Faculty Bibliography

Behavioral choices made by the brain during stress depend on glucocorticoid and brain-derived neurotrophic factor (BDNF) signaling pathways acting in synchrony in the mesolimbic (reward) and corticolimbic (emotion) neural networks. Deregulated expression of BDNF and glucocorticoid receptors in brain valuation areas may compromise the integration of signals. Glucocorticoid receptor phosphorylation upon BDNF signaling in neurons represents one mechanism underlying the integration of BDNF and glucocorticoid signals that when off balance may lay the foundation of maladaptations to stress. Here, we propose that BDNF signaling conditions glucocorticoid responses impacting neural plasticity in the mesocorticolimbic system. This provides a novel molecular framework for understanding how brain networks use BDNF and glucocorticoid signaling contingencies to forge receptive neuronal fields in temporal domains defined by behavioral experience, and in mood disorders.

Objective: To provide a comprehensive assessment of the direct and indirect medical costs of PD in the US Background: In addition to the debilitating symptoms of PD itself, people with PD (PWP) also experience injuries from falls and other comorbidities. As a result, PWP have higher medical needs, often miss work, retire early and require caregiver assistance. PD prevalence is predicted to increase in coming decades. Comprehensive information on the economic burden of PD is needed.
Method(s): Multiple data sources were used to estimate the different components of the cost of PD, including: The US Census population projections combined with Medicare Current Beneficiary Survey (MCBS) and the Medical Expenditure Panel Survey (MEPS) data; claims data from Medicare Standard Analytical File (SAF), nonacute care and prescription drug components from the MCBS, CDC Wonder data, average earnings data from Bureau of Labor Statistics, and one of the largest claims databases for the privately insured. Other indirect and non-medical cost components were estimated using a primary survey that was designed and implemented for this study. Costs were determined for an estimated 1 million Americans with PD using 2017 costs.
Result(s): The estimated total medical cost attributable to PD is just over $25 billion in the US. Nearly 90% of the total direct medical cost of PD are borne by Medicare and its beneficiaries with PD, with inpatient and non-acute institutional care representing the largest shares of the total direct cost. The average per-person direct cost was $22,671 for the privately insured PWP 65 years of age) with PD. The average indirect and non-medical cost per PWP is $18,229 for PWP alone and $24,149 for PWP combined with unpaid care partner burden. The estimated total indirect and non-medical cost of PD is $25.05 billion in 2017, with $18.9 billion attributed to PWP and another $6.1 billion to unpaid care partners.
Conclusion(s): This is the most comprehensive US study to-date in examining the overall economic burden of PD. Our findings underscore the significant burden of PD to society, payers, people with PD and their care partners

State-level variations in disease, healthcare utilization, and spending influence healthcare planning at federal and state levels and should be examined to understand national disparities in health outcomes. This descriptive study examined state-level variations in Parkinson disease (PD) prevalence, patient characteristics, Medicare spending, out-of-pocket costs, and health service utilization using data on 27.5 million Medicare beneficiaries in the US in 2014. We found that 45.8% (n = 179,496) of Medicare beneficiaries diagnosed with PD were women; 26.1% (n = 102,205) were aged 85+. The District of Columbia, New York, Illinois, Connecticut, and Florida had the highest age-, race-, and sex-adjusted prevalence of Parkinson disease among Medicare beneficiaries in the US. Women comprised over 48.5% of PD patient populations in West Virginia, Kentucky, Mississippi, Louisiana, and Arkansas. More than 31% of the PD populations in Connecticut, Pennsylvania, Hawaii, and Rhode Island were aged 85+. PD patients who were "dual-eligible"-receiving both Medicare and Medicaid benefits-also varied by state, from <10% to >25%. Hospitalizations varied from 304 to 653 stays per 1000 PD patients and accounted for 26.5% of the 7.9 billion United States Dollars (USD) paid by the Medicare program for healthcare services delivered to our sample. A diagnosis of PD was associated with greater healthcare use and spending. This study provides initial evidence of substantial geographic variation in PD patient characteristics, health service use, and spending. Further study is necessary to inform the development of state- and federal-level health policies that are cost-efficient and support desired outcomes for PD patients.

Slow-oscillations and spindle activity during non-REM sleep have been implicated in memory consolidation. Closed-loop acoustic stimulation has previously been shown to enhance slow oscillations and spindle activity during sleep and improve verbal associative memory. We assessed the effect of closed-loop acoustic stimulation during a daytime nap on a virtual reality spatial navigation task in 12 healthy human subjects in a randomized within-subject crossover design. We show robust enhancement of slow-spindle activity during sleep. However, no effects on behavioral performance were observed when comparing real versus sham stimulation. To explore whether memory enhancement effects were task-specific and dependent on nocturnal sleep, in a second experiment with 19 healthy subjects, we aimed to replicate a previous study which used closed-loop acoustic stimulation to enhance memory for word pairs. Methods were as close as possible to the original study, except we used a double-blind protocol, in which both subject and experimenter were unaware of the test condition. Again, we successfully enhanced slow-spindle power, but again did not strengthen associative memory performance with stimulation. We conclude that enhancement of slow-spindle oscillations may be insufficient to enhance memory performance in spatial navigation or verbal association tasks, and provide possible explanations for lack of behavioral replication.SIGNIFICANCE STATEMENT Prior studies have demonstrated that a closed-loop acoustic pulse paradigm during sleep can enhance verbal memory performance. This technique has widespread scientific and clinical appeal due to its non-invasive nature and ease of application. We tested with a rigorous double-blind design whether this technique could enhance key sleep rhythms associated sleep-dependent memory performance. We discovered that we could reliably enhance slow and spindle rhythms, but did not improve memory performance in the stimulation condition compared to sham condition. Our findings suggest that enhancing slow-spindle rhythms is insufficient to enhance sleep-dependent learning.

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.

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.

Different strategies for treatment and prevention of Alzheimer's disease (AD) are currently under investigation, including passive immunization with anti-amyloid β (anti-Aβ) monoclonal antibodies (mAbs). Here, we investigate the therapeutic potential of a novel type of Aβ-targeting agent based on an affibody molecule with fundamentally different properties to mAbs. We generated a therapeutic candidate, denoted Z_SYM73-albumin-binding domain (ABD; 16.8 kDa), by genetic linkage of the dimeric Z_SYM73 affibody for sequestering of monomeric Aβ-peptides and an ABD for extension of its in vivo half-life. Amyloid precursor protein (APP)/PS1 transgenic AD mice were administered with Z_SYM73-ABD, followed by behavioral examination and immunohistochemistry. Results demonstrated rescued cognitive functions and significantly lower amyloid burden in the treated animals compared to controls. No toxicological symptoms or immunology-related side-effects were observed. To our knowledge, this is the first reported in vivo investigation of a systemically delivered scaffold protein against monomeric Aβ, demonstrating a therapeutic potential for prevention of AD.