bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy
Authors: Pernice Riccardo , Faes Luca , Feucht Martha , Benninger Franz , Mangione Stefano , Schiecke Karin 
Published: July 2022

Abstract

Objective. While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger Causality (GC) and partial information decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy. Approach. HRV and the envelopes of δ and α EEG activity recorded from ipsilateral (ipsi-EEG) and contralateral (contra-EEG) scalp regions were analyzed in 18 children suffering from temporal lobe epilepsy monitored during pre-ictal, ictal and post-ictal periods. After linear parametric model identification, we compared pairwise GC measures computed between HRV and a single EEG component with PID measures quantifying the unique, redundant and synergistic information transferred from ipsi-EEG and contra-EEG to HRV. Main results. The analysis of GC revealed a dominance of the information transfer from EEG to HRV and negligible transfer from HRV to EEG, suggesting that CNS activities drive the ANS modulation of the heart rhythm, but did not evidence clear differences between δ and α rhythms, ipsi-EEG and contra-EEG, or pre- and post-ictal periods. On the contrary, PID revealed that epileptic seizures induce a reorganization of the interactions from brain to heart, as the unique predictability of HRV originated from the ipsi-EEG for the δ waves and from the contra-EEG for the α waves in the pre-ictal phase, while these patterns were reversed after the seizure. Significance. These results highlight the importance of considering higher-order interactions elicited by PID for the study of the neuro-autonomic effects of focal epilepsy, and may have neurophysiological and clinical implications.
Automated optimization of multilevel models of collective behaviour: application to mixed society of animals and robots
Authors: Cazenille Leo , Bredeche Nicolas , Halloy José 
Published: July 2022

Abstract
Animal societies exhibit complex dynamics that require multi-level descriptions. They are difficult to model, as they encompass information at different levels of description, such as individual physiology, individual behaviour, group behaviour and features of the environment. The collective behaviour of a group of animals can be modelled as a dynamical system. Typically, models of behaviour are either macroscopic (differential equations of population dynamics) or microscopic (such as Markov chains, explicitly specifying the spatio-temporal state of each individual). These two kind of models offer distinct and complementary descriptions of the observed behaviour. Macroscopic models offer mean field description of the collective dynamics, where collective choices are considered as the stable steady states of a nonlinear system governed by control parameters leading to bifurcation diagrams. Microscopic models can be used to perform computer simulations or as building blocks for robot controllers, at the individual level, of the observed spatial behaviour of animals. Here, we present a methodology to translate a macroscopic model into different microscopic models. We automatically calibrate the microscopic models so that the resulting simulated collective dynamics fit the solutions of the reference macroscopic model for a set of parameter values corresponding to a bifurcation diagram leading to multiple steady states. We apply evolutionary algorithms to simultaneously optimize the parameters of the models at different levels of description. This methodology is applied, in simulation, to an experimentally validated shelter-selection problem solved by gregarious insects and robots. Our framework can be used for multi-level modelling of collective behaviour in animals and robots.
Wide-range characteristics of beam perveance and saddle point potential of LIPS-200 ion thruster
Authors: ZHANG Xueer , ZHANG Tianping , LI Detian , CHEN Juanjuan , JIA Yanhui 
Published: July 2022

Abstract
Both the long-life and multi-mode versions of LIPS-200 ion thruster are under investigation in LIP (Lanzhou Institute of Physics). To confirm the feasible ranges of the beam current and accel (abbreviation for accelaration) grid potential to apply to the thruster, the wide-range beam perveance (the state of beam focus) and saddle point potential (the lowest potential along beamlet centerline) characteristics of LIPS-200 are studied with a test-verified PIC-MCC (Particle in Cell-Monte Carlo Collisions) model. These characteristics are investigated with both the initial and the eroded states of the accel grid aperture diameter. The results show that the feasible ranges of these parameters with respect to perveance/crossover (overfocused) limit extend as the operating time accumulates, while the feasible range of accel grid potential narrows due to a reduced EBSF (electron backstreaming failure) margin. The feasible ranges determined by the initial condition are: (i) the beam current up to 0.981 A, and (ii) the accel grid potential up to −85 V. A 23% enlargement of the aperture diameter would bring up to 48 V of EBSF margin loss.
Recent developments and perspectives of advanced high-strength medium Mn steel: from material design to failure mechanisms
Authors: Huang Chengpeng , Hu Chen , Liu Yuxuan , Liang Zhiyuan , Huang Mingxin 
Published: July 2022

Abstract
Advanced high-strength steels are key structural materials for the development of next-generation energy-efficient and environmentally friendly vehicles. Medium Mn steel, as one of the latest generation advanced high-strength steels, has attracted tremendous attentions over the past decade due to its excellent mechanical properties. Here, the state-of-the-art developments of medium Mn steel are systematically reviewed with focus on the following crucial aspects: (a) the alloy design strategies; (b) the thermomechanical processing routes for the optimizations of microstructure and mechanical properties; (c) the fracture mechanisms and toughening strategies; (d) the hydrogen embrittlement mechanisms and improvement strategies.
Solid-state Z-scheme assisted hydrated tungsten trioxide/ZnIn2S4 photocatalyst for efficient photocatalytic H2 production
Authors: Ye Lin , Peng Xinxin , Wen Zhenhai , Huang Haitao 
Published: July 2022

