bluuebunny/crossref_metadata_2025_split huggingface dataset:
Instrumentation based material characterization of a split square ring metamaterial and its analytical study as cloak for microwave communication applications
Authors: Srilatha K , Madhav B T P , Reddy S S Mohan , Ahamad Shaik Shakeel , Das Sudipta , Narayana J Lakshmi 
Published: November 2022

Abstract
The study of materials with flexibility, compressive strength, and outstanding resistance is in high demand in the domain of wireless technology. The aim of this study is to design a flexible substrate material that is suitable for cloaking in the microwave frequency range. To determine the characteristics of the materials, commercially obtainable analyzing techniques such as Scanning Electron Microscopy (SEM), x-ray Diffractometer (XRD), and Fourier Transform Infrared Spectroscopy (FTIR) are used. The proposed structure is validated using an electromagnetic simulator, and the metamaterial characteristics are seen as a result. The metasurface is now wrapped around the cylindrical object that will be concealed. The power flow distributions are used to examine the cloaked cylindrical object. The cloak’s resonating frequencies are 4.17 GHz, 6.98 GHz, 9.79 GHz, 14.38 GHz, and 17.07 GHz. Finally, the cloak is measured in the near field using a horn antenna arrangement. The measured results agree perfectly with the simulated ones and are suitable for microwave applications in the X, C, and Ku bands.
Complete cycle of modeling and simulation for wireless power transfer using circuit theory, simple electronics, and open-source software
Authors: El Hage Fabio S 
Published: November 2022

Abstract
This article presents a complete modeling and simulation framework for a simple resonant inductive coupling circuit, composed of a pair of inductive resonators that can wirelessly transfer about 60 W of power at a distance of approximately 15 cm. The circuit was physically implemented, and the transmitting coil was powered by a simple half-bridge electronic circuit that generated a square voltage signal. Measurements were compared to simulation results, and it was found that the proposed model could accurately explain and predict the behavior of the circuit. Our results show that optimum transfer of power varies according to the load values, the fRequency and the distance between the transmitter and receiver, which can vary considerably depending on the application. Simulations using AC circuit analysis helped in depicting the behavior of the circuit under this kind of variability, and in characterizing the presence of the optimum points for power transfer, although these were attained at lower efficiency. The present analysis paves the way for further investigations using control theory to track the frequencies at which maximum power is delivered for each set of variables, i.e., the distance between the resonators and the load value.
Self-assembled supramolecular materials for photocatalytic H2 production and CO2 reduction
Authors: Tian Jia , Yu Junlai , Tang Qingxuan , Zhang Jiangshan , Ma Danying , Lei Yifei , Li Zhan-Ting 
Published: November 2022

Abstract
Photosynthetic organisms harness solar radiation to produce energy-rich compounds from water and atmospheric CO2 via exquisite supramolecular assemblies, which offers a design principle for highly efficient artificial photocatalytic systems. As an emerging research field, significant effort has been devoted to self-assembled supramolecular materials for photocatalytic H2 production and CO2 reduction. In this review, we introduce the basic concepts of supramolecular photocatalytic materials. After that, we will discuss recent advances in the preparation of supramolecular photocatalytic materials from zero-dimension to three-dimension which include molecular assemblies, micelles, hybrid nanoparticles, nanofibers, nanosheets, microcrystals, lipid bilayers, supramolecular organic frameworks, supramolecular metal-organic frameworks, gels, and host-guest metal-organic frameworks, etc. Furthermore, we show the recent progress in the photocatalytic properties of supramolecular photocatalytic materials, i.e. photocatalytic proton reduction, water splitting, CO2 to HCOOH, CO2 to CO, CO2 to CH4 conversions, etc. Finally, we provide our perspective for the future research, with a focus on the development of new structures and highly efficient photocatalysis.
Smooth solutions to the heat equation which are nowhere analytic in time
Authors: Yang Xin , Zeng Chulan , Zhang Qi 
Published: November 2022

