Ultrasound-Mediated Release of Gaseous Signaling Molecules for Biomedical Applications.

Although nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H S) have been considered as notorious gas pollutants for decades, they are considered as endogenous gaseous signaling molecules (GSMs), which have been widely recognized for their important signaling functions and prominent medical applications in human physiology. To achieve local delivery of GSMs to optimize therapeutic efficacy and reduce systemic side effects, stimuli-responsive nanocarriers have been successfully developed. Among them, ultrasound is considered as an attractive theranostic modality that can be used to track drug carriers, trigger drug release, and improve drug deposition, etc.

2D probabilistic undersampling pattern optimization for MR image reconstruction.

With 3D magnetic resonance imaging (MRI), a tradeoff exists between higher image quality and shorter scan time. One way to solve this problem is to reconstruct high-quality MRI images from undersampled k-space. There have been many recent studies exploring effective k-space undersampling patterns and designing MRI reconstruction methods from undersampled k-space, which are two necessary steps.

Symplectic Ramanujan Mode Decomposition and its application to compound fault diagnosis of bearings.

The existing compound-fault diagnosis methods of rolling bearings have their own defects, which makes their accuracy of fault diagnosis impossible to be guaranteed. Therefore, this paper attempts to combine symplectic similarity transformation with Ramanujan subspace theory, and then a periodic impulse extraction method called symplectic Ramanujan mode decomposition (SRMD) method is proposed. SRMD separates the components with different fault features through symplectic similarity transformation and hierarchical clustering method to obtain symplectic clustering components (SCCs).

Risk Factors for Progression in Vestibular Schwannomas After Incomplete Resection: A Single Center Retrospective Study.

The risk factors for progression in vestibular schwannomas (VSs) after incomplete resection (IR) remain to be elucidated. The purpose of this study was to investigate the risk factors for progression in remnant VSs after surgery. From January 2009 to January 2018, 140 consecutive patients who underwent IR of VSs suboccipital retrosigmoid approach in our institution were retrospectively analyzed.

Cell population-based framework of genetic epidemiology in the single-cell omics era.

Genetic epidemiology is a rapidly advancing field due to the recent availability of large amounts of omics data. In recent years, it has become possible to obtain omics information at the single-cell level, so genetic epidemiological models need to be updated to integrate with single-cell expression data. In this perspective paper, we propose a cell population-based framework for genetic epidemiology in the single-cell era.

Engineering Yeast for Methanol Assimilation.

Conferring methylotrophy on industrial microorganisms would enable the production of diverse products from one-carbon feedstocks and contribute to establishing a low-carbon society. Rebuilding methylotrophs, however, requires a thorough metabolic refactoring and is highly challenging. Only recently was synthetic methylotrophy achieved in model microorganisms─ and baker's yeast .

ADT-OH inhibits malignant melanoma metastasis in mice via suppressing CSE/CBS and FAK/Paxillin signaling pathway.

Hydrogen sulfide (HS) is widely recognized as the third endogenous gas signaling molecule and may play a key role in cancer biological processes. ADT-OH (5-(4-hydroxyphenyl)-3H-1,2-dithiocyclopentene-3-thione) is one of the most widely used organic donors for the slow release of HS and considered to be a potential anticancer compound. In this study, we investigated the antimetastatic effects of ADT-OH in highly metastatic melanoma cells.

Association of childhood asthma with intra-day and inter-day temperature variability in Shanghai, China.

Objectives: Short-term temperature variability (TV) is associated with the exacerbation of asthma, but little is known about the relative effects of intra- and inter-day TV. We aimed to assess the relative impacts of intra- and inter-day TV on childhood asthma and to explore the modification effects by season.

Methods: A quasi-Poisson generalized linear regression model combined with a distributed lag nonlinear model was adopted to evaluate the nonlinear and lagged effects of TV on childhood asthma in Shanghai from 2009 to 2017.

Extremely Sparse Networks via Binary Augmented Pruning for Fast Image Classification.

Network pruning and binarization have been demonstrated to be effective in neural network accelerator design for high speed and energy efficiency. However, most existing pruning approaches achieve a poor tradeoff between accuracy and efficiency, which on the other hand, has limited the progress of neural network accelerators. At the same time, binary networks are highly efficient, however, a large accuracy gap exists between binary networks and their full-precision counterparts.

Data-driven comparison of multiple high-dimensional single-cell expression profiles.

Comparing multiple single-cell expression datasets such as cytometry and scRNA-seq data between case and control donors provides information to elucidate the mechanisms of disease. We propose a completely data-driven computational biological method for this task. This overcomes the challenges of conventional cellular subset-based comparisons and facilitates further analyses such as machine learning and gene set analysis of single-cell expression datasets.

Effects of extreme precipitation on hospitalization risk and disease burden of schizophrenia in urban and rural Lu'an, China, from 2010 to 2019.

With the increasing frequency of extreme events caused by global climate change, the association between extreme precipitation (EP) and disease has aroused concern currently. However, no study has examined the relationship between EP and schizophrenia. Our study aimed to explore the relationship between EP and schizophrenia, and to further examine the difference between urban and rural areas.

GPENs: Graph Data Learning With Graph Propagation-Embedding Networks.

Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured data representation and learning tasks, such as graph semi-supervised learning, clustering, and low-dimensional embedding. In this article, we present graph propagation-embedding networks (GPENs), a new model for graph-structured data representation and learning problem.

White matter hyperintensities segmentation using an ensemble of neural networks.

