Natural biological enzymes possess catalytic sites that are generally surrounded by a large three-dimensional scaffold. However, the proportion of the protein molecule that participates in the ...catalytic reaction is relatively small. The generation of artificial or miniature enzymes has long been a focus of research because enzyme mimetics can be produced with high activity at low cost. These enzymes aim to mimic the active sites without the additional architecture contributed by the protein chain. Previous work has shown that amyloidogenic peptides are able to self-assemble to create an active site that is capable of binding zinc and catalysing an esterase reaction. Here, we describe the structural characterisation of a set of designed peptides that form an amyloid-like architecture and reveal that their capability to mimic carbonic anhydrase and serve as enzyme-like catalysts is related to their ability to self-assemble. These amyloid fibril structures can bind the metal ion Zn
via a three-dimensional arrangement of His residues created by the amyloid architecture. Our results suggest that the catalytic efficiency of amyloid-like assembly is not only zinc-dependent but also depends on an active centre created by the peptides which is, in turn, dependent on the ordered architecture. These fibrils have good esterase activity, and they may serve as good models for the evolution of modern-day enzymes. Furthermore, they may be useful in designing self-assembling fibrils for applications as metal ion catalysts. This study also demonstrates that the ligands surrounding the catalytic site affect the affinity of the zinc-binding site to bind the substrate contributing to the enzymatic activity of the assembled peptides.
Recent theoretical and empirical work has focused on the variability of network dynamics in maturation. Such variability seems to reflect the spontaneous formation and dissolution of different ...functional networks. We sought to extend these observations into healthy aging. Two different data sets, one EEG (total n = 48, ages 18-72) and one magnetoencephalography (n = 31, ages 20-75) were analyzed for such spatiotemporal dependency using multiscale entropy (MSE) from regional brain sources. In both data sets, the changes in MSE were timescale dependent, with higher entropy at fine scales and lower at more coarse scales with greater age. The signals were parsed further into local entropy, related to information processed within a regional source, and distributed entropy (information shared between two sources, i.e., functional connectivity). Local entropy increased for most regions, whereas the dominant change in distributed entropy was age-related reductions across hemispheres. These data further the understanding of changes in brain signal variability across the lifespan, suggesting an inverted U-shaped curve, but with an important qualifier. Unlike earlier in maturation, where the changes are more widespread, changes in adulthood show strong spatiotemporal dependence.
Many neutron star properties, such as the proton fraction, reflect the symmetry energy contributions to the equation of state that dominate when neutron and proton densities differ strongly. To ...constrain these contributions at suprasaturation densities, we measure the spectra of charged pions produced by colliding rare isotope tin (Sn) beams with isotopically enriched Sn targets. Using ratios of the charged pion spectra measured at high transverse momenta, we deduce the slope of the symmetry energy to be 42<L<117 MeV. This value is slightly lower but consistent with the L values deduced from a recent measurement of the neutron skin thickness of ^{208}Pb.
We study neutron-proton equilibration in dynamically deformed atomic nuclei created in nuclear collisions. The two ends of the elongated nucleus are initially dissimilar in composition and ...equilibrate on a subzeptosecond time scale following first-order kinetics. We use angular momentum to relate the breakup orientation to the time scale of the breakup. The extracted rate constant is 3 zs^{-1}, which corresponds to a mean equilibration time of 0.3 zs. This technique enables new insight into the nuclear equation of state that governs many nuclear and astrophysical phenomena leading to the origin of the chemical elements.
Bilayers composed of phosphatidylcholine (PC), sphingomyelin (SM), and cholesterol (CHOL) are commonly used as systems to model the raft-lipid domain structure believed to compartmentalize particular ...cell membrane proteins. In this work, micropipette aspiration of giant unilamellar vesicles was used to test the elasticities, water permeabilities, and rupture tensions of single-component PC, binary 1:1 PC/CHOL, and 1:1 SM/CHOL, and ternary 1:1:1 PC/SM/CHOL bilayers, one set of measurements with dioleoyl PC (DOPC; C18:1/C18:1 PC) and the other with stearoyloleoyl PC (SOPC; C18:0/C18:1 PC). Defining the elastic moduli (KA), the initial slopes of the increase in tension (σ) versus stretch in lipid surface area (αe) were determined for all systems at low (15°C) and high (32–33°C) temperatures. The moduli for the single-component PC and binary phospholipid/CHOL bilayers followed a descending hierarchy of stretch resistance with SM/CHOL>SOPC/CHOL>DOPC/CHOL>PC. Although much more resistant to stretch than the single-component PC bilayers, the elastic response of vesicle bilayers made from the ternary phospholipid/CHOL mixtures showed an abrupt softening (discontinuity in slope), when immediately subjected to a steady ramp of tension at the low temperature (15°C). However, the discontinuities in elastic stretch resistance at low temperature vanished when the bilayers were held at ∼1mN/m prestress for long times before a tension ramp and when tested at the higher temperature 32–33°C. The elastic moduli of single-component PC and DOPC/CHOL bilayers changed very little with temperature, whereas the moduli of the binary SOPC/CHOL and SM/CHOL bilayers diminished markedly with increase in temperature, as did the ternary SOPC/SM/CHOL system. For all systems, increasing temperature increased the water permeability but decreased rupture tension. Concomitantly, the measurements of permeability exhibited a prominent correlation with the rupture tension across all the systems. Together, these micromechanical tests of binary and ternary phospholipid/CHOL bilayers demonstrate that PC hydrocarbon chain unsaturation and temperature are major determinants of the mechanical and permeation properties of membranes composed of raft microdomain-forming lipids.
