The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.
If you have any questions or comments, please contact us.
We sought to replicate previous findings that low endogenous opioid (EO) function predicts greater morphine analgesia and extended these findings by examining whether circulating endocannabinoids and related lipids moderate EO-related predictive effects. Individuals with chronic low-back pain (n = 46) provided blood samples for endocannabinoid analyses, then underwent separate identical laboratory sessions under 3 drug conditions: saline placebo, intravenous (i.v.) naloxone (opioid antagonist; 12-mg total), and i.v. morphine (0.09-mg/kg total). During each session, participants rated low-back pain intensity, evoked heat pain intensity, and nonpain subjective effects 4 times in sequence after incremental drug dosing. Mean morphine effects (morphine-placebo difference) and opioid blockade effects (naloxone-placebo difference; to index EO function) for each primary outcome (low-back pain intensity, evoked heat pain intensity, and nonpain subjective effects) were derived by averaging across the 4 incremental doses. The association between EO function and morphine-induced back pain relief was significantly moderated by endocannabinoids [2-arachidonoylglycerol (2-AG) and N-arachidonoylethanolamine (AEA)]. Lower EO function predicted greater morphine analgesia only for those with relatively lower endocannabinoids. Endocannabinoids also significantly moderated EO effects on morphine-related changes in visual analog scale-evoked pain intensity (2-AG), drug liking (AEA and 2-AG), and desire to take again (AEA and 2-AG). In the absence of significant interactions, lower EO function predicted significantly greater morphine analgesia (as in past work) and euphoria. Results indicate that EO effects on analgesic and subjective responses to opioid medications are greatest when endocannabinoid levels are low. These findings may help guide development of mechanism-based predictors for personalized pain medicine algorithms.
Computational protein design has been successful in modeling fixed backbone proteins in a single conformation. However, when modeling large ensembles of flexible proteins, current methods in protein design have been insufficient. Large barriers in the energy landscape are difficult to traverse while redesigning a protein sequence, and as a result current design methods only sample a fraction of available sequence space. We propose a new computational approach that combines traditional structure-based modeling using the Rosetta software suite with machine learning and integer linear programming to overcome limitations in the Rosetta sampling methods. We demonstrate the effectiveness of this method, which we call BROAD, by benchmarking the performance on increasing predicted breadth of anti-HIV antibodies. We use this novel method to increase predicted breadth of naturally-occurring antibody VRC23 against a panel of 180 divergent HIV viral strains and achieve 100% predicted binding against the panel. In addition, we compare the performance of this method to state-of-the-art multistate design in Rosetta and show that we can outperform the existing method significantly. We further demonstrate that sequences recovered by this method recover known binding motifs of broadly neutralizing anti-HIV antibodies. Finally, our approach is general and can be extended easily to other protein systems. Although our modeled antibodies were not tested in vitro, we predict that these variants would have greatly increased breadth compared to the wild-type antibody.
BACKGROUND - Working memory (WM) is often assessed with serial order tests such as repeating digits backward. In prior dementia research using the Backward Digit Span Test (BDT), only aggregate test performance was examined.
OBJECTIVE - The current research tallied primacy/recency effects, out-of-sequence transposition errors, perseverations, and omissions to assess WM deficits in patients with mild cognitive impairment (MCI).
METHODS - Memory clinic patients (n = 66) were classified into three groups: single domain amnestic MCI (aMCI), combined mixed domain/dysexecutive MCI (mixed/dys MCI), and non-MCI where patients did not meet criteria for MCI. Serial order/WM ability was assessed by asking participants to repeat 7 trials of five digits backwards. Serial order position accuracy, transposition errors, perseverations, and omission errors were tallied.
RESULTS - A 3 (group)×5 (serial position) repeated measures ANOVA yielded a significant group×trial interaction. Follow-up analyses found attenuation of the recency effect for mixed/dys MCI patients. Mixed/dys MCI patients scored lower than non-MCI patients for serial position 3 (p < 0.003) serial position 4 (p < 0.002); and lower than both group for serial position 5 (recency; p < 0.002). Mixed/dys MCI patients also produced more transposition errors than both groups (p < 0.010); and more omissions (p < 0.020), and perseverations errors (p < 0.018) than non-MCI patients.
CONCLUSIONS - The attenuation of a recency effect using serial order parameters obtained from the BDT may provide a useful operational definition as well as additional diagnostic information regarding working memory deficits in MCI.
