Faculty Bibliography

Background/UNASSIGNED:Nephrolithiasis is a complex phenotype influenced by both genetic and environmental factors. Previously we found a genetic component to stone disease using a sample of male twin pairs. We now report on the genetic contribution to stones in a sample of female and male twin pairs. Methods/UNASSIGNED:We conducted a classic twin study of kidney stones using the Washington State Twin Registry. Data were collected by questionnaire to obtain self-reported history of kidney stones. Univariate structural equation modeling was used to determine the relative contributions of additive genetics, common environment, and unique environment. Results/UNASSIGNED: < 0.05). Conclusions/UNASSIGNED:Nephrolithiasis in women has a heritable component less than that we again demonstrate in men. This finding may in part explain why more stone formers are men than women. Women twins demonstrated a greater effect of the unique environment on stone prevalence. The specific environmental risk factors that account for this effect are not currently known.

PURPOSE/OBJECTIVE:The purpose of the study was to assess the differences in the concentration and function of urinary proteins between patients with cystine stones (CYS) and healthy controls (HC). We postulated that CYS and HC groups would demonstrate different proteomic profiles. METHODS:A pilot study was performed comparing urinary proteomes of 10 patients with CYS and 10 age- and gender-matched HC, using liquid chromatography-mass spectrometry. Proteins which met the selection criteria (i) ≥ 2 unique peptide identifications; (ii) ≥ twofold difference in protein abundance; and (iii) ≤ 0.05 p value for the Fisher's Exact Test were analyzed using Gene Ontology classifications. RESULTS:Of the 2097 proteins identified by proteomic analysis, 398 proteins were significantly different between CYS and HC. Of those, 191 were involved in transport processes and 61 in inflammatory responses. The majority were vesicle-mediated transport proteins (78.5%), and 1/3 of them were down-regulated; of those, 12 proteins were involved in endosomal transport (including 6 charged multivesicular body proteins (CHMP) and 3 vacuolar sorting-associated proteins) and 9 in transmembrane transport. Myosin-2 and two actin-related proteins were significantly up-regulated in the vesicle-mediated transport group. CONCLUSION/CONCLUSIONS:We provide proteomic evidence of impaired endocytosis, dysregulation of actin and myosin cytoskeleton, and inflammation in CYS. Endosomal transport proteins were down-regulated mainly through defective CHMP. These findings may contribute to further understanding of the pathogenesis of CYS, potentially affecting its management.

Introduction: We determined whether Obstructive Sleep Apnea (OSA) and beta-Amyloid Burden (Abeta) act additively or synergistically to promote conversion from cognitive normal (CN) to mild cognitive impairment (MCI) and from MCI to AD.
Method(s): In this longitudinal observational study, we examined CN (n=298) and MCI (n=418) older adults from the ADNI database (adni.loni.usc.edu). OSA was self-reported during a clinical interview. Brain Abeta was assessed using Florbetapir-PET imaging. The primary outcome of the analysis was conversion from CN to MCI (CN participants) and from MCI to AD (MCI participants). Participants were required to have a baseline and at least one follow-up clinical visit that identified their cognitive status. Logistic mixed-effects models with random intercept and slope were used to assess associations between OSA, Abeta, and risk of conversion from CN to MCI, and MCI to AD. All models included age at baseline, sex, APOE4 status, years of education, and their interactions with time.
Result(s): Of the 716 participants, 329 (46%) were women. The overall mean (SD) age was 74.7 (5.0) years, and the overall mean (SD) follow-up time was 5.5 (1.7) years (Range: 2.7 - 10.9 years). In CN participants at baseline, conversion to MCI was associated with both OSA (beta = 0.418; 95% CI, 0.133 to 0.703; P < .001) and higher Abeta-burden (beta = 0.554; 95% CI, 0.215 to 0.892; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.169, 95% CI, 0.776 to 1.562; P < .001), suggesting a synergistic effect. In MCI participants at baseline, conversion to AD was associated with both OSA (beta = 0.637; 95% CI, 0.291 to 0.982; P < .001) and higher Abeta-burden (beta = 1.061; 95% CI, 0.625 to 1.497; P < .001). The interaction of OSA and Abeta burden with time was significant (beta = 1.312, 95% CI, 0.952 to 1.671; P < .001), suggesting a synergistic effect.
Conclusion(s): In both CN and MCI elderly, Abeta modified the risk of progression to AD in OSA participants. OSA patients maybe more physiologically susceptible as Abeta load becomes increasingly abnormal

