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Non-Invasive 3D Photoacoustic Tomography of Angiographic Anatomy and Hemodynamics of Fatty Livers in Rats
No full textNon-alcoholic fatty liver disease is the most common liver disorder worldwide, which strongly correlates to obesity, diabetes, and metabolic syndromes. Complementary to mainstream liver diagnostic modalities, photoacoustic tomography (PAT) can provide high-speed images with functional optical contrast. However, PAT has not been demonstrated to study fatty liver anatomy with clear volumetric vasculatures. The livers of multiple rats are non-invasively imaged in vivo using the recently developed 3D PAT platform. The system provides isotropically high spatial resolution in 3D space, presenting clear angiographic structures of rat livers without injecting contrast agents. Furthermore, to quantitatively analyze the difference between the livers of lean and obese rats, the authors measured several PAT features and statistical differences between the two groups are observed. In addition to the anatomy, a time-gated strategy is applied to correct respiration-induced motion artifacts and extracted the hemodynamics of major blood vessels during the breathing cycles. This study demonstrates the capabilities of 3D-PAT to reveal both angiographic anatomy and function in rat livers, providing hematogenous information for fatty liver diagnosis. 3D-PAT, as a new tool for preclinical research, warrants further improvements to be transferred to human pediatric liver imaging
Synthesis of a Systematic 64-Membered Heparan Sulfate Tetrasaccharide Library
No full textHeparan sulfate (HS) has multifaceted biological activities. To date, no libraries of HS oligosaccharides bearing systematically varied sulfation structures are available owing to the challenges in synthesizing a large number of HS oligosaccharides. To overcome the obstacles and expedite the synthesis, a divergent approach was designed, where 64 HS tetrasaccharides covering all possible structures of 2-O-, 6-O- and N-sulfation with the glucosamine-glucuronic acid-glucosamine-iduronic acid backbone were successfully produced from a single strategically protected tetrasaccharide intermediate. This extensive library helped identify the structural requirements for HS sequences to have strong fibroblast growth factor-2 binding but a weak affinity for platelet factor-4. Such a strategy to separate out these two interactions could lead to new HS-based potential therapeutics without the dangerous adverse effect of heparin-induced thrombocytopenia
Weighted ensemble: Recent mathematical developments
No full textWeighted ensemble (WE) is an enhanced sampling method based on periodically replicating and pruning trajectories generated in parallel. WE has grown increasingly popular for computational biochemistry problems due, in part, to improved hardware and accessible software implementations. Algorithmic and analytical improvements have played an important role, and progress has accelerated in recent years. Here, we discuss and elaborate on the WE method from a mathematical perspective, highlighting recent results that enhance the computational efficiency. The mathematical theory reveals a new strategy for optimizing trajectory management that approaches the best possible variance while generalizing to systems of arbitrary dimension
Gazing through the bubble: an experimental investigation into financial risk-taking using eye-tracking
No full textEye tracking can facilitate understanding irrational decision-making in contexts such as financial risk-taking. For this purpose, we develop an experimental framework in which participants trade a risky asset in a simulated bubble market to maximize individual returns while their eye movements are recorded. Returns are sensitive to eye movement dynamics, depending on the presented visual stimuli. Using eye-tracking data, we investigated the effects of arousal, attention, and disengagement on individual payoffs using linear and nonlinear approaches. By estimating a nonlinear model using attention as a threshold variable, our results suggest that arousal positively influences trading returns, but its effect becomes smaller when attention exceeds a certain threshold, whereas disengagement has a higher negative impact on reduced attention levels and becomes almost irrelevant when attention increases. Hence, we provide a neurobehavioral metric as a function of attention that predicts financial gains in boom-and-bust scenarios. This study serves as a proof-of-concept for developing future psychometric measures to enhance decision-making
Early Results from GLASS-JWST. XIII. A Faint, Distant, and Cold Brown Dwarf
