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Single particle tracking (SPT) experiments have provided the scientific community with invaluable single-molecule information about the dynamic regulation of individual receptors, transporters, kinases, lipids, and molecular motors. SPT is an alternative to ensemble averaging approaches, where heterogeneous modes of motion might be lost. Quantum dots (QDs) are excellent probes for SPT experiments due to their photostability, high brightness, and size-dependent, narrow emission spectra. In a typical QD-based SPT experiment, QDs are bound to the target of interest and imaged for seconds to minutes via fluorescence video microscopy. Single QD spots in individual frames are then linked to form trajectories that are analyzed to determine their mean square displacement, diffusion coefficient, confinement index, and instantaneous velocity. This chapter describes a generalizable protocol for the single particle tracking of membrane neurotransmitter transporters on cell membranes with either unmodified extracellular antibody probes and secondary antibody-conjugated quantum dots or biotinylated extracellular antibody probes and streptavidin-conjugated quantum dots in primary neuronal cultures. The neuronal cell culture, the biotinylation protocol and the quantum dot labeling procedures, as well as basic data analysis are discussed.
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.
OBJECTIVE - The dopamine D2/3 receptor subtypes (DRD2/3) are the most widely studied neurotransmitter biomarker in research on obesity, but results to date have been inconsistent, have typically involved small samples, and have rarely accounted for subjects' ages despite the large impact of age on DRD2/3 levels. We aimed to clarify the relation between DRD2/3 availability and BMI by examining this association in a large sample of subjects with BMI spanning the continuum from underweight to extremely obese.
SUBJECTS - 130 healthy subjects between 18 and 81years old underwent PET with [18F]fallypride, a high affinity DRD2/3 ligand.
RESULTS - As expected, DRD2/3 availability declined with age. Critically, age significantly interacted with DRD2/3 availability in predicting BMI in the midbrain and striatal regions (caudate, putamen, and ventral striatum). Among subjects under 30years old, BMI was not associated with DRD2/3 availability. By contrast, among subjects over 30years old, BMI was positively associated with DRD2/3 availability in the midbrain, putamen, and ventral striatum.
CONCLUSION - The present results are incompatible with the prominent dopaminergic hypofunction hypothesis that proposes that a reduction in DRD2/3 availability is associated with increased BMI, and highlights the importance of age in assessing correlates of DRD2/3 function.
Copyright © 2016 Elsevier Inc. All rights reserved.
BACKGROUND - Conservative fluid management increases ventilator-free days without influencing overall mortality in acute respiratory distress syndrome. Plasma concentrations of B-type natriuretic peptide (a marker of ventricular filling) or aldosterone (a marker of effective circulating volume) may identify patients for whom fluid management impacts survival.
METHODS - This was a retrospective analysis of the Fluid and Catheter Treatment Trial (FACTT), a randomized trial comparing conservative with liberal fluid management in acute respiratory distress syndrome. Using plasma collected at study enrollment, we measured B-type natriuretic peptide and aldosterone by immunoassay. Multivariable analyses examined the interaction between B-type natriuretic peptide or aldosterone concentration and fluid strategy with regard to 60-day in-hospital mortality.
RESULTS - Among 625 patients with adequate plasma, median B-type natriuretic peptide concentration was 825 pg/mL (interquartile range, 144-1,574 pg/mL), and median aldosterone was 2.49 ng/dL (interquartile range, 1.1-4.3 ng/dL). B-type natriuretic peptide did not predict overall mortality, correlate with fluid balance, or modify the effect of conservative vs liberal fluid management on outcomes. In contrast, among patients with lower aldosterone concentrations, conservative fluid management increased ventilator-free days (17.1 ± 9.8 vs 12.5 ± 10.3, P < .001) and decreased mortality (19% vs 30%, P = .03) (P value for interaction = .01).
CONCLUSIONS - In acute respiratory distress syndrome, B-type natriuretic peptide does not modify the effect of fluid management on outcomes. Lower initial aldosterone appears to identify patients for whom conservative fluid management may improve mortality.
Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
Are face and object recognition abilities independent? Although it is commonly believed that they are, Gauthier et al. [Gauthier, I., McGugin, R. W., Richler, J. J., Herzmann, G., Speegle, M., & VanGulick, A. E. Experience moderates overlap between object and face recognition, suggesting a common ability. Journal of Vision, 14, 7, 2014] recently showed that these abilities become more correlated as experience with nonface categories increases. They argued that there is a single underlying visual ability, v, that is expressed in performance with both face and nonface categories as experience grows. Using the Cambridge Face Memory Test and the Vanderbilt Expertise Test, they showed that the shared variance between Cambridge Face Memory Test and Vanderbilt Expertise Test performance increases monotonically as experience increases. Here, we address why a shared resource across different visual domains does not lead to competition and to an inverse correlation in abilities? We explain this conundrum using our neurocomputational model of face and object processing ["The Model", TM, Cottrell, G. W., & Hsiao, J. H. Neurocomputational models of face processing. In A. J. Calder, G. Rhodes, M. Johnson, & J. Haxby (Eds.), The Oxford handbook of face perception. Oxford, UK: Oxford University Press, 2011]. We model the domain general ability v as the available computational resources (number of hidden units) in the mapping from input to label and experience as the frequency of individual exemplars in an object category appearing during network training. Our results show that, as in the behavioral data, the correlation between subordinate level face and object recognition accuracy increases as experience grows. We suggest that different domains do not compete for resources because the relevant features are shared between faces and objects. The essential power of experience is to generate a "spreading transform" for faces (separating them in representational space) that generalizes to objects that must be individuated. Interestingly, when the task of the network is basic level categorization, no increase in the correlation between domains is observed. Hence, our model predicts that it is the type of experience that matters and that the source of the correlation is in the fusiform face area, rather than in cortical areas that subserve basic level categorization. This result is consistent with our previous modeling elucidating why the FFA is recruited for novel domains of expertise [Tong, M. H., Joyce, C. A., & Cottrell, G. W. Why is the fusiform face area recruited for novel categories of expertise? A neurocomputational investigation. Brain Research, 1202, 14-24, 2008].
BACKGROUND - Bloodstream infection (BSI) among neonatal intensive care unit (NICU) infants is a frequent problem associated with poor outcomes. Monitoring for abnormal heart rate characteristics (HRCs) may decrease infant mortality by alerting clinicians to sepsis before it becomes clinically apparent.
METHODS - HRC scores were acquired using the HRC (HeRO) monitor system from Medical Predictive Science Corporation and entered into the electronic medical record by bedside staff. We retrospectively analysed HRC scores recorded twice daily in the medical record during a 30-month period (1 January 2010 through 30 June 2012) for infants in the NICU at the Monroe Carell Jr. Children's Hospital at Vanderbilt. We identified infants that met Centers for Disease Control criteria for late-onset BSI (>3 days of life) during the study period.
RESULTS - During the study period, we recorded 127 673 HRC scores from 2384 infants. We identified 46 infants with BSI. Although 8% (9701/127 673) of the HRC scores were ≥2 and 1% (1387/127 673) were ≥5, BSI (at any time) was observed in just 5% of patients with HRC scores ≥2, and 9% of patients with HRC scores ≥5. Of infants with BSI, 5/46 (11%) had at least one HRC score ≥5 and 17/46 (37%) had at least one score ≥2 recorded in the 48 h period prior to the evaluation that resulted in the first positive blood culture of the episode.
CONCLUSIONS - In our single-centre retrospective study, elevated HRC scores had limited ability to detect BSI. BSI was infrequent at any time during hospitalisation in infants with significantly elevated HRC scores.
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Functional magnetic resonance imaging usually detects changes in blood oxygenation level dependent (BOLD) signals from T2*-sensitive acquisitions, and is most effective in detecting activity in brain cortex which is irrigated by rich vasculature to meet high metabolic demands. We recently demonstrated that MRI signals from T2*-sensitive acquisitions in a resting state exhibit structure-specific temporal correlations along white matter tracts. In this report we validate our preliminary findings and introduce spatio-temporal functional correlation tensors to characterize the directional preferences of temporal correlations in MRI signals acquired at rest. The results bear a remarkable similarity to data obtained by diffusion tensor imaging but without any diffusion-encoding gradients. Just as in gray matter, temporal correlations in resting state signals may reflect intrinsic synchronizations of neural activity in white matter. Here we demonstrate that functional correlation tensors are able to visualize long range white matter tracts as well as short range sub-cortical fibers imaged at rest, and that evoked functional activities alter these structures and enhance the visualization of relevant neural circuitry. Furthermore, we explore the biophysical mechanisms underlying these phenomena by comparing pulse sequences, which suggest that white matter signal variations are consistent with hemodynamic (BOLD) changes associated with neural activity. These results suggest new ways to evaluate MRI signal changes within white matter.
