junctional sarcoplasmic reticulum and that their contribution to alternans occurrence depends on the cardiac remodeling conditions and on myocyte-fibroblast interactions. CONCLUSION/CONCLUSIONS:It can thus be concluded that fibroblasts modulate the formation of Ca-alt in human ventricular tissue subjected to heart failure-related electrophysiological remodeling. Pharmacological therapies should thus consider the extent of both the electrophysiological and structural remodeling present in the failing heart.
PMID: 31211790
ISSN: 1932-6203
CID: 3939102
arXiv. 2019.DOI:
Deep learning methods for parallel magnetic resonance image reconstruction [PrePrint]
Following the success of deep learning in a wide range of applications, neural network-based machine learning techniques have received interest as a means of accelerating magnetic resonance imaging (MRI). A number of ideas inspired by deep learning techniques from computer vision and image processing have been successfully applied to non-linear image reconstruction in the spirit of compressed sensing for both low dose computed tomography and accelerated MRI. The additional integration of multi-coil information to recover missing k-space lines in the MRI reconstruction process, is still studied less frequently, even though it is the de-facto standard for currently used accelerated MR acquisitions. This manuscript provides an overview of the recent machine learning approaches that have been proposed specifically for improving parallel imaging. A general background introduction to parallel MRI is given that is structured around the classical view of image space and k-space based methods. Both linear and non-linear methods are covered, followed by a discussion of recent efforts to further improve parallel imaging using machine learning, and specifically using artificial neural networks. Image-domain based techniques that introduce improved regularizers are covered as well as k-space based methods, where the focus is on better interpolation strategies using neural networks. Issues and open problems are discussed as well as recent efforts for producing open datasets and benchmarks for the community.
ORIGINAL:0014687
ISSN: 2331-8422
CID: 4534322
Algorithms And Circuits For Olfactory Navigation In Drosophila [Meeting Abstract]
ISI:000493389500058
ISSN: 0379-864x
CID: 4221922
Principles and Techniques Applied to Enhance Elimination
New York : McGraw-Hill Education, [2019]
pp. ?-?
ISBN: 1259859614
CID: 3697902
Isolated Murine Brain Model for Large-Scale Optoacoustic Calcium Imaging
Real-time visualization of large-scale neural dynamics in whole mammalian brains is hindered with existing neuroimaging methods having limited capacity when it comes to imaging large tissue volumes at high speeds. Optoacoustic imaging has been shown to be capable of real-time three-dimensional imaging of multiple cerebral hemodynamic parameters in rodents. However, optoacoustic imaging of calcium activity deep within the mammalian brain is hampered by strong blood absorption in the visible light spectrum as well as a lack of activity labels excitable in the near-infrared window. We have developed and validated an isolated whole mouse brain preparation labeled with genetically encoded calcium indicator GCaMP6f, which can closely resemble in vivo conditions. An optoacoustic imaging system coupled to a superfusion system was further designed and used for rapid volumetric monitoring of stimulus-evoked calcium dynamics in the brain. These new imaging setup and isolated preparation's protocols and characteristics are described here in detail. Our new technique captures calcium fluxes as true three-dimensional information across the entire brain with temporal resolution of 10 ms and spatial resolution of 150 μm, thus enabling large-scale neural recording at penetration depths and spatio-temporal resolution scales not covered with any existing neuroimaging techniques.
PMCID:6491858
PMID: 31068768
ISSN: 1662-4548
CID: 4606582
Response to: Human papillomavirus (HPV) vaccine safety concerning POTS, CRPS and related conditions [Letter]
ISI:000500606000001
ISSN: 0959-9851
CID: 4228252
Posterior Piriform Cortical Modulation of Odor Fear Memory [Meeting Abstract]
ISI:000493389500274
ISSN: 0379-864x
CID: 4221952
arXiv. 2019.DOI:
Training a Neural Network for Gibbs and Noise Removal in Diffusion MRI [PrePrint]
We develop and evaluate a neural network-based method for Gibbs artifact and noise removal. 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. 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. 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
ORIGINAL:0014689
ISSN: 2331-8422
CID: 4534342
