Reliability-Aware Restoration Framework for 4D Spectral Photoacoustic Data.

Spectral photoacoustic imaging (PAI) is a new technology that is able to provide 3D geometric structure associated with 1D wavelength-dependent absorption information of the interior of a target in a non-invasive manner. It has potentially broad applications in clinical and medical diagnosis. Unfortunately, the usability of spectral PAI is severely affected by a time-consuming data scanning process and complex noise. Therefore in this study, we propose a reliability-aware restoration framework to recover clean 4D data from incomplete and noisy observations. To the best of our knowledge, this is the first attempt for the 4D spectral PA data restoration problem that solves data completion and denoising simultaneously. We first present a sequence of analyses, including modeling of data reliability in the depth and spectral domains, developing an adaptive correlation graph, and analyzing local patch orientation. On the basis of these analyses, we explore global sparsity and local self-similarity for restoration. We demonstrated the effectiveness of our proposed approach through experiments on real data captured from patients, where our approach outperformed the state-of-the-art methods in both objective evaluation and subjective assessment.

Specific in situ inflammatory states associate with progression to renal failure in lupus nephritis.

BACKGROUNDIn human lupus nephritis (LN), tubulointerstitial inflammation (TII) on biopsy predicts progression to end-stage renal disease (ESRD). However, only about half of patients with moderate-to-severe TII develop ESRD. We hypothesized that this heterogeneity in outcome reflects different underlying inflammatory states. Therefore, we interrogated renal biopsies from LN longitudinal and cross-sectional cohorts.METHODSData were acquired using conventional and highly multiplexed confocal microscopy. To accurately segment cells across whole biopsies, and to understand their spatial relationships, we developed computational pipelines by training and implementing several deep-learning models and other computer vision techniques.RESULTSHigh B cell densities were associated with protection from ESRD. In contrast, high densities of CD8+, γδ, and other CD4-CD8- T cells were associated with both acute renal failure and progression to ESRD. B cells were often organized into large periglomerular neighborhoods with Tfh cells, while CD4- T cells formed small neighborhoods in the tubulointerstitium, with frequency that predicted progression to ESRD.CONCLUSIONThese data reveal that specific in situ inflammatory states are associated with refractory and progressive renal disease.FUNDINGThis study was funded by the NIH Autoimmunity Centers of Excellence (AI082724), Department of Defense (LRI180083), Alliance for Lupus Research, and NIH awards (S10-OD025081, S10-RR021039, and P30-CA14599).

Estimation of Wetness and Color from a Single Multispectral Image.

Recognizing wet surfaces and their degrees of wetness is essential for many computer vision applications. Surface wetness can inform us slippery spots on a road to autonomous vehicles, muddy areas of a trail to humanoid robots, and the freshness of groceries to us. The fact that surfaces darken when wet, i.e., monochromatic appearance change, has been modeled to recognize wet surfaces in the past. In this paper, we show that color change, particularly in its spectral behavior, carries rich information about surface wetness. We first derive an analytical spectral appearance model of wet surfaces that expresses the characteristic spectral sharpening due to multiple scattering and absorption in the surface. We present a novel method for estimating key parameters of this spectral appearance model, which enables the recovery of the original surface color and the degree of wetness from a single multispectral image. Applied to a multispectral image, the method estimates the spatial map of wetness together with the dry spectral distribution of the surface. To our knowledge, this is the first work to model and leverage the spectral characteristics of wet surfaces to decipher its appearance. We conduct comprehensive experimental validation with a number of wet real surfaces. The results demonstrate the accuracy of our model and the effectiveness of our method for surface wetness and color estimation.

Effects of polymers on the cavitating flow around a cylinder: A large-scale molecular dynamics analysis.

The cavitation flow of linear-polymer solutions around a cylinder is studied by performing a large-scale molecular dynamics simulation. The addition of polymer chains remarkably suppresses cavitation. The polymers are stretched into a linear shape near the cylinder and entrained in the vortex behind the cylinder. As the polymers stretch, the elongational viscosity increases, which suppresses the vortex formation. Furthermore, the polymers exhibit an entropic elasticity owing to stretching. This elastic energy increases the local temperature, which inhibits the cavitation inception. These effects of polymers result in the dramatic suppression of cavitation.

Innate-like self-reactive B cells infiltrate human renal allografts during transplant rejection.

Intrarenal B cells in human renal allografts indicate transplant recipients with a poor prognosis, but how these cells contribute to rejection is unclear. Here we show using single-cell RNA sequencing that intrarenal class-switched B cells have an innate cell transcriptional state resembling mouse peritoneal B1 or B-innate (Bin) cells. Antibodies generated by Bin cells do not bind donor-specific antigens nor are they enriched for reactivity to ubiquitously expressed self-antigens. Rather, Bin cells frequently express antibodies reactive with either renal-specific or inflammation-associated antigens. Furthermore, local antigens can drive Bin cell proliferation and differentiation into plasma cells expressing self-reactive antibodies. These data show a mechanism of human inflammation in which a breach in organ-restricted tolerance by infiltrating innate-like B cells drives local tissue destruction.