BACKGROUND - Systemic inflammation and muscle wasting are highly prevalent and coexist in patients on maintenance hemodialysis (MHD). We aimed to determine the effects of systemic inflammation on skeletal muscle protein metabolism in MHD patients.
METHODS - Whole body and skeletal muscle protein turnover were assessed by stable isotope kinetic studies. We incorporated expressions of E1, E214K, E3αI, E3αII, MuRF-1, and atrogin-1 in skeletal muscle tissue from integrin β1 gene KO CKD mice models.
RESULTS - Among 129 patients with mean (± SD) age 47 ± 12 years, 74% were African American, 73% were male, and 22% had diabetes mellitus. Median high-sensitivity C-reactive protein (hs-CRP) concentration was 13 (interquartile range 0.8, 33) mg/l. There were statistically significant associations between hs-CRP and forearm skeletal muscle protein synthesis, degradation, and net forearm skeletal muscle protein balance (P < 0.001 for all). The associations remained statistically significant after adjustment for clinical and demographic confounders, as well as in sensitivity analysis, excluding patients with diabetes mellitus. In attempting to identify potential mechanisms involved in this correlation, we show increased expressions of E1, E214K, E3αI, E3αII, MuRF-1, and atrogin-1 in skeletal muscle tissue obtained from an animal model of chronic kidney disease.
CONCLUSION - These data suggest that systemic inflammation is a strong and independent determinant of skeletal muscle protein homeostasis in MHD patients, providing rationale for further studies using anticytokine therapies in patients with underlying systemic inflammation.
FUNDING - This study was in part supported by NIH grants R01 DK45604 and 1K24 DK62849, the Clinical Translational Science Award UL1-TR000445 from the National Center for Advancing Translational Sciences, the Veterans Administration Merit Award I01 CX000414, the SatelliteHealth Normon Coplon Extramural Grant Program, and the FDA grant 000943.
PURPOSE - To evaluate the magnitude of chemical exchange effects and R dispersion in muscle and their relationship to tissue sodium levels with aging.
METHODS - Seven healthy volunteers (aged 24 to 87years, median age 47) underwent MRI to assess tissue sodium levels and water T values at different spin-locking frequencies in calf muscles. T values at each locking field were computed based on a three-parameter mono-exponential model to fit signals obtained at different locking times, and R (=1/T) rates were compared at different locking fields. In particular, the dispersion of R (ΔR=R(0Hz)-R(500Hz)) was examined as a function of subject age. Muscle sodium content was calculated by comparing signal intensities between tissues and reference standards within the same image. The variations of ΔR with age and sodium were analyzed by linear regression.
RESULTS - T values and sodium content both increased with age. R dispersion also increased with age and showed a strong linear correlation (correlation coefficient r=0.98, P=0.000578) with sodium content.
CONCLUSION - ΔR reports on the contribution of labile protons such as hydroxyls which may be associated with macromolecule accumulation in the extracellular matrix (ECM). An increase of sodium signal suggests an enlarged ECM volume fraction and/or an increase in sodium concentration, which occurs during normal aging. The strong correlation between ΔR and sodium is likely the consequence of increased ECM and density of total charged sites within the matrix from molecules such as collagens and proteoglycans. The results from this study show the potential use of R dispersion and sodium imaging in the assessment of pathological changes in muscle such as fibrosis.
Copyright © 2017 Elsevier Inc. All rights reserved.
To assess the effect of chemotherapy on mitochondrial genome mutations in cancer survivors and their offspring, a study sequenced the full mitochondrial genome and determined the mitochondrial DNA heteroplasmic (mtDNA) mutation rate. To build a model for counts of heteroplasmic mutations in mothers and their offspring, bivariate Poisson regression was used to examine the relationship between mutation count and clinical information while accounting for the paired correlation. However, if the sequencing depth is not adequate, a limited fraction of the mtDNA will be available for variant calling. The classical bivariate Poisson regression model treats the offset term as equal within pairs; thus, it cannot be applied directly. In this research, we propose an extended bivariate Poisson regression model that has a more general offset term to adjust the length of the accessible genome for each observation. We evaluate the performance of the proposed method with comprehensive simulations, and the results show that the regression model provides unbiased parameter estimations. The use of the model is also demonstrated using the paired mtDNA dataset.