The existence of smooth but nowhere analytic functions is well-known (du Bois-Reymond [Math. Ann. 21 (1883), no. 1, pp. 109–117]). However, smooth solutions to the heat equation are usually analytic in the space variable. It is also well-known (Kowalevsky [Crelle 80 (1875), pp. 1–32]) that a solution to the heat equation may not be time-analytic at

t
=
0

t=0

even if the initial function is real analytic. Recently, it was shown by Dong and Pan [J Math. Fluid Mech. 22 (2020), no. 4, Paper No. 53]; Dong and Zhang [J. Funct. Anal. 279 (2020), no. 4, Paper No. 108563]; Zhang [Proc. Amer. Math. Soc. 148 (2020), no. 4, pp. 1665–1670] that solutions to the heat equation in the whole space, or in the half space with zero boundary value, are analytic in time under an essentially optimal growth condition. In this paper, we show that time analyticity is not always true in domains with general boundary conditions or without suitable growth conditions. More precisely, we construct two bounded solutions to the heat equation in the half plane which are nowhere analytic in time. In addition, for any

δ
>
0

\delta >0

, we find a solution to the heat equation on the whole plane, with exponential growth of order

2
+
δ

2+\delta

, which is nowhere analytic in time.
Inferring disease-associated circRNAs by multi-source aggregation based on heterogeneous graph neural network
Authors: Lu Chengqian , Zhang Lishen , Zeng Min , Lan Wei , Duan Guihua , Wang Jianxin 
Published: November 2022

Abstract
Emerging evidence has proved that circular RNAs (circRNAs) are implicated in pathogenic processes. They are regarded as promising biomarkers for diagnosis due to covalently closed loop structures. As opposed to traditional experiments, computational approaches can identify circRNA–disease associations at a lower cost. Aggregating multi-source pathogenesis data helps to alleviate data sparsity and infer potential associations at the system level. The majority of computational approaches construct a homologous network using multi-source data, but they lose the heterogeneity of the data. Effective methods that use the features of multi-source data are considered as a matter of urgency. In this paper, we propose a model (CDHGNN) based on edge-weighted graph attention and heterogeneous graph neural networks for potential circRNA–disease association prediction. The circRNA network, micro RNA network, disease network and heterogeneous network are constructed based on multi-source data. To reflect association probabilities between nodes, an edge-weighted graph attention network model is designed for node features. To assign attention weights to different types of edges and learn contextual meta-path, CDHGNN infers potential circRNA–disease association based on heterogeneous neural networks. CDHGNN outperforms state-of-the-art algorithms in terms of accuracy. Edge-weighted graph attention networks and heterogeneous graph networks have both improved performance significantly. Furthermore, case studies suggest that CDHGNN is capable of identifying specific molecular associations and investigating biomolecular regulatory relationships in pathogenesis. The code of CDHGNN is freely available at https://github.com/BioinformaticsCSU/CDHGNN.
Robust genetic model-based SNP-set association test using CauchyGM
Authors: Kim Yeonil , Chi Yueh-Yun , Shen Judong , Zou Fei 
Published: November 2022

Abstract

Motivation
Association testing on genome-wide association studies (GWAS) data is commonly performed under a single (mostly additive) genetic model framework. However, the underlying true genetic mechanisms are often unknown in practice for most complex traits. When the employed inheritance model deviates from the underlying model, statistical power may be reduced. To overcome this challenge, an integrative association test that directly infers the underlying genetic model from GWAS data has previously been proposed for single-SNP analysis.

Results
In this article, we propose a Cauchy combination Genetic Model-based association test (CauchyGM) under a generalized linear model framework for SNP-set level analysis. CauchyGM does not require prior knowledge on the underlying inheritance pattern of each SNP. It performs a score test that first estimates an individual P-value of each SNP in an SNP-set with both minor allele frequency (MAF) &gt; 1% and three genotypes and further aggregates the rest SNPs using SKAT. CauchyGM then combines the correlated P-values across multiple SNPs and different genetic models within the set using Cauchy Combination Test. To further accommodate both sparse and dense signal patterns, we also propose an omnibus association test (CauchyGM-O) by combining CauchyGM with SKAT and the burden test. Our extensive simulations show that both CauchyGM and CauchyGM-O maintain the type I error well at the genome-wide significance level and provide substantial power improvement compared to existing methods. We apply our methods to a pharmacogenomic GWAS data from a large cardiovascular randomized clinical trial. Both CauchyGM and CauchyGM-O identify several novel genome-wide significant genes.