Copyright © 2015 Elsevier Inc. All rights reserved.
Diagnosis and management of peripheral nerve injury is complicated by the inability to assess microstructural features of injured nerve fibers via clinical examination and electrophysiology. Diffusion tensor imaging (DTI) has been shown to accurately detect nerve injury and regeneration in crush models of peripheral nerve injury, but no prior studies have been conducted on nerve transection, a surgical emergency that can lead to permanent weakness or paralysis. Acute sciatic nerve injuries were performed microsurgically to produce multiple grades of nerve transection in rats that were harvested 1 hour after surgery. High-resolution diffusion tensor images from ex vivo sciatic nerves were obtained using diffusion-weighted spin-echo acquisitions at 4.7 T. Fractional anisotropy was significantly reduced at the injury sites of transected rats compared with sham rats. Additionally, minor eigenvalues and radial diffusivity were profoundly elevated at all injury sites and were negatively correlated to the degree of injury. Diffusion tensor tractography showed discontinuities at all injury sites and significantly reduced continuous tract counts. These findings demonstrate that high-resolution DTI is a promising tool for acute diagnosis and grading of traumatic peripheral nerve injuries.
A symptom of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is a flat learning profile. Learning slope calculation methods vary, and the optimal method for capturing neuroanatomical changes associated with MCI and early AD pathology is unclear. This study cross-sectionally compared four different learning slope measures from the Rey Auditory Verbal Learning Test (simple slope, regression-based slope, two-slope method, peak slope) to structural neuroimaging markers of early AD neurodegeneration (hippocampal volume, cortical thickness in parahippocampal gyrus, precuneus, and lateral prefrontal cortex) across the cognitive aging spectrum [normal control (NC); (n=198; age=76±5), MCI (n=370; age=75±7), and AD (n=171; age=76±7)] in ADNI. Within diagnostic group, general linear models related slope methods individually to neuroimaging variables, adjusting for age, sex, education, and APOE4 status. Among MCI, better learning performance on simple slope, regression-based slope, and late slope (Trial 2-5) from the two-slope method related to larger parahippocampal thickness (all p-values<.01) and hippocampal volume (p<.01). Better regression-based slope (p<.01) and late slope (p<.01) were related to larger ventrolateral prefrontal cortex in MCI. No significant associations emerged between any slope and neuroimaging variables for NC (p-values ≥.05) or AD (p-values ≥.02). Better learning performances related to larger medial temporal lobe (i.e., hippocampal volume, parahippocampal gyrus thickness) and ventrolateral prefrontal cortex in MCI only. Regression-based and late slope were most highly correlated with neuroimaging markers and explained more variance above and beyond other common memory indices, such as total learning. Simple slope may offer an acceptable alternative given its ease of calculation.
Fluorescence Recovery After Photobleaching (FRAP) has been a versatile tool to study transport and reaction kinetics in live cells. Since the fluorescence data generated by fluorescence microscopy are in a relative scale, a wide variety of scalings and normalizations are used in quantitative FRAP analysis. Scaling and normalization are often required to account for inherent properties of diffusing biomolecules of interest or photochemical properties of the fluorescent tag such as mobile fraction or photofading during image acquisition. In some cases, scaling and normalization are also used for computational simplicity. However, to our best knowledge, the validity of those various forms of scaling and normalization has not been studied in a rigorous manner. In this study, we investigate the validity of various scalings and normalizations that have appeared in the literature to calculate mobile fractions and correct for photofading and assess their consistency with FRAP equations. As a test case, we consider linear or affine scaling of normal or anomalous diffusion FRAP equations in combination with scaling for immobile fractions. We also consider exponential scaling of either FRAP equations or FRAP data to correct for photofading. Using a combination of theoretical and experimental approaches, we show that compatible scaling schemes should be applied in the correct sequential order; otherwise, erroneous results may be obtained. We propose a hierarchical workflow to carry out FRAP data analysis and discuss the broader implications of our findings for FRAP data analysis using a variety of kinetic models.