In the olfactory system, odor percepts retain their identity despite substantial variations in concentration, timing, and background. We study a novel strategy for encoding intensity-invariant stimulus identity that is based on representing relative rather than absolute values of stimulus features. For example, in what is known as the primacy coding model, odorant identities are represented by the conditions that some odorant receptors are activated more strongly than others. Because, in this scheme, odorant identity depends only on the relative amplitudes of olfactory receptor responses, identity is invariant to changes in both intensity and monotonic nonlinear transformations of its neuronal responses. Here we show that sparse vectors representing odorant mixtures can be recovered in a compressed sensing framework via elastic net loss minimization. In the primacy model, this minimization is performed under the constraint that some receptors respond to a given odorant more strongly than others. Using duality transformation, we show that this constrained optimization problem can be solved by a neural network whose Lyapunov function represents the dual Lagrangian and whose neural responses represent the Lagrange coefficients of primacy and other constraints. The connectivity in such a dual network resembles known features of connectivity in olfactory circuits. We thus propose that networks in the piriform cortex implement dual computations to compute odorant identity with the sparse activities of individual neurons representing Lagrange coefficients. More generally, we propose that sparse neuronal firing rates may represent Lagrange multipliers, which we call the dual brain hypothesis. We show such a formulation is well suited to solve problems with multiple interacting relative constraints.

PURPOSE/OBJECTIVE:To investigate how high-permittivity materials (HPMs) can improve SNR when placed between MR detectors and the imaged body. METHODS:We used a simulation framework based on dyadic Green's functions to calculate the electromagnetic field inside a uniform dielectric sphere at 7 Tesla, with and without a surrounding layer of HPM. SNR-optimizing (ideal) current patterns were expressed as the sum of signal-optimizing (signal-only) current patterns and dark mode current patterns that minimize sample noise while contributing nothing to signal. We investigated how HPM affects the shape and amplitude of these current patterns, sample noise, and array SNR. RESULTS:Ideal and signal-only current patterns were identical for a central voxel. HPMs introduced a phase shift into these patterns, compensating for signal propagation delay in the HPMs. For an intermediate location within the sphere, dark mode current patterns were present and illustrated the mechanisms by which HPMs can reduce sample noise. High-amplitude signal-only current patterns were observed for HPM configurations that shield the electromagnetic field from the sample. For coil arrays, these configurations corresponded to poor SNR in deep regions but resulted in large SNR gains near the surface due to enhanced fields in the vicinity of the HPM. For very high relative permittivity values, HPM thicknesses corresponding to even multiples of λ/4 resulted in coil SNR gains throughout the sample. CONCLUSION/CONCLUSIONS:HPMs affect both signal sensitivity and sample noise. Lower amplitude signal-only optimal currents corresponded to higher array SNR performance and could guide the design of coils integrated with HPM.