Availability and implementation
The R package CauchyGM is publicly available on github: https://github.com/ykim03517/CauchyGM.

Supplementary information
Supplementary data are available at Bioinformatics online.
Clustering single-cell multi-omics data with MoClust
Authors: Yuan Musu , Chen Liang , Deng Minghua 
Published: November 2022

Abstract

Motivation
Single-cell multi-omics sequencing techniques have rapidly developed in the past few years. Clustering analysis with single-cell multi-omics data may give us novel perspectives to dissect cellular heterogeneity. However, multi-omics data have the properties of inherited large dimension, high sparsity and existence of doublets. Moreover, representations of different omics from even the same cell follow diverse distributions. Without proper distribution alignment techniques, clustering methods will encounter less separable clusters easily affected by less informative omics data.

Results
We developed MoClust, a novel joint clustering framework that can be applied to several types of single-cell multi-omics data. A selective automatic doublet detection module that can identify and filter out doublets is introduced in the pretraining stage to improve data quality. Omics-specific autoencoders are introduced to characterize the multi-omics data. A contrastive learning way of distribution alignment is adopted to adaptively fuse omics representations into an omics-invariant representation. This novel way of alignment boosts the compactness and separableness of clusters, while accurately weighting the contribution of each omics to the clustering object. Extensive experiments, over both simulated and real multi-omics datasets, demonstrated the powerful alignment, doublet detection and clustering ability features of MoClust.

Availability and implementation
An implementation of MoClust is available from https://doi.org/10.5281/zenodo.7306504.

Supplementary information
Supplementary data are available at Bioinformatics online.
SEGCOND predicts putative transcriptional condensate-associated genomic regions by integrating multi-omics data
Authors: Klonizakis Antonios , Nikolaou Christoforos , Graf Thomas 
Published: November 2022

Abstract

Motivation
The compartmentalization of biochemical reactions, involved in the activation of gene expression in the eukaryotic nucleus, leads to the formation of membraneless bodies through liquid–liquid phase separation. These formations, called transcriptional condensates, appear to play important roles in gene regulation as they are assembled through the association of multiple enhancer regions in 3D genomic space. To date, we are still lacking efficient computational methodologies to identify the regions responsible for the formation of such condensates, based on genomic and conformational data.

Results
In this work, we present SEGCOND, a computational framework aiming to highlight genomic regions involved in the formation of transcriptional condensates. SEGCOND is flexible in combining multiple genomic datasets related to enhancer activity and chromatin accessibility, to perform a genome segmentation. It then uses this segmentation for the detection of highly transcriptionally active regions of the genome. At a final step, and through the integration of Hi-C data, it identifies regions of putative transcriptional condensates (PTCs) as genomic domains where multiple enhancer elements coalesce in 3D space. SEGCOND identifies a subset of enhancer segments with increased transcriptional activity. PTCs are also found to significantly overlap highly interconnected enhancer elements and super enhancers obtained through two independent approaches. Application of SEGCOND on data from a well-defined system of B-cell to macrophage transdifferentiation leads to the identification of previously unreported genes with a likely role in the process.

Availability and implementation
Source code and details for the implementation of SEGCOND is available at https://github.com/AntonisK95/SEGCOND

Supplementary information
Supplementary data are available at Bioinformatics online.
The genetic and phenotypic spectra of adult genetic leukoencephalopathies in a cohort of 309 patients
Authors: Wu Chujun , Wang Mengwen , Wang Xingao , Li Wei , Li Shaowu , Chen Bin , Niu Songtao , Tai Hongfei , Pan Hua , Zhang Zaiqiang 
Published: November 2022