Understanding brain volumetry is essential to understand neurodevelopment and disease. Historically, age-related changes have been studied in detail for specific age ranges (e.g., early childhood, teen, young adults, elderly, etc.) or more sparsely sampled for wider considerations of lifetime aging. Recent advancements in data sharing and robust processing have made available considerable quantities of brain images from normal, healthy volunteers. However, existing analysis approaches have had difficulty addressing (1) complex volumetric developments on the large cohort across the life time (e.g., beyond cubic age trends), (2) accounting for confound effects, and (3) maintaining an analysis framework consistent with the general linear model (GLM) approach pervasive in neuroscience. To address these challenges, we propose to use covariate-adjusted restricted cubic spline (C-RCS) regression within a multi-site cross-sectional framework. This model allows for flexible consideration of non-linear age-associated patterns while accounting for traditional covariates and interaction effects. As a demonstration of this approach on lifetime brain aging, we derive normative volumetric trajectories and 95% confidence intervals from 5111 healthy patients from 64 sites while accounting for confounding sex, intracranial volume and field strength effects. The volumetric results are shown to be consistent with traditional studies that have explored more limited age ranges using single-site analyses. This work represents the first integration of C-RCS with neuroimaging and the derivation of structural covariance networks (SCNs) from a large study of multi-site, cross-sectional data.
The 2-component leukotoxin LukAB is critical for Staphylococcus aureus targeting and killing of human neutrophils ex vivo and is produced in the setting of human infection. We report 3 LukAB-specific human monoclonal antibodies (mAbs) with distinct mechanisms of toxin neutralization and in vivo efficacy. Three hybridomas secreting mAbs with anti-LukAB activity (designated SA-13, -15, and -17) were generated from B cells obtained from a 12-year-old boy with S. aureus osteomyelitis. Each of the 3 mAbs neutralized LukAB-mediated neutrophil toxicity, exhibited differing levels of potency, recognized different antigenic sites on the toxin, and displayed at least 2 distinct mechanisms for cytotoxic inhibition. SA-15 bound exclusively to the dimeric form of the toxin, suggesting that human B cells recognize epitopes on the dimerized form of LukAB during natural infection. Both SA-13 and SA-17 bound the LukA monomer and the LukAB dimer. Although all 3 mAbs potently neutralized cytotoxicity, only SA-15 and SA-17 significantly inhibited toxin association with the cell surface. Treatment with a 1:1 mixture of mAbs SA-15 and SA-17 resulted in significantly lower bacterial colony counts in heart, liver, and kidneys in a murine model of S. aureus sepsis. These data describe the isolation of diverse and efficacious antitoxin mAbs.
© The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: firstname.lastname@example.org.
INTRODUCTION - Deep brain stimulation (DBS) is an established therapy for movement disorders, and is under active investigation for other neurologic and psychiatric indications. While many studies describe outcomes and complications related to stimulation therapies, the majority of these are from large academic centers, and results may differ from those in general neurosurgical practice.
METHODS - Using data from both the Centers for Medicare and Medicaid Services (CMS) and the National Surgical Quality Improvement Program (NSQIP), we identified all DBS procedures related to primary placement, revision, or removal of intracranial electrodes. Cases of cortical stimulation and stimulation for epilepsy were excluded.
RESULTS - Over 28,000 cases of DBS electrode placement, revision, and removal were identified during the years 2004-2013. In the Medicare dataset, 15.2% and of these procedures were for intracranial electrode revision or removal, compared to 34.0% in the NSQIP dataset. In NSQIP, significant predictors of revision and removal were decreased age (odds ratio (OR) of 0.96; 95% CI: 0.94, 0.98) and higher ASA classification (OR 2.41; 95% CI: 1.22, 4.75). Up to 48.5% of revisions may have been due to improper targeting or lack of therapeutic effect.
CONCLUSION - Data from multiple North American databases suggest that intracranial neurostimulation therapies have a rate of revision and removal higher than previously reported, between 15.2 and 34.0%. While there are many limitations to registry-based studies, there is a clear need to better track and understand the true prevalence and nature of such failures as they occur in the wider surgical community.
Copyright © 2016 Elsevier Ltd. All rights reserved.
A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation coefficients that exhibit substantial heterogeneity, some of which obscures the relationships between the constructs of interest or undermines the comparability of the correlations across the cells. One component of this approach is a three-level random effects model capable of synthesizing a pooled correlation matrix with dependent correlation coefficients. Another component is a meta-regression that can be used to generate covariate-adjusted correlation coefficients that reduce the influence of selected unevenly distributed moderator variables. A non-technical presentation of these techniques is given, along with an illustration of the procedures with a meta-analytic dataset. Copyright © 2016 John Wiley & Sons, Ltd.
Copyright © 2016 John Wiley & Sons, Ltd.