No full textWe present the serendipitous discovery of a late T-type brown dwarf candidate in JWST NIRCam observations of the Early Release Science Abell 2744 parallel field. The discovery was enabled by the sensitivity of JWST at 4 μm wavelengths and the panchromatic 0.9–4.5 μm coverage of the spectral energy distribution. The unresolved point source has magnitudes F115W = 27.95 ± 0.15 and F444W = 25.84 ± 0.01 (AB), and its F115W−F444W and F356W−F444W colors match those expected for other known T dwarfs. We can exclude it as a reddened background star, high redshift quasar, or a very high redshift galaxy. Comparison with stellar atmospheric models indicates a temperature of T_(eff) ≈ 650 K and surface gravity log g ≈ 5.25, implying a mass of 0.03 M_⊙ and age of 5 Gyr. We estimate the distance of this candidate to be 570–720 pc in a direction perpendicular to the Galactic plane, making it a likely thick disk or halo brown dwarf. These observations underscore the power of JWST to probe the very low-mass end of the substellar mass function in the Galactic thick disk and halo
Exploring PROTAC Cooperativity with Coarse-Grained Alchemical Methods
No full textProteolysis targeting chimera (PROTAC) is a novel drug modality that facilitates the degradation of a target protein by inducing proximity with an E3 ligase. In this work, we present a new computational framework to model the cooperativity between PROTAC–E3 binding and PROTAC–target binding principally through protein–protein interactions (PPIs) induced by the PROTAC. Due to the scarcity and low resolution of experimental measurements, the physical and chemical drivers of these non-native PPIs remain to be elucidated. We develop a coarse-grained (CG) approach to model interactions in the target–PROTAC–E3 complexes, which enables converged thermodynamic estimations using alchemical free energy calculation methods despite an unconventional scale of perturbations. With minimal parametrization, we successfully capture fundamental principles of cooperativity, including the optimality of intermediate PROTAC linker lengths that originates from configurational entropy. We qualitatively characterize the dependency of cooperativity on PROTAC linker lengths and protein charges and shapes. Minimal inclusion of sequence- and conformation-specific features in our current force field, however, limits quantitative modeling to reproduce experimental measurements, but further development of the CG model may allow for efficient computational screening to optimize PROTAC cooperativity
Massively parallelized interpolated factored Green function method
No full textThis paper presents the first parallel implementation of the novel "Interpolated Factored Green Function" (IFGF) method introduced recently for the accelerated evaluation of discrete integral operators arising in wave scattering and other areas (Bauinger and Bruno, Jour. Computat. Phys., 2021). On the basis of the hierarchical IFGF interpolation strategy, the proposed (hybrid MPI-OpenMP) parallel implementation results in efficient data communication, and it scales up to large numbers of cores—without any hard limitations on the number of cores efficiently employed. Moreover, on any given number of cores, the proposed parallel approach preserves the O(N log N) computing cost inherent in the sequential version of the IFGF algorithm. Unlike other approaches, the IFGF method does not utilize the Fast Fourier Transform (FFT), and it is thus better suited for efficient parallelization in distributed-memory computer systems. In particular, the IFGF method relies on a “peer-to-peer” strategy wherein, at every level, field propagation is directly enacted via “exchanges” between “peer” polynomials of constant degree, without data accumulation in large-scale “telephone-central” mathematical constructs such as those used in the Fast Multipole Method (FMM) and pure FFT-based approaches. A variety of numerical results presented in this paper illustrate the character of the proposed parallel algorithm, in particular demonstrating scaling from 1 to all 1,680 cores available in the High Performance Computing cluster used, and for problems of up to 4,096 wavelengths in acoustic size
Shear properties of MgO inferred using neural networks
No full textShear properties of mantle minerals are vital for interpreting seismic shear wave speeds and therefore inferring the composition and dynamics of a planetary interior. Shear wave speed and elastic tensor components, from which the shear modulus can be computed, are usually measured in the laboratory mimicking the Earth's (or a planet's) internal pressure and temperature conditions. A functional form that relates the shear modulus to pressure (and temperature) is fitted to the measurements and used to interpolate within and extrapolate beyond the range covered by the data. Assuming a functional form provides prior information, and the constraints on the predicted shear modulus and its uncertainties might depend largely on the assumed prior rather than the data. In the present study, we propose a data-driven approach in which we train a neural network to learn the relationship between the pressure, temperature and shear modulus from the experimental data without prescribing a functional form a priori. We present an application to MgO, but the same approach works for any other mineral if there are sufficient data to train a neural network. At low pressures, the shear modulus of MgO is well-constrained by the data. However, our results show that different experimental results are inconsistent even at room temperature, seen as multiple peaks and diverging trends in probability density functions predicted by the network. Furthermore, although an explicit finite-strain equation mostly agrees with the likelihood predicted by the neural network, there are regions where it diverges from the range given by the networks. In those regions, it is the prior assumption of the form of the equation that provides constraints on the shear modulus regardless of how the Earth behaves (or data behave). In situations where realistic uncertainties are not reported, one can become overconfident when interpreting seismic models based on those defined equations of state. In contrast, the trained neural network provides a reasonable approximation to experimental data and quantifies the uncertainty from experimental errors, interpolation uncertainty, data sparsity and inconsistencies from different experiments
Hypersonic flow over spherically blunted cone capsules for atmospheric entry. Part 2. Vibrational non-equilibrium effects
No full textAtmospheric entry capsules shaped as spherically blunted, large apex-angle cones are widely used in space missions. In Part 1 of this study (Hornung, Martinez Schramm & Hannemann, J. Fluid Mech., vol. 871, 2019, pp. 1097–1116) we explored flows over the two elements of the capsule shape, the sphere and the sharp cone with detached shock, theoretically and computationally. Using a large number of inviscid, perfect-gas computations, analytical functions of two independent variables, the normal-shock density ratio ε and a cone-angle parameter η (which is a function of ε and the cone half-angle θ) were found for the dimensionless shock wave stand-off distance and the drag coefficient of a sharp cone. An analytical description was found for the shock stand-off distance in the transition from the 90° cone (flat-faced cylinder) to the sphere. In Part 1, it was speculated that the perfect-gas results have relevance to non-equilibrium situations if the normal-shock density ratio is replaced by the density ratio based on the average density along the stagnation streamline. In Part 2, the investigation is extended to blunted-cone capsule shapes. High-precision force measurements and schlieren image analysis are performed in the High-Enthalpy Shock Tunnel Göttingen (HEG) of the German Aerospace Centre using air as the test gas, at conditions where vibrational non-equilibrium effects are significant. Accordingly, results are compared with viscous numerical predictions using different physico-chemical models. A theoretical model is constructed for the density profile along the stagnation streamline that is determined by the free stream conditions and gives the average density. Comparisons of the experimental and numerical results for the dimensionless shock stand-off distance and the drag coefficient, with the extension of the analytical functions of Part 1 to vibrationally relaxing flow, exhibit very good agreement in all of a range of geometries
Near-horizon quantum dynamics of 4D Einstein gravity from 2D Jackiw-Teitelboim gravity
No full textWe study quantum fluctuations in the light-cone metric of the 4D Einstein-Hilbert action via dimensional reduction to Jackiw-Teitelboim (JT) gravity. In particular, we show that, in Einstein gravity, the causal development of a region in flat Minkowski spacetime, near a horizon defined by light sheets, can be described by an effective two-dimensional dilaton theory. This enables us to make use of known solutions of the JT action, where the spacetime position of a horizon has quantum uncertainty due to metric fluctuations. This quantum uncertainty can be then directly related to the original 4D light-cone coordinates, allowing us to compute the uncertainty in the time of a photon to travel from tip-to-tip of a causal diamond in flat 4D Minkowski space. We find that both Planck and infrared scales (with the latter set by the size of the causal diamond) enter the uncertainty in photon travel time, such that the quantum fluctuation in the arrival time may be observably large