Abstract
Genetic leukoencephalopathies (gLEs) are a highly heterogeneous group of rare genetic disorders. The spectrum of gLEs varies among patients of different ages. Distinct from the relatively more abundant studies of gLEs in children, only a few studies that explore the spectrum of adult gLEs have been published, and it should be noted that the majority of these excluded certain gLEs. Thus, to date, no large study has been designed and conducted to characterize the genetic and phenotypic spectra of gLEs in adult patients.
We recruited a consecutive series of 309 adult patients clinically suspected of gLEs from Beijing Tiantan Hospital between January 2014 and December 2021. Whole-exome sequencing, mitochondrial DNA sequencing and repeat analysis of NOTCH2NLC, FMR1, DMPK and ZNF9 were performed for patients. We describe the genetic and phenotypic spectra of the set of patients with a genetically confirmed diagnosis and summarize their clinical and radiological characteristics.
A total of 201 patients (65%) were genetically diagnosed, while 108 patients (35%) remained undiagnosed. The most frequent diseases were leukoencephalopathies related to NOTCH3 (25%), NOTCH2NLC (19%), ABCD1 (9%), CSF1R (7%) and HTRA1 (5%). Based on a previously proposed pathological classification, the gLEs in our cohort were divided into leukovasculopathies (35%), leuko-axonopathies (31%), myelin disorders (21%), microgliopathies (7%) and astrocytopathies (6%). Patients with NOTCH3 mutations accounted for 70% of the leukovasculopathies, followed by HTRA1 (13%) and COL4A1/2 (9%). The leuko-axonopathies contained the richest variety of associated genes, of which NOTCH2NLC comprised 62%. Among myelin disorders, demyelinating leukoencephalopathies (61%)—mainly adrenoleukodystrophy and Krabbe disease—accounted for the majority, while hypomyelinating leukoencephalopathies (2%) were rare. CSF1R was the only mutated gene detected in microgliopathy patients. Leukoencephalopathy with vanishing white matter disease due to mutations in EIF2B2-5 accounted for half of the astrocytopathies.
We characterized the genetic and phenotypic spectra of adult gLEs in a large Chinese cohort. The most frequently mutated genes were NOTCH3, NOTCH2NLC, ABCD1, CSF1R and HTRA1.
Tau seeds from patients induce progressive supranuclear palsy pathology and symptoms in primates
Authors: Darricau Morgane , Katsinelos Taxiarchis , Raschella Flavio , Milekovic Tomislav , Crochemore Louis , Li Qin , Courtine Grégoire , McEwan William A , Dehay Benjamin , Bezard Erwan , Planche Vincent 
Published: November 2022

Abstract
Progressive supranuclear palsy is a primary tauopathy affecting both neurons and glia and is responsible for both motor and cognitive symptoms. Recently, it has been suggested that progressive supranuclear palsy tauopathy may spread in the brain from cell to cell in a ‘prion-like’ manner. However, direct experimental evidence of this phenomenon, and its consequences on brain functions, is still lacking in primates.
In this study, we first derived sarkosyl-insoluble tau fractions from post-mortem brains of patients with progressive supranuclear palsy. We also isolated the same fraction from age-matched control brains. Compared to control extracts, the in vitro characterization of progressive supranuclear palsy-tau fractions demonstrated a high seeding activity in P301S-tau expressing cells, displaying after incubation abnormally phosphorylated (AT8- and AT100-positivity), misfolded, filamentous (pentameric formyl thiophene acetic acid positive) and sarkosyl-insoluble tau. We bilaterally injected two male rhesus macaques in the supranigral area with this fraction of progressive supranuclear palsy-tau proteopathic seeds, and two other macaques with the control fraction. The quantitative analysis of kinematic features revealed that progressive supranuclear palsy-tau injected macaques exhibited symptoms suggestive of parkinsonism as early as 6 months after injection, remaining present until euthanasia at 18 months. An object retrieval task showed the progressive appearance of a significant dysexecutive syndrome in progressive supranuclear palsy-tau injected macaques compared to controls. We found AT8-positive staining and 4R-tau inclusions only in progressive supranuclear palsy-tau injected macaques. Characteristic pathological hallmarks of progressive supranuclear palsy, including globose and neurofibrillary tangles, tufted astrocytes and coiled bodies, were found close to the injection sites but also in connected brain regions that are known to be affected in progressive supranuclear palsy (striatum, pallidum, thalamus). Interestingly, while glial AT8-positive lesions were the most frequent near the injection site, we found mainly neuronal inclusions in the remote brain area, consistent with a neuronal transsynaptic spreading of the disease.
Our results demonstrate that progressive supranuclear palsy patient-derived tau aggregates can induce motor and behavioural impairments in non-human primates related to the prion-like seeding and spreading of typical pathological progressive supranuclear palsy lesions. This pilot study paves the way for supporting progressive supranuclear palsy-tau injected macaque as a relevant animal model to accelerate drug development targeting this rare and fatal neurodegenerative disease.
Deaf and hearing children: A comparison of face perception
Authors: He Huizhong , Zhang Yunxiang , Su Mengmeng , Yi Lixin , Lv Jiayi 
Published: November 2022