Introduction: Obstructive sleep apnea (OSA) is a common sleep disorder associated with inconsistent cognitive consequences. Spatial disorientation increases with age and is an early sign of cognitive dysfunction in Alzheimer disease (AD). Sleep and related EEG oscillations, slow wave activity (SWA) and slow oscillations (SOs), are important for processing spatial memories, however it is not known if OSA-related sleep disruption effects spatial navigational memory processing in older adults.
Method(s): 42 older (age=66.5+/-7.9 years, 54.8% female) cognitively normal adults were recruited from the community. Participants performed timed trials on a 3D spatial maze navigational task and psychomotor vigilance test (PVT), before and after polysomnography (PSG). Maze completion time, PVT, sleep EEG macro and microstructure measures were compared between participants with and without OSA (AHI4%>=5.0/hour). Associations between sleep EEG microstructure (relative SWA (0.5-4Hz) & SOs (<1Hz) spectral power) and maze completion times were explored separately according to OSA diagnosis.
Result(s): Median AHI4% was 0.5/hour in those without OSA(n=30) and 10.7/hour in OSA(n=12). N1 sleep was significantly increased and N2 significantly decreased with OSA. No significant group differences in SWS, REM sleep or PVT performance were observed. There were no significant groups differences in pre-sleep maze completion time, whereas post-sleep maze performance was significantly different. On average participants without OSA continued to improve maze completion time across 3 morning trials whereas participants with OSA performed best on the first morning trial and performed worse on average with each subsequent trial (significant interaction between OSA group and morning trial number, p=0.016, Two Way Repeated Measures ANOVA). There were no significant differences in EEG microstructure observed between groups but in OSA, post-sleep maze performance showed a significant negative association with <1Hz spectral power at frontal (-0.78, p=0.007), central (-0.8, p=0.005) and occipital EEG (-0.71, p=0.02) during SWS.
Conclusion(s): Cognitively normal older adults with mild OSA demonstrated significantly worse morning spatial navigation performance compared to individuals without OSA after equivalent evening encoding. The associations between greater SOs and worse morning maze performance in OSA require replication

The sensitivity of multiple diffusion MRI (dMRI) parameters to longitudinal changes in white matter microstructure was investigated for the 3xTg-AD transgenic mouse model of Alzheimer's disease, which manifests both amyloid beta plaques and neurofibrillary tangles. By employing a specific dMRI method known as diffusional kurtosis imaging, eight different diffusion parameters were quantified to characterize distinct aspects of water diffusion. Four female 3xTg-AD mice were imaged at five time points, ranging from 4.5 to 18 months of age, and the diffusion parameters were investigated in four white matter regions (fimbria, external capsule, internal capsule and corpus callosum). Significant changes were observed in several diffusion parameters, particularly in the fimbria and in the external capsule, with a statistically significant decrease in diffusivity and a statistically significant increase in kurtosis. Our preliminary results demonstrate that dMRI can detect microstructural changes in white matter for the 3xTg-AD mouse model due to aging and/or progression of pathology, depending strongly on the diffusion parameter and anatomical region.

OBJECTIVE:The orofacial primary motor cortex (MIo) plays a critical role in controlling tongue and jaw movements during oral motor functions, such as chewing, swallowing and speech. However, the neural mechanisms of MIo during naturalistic feeding are still poorly understood. There is a strong need for a systematic study of motor cortical dynamics during feeding behavior. APPROACH/METHODS:To investigate the neural dynamics and variability of MIo neuronal activity during naturalistic feeding, we used chronically implanted micro-electrode arrays to simultaneously recorded ensembles of neuronal activity in MIo of two monkeys (Macaca mulatta) while eating various types of food. We developed a Bayesian nonparametric latent variable model to reveal latent structures of neuronal population activity of MIo and identify the complex mapping between MIo ensemble spike activity and high-dimensional kinematics. MAIN RESULTS/RESULTS:Rhythmic neuronal firing patterns and oscillatory dynamics are evident in single-unit activity. At the population level, we uncovered the neural dynamics of rhythmic chewing, and quantified the neural variability at multiple timescales (complete feeding sequences, chewing sequence stages, chewing gape cycle phases) across food types. Our approach accommodates time-warping of chewing sequences and automatic model selection, and maps the latent states to chewing behaviors at fine timescales. SIGNIFICANCE/CONCLUSIONS:Our work shows that neural representations of MIo ensembles display spatiotemporal patterns in chewing gape cycles at different chew sequence stages, and these patterns vary in a stage-dependent manner. Unsupervised learning and decoding analysis may reveal the link between complex MIo spatiotemporal patterns and chewing kinematics.

A Quick guide to singing mice.