Abstract
Efficient water splitting for H2 evolution over semiconductor photocatalysts is highly attractive in the field of clean energy. It is of great significance to construct heterojunctions, among which the direct Z-scheme nanocomposite photocatalyst provides effective separation of photo-generated carriers to boost the photocatalytic performance. Herein, Z-scheme hydrated tungsten trioxide/ZnIn2S4 is fabricated via an in-situ hydrothermal method where ZnIn2S4 nanosheets are grown on WO3⋅xH2O. The close contact between WO3⋅0.5H2O and WO3⋅0.33H2O as well as ZnIn2S4 improve the charge carrier separation and migration in the photocatalyst, where the strong reducing electrons in the conduction band of ZnIn2S4 and the strong oxidizing holes in the valence band of WO3⋅0.33H2O are retained, leading to enhanced photocatalytic hydrogen production. The obtained WO3⋅xH2O/ZnIn2S4 shows an excellent H2 production rate of 7200 μmol g−1 h−1, which is 11 times higher than pure ZnIn2S4. To the best of our knowledge, this value is higher than most of the WO3-based noble metal-free semiconductor photocatalysts. The improved stability and activity are attributed to the formation of the Z-scheme heterojunction, which can markedly accelerate the interfacial charge separation for surface reaction. This work offers a promising strategy towards the design of an efficient Z-scheme photocatalyst to suppress electron–hole recombination and optimize redox potential.
Rhytidoplasty Through Minimal Incisions (Rhythmic)
Authors: Castillo-Campos Porfirio 
Published: July 2022

Abstract

Background
In the present report, an innovative alternative approach for rhytidoplasty is described. Rhytidoplasty Through Minimal Incisions (Rhythmic) is an effective, efficient, safe, and reproducible alternative procedure for facial rejuvenation. It has several advantages over traditional procedures.

Objective
The main objective of this report is to describe the surgical technique of Rhythmic.

Methods
The surgical technique for the foreheadplasty requires only a transverse ~7-mm incision ~1 cm behind the hairline at the midline. The upper and lower blepharoplasty are made with incisions of ~3 mm, and no suture is needed. Liposuction of the neck can also be performed, and the face-lift can be achieved through preauricular incisions.

Results
Here, we summarize the results obtained in 741 patients subjected to rhytidoplasty through minimal incisions. The follow-up of these patients extended up to 20 years. This technique drastically reduced the length of scars; the eyebrows elevated 8-13 mm, and in some cases, the tip of the nose was also elevated ~7 mm. It minimized or eliminated the vertical frown lines and the horizontal furrows in the forehead. The use of this technique allowed an excellent definition of the cervicofacial angle in the patients.

Conclusions
In conclusion, rhytidoplasty through minimal incisions drastically reduced the length of scars, bleeding, surgical time, avoided the use of drains, reduced costs, and shorted the convalescent period. It also offered the patients a natural appearance with minor complications.

Level of Evidence: 2
BubbleGun: enumerating bubbles and superbubbles in genome graphs
Authors: Dabbaghie Fawaz , Ebler Jana , Marschall Tobias 
Published: July 2022

AbstractMotivationWith the fast development of sequencing technology, accurate de novo genome assembly is now possible even for larger genomes. Graph-based representations of genomes arise both as part of the assembly process, but also in the context of pangenomes representing a population. In both cases, polymorphic loci lead to bubble structures in such graphs. Detecting bubbles is hence an important task when working with genomic variants in the context of genome graphs.ResultsHere, we present a fast general-purpose tool, called BubbleGun, for detecting bubbles and superbubbles in genome graphs. Furthermore, BubbleGun detects and outputs runs of linearly connected bubbles and superbubbles, which we call bubble chains. We showcase its utility on de Bruijn graphs and compare our results to vg’s snarl detection. We show that BubbleGun is considerably faster than vg especially in bigger graphs, where it reports all bubbles in less than 30 min on a human sample de Bruijn graph of around 2 million nodes.Availability and implementationBubbleGun is available and documented as a Python3 package at https://github.com/fawaz-dabbaghieh/bubble_gun under MIT license.Supplementary informationSupplementary data are available at Bioinformatics online.
DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images
Authors: Wang Yanan , Hu Changyuan , Kwok Terry , Bain Christopher A , Xue Xiangyang , Gasser Robin B , Webb Geoffrey I , Boussioutas Alex , Shen Xian , Daly Roger J , Song Jiangning 
Published: July 2022