AbstractDeaf and hearing adults perceive faces differently. This study investigates whether these differences are acquired during childhood development. We characterized facial perception in deaf and hearing children aged 7–17 using a perceptual discrimination task. Configural and featural information was manipulated in the eye and mouth facial regions. Participants were asked whether two faces presented simultaneously were different. Deaf and hearing children performed better in featural than configural discriminations and in mouth than eye discriminations. Compared with children with typical hearing, deaf children performed better in featural and mouth judgments but had longer reaction times with strongest effects at 7–8 and 13–14 years old. Type and location contributed jointly in deaf children’s face perception with different configural but similar featural discriminations in mouth and eye locations. However, children with typical hearing showed different featural and configural judgments in both locations. Thus, featural and configural information effects on location processing differ between the two groups.
Vinculin phosphorylation impairs vascular endothelial junctions promoting atherosclerosis
Authors: Shih Yu-Tsung , Wei Shu-Yi , Chen Jin-Hua , Wang Wei-Li , Wu Hsin-Yi , Wang Mei-Cun , Lin Chia-Yu , Lee Pei-Lin , Lin Chih-Yuan , Chiang Hung-Che , Chen Yu-Ju , Chien Shu , Chiu Jeng-Jiann 
Published: November 2022

Abstract

Background and aims
Atherosclerosis preferentially develops in arterial branches and curvatures where vascular endothelium is exposed to disturbed flow. In this study, the effects of disturbed flow on the regulation of vascular endothelial phosphoproteins and their contribution to therapeutic application in atherogenesis were elucidated.

Methods
Porcine models, large-scale phosphoproteomics, transgenic mice, and clinical specimens were used to discover novel site-specific phosphorylation alterations induced by disturbed flow in endothelial cells (ECs).

Results
A large-scale phosphoproteomics analysis of native endothelium from disturbed (athero-susceptible) vs. pulsatile flow (athero-resistant) regions of porcine aortas led to the identification of a novel atherosclerosis-related phosphoprotein vinculin (VCL) with disturbed flow-induced phosphorylation at serine 721 (VCLS721p). The induction of VCLS721p was mediated by G-protein-coupled receptor kinase 2 (GRK2)S29p and resulted in an inactive form of VCL with a closed conformation, leading to the VE-cadherin/catenin complex disruption to enhance endothelial permeability and atherogenesis. The generation of novel apolipoprotein E-deficient (ApoE−/−) mice overexpressing S721-non-phosphorylatable VCL mutant in ECs confirmed the critical role of VCLS721p in promoting atherosclerosis. The administration of a GRK2 inhibitor to ApoE−/− mice suppressed plaque formation by inhibiting endothelial VCLS721p. Studies on clinical specimens from patients with coronary artery disease (CAD) revealed that endothelial VCLS721p is a critical clinicopathological biomarker for atherosclerosis progression and that serum VCLS721p level is a promising biomarker for CAD diagnosis.

Conclusions
The findings of this study indicate that endothelial VCLS721p is a valuable hemodynamic-based target for clinical assessment and treatment of vascular disorders resulting from atherosclerosis.