Partial least squares (PLS) has proven to be a important multivariate analytic tool for positron emission tomographic and, more recently, event-related potential (ERP) data. The application to ERP ...incorporates the ability to analyze space and time together, a feature that has obvious appeal for event-related functional magnetic resonance imaging (fMRI) data. This paper presents the extension of spatiotemporal PLS (ST-PLS) to fMRI, explaining the theoretical foundation and application to an fMRI study of auditory and visual perceptual memory. Analysis of activation effects with ST-PLS was compared with conventional univariate random effects analysis, showing general consensus for both methods, but several unique observations by ST-PLS, including enhanced statistical power. The application of ST-PLS for assessment of task-dependent brain–behavior relationships is also presented. Singular features of ST-PLS include (1) no assumptions about the shape of the hemodynamic response functions (HRFs); (2) robust statistical assessment at the image level through permutation tests; (3) protection against outlier influences at the voxel level through bootstrap resampling; (4) flexible analytic configurations that allow assessment of activation difference, brain–behavior relations, and functional connectivity. These features enable ST-PLS to act as an important complement to other multivariate and univariate approaches used in neuroimaging research.
The introduction of cyclosporine has resulted in improvement in the short-term outcome of renal transplantation, but its effect on the long-term survival of kidney transplants is not known.
We ...analyzed the influence of demographic characteristics (age, sex, and race), transplant-related variables (living or cadaveric donor, panel-reactive antibody titer, extent of HLA matching, and cold-ischemia time), and post-transplantation variables (presence or absence of acute rejection, delayed graft function, and therapy with mycophenolate mofetil and tacrolimus) on graft survival for all 93,934 renal transplantations performed in the United States between 1988 and 1996. A regression analysis adjusted for these variables was used to estimate the risk of graft failure within the first year and more than one year after transplantation.
From 1988 to 1996, the one-year survival rate for grafts from living donors increased from 88.8 to 93.9 percent, and the rate for cadaveric grafts increased from 75.7 to 87.7 percent. The half-life for grafts from living donors increased steadily from 12.7 to 21.6 years, and that for cadaveric grafts increased from 7.9 to 13.8 years. After censoring of data for patients who died with functioning grafts, the half-life for grafts from living donors increased from 16.9 years to 35.9 years, and that for cadaveric grafts increased from 11.0 years to 19.5 years. The average yearly reduction in the relative hazard of graft failure after one year was 4.2 percent for all recipients (P<0.001), 0.4 percent for those who had acute rejection (P=0.57), and 6.3 percent for those who did not have acute rejection (P<0.001).
Since 1988, there has been a substantial increase in short-term and long-term survival of kidney grafts from both living and cadaveric donors.
The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to ...analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.
Three structural classes of (1-->3)-beta-D-glucans are encountered in some important soil-dwelling, plant-associated or human pathogenic bacteria. Linear (1-->3)-beta-glucans and side-chain-branched ...(1-->3,1-->2)-beta-glucans are major constituents of capsular materials, with roles in bacterial aggregation, virulence and carbohydrate storage. Cyclic (1-->3,1-->6)-beta-glucans are predominantly periplasmic, serving in osmotic adaptation. Curdlan, the linear (1-->3)-beta-glucan from Agrobacterium, has unique rheological and thermal gelling properties, with applications in the food industry and other sectors. This review includes information on the structure, properties and molecular genetics of the bacterial (1-->3)-beta-glucans, together with an overview of the physiology and biotechnology of curdlan production and applications of this biopolymer and its derivatives.
Accurate automated infarct segmentation is needed for acute ischemic stroke studies relying on infarct volumes as an imaging phenotype or biomarker that require large numbers of subjects. This study ...investigated whether an ensemble of convolutional neural networks trained on multiparametric DWI maps outperforms single networks trained on solo DWI parametric maps.
Convolutional neural networks were trained on combinations of DWI, ADC, and low b-value-weighted images from 116 subjects. The performances of the networks (measured by the Dice score, sensitivity, and precision) were compared with one another and with ensembles of 5 networks. To assess the generalizability of the approach, we applied the best-performing model to an independent Evaluation Cohort of 151 subjects. Agreement between manual and automated segmentations for identifying patients with large lesion volumes was calculated across multiple thresholds (21, 31, 51, and 70 cm
).
An ensemble of convolutional neural networks trained on DWI, ADC, and low b-value-weighted images produced the most accurate acute infarct segmentation over individual networks (
< .001). Automated volumes correlated with manually measured volumes (Spearman ρ = 0.91,
< .001) for the independent cohort. For the task of identifying patients with large lesion volumes, agreement between manual outlines and automated outlines was high (Cohen κ, 0.86-0.90;
< .001).
Acute infarcts are more accurately segmented using ensembles of convolutional neural networks trained with multiparametric maps than by using a single model trained with a solo map. Automated lesion segmentation has high agreement with manual techniques for identifying patients with large lesion volumes.
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