bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparative proteomic analysis highlights metabolic dysfunction in α-synucleinopathy
Authors: Sarkar Souvarish , Murphy Michael A. , Dammer Eric B. , Olsen Abby L. , Rangaraju Srikant , Fraenkel Ernest , Feany Mel B. 
Published: December 2020

AbstractThe synaptic protein α-synuclein is linked through genetics and neuropathology to the pathogenesis of Parkinson’s disease and related disorders. However, the mechanisms by which α-synuclein influences disease onset and progression are incompletely understood. To identify pathogenic pathways and therapeutic targets we performed proteomic analysis in a highly penetrant new Drosophila model of α-synucleinopathy. We identified 476 significantly upregulated and 563 significantly downregulated proteins in heads from α-synucleinopathy model flies compared to controls. We then used multiple complementary analyses to identify and prioritize genes and pathways within the large set of differentially expressed proteins for functional studies. We performed Gene Ontology enrichment analysis, integrated our proteomic changes with human Parkinson’s disease genetic studies, and compared the α-synucleinopathy proteome with that of tauopathy model flies, which are relevant to Alzheimer’s disease and related disorders. These approaches identified GTP cyclohydrolase (GCH1) and folate metabolism as candidate mediators of α-synuclein neurotoxicity. In functional validation studies, we found that the knockdown of Drosophila Gch1 enhanced locomotor deficits in α-synuclein transgenic flies, while folate supplementation protected from α-synuclein toxicity. Our integrative analysis suggested that mitochondrial dysfunction was a common downstream mediator of neurodegeneration. Accordingly, Gch1 knockdown enhanced metabolic dysfunction in α-synuclein transgenic fly brains while folate supplementation partially normalized brain bioenergetics. Here we outline and implement an integrative approach to identify and validate potential therapeutic pathways using comparative proteomics and genetics and capitalizing on the facile genetic and pharmacological tools available in Drosophila.
Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling
Authors: Wang Jou-Kou , Chang Yun-Fan , Tsai Kun-Hsi , Wang Wei-Chien , Tsai Chang-Yen , Cheng Chui-Hsuan , Tsao Yu 
Published: December 2020

AbstractRecognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is challenging for young and inexperienced clinicians. This study is aimed at the development of a novel algorithm that can automatically recognize systolic murmurs in patients with ventricular septal defects (VSDs). Heart sounds from 51 subjects with VSDs and 25 subjects without a significant heart malformation were obtained in this study. Subsequently, the soundtracks were divided into different training and testing sets to establish the recognition system and evaluate the performance. The automatic murmur recognition system was based on a novel temporal attentive pooling-convolutional recurrent neural network (TAP-CRNN) model. On analyzing the performance using the test data that comprised 178 VSD heart sounds and 60 normal heart sounds, a sensitivity rate of 96.0% was obtained along with a specificity of 96.7%. When analyzing the heart sounds recorded in the second aortic and tricuspid areas, both the sensitivity and specificity were 100%. We demonstrated that the proposed TAP-CRNN system can accurately recognize the systolic murmurs of VSD patients, showing promising potential for the development of software for classifying the heart murmurs of several other structural heart diseases.
Characterization, biological evaluation and molecular docking of mulberry fruit pectin
Authors: Kumar R. Venkatesh , Srivastava Devika , Singh Vandana , Kumar Umesh , Vishvakarma Vijay Kumar , Singh Prashant , Kumar Dinesh , Kumar Rajesh 
Published: December 2020

AbstractContemplating the exemplary benefits of pectin on human health, we precisely characterized and evaluated the antibacterial and anticancer activities from purified Mulberry Fruit Pectins (MFP). Here, we tested BR-2 and S-13 varieties of mulberry fruit pectins against six bacterial strains and two human cancer cell lines (HT-29 and Hep G-2), using MIC and an in vitro cell-based assay respectively. The BR-2 mulberry fruit pectin performs superior to S-13 by inhibiting strong bacterial growth (MIC = 500–1000 μg/mL) against tested bacterial strains and cytotoxic activities at the lowest concentration (10 µg/ml) against the Hep G-2 cell line. However, both tested drugs failed to exhibit cytotoxicity on the human colon cancer cell line (HT-29). Based on molecular interaction through docking, pectin binds effectively with the receptors (1e3g, 3t0c, 5czz, 6j7l, 6v40, 5ibs, 5zsy, and 6ggb) and proven to be a promising antimicrobial and anti-cancer agents. The pursuit of unexploited drugs from mulberry fruit pectin will potentially combat against bacterial and cancer diseases. Finally, future perspectives of MFP for the treatment of many chronic diseases will help immensely due to their therapeutic properties.
Improving wear resistance of plasma-sprayed calcia and magnesia-stabilized zirconia mixed coating: roles of phase stability and microstructure
Authors: Hafez Mohamed Abd-Elsattar , Akila Sameh Ahmed , Khedr Mohamed Atta , Khalil Ali Saeid 
Published: December 2020

AbstractThe phase stability and microstructure of ZrO2–5CaO and ZrO2–24MgO mixed coating (wt%) by air plasma spraying on 304 stainless steel substrates were investigated. A Ni–5Al (wt%) metallic bond coating was firstly sprayed between the substrate and the ceramic top layer. The results were compared with the individual coatings of ZrO2–5CaO and ZrO2–24MgO for a better understanding of the correlation between their microstructures and mechanical properties. Mixed zirconia coating was found to have a mixture of cubic and tetragonal phases that stabilized under different plasma spray conditions. Microscopic observations and elemental composition analysis of as-sprayed mixed coating showed that modified ceramic-matrix grains had been formed. Microsized ZrO2–5CaO particles were embedded in the matrix grain creating an intragranular microstructure. Results indicated that ceramic-matrix grains provided a diffusion barrier for the growth of oxides induced stress near and onto the bond layer that reduced cracks, thereby overcoming the top delamination of the ceramic coating. Moreover, disparity in wear resistance and microhardness behavior of the coatings was influenced by initial feedstock powder and matrix microstructures. Improvement in the wear resistance of the mixed zirconia coating was attributed to a decrease in oxide content, which resulted in an increase in intersplat cohesive strength.
Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning
Authors: Shahzad Rahil , Pennig Lenhard , Goertz Lukas , Thiele Frank , Kabbasch Christoph , Schlamann Marc , Krischek Boris , Maintz David , Perkuhn Michael , Borggrefe Jan 
Published: December 2020

AbstractIn aneurysmal subarachnoid hemorrhage (aSAH), accurate diagnosis of aneurysm is essential for subsequent treatment to prevent rebleeding. However, aneurysm detection proves to be challenging and time-consuming. The purpose of this study was to develop and evaluate a deep learning model (DLM) to automatically detect and segment aneurysms in patients with aSAH on computed tomography angiography. In this retrospective single-center study, three different DLMs were trained on 68 patients with 79 aneurysms treated for aSAH (2016–2017) using five-fold-cross-validation. Their outputs were combined to a single DLM via ensemble-learning. The DLM was evaluated on an independent test set consisting of 185 patients with 215 aneurysms (2010–2015). Independent manual segmentations of aneurysms in a 3D voxel-wise manner by two readers (neurosurgeon, radiologist) provided the reference standard. For aneurysms > 30 mm3 (mean diameter of ~ 4 mm) on the test set, the DLM provided a detection sensitivity of 87% with false positives (FPs)/scan of 0.42. Automatic segmentations achieved a median dice similarity coefficient (DSC) of 0.80 compared to the reference standard. Aneurysm location (anterior vs. posterior circulation; P = .07) and bleeding severity (Fisher grade ≤ 3 vs. 4; P = .33) did not impede detection sensitivity or segmentation performance. For aneurysms > 100 mm3 (mean diameter of ~ 6 mm), a sensitivity of 96% with DSC of 0.87 and FPs/scan of 0.14 were obtained. In the present study, we demonstrate that the proposed DLM detects and segments aneurysms > 30 mm3 in patients with aSAH with high sensitivity independent of cerebral circulation and bleeding severity while producing FP findings of less than one per scan. Hence, the DLM can potentially assist treating physicians in aSAH by providing automated detection and segmentations of aneurysms.
Prevalence of Ascaris lumbricoides in contaminated faecal samples of children residing in urban areas of Lahore, Pakistan
Authors: Ali Shahida Azhar , Niaz Sadaf , Aguilar-Marcelino Liliana , Ali Wajid , Ali Majid , Khan Adil , Amir Sohail , Nasreen  , Alanazi Abdullah D. , Cossio-Bayugar Raquel , Amaro-Estrada Itzel 
Published: December 2020

AbstractAscariasis is a common public health problem of preschool and primary school children in developing countries like Pakistan. The aim of the present study was to determine the prevalence and pattern of Ascaris lumbericoides (A. lumbricoides) infection among children residing in urban areas of Lahore, to provide information on ascariasis to promote awareness and prevention programs between the participants specially on the months or season of higher prevalence. To investigate the prevalence of Ascaris Lumbricoides in the contaminated faecal samples of children residing in urban areas of Lahore, a study was conducted from November 2010 to October 2012 and we collected 3600 stratified faecal samples from six urban study areas. Overall 32/3600 (0.88%) prevalence of fecal samples was found positive for eggs of Ascaris lumbricoides. Area wise highest presence positivity 1.67% was observed in Allama Iqbal Town followed by 1.17% in Samanabad, 1.00% in Wapda Town, 1.00% in Gulberg, 0.50% in Cantt, and the lowest 0.00% in Valencia Town respectively (p < 0.001) The highest month wise positivity prevalence 3/300 (3.33%) (p < 0.001) was observed in the month of September that gradually declined up to 0/300 (0.00%) in the month of March. The results reveal that urban areas of Lahore are susceptible to Ascaris Lubricoides infection and the highest prevalence were observed autumn on the month of September.
Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
Authors: Gómez Catalina , Arbeláez Pablo , Navarrete Miguel , Alvarado-Rojas Catalina , Le Van Quyen Michel , Valderrama Mario 
Published: December 2020

AbstractSeizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method to detect epileptic seizures using an imaged-EEG representation of brain signals. To accomplish this, we analyzed EEG signals from two different datasets: the CHB-MIT Scalp EEG database and the EPILEPSIAE project that includes scalp and intracranial recordings. We used fully convolutional neural networks to automatically detect seizures. For our best model, we reached average accuracy and specificity values of 99.3% and 99.6%, respectively, for the CHB-MIT dataset, and corresponding values of 98.0% and 98.3% for the EPILEPSIAE patients. For these patients, the inclusion of intracranial electrodes together with scalp ones increased the average accuracy and specificity values to 99.6% and 58.3%, respectively. Regarding the other metrics, our best model reached average precision of 62.7%, recall of 58.3%, F-measure of 59.0% and AP of 54.5% on the CHB-MIT recordings, and comparatively lowers performances for the EPILEPSIAE dataset. For both databases, the number of false alarms per hour reached values less than 0.5/h for 92% of the CHB-MIT patients and less than 1.0/h for 80% of the EPILEPSIAE patients. Compared to recent studies, our lightweight approach does not need any estimation of pre-selected features and demonstrates high performances with promising possibilities for the introduction of such automatic methods in the clinical practice.
Genome-wide association identifies several QTLs controlling cysteine and methionine content in soybean seed including some promising candidate genes
Authors: Malle Sidiki , Eskandari Milad , Morrison Malcolm , Belzile François 
Published: December 2020

AbstractSoybean is an important source of protein, oil and carbohydrates, as well as other beneficial nutrients. A major function of proteins in nutrition is to supply adequate amounts of amino acids. Although they are essential for human nutrition, the sulfur-containing amino acids cysteine (Cys) and methionine (Met) are often limited and the genetic control of their content in soybean seeds is poorly characterized. This study aimed to characterize the phenotypic variation and identify quantitative trait loci (QTL) associated with Cys and Met content in a core set of 137 soybean lines, representative of the genetic diversity among Canadian short-season soybean, spanning maturity groups 000-II (MG000-II). Significant phenotypic differences were found among these lines for Cys, Met and Cys + Met content. Using both a mixed linear model and six multi-locus methods with a catalogue of 2.18 M SNPs, we report a total of nine QTLs and seventeen QTNs of which seven comprise promising candidate genes. This work allowed us to reproducibly detect multiple novel loci associated with sulfur-containing amino acid content. The markers and genes identified in this study may be useful for soybean genetic improvement aiming to increase Cys and Met content.
Proteomic profile of extracellular vesicles released by Lactiplantibacillus plantarum BGAN8 and their internalization by non-polarized HT29 cell line
Authors: Bajic Svetlana Sokovic , Cañas Maria-Alexandra , Tolinacki Maja , Badia Josefa , Sánchez Borja , Golic Natasa , Margolles Abelardo , Baldomá Laura , Ruas-Madiedo Patricia 
Published: December 2020

AbstractIn recent years the role of extracellular vesicles (EVs) of Gram-positive bacteria in host-microbe cross-talk has become increasingly appreciated, although the knowledge of their biogenesis, release and host-uptake is still limited. The aim of this study was to characterize the EVs released by the dairy isolate Lactiplantibacillus plantarum BGAN8 and to gain an insight into the putative mechanism of EVs uptake by intestinal epithelial cells. The cryo-TEM observation undoubtedly demonstrated the release of EVs (20 to 140 nm) from the surface of BGAN8, with exopolysaccharides seems to be part of EVs surface. The proteomic analysis revealed that the EVs are enriched in enzymes involved in central metabolic pathways, such as glycolysis, and in membrane components with the most abundant proteins belonging to amino acid/peptide ABC transporters. Putative internalization pathways were evaluated in time-course internalization experiments with non-polarized HT29 cells in the presence of inhibitors of endocytic pathways: chlorpromazine and dynasore (inhibitors of clathrin-mediated endocytosis—CME) and filipin III and nystatin (disrupting lipid rafts). For the first time, our results revealed that the internalization was specifically inhibited by dynasore and chlorpromazine but not by filipin III and nystatin implying that one of the entries of L. plantarum vesicles was through CME pathway.
Unveiling giant hidden Rashba effects in two-dimensional Si2Bi2
Authors: Lee Seungjun , Kwon Young-Kyun 
Published: December 2020

AbstractRecently, it has been known that the hidden Rashba (R-2) effect in two-dimensional materials gives rise to a physical phenomenon called spin-layer locking (SLL). However, not only its underlying fundamental mechanism has been unclear, but also there are only a few materials exhibiting weak SLL. Here, through the first-principles density functional theory and model Hamiltonian calculation, we reveal that the R-2 SLL can be determined by the competition between the sublayer–sublayer interaction and the spin–orbit coupling, which is related to the Rashba strength. In addition, the orbital angular momentum distribution is another crucial point to realize the strong R-2 SLL. We propose that a 2D material Si2Bi2 possesses an ideal condition for the strong R-2 SLL, whose Rashba strength is evaluated to be 2.16 eVÅ, which is the greatest value ever observed in 2D R-2 materials to the best of our knowledge. Furthermore, we reveal that the interlayer interaction in a bilayer structure ensures R-2 states spatially farther apart, implying a potential application in spintronics.
Differential longitudinal establishment of human fecal bacterial communities in germ-free porcine and murine models
Authors: Aluthge Nirosh D. , Tom Wesley A. , Bartenslager Alison C. , Burkey Thomas E. , Miller Phillip S. , Heath Kelly D. , Kreikemeier-Bower Craig , Kittana Hatem , Schmaltz Robert J. , Ramer-Tait Amanda E. , Fernando Samodha C. 
Published: December 2020

AbstractThe majority of microbiome studies focused on understanding mechanistic relationships between the host and the microbiota have used mice and other rodents as the model of choice. However, the domestic pig is a relevant model that is currently underutilized for human microbiome investigations. In this study, we performed a direct comparison of the engraftment of fecal bacterial communities from human donors between human microbiota-associated (HMA) piglet and mouse models under identical dietary conditions. Analysis of 16S rRNA genes using amplicon sequence variants (ASVs) revealed that with the exception of early microbiota from infants, the more mature microbiotas tested established better in the HMA piglets compared to HMA mice. Of interest was the greater transplantation success of members belonging to phylum Firmicutes in the HMA piglets compared to the HMA mice. Together, these results provide evidence for the HMA piglet model potentially being more broadly applicable for donors with more mature microbiotas while the HMA mouse model might be more relevant for developing microbiotas such as those of infants. This study also emphasizes the necessity to exercise caution in extrapolating findings from HMA animals to humans, since up to 28% of taxa from some donors failed to colonize either model.
The human primary somatosensory cortex encodes imagined movement in the absence of sensory information
Authors: Jafari Matiar , Aflalo Tyson , Chivukula Srinivas , Kellis Spencer Sterling , Salas Michelle Armenta , Norman Sumner Lee , Pejsa Kelsie , Liu Charles Yu , Andersen Richard Alan 
Published: December 2020

AbstractClassical systems neuroscience positions primary sensory areas as early feed-forward processing stations for refining incoming sensory information. This view may oversimplify their role given extensive bi-directional connectivity with multimodal cortical and subcortical regions. Here we show that single units in human primary somatosensory cortex encode imagined reaches in a cognitive motor task, but not other sensory–motor variables such as movement plans or imagined arm position. A population reference-frame analysis demonstrates coding relative to the cued starting hand location suggesting that imagined reaching movements are encoded relative to imagined limb position. These results imply a potential role for primary somatosensory cortex in cognitive imagery, engagement during motor production in the absence of sensation or expected sensation, and suggest that somatosensory cortex can provide control signals for future neural prosthetic systems.
Instantaneous generation of protein hydration properties from static structures
Authors: Ghanbarpour Ahmadreza , Mahmoud Amr H. , Lill Markus A. 
Published: December 2020

AbstractComplex molecular simulation methods are typically required to calculate the thermodynamic properties of biochemical systems. One example thereof is the thermodynamic profiling of (de)solvation of proteins, which is an essential driving force for protein-ligand and protein-protein binding. The thermodynamic state of water molecules depends on its enthalpic and entropic components; the latter is governed by dynamic properties of the molecule. Here, we developed, to the best of our knowledge, two novel machine learning methods based on deep neural networks that are able to generate the converged thermodynamic state of dynamic water molecules in the heterogeneous protein environment based solely on the information of the static protein structure. The applicability of our machine learning methods to predict the hydration information is demonstrated in two different studies, the qualitative analysis and quantitative prediction of structure-activity relationships, and the prediction of protein-ligand binding modes.
Identification of ribosomal protein family in triple-negative breast cancer by bioinformatics analysis
Authors: Lin Ziyue , Peng Rui , Sun Yan , Zhang Luyu , Zhang Zheng 
Published: December 2020

Abstract
Triple-negative breast cancer (TNBC) accounts for ∼20% of all breast cancer (BC) cases. The management of TNBC represents a challenge due to its worse prognosis, heterogeneity and lack of targeted therapy. Moreover, its mechanisms are not fully clear. The aim of the study is to identify crucial genes between TNBC and non-TNBC for underlying targets for diagnostic and therapeutic methods of TNBC. The differentially expressed genes (DEGs) between TNBC and non-TNBC were selected from the Gene Expression Omnibus (GEO) database after the integrated analysis of two datasets (GSE65194 and GSE76124). Then Gene ontology (GO) and KEGG analysis were performed by DAVID database, protein–protein interaction (PPI) of DEGs was constructed by Search Tool for the Retrieval of Reciprocity Genes (STRING) database. Furthermore, centrality analysis and module analysis were carried out by Cytoscape to analyze the TNBC-related PPI. Subsequently, overall survival (OS) analysis was performed by GEPIA. Finally, the expressions of these key genes in TNBC and non-TNBC tissues were tested by qRT-PCR. The results showed that 955 DEGs were obtained, which were mainly enriched in ribosome, ribosomal subunit, and so on. Moreover, 19 candidate genes were focused on by centrality analysis and module analysis. Furthermore, we found the low expressions of ribosomal protein S9 (RPS9), ribosomal protein S14 (RPS14), ribosomal protein S27 (RPS27), ribosomal protein L11 (RPL11) and ribosomal protein L14 (RPL14) were related to a poor OS in BC patients. Additionally, qRT-PCR results suggested that these five genes were notably down-regulated in TNBC tissues. In summary, the present study suggests that ribosomal proteins are related to TNBC, and they may play an important role in the diagnosis, treatment and prognosis of TNBC.