Rotational Dynamics of Water at the Phospholipid Bilayer Depending on the Head Groups Studied by Molecular Dynamics Simulations.

Hydration states are a crucial factor that affect the self-assembly and properties of soft materials and biomolecules. Although previous experiments have revealed that the hydration state strongly depends on the chemical structure of lipid molecules, the mechanisms at the molecular level remain unknown. Classical and density-functional tight-binding (DFTB) molecular dynamics (MD) simulations are employed to determine the mechanisms underlying dissimilar water dynamics between lipid membranes with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) head groups. The classical MD simulation shows that rotational relaxations of water are faster on the PE lipid than on the PC lipid, which is consistent with a previous experimental study using terahertz spectroscopy. Furthermore, DFTB-MD simulation of N(CH3)4+ and NH4+ ions, which correspond to the different head groups in PC and PE, respectively, shows qualitative agreement with the classical MD simulation. Remarkably, the PE lipids and the NH4+ ions break hydrogen bonds between water molecules in the secondary hydration shell. In contrast, the PC lipids and the N(CH3)4+ ions bind water molecules weakly in both the primary and secondary hydration shells and increase hydrogen bonds between water. Our atomistic simulations show that these changes in the hydrogen-bond network of water molecules cause the different rotational relaxation of water molecules between the two lipids.

Depth Sensing by Near-Infrared Light Absorption in Water.

This paper introduces a novel depth recovery method based on light absorption in water. Water absorbs light at almost all wavelengths whose absorption coefficient is related to the wavelength. Based on the Beer-Lambert model, we introduce a bispectral depth recovery method that leverages the light absorption difference between two near-infrared wavelengths captured with a distant point source and orthographic cameras. Through extensive analysis, we show that accurate depth can be recovered irrespective of the surface texture and reflectance, and introduce algorithms to correct for nonidealities of a practical implementation including tilted light source and camera placement, nonideal bandpass filters and the perspective effect of the camera with a diverging point light source. We construct a coaxial bispectral depth imaging system using low-cost off-the-shelf hardware and demonstrate its use for recovering the shapes of complex and dynamic objects in water. We also present a trispectral variant to further improve robustness to extremely challenging surface reflectance. Experimental results validate the theory and practical implementation of this novel depth recovery paradigm, which we refer to as shape from water.

Machine Learning to Quantify In Situ Humoral Selection in Human Lupus Tubulointerstitial Inflammation.

In human lupus nephritis, tubulointerstitial inflammation (TII) is associated with in situ expansion of B cells expressing anti-vimentin antibodies (AVAs). The mechanism by which AVAs are selected is unclear. Herein, we demonstrate that AVA somatic hypermutation (SHM) and selection increase affinity for vimentin. Indeed, germline reversion of several antibodies demonstrated that higher affinity AVAs can be selected from both low affinity B cell germline clones and even those that are strongly reactive with other autoantigens. While we demonstrated affinity maturation, enzyme-linked immunosorbent assays (ELISAs) suggested that affinity maturation might be a consequence of increasing polyreactivity or even non-specific binding. Therefore, it was unclear if there was also selection for increased specificity. Subsequent multi-color confocal microscopy studies indicated that while TII AVAs often appeared polyreactive by ELISA, they bound selectively to vimentin fibrils in whole cells or inflamed renal tissue. Using a novel machine learning pipeline (CytoSkaler) to quantify the cellular distribution of antibody staining, we demonstrated that TII AVAs were selected for both enhanced binding and specificity in situ. Furthermore, reversion of single predicted amino acids in antibody variable regions indicated that we could use CytoSkaler to capture both negative and positive selection events. More broadly, our data suggest a new approach to assess and define antibody polyreactivity based on quantifying the distribution of binding to native and contextually relevant antigens.

Molecular dynamics simulation of soundwave propagation in a simple fluid.

A molecular dynamics (MD) simulation was performed to study the propagation of soundwaves in a fluid. Soundwaves are generated by a sinusoidally oscillating wall and annihilated by a locally applied Langevin thermostat near the opposite wall. The waveform changes from sinusoidal to sawtooth with increasing wave amplitude. For low-frequency sounds, the simulation results show a very good agreement with Burgers's equation without any fitting parameters. In contrast, for high-frequency sounds, significant deviations are obtained because of acoustic streaming. The speed of sound can be directly determined from the Fourier transform of a waveform with high accuracy. Although obtaining the attenuation rate directly from the simulation results is difficult because of the nonlinear effects of the wave amplitude, it can be estimated via Burgers's equation. The results demonstrate that MD simulations are a useful tool for the quantitative analysis of soundwaves.

