Structure-Preserving Graph Representation Learning

Though graph representation learning (GRL) has made significant progress, it is still a challenge to extract and embed the rich topological structure and feature information in an adequate way. Most existing methods focus on local structure and fail to fully incorporate the global topological structure. To this end, we propose a novel Structure-Preserving Graph Representation Learning (SPGRL) method, to fully capture the structure information of graphs. Specifically, to reduce the uncertainty and misinformation of the original graph, we construct a feature graph as a complementary view via k-Nearest Neighbor method. The feature graph can be used to contrast at node-level to capture the local relation. Besides, we retain the global topological structure information by maximizing the mutual information (MI) of the whole graph and feature embeddings, which is theoretically reduced to exchanging the feature embeddings of the feature and the original graphs to reconstruct themselves. Extensive experiments show that our method has quite superior performance on semi-supervised node classification task and excellent robustness under noise perturbation on graph structure or node features.Comment: Accepted by the IEEE International Conference on Data Mining (ICDM) 2022. arXiv admin note: text overlap with arXiv:2108.0482

A next generation sequencing-based protocol for screening of variants of concern in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic influences. There is an increasing demand for ASD genetic testing beyond the traditionally recommended microarray and syndromic autism testing; however, the current whole genome sequencing (WGS) and whole exome sequencing (WES) methods are lacking an academic standard for WGS variant annotation, reporting, and interpretation, tailored towards patients with ASD and offer very limited interpretation for clinical significance. Using WGS data from six family trios, we demonstrate the clinical feasibility and technical implementation of an evidence-based, fully transparent bioinformatics pipeline and report framework for an ASD-focused WGS genetic report. We confirmed a portion of the key variants with Sanger sequencing and provided interpretation with consideration of patients\u27 clinical symptoms and detailed literature review. Furthermore, we showed that identification of the genetic contributions of ASD core symptoms and comorbidities may promote a better understanding of the ASD pathophysiology, lead to early detection of associated comorbidities, and facilitate pharmacologic intervention based on pathological pathways inferred from the genetic information. We will make the bioinformatics pipeline and interpretation framework publicly available, in an easily accessible format, after validation with a larger cohort. We hope that the present proposed protocol can serve as a starting point to invite discourse and debate to further improve approaches in WGS-based genetic consultation for patients with ASD

Apolipoprotein E deficiency potentiates macrophage against Staphylococcus aureus in mice with osteomyelitis via regulating cholesterol metabolism

IntroductionStaphylococcus aureus (S. aureus) osteomyelitis causes a variety of metabolism disorders in microenvironment and cells. Defining the changes in cholesterol metabolism and identifying key factors involved in cholesterol metabolism disorders during S. aureus osteomyelitis is crucial to understanding the mechanisms of S. aureus osteomyelitis and is important in designing host-directed therapeutic strategies.MethodsIn this study, we conducted in vitro and in vivo experiments to define the effects of S. aureus osteomyelitis on cholesterol metabolism, as well as the role of Apolipoprotein E (ApoE) in regulating cholesterol metabolism by macrophages during S. aureus osteomyelitis.ResultsThe data from GSE166522 showed that cholesterol metabolism disorder was induced by S. aureus osteomyelitis. Loss of cholesterol from macrophage obtained from mice with S. aureus osteomyelitis was detected by liquid chromatography-tandem mass spectrometry(LC-MS/MS), which is consistent with Filipin III staining results. Changes in intracellular cholesterol content influenced bactericidal capacity of macrophage. Subsequently, it was proven by gene set enrichment analysis and qPCR, that ApoE played a key role in developing cholesterol metabolism disorder in S. aureus osteomyelitis. ApoE deficiency in macrophages resulted in increased resistance to S. aureus. ApoE-deficient mice manifested abated bone destruction and decreased bacteria load. Moreover, the combination of transcriptional analysis, qPCR, and killing assay showed that ApoE deficiency led to enhanced cholesterol biosynthesis in macrophage, ameliorating anti-infection ability.ConclusionWe identified a previously unrecognized role of ApoE in S. aureus osteomyelitis from the perspective of metabolic reprogramming. Hence, during treating S. aureus osteomyelitis, considering cholesterol metabolism as a potential therapeutic target presents a new research direction

A Flexible Flow Sensor System and Its Characteristics for Fluid Mechanics Measurements

In this paper, we present a novel micromachined hot-film flow sensor system realized by a technique using a film depositing processes and incorporating a standard printed circuit. Sensor electrodes and electronic circuits are preprinted on a flexible substrate of polyimide (PI), i.e., a flexible printed circuit board (FPCB). The sensing element, which is made of Cr/Ni/Pt with a temperature coefficient of resistance around 2,000 ppm/K, is fabricated on the FPCB by either magnetron sputtering technology or pulsed laser deposition (PLD). The sensor can be packed efficiently at high-density and integrated with signal processing circuits without additional pads. A simple fabrication process using mature technique and materials selection guarantees that the time and costs are greatly reduced. Both steady-state and transient characteristics of the sensors are experimentally tested, and the results presented to validate the effectiveness of the sensors

Optimization of Preparation Process of Bayberry Soft Candy and Analysis of Its Hypoglycemic Function