AbstractMotivationThe molecular subtyping of gastric cancer (adenocarcinoma) into four main subtypes based on integrated multiomics profiles, as proposed by The Cancer Genome Atlas (TCGA) initiative, represents an effective strategy for patient stratification. However, this approach requires the use of multiple technological platforms, and is quite expensive and time-consuming to perform. A computational approach that uses histopathological image data to infer molecular subtypes could be a practical, cost- and time-efficient complementary tool for prognostic and clinical management purposes.ResultsHere, we propose a deep learning ensemble approach (called DEMoS) capable of predicting the four recognized molecular subtypes of gastric cancer directly from histopathological images. DEMoS achieved tile-level area under the receiver-operating characteristic curve (AUROC) values of 0.785, 0.668, 0.762 and 0.811 for the prediction of these four subtypes of gastric cancer [i.e. (i) Epstein–Barr (EBV)-infected, (ii) microsatellite instability (MSI), (iii) genomically stable (GS) and (iv) chromosomally unstable tumors (CIN)] using an independent test dataset, respectively. At the patient-level, it achieved AUROC values of 0.897, 0.764, 0.890 and 0.898, respectively. Thus, these four subtypes are well-predicted by DEMoS. Benchmarking experiments further suggest that DEMoS is able to achieve an improved classification performance for image-based subtyping and prevent model overfitting. This study highlights the feasibility of using a deep learning ensemble-based method to rapidly and reliably subtype gastric cancer (adenocarcinoma) solely using features from histopathological images.Availability and implementationAll whole slide images used in this study was collected from the TCGA database. This study builds upon our previously published HEAL framework, with related documentation and tutorials available at http://heal.erc.monash.edu.au. The source code and related models are freely accessible at https://github.com/Docurdt/DEMoS.git.Supplementary informationSupplementary data are available at Bioinformatics online.
SLPred: a multi-view subcellular localization prediction tool for multi-location human proteins
Authors: Özsarı Gökhan , Rifaioglu Ahmet Sureyya , Atakan Ahmet , Doğan Tunca , Martin Maria Jesus , Çetin Atalay Rengül , Atalay Volkan 
Published: July 2022

AbstractSummaryAccurate prediction of the subcellular locations (SLs) of proteins is a critical topic in protein science. In this study, we present SLPred, an ensemble-based multi-view and multi-label protein subcellular localization prediction tool. For a query protein sequence, SLPred provides predictions for nine main SLs using independent machine-learning models trained for each location. We used UniProtKB/Swiss-Prot human protein entries and their curated SL annotations as our source data. We connected all disjoint terms in the UniProt SL hierarchy based on the corresponding term relationships in the cellular component category of Gene Ontology and constructed a training dataset that is both reliable and large scale using the re-organized hierarchy. We tested SLPred on multiple benchmarking datasets including our-in house sets and compared its performance against six state-of-the-art methods. Results indicated that SLPred outperforms other tools in the majority of cases.Availability and implementationSLPred is available both as an open-access and user-friendly web-server (https://slpred.kansil.org) and a stand-alone tool (https://github.com/kansil/SLPred). All datasets used in this study are also available at https://slpred.kansil.org.Supplementary informationSupplementary data are available at Bioinformatics online.
HARIBOSS: a curated database of RNA-small molecules structures to aid rational drug design
Authors: Panei F P , Torchet R , Ménager H , Gkeka P , Bonomi M 
Published: July 2022

AbstractMotivationRNA molecules are implicated in numerous fundamental biological processes and many human pathologies, such as cancer, neurodegenerative disorders, muscular diseases and bacterial infections. Modulating the mode of action of disease-implicated RNA molecules can lead to the discovery of new therapeutical agents and even address pathologies linked to ‘undruggable’ protein targets. This modulation can be achieved by direct targeting of RNA with small molecules. As of today, only a few RNA-targeting small molecules are used clinically. One of the main obstacles that have hampered the development of a rational drug design protocol to target RNA with small molecules is the lack of a comprehensive understanding of the molecular mechanisms at the basis of RNA-small molecule (RNA-SM) recognition.ResultsHere, we present Harnessing RIBOnucleic acid—Small molecule Structures (HARIBOSS), a curated collection of RNA-SM structures determined by X-ray crystallography, nuclear magnetic resonance spectroscopy and cryo-electron microscopy. HARIBOSS facilitates the exploration of drug-like compounds known to bind RNA, the analysis of ligands and pockets properties and ultimately the development of in silico strategies to identify RNA-targeting small molecules.Availability and implementationHARIBOSS can be explored via a web interface available at http://hariboss.pasteur.cloud.Supplementary informationSupplementary data are available at Bioinformatics online.
Docking cyclic peptides formed by a disulfide bond through a hierarchical strategy
Authors: Tao Huanyu , Zhao Xuejun , Zhang Keqiong , Lin Peicong , Huang Sheng-You 
Published: July 2022

AbstractMotivationCyclization is a common strategy to enhance the therapeutic potential of peptides. Many cyclic peptide drugs have been approved for clinical use, in which the disulfide-driven cyclic peptide is one of the most prevalent categories. Molecular docking is a powerful computational method to predict the binding modes of molecules. For protein-cyclic peptide docking, a big challenge is considering the flexibility of peptides with conformers constrained by cyclization.ResultsIntegrating our efficient peptide 3D conformation sampling algorithm MODPEP2.0 and knowledge-based scoring function ITScorePP, we have proposed an extended version of our hierarchical peptide docking algorithm, named HPEPDOCK2.0, to predict the binding modes of the peptide cyclized through a disulfide against a protein. Our HPEPDOCK2.0 