White matter hyperintensities (WMHs) represent the most common neuroimaging marker of cerebral small vessel disease (CSVD). The volume and location of WMHs are important clinical measures. We present a pipeline using deep fully convolutional network and ensemble models, combining U-Net, SE-Net, and multi-scale features, to automatically segment WMHs and estimate their volumes and locations.

Orchestrating Nitric Oxide and Carbon Monoxide Signaling Molecules for Synergistic Treatment of MRSA Infections.

The local delivery of gaseous signaling molecules (GSMs) has shown promising therapeutic potential. However, although GSMs have a subtle interplay in physiological and pathological conditions, the co-delivery of different GSMs for therapeutic purposes remains unexplored. Herein, we covalently graft a nitric oxide (NO)-releasing N-nitrosamine moiety onto the carbon monoxide (CO)-releasing 3-hydroxyflavone (3-HF) antenna, resulting in the first NO/CO-releasing donor.

Pore Fractal Characteristics of Suancigou Long-Flame Coal after Electrochemical Treatment: An Experimental Study through the Implementation of N Adsorption and Mercury Intrusion Prosimetry Techniques.

The application of electrochemical treatment in coal seams for enhancing coalbed methane (CBM) recovery can also decrease the risks of outburst disasters. The long-flame coal samples were electrochemically modified with 0, 1, 2, and 4 V/cm electric potential gradients, and the pore structures were measured and analyzed by combined low-temperature nitrogen gas adsorption, mercury intrusion prosimetry, and fractal theory. The experimental test results indicated that the pore volumes of macropores (>50 nm) and mesopores (2-50 nm) increased after electrochemical modification and further increased with the increase in electric potential gradient.

A parallel attention-augmented bilinear network for early magnetic resonance imaging-based diagnosis of Alzheimer's disease.

Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Recently, many sMRI-based deep learning methods have been developed for AD diagnosis. Some of these methods utilize neural networks to extract high-level representations on the basis of handcrafted features, while others attempt to learn useful features from brain regions proposed by a separate module.

Fully automated grading system for the evaluation of punctate epithelial erosions using deep neural networks.

Purpose: The goal was to develop a fully automated grading system for the evaluation of punctate epithelial erosions (PEEs) using deep neural networks.

Methods: A fully automated system was developed to detect corneal position and grade staining severity given a corneal fluorescein staining image. The fully automated pipeline consists of the following three steps: a corneal segmentation model extracts corneal area; five image patches are cropped from the staining image based on the five subregions of extracted cornea; a staining grading model predicts a score for each image patch from 0 to 3, and automated grading score for the whole cornea is obtained from 0 to 15.

Oxidative stress-mediated particulate matter affects the risk of relapse in schizophrenia patients: Air purification intervention-based panel study.

Particulate matter (PM) exposure increased the risk of hospital admission and was related to symptoms of schizophrenia (SCZ). However, there are limited studies on the relationship between PM exposure and SCZ relapse risk, and the underlying biological mechanisms remain unclear. We designed an air purification intervention study under a 16-day real air purifier scenario and another 16-day sham air purifier scenario, with a 2-day washout period.

Formation mechanism of bubbles in the crack healing process of fused silica using a CO laser.

The machining-induced cracks and other defects on the surface of fused silica would incur damage when irradiated by intense lasers, which greatly shortens the service life of the fused silica optical components. The high absorption coefficient of fused silica for far-infrared lasers makes it possible to use low-energy CO lasers to melt and heal micro defects on the surface, and hence improve its damage threshold under the service conditions of extremely intense laser. However, the air in the cracks may evolve into bubbles during the laser healing process, but the law of crack morphology evolution and the bubble formation mechanism have not been clearly revealed.

Recent Advances on Carbon Monoxide Releasing Molecules for Antibacterial Applications.

Carbon monoxide (CO) has been known as an endogenous signaling molecule in addition to an air pollutant. It plays a critical role in many physiological and pathological processes. Therefore, CO has been recognized as a potent therapeutic agent for the treatment of numerous diseases such as cancers, rheumatoid arthritis, and so on.

Seasonal characteristics of temperature variability impacts on childhood asthma hospitalization in Hefei, China: Does PM modify the association?

Objectives: Evidence of childhood asthma hospitalizations associated with temperature variability (TV) and the attributable risk are limited in China. We aim to use a comprehensive index that reflected both intra- and inter-day TV to assess the TV-childhood asthma relationship and disease burden, further to identify seasonality vulnerable populations, and to explore the effect modification of PM.

Methods: A quasi-distributed lagged nonlinear model (DLNM) combined with a linear threshold function was applied to estimate the association between TV and childhood asthma hospitalizations during 2013-2016 in Hefei, China.

Electrochemical Modification on CH and HO Wettability of Qinshui Anthracite Coal: A Combined Experimental and Molecular Dynamics Simulation Study.

The wettability of gas and liquid on the coal surface is one of the fundamental factors that affect the depressurization process during the coalbed methane (CBM) extraction. The wettability of coal surface changed after electrochemical modification, leading to the change in methane adsorption/desorption and water movement in coal reservoirs. Thus, the CH adsorption amount, desorption ratio, and coal-water contact angle of raw and modified anthracite samples were measured and simulated.

Does the gut microbiome partially mediate the impact of air pollutants exposure on liver function? Evidence based on schizophrenia patients.

Air pollution may alter the composition of gut microbiome and subsequent liver-related metabolic disorders. Schizophrenia was often accompanied by liver dysfunction. But it was still unclear whether air pollutants affected liver function in patients with schizophrenia through gut microbiome.