In order to develop soft fruit candy products with hypoglycemic function, the preparation method was optimized by single-factor and response surface studies. The texture profile analysis and sensory score was regarded as the evaluation indices, while bayberry juice was used as the main raw material, carrageenan and gelatin as the gelling agent, and xylitol as the sweetener. Additionally, the hypoglycemic effect of bayberry soft candy extract was evaluated by in vitro study, and the components of bayberry juice was detected by using UPLC-MS/MS assay. Finally, the hypoglycemic components and related pathways of action were predicted by network pharmacology. The results showed that in the 100 mL bayberry soft candy gel solution system, the optimal formulation of bayberry soft candy obtained by response surface methodology was as follows: 89.37% bayberry juice for swelling and constant volume, with 9.90% gelatin, 1.41% carrageenan, and 30.86% xylitol addition. The sensory score of bayberry soft candy produced under this process was 87.30, which was close to the theoretical value. The in vitro hypoglycemic study showed that the inhibition of α-glucosidase and α-amylase by 4 mg/mL of bayberry soft candy extract reached 98.58% and 86.89%, respectively. The network pharmacological analysis postulated that 3,5-diacetyltambrin (YM16), azaleatin (YM17) and raspberry ketone glucoside (YM1) were the key hypoglycemic components in bayberry juice, in addition, the human cancer pathway and PI3K-Akt pathway were important pathways of their action. The soft candy prepared under the optimal process condition showed good elasticity, fantastic taste and certain hypoglycemic effects. These results provide a certain theoretical basis for the development of fruit-flavored functional soft candy

Wall shear stress and its role in atherosclerosis

Atherosclerosis (AS) is the major form of cardiovascular disease and the leading cause of morbidity and mortality in countries around the world. Atherosclerosis combines the interactions of systemic risk factors, haemodynamic factors, and biological factors, in which biomechanical and biochemical cues strongly regulate the process of atherosclerosis. The development of atherosclerosis is directly related to hemodynamic disorders and is the most important parameter in the biomechanics of atherosclerosis. The complex blood flow in arteries forms rich WSS vectorial features, including the newly proposed WSS topological skeleton to identify and classify the WSS fixed points and manifolds in complex vascular geometries. The onset of plaque usually occurs in the low WSS area, and the plaque development alters the local WSS topography. low WSS promotes atherosclerosis, while high WSS prevents atherosclerosis. Upon further progression of plaques, high WSS is associated with the formation of vulnerable plaque phenotype. Different types of shear stress can lead to focal differences in plaque composition and to spatial variations in the susceptibility to plaque rupture, atherosclerosis progression and thrombus formation. WSS can potentially gain insight into the initial lesions of AS and the vulnerable phenotype that gradually develops over time. The characteristics of WSS are studied through computational fluid dynamics (CFD) modeling. With the continuous improvement of computer performance-cost ratio, WSS as one of the effective parameters for early diagnosis of atherosclerosis has become a reality and will be worth actively promoting in clinical practice. The research on the pathogenesis of atherosclerosis based on WSS is gradually an academic consensus. This article will comprehensively review the systemic risk factors, hemodynamics and biological factors involved in the formation of atherosclerosis, and combine the application of CFD in hemodynamics, focusing on the mechanism of WSS and the complex interactions between WSS and plaque biological factors. It is expected to lay a foundation for revealing the pathophysiological mechanisms related to abnormal WSS in the progression and transformation of human atherosclerotic plaques

Probiotic and Oxytocin Combination Therapy in Patients with Autism Spectrum Disorder: A Randomized, Double-Blinded, Placebo-Controlled Pilot Trial

Autism spectrum disorder (ASD) is a rapidly growing neurodevelopmental disorder. Both probiotics and oxytocin were reported to have therapeutic potential; however, the combination therapy has not yet been studied. We conducted a randomized, double-blinded, placebo-controlled, 2-stage pilot trial in 35 individuals with ASD aged 3-20 years (median = 10.30 years). Subjects were randomly assigned to receive daily Lactobacillus plantarum PS128 probiotic (6 × 1010 CFUs) or a placebo for 28 weeks; starting on week 16, both groups received oxytocin. The primary outcomes measure socio-behavioral severity using the Social Responsiveness Scale (SRS) and Aberrant Behavior Checklist (ABC). The secondary outcomes include measures of the Clinical Global Impression (CGI) scale, fecal microbiome, blood serum inflammatory markers, and oxytocin. All outcomes were compared between the two groups at baseline, 16 weeks, and 28 weeks into treatment. We observed improvements in ABC and SRS scores and significant improvements in CGI-improvement between those receiving probiotics and oxytocin combination therapy compared to those receiving placebo (p < 0.05). A significant number of favorable gut microbiome network hubs were also identified after combination therapy (p < 0.05). The favorable social cognition response of the combination regimen is highly correlated with the abundance of the Eubacterium hallii group. Our findings suggest synergic effects between probiotics PS128 and oxytocin in ASD patients, although further investigation is warranted

Sequence-defined multifunctional polyethers via liquid-phase synthesis with molecular sieving

Synthetic chemists have devoted tremendous effort towards the production of precision synthetic polymers with defined sequences and specific functions. However, the creation of a general technology that enables precise control over monomer sequence, with efficient isolation of the target polymers, is highly challenging. Here, we report a robust strategy for the production of sequence-defined synthetic polymers through a combination of liquid-phase synthesis and selective molecular sieving. The polymer is assembled in solution with real-time monitoring to ensure couplings proceed to completion, on a three-armed star-shaped macromolecule to maximize efficiency during the molecular sieving process. This approach is applied to the construction of sequence-defined polyethers, with side-arms at precisely defined locations that can undergo site-selective modification after polymerization. Using this versatile strategy, we have introduced structural and functional diversity into sequence-defined polyethers, unlocking their potential for real-life applications in nanotechnology, healthcare and information storage