Effects of cavitation on Kármán vortex behind circular-cylinder arrays: A molecular dynamics study.

The effects of cavitation on the flow around a circular-cylinder array are studied by using a molecular dynamics simulation. Cavitation significantly affects vortex shedding characteristics. As the cavitation develops, the vibration acting on the cylinders decreases and eventually disappears. The further cavitation development generates a longer vapor region next to the cylinders, and the vortex streets are formed at further positions from the cylinders. The neighboring Kármán vortexes are synchronized in the antiphase in the absence of the cavitation. This synchronization is weakened by the cavitation, and an asymmetric wake mode can be induced. These findings help mechanical designs of fluid machinery that include cylinder arrays.

Polymer effects on Kármán vortex: Molecular dynamics study.

We investigated the Kármán vortex behind a circular cylinder in a polymer solution by a molecular dynamics simulation. The vortex characteristics are distinctly different for short and long polymers. The solution with the long polymer exhibits a reduction in the vortex shedding frequency and broadening of the lift coefficient spectrum. On the other hand, the characteristics of the short-polymer solution are almost the same as those of the Newtonian fluid. These facts are consistent with the experiments. Because the distributions of the gyration radius and the orientational order of the long-polymer solution are highly inhomogeneous in the flow field, we conclude that the extensional property of the polymer plays an important role in changing the flow characteristics.

Structure of a molecular liquid GeI4.

A molecular liquid GeI4 is a candidate that undergoes a pressure-induced liquid-to-liquid phase transition. This study establishes the reference structure of the low-pressure liquid phase. Synchrotron x-ray diffraction measurements were carried out at several temperatures between the melting and the boiling points under ambient pressure. The molecule has regular tetrahedral symmetry, and the intramolecular Ge-I length of 2.51 Å is almost temperature-independent within the measured range. A reverse Monte Carlo (RMC) analysis is employed to find that the distribution of molecular centers remains self-similar against heating, and thus justifying the length-scaling method adopted in determining the density. The RMC analysis also reveals that the vertex-to-face orientation of the nearest molecules are not straightly aligned, but are inclined at about 20 degrees, thereby making the closest intermolecular I-I distance definitely shorter than the intramolecular one. The prepeak observed at ∼1 Å(-1) in the structural factor slightly shifts and increases in height with increasing temperature. The origin of the prepeak is clearly identified to be traces of the 111 diffraction peak in the crystalline state. The prepeak, assuming the residual spatial correlation between germanium sites in the densest direction, thus shifts toward lower wavenumbers with thermal expansion. The aspect that a relative reduction in molecular size associated with the volume expansion is responsible for the increase in the prepeak's height is confirmed by a simulation, in which the molecular size is changed.

Individual Colorimetric Observer Model.

This study proposes a vision model for individual colorimetric observers. The proposed model can be beneficial in many color-critical applications such as color grading and soft proofing to assess ranges of color matches instead of a single average match. We extended the CIE 2006 physiological observer by adding eight additional physiological parameters to model individual color-normal observers. These eight parameters control lens pigment density, macular pigment density, optical densities of L-, M-, and S-cone photopigments, and λmax shifts of L-, M-, and S-cone photopigments. By identifying the variability of each physiological parameter, the model can simulate color matching functions among color-normal populations using Monte Carlo simulation. The variabilities of the eight parameters were identified through two steps. In the first step, extensive reviews of past studies were performed for each of the eight physiological parameters. In the second step, the obtained variabilities were scaled to fit a color matching dataset. The model was validated using three different datasets: traditional color matching, applied color matching, and Rayleigh matches.

Phase diagram of the modified Lennard-Jones system.

An investigation of the precise determination of melting temperature in the modified Lennard-Jones system under pressure-free conditions [Y. Asano and K. Fuchizaki, J. Phys. Soc. Jpn. 78, 055002 (2009)] was extended under finite-pressure conditions to obtain the phase diagram. The temperature and pressure of the triple point were estimated to be 0.61 ε∕k(B) and 0.0018(5) ε∕σ(3), and those of the critical point were 1.0709(19) ε∕k(B) and 0.1228(20) ε∕σ(3), where ε and σ are the Lennard-Jones parameters for energy and length scales, respectively, and k(B) is the Boltzmann constant. The potential used here has a finite attractive tail and does not suffer from cutoff problems. The potential can thus be a useful standard in examining statistical-mechanical problems in which different treatments for the tail would lead to different conclusions. The present phase diagram will then be a useful guide not only for equilibrium calculations but also for nonequilibrium problems such as discussions of the limits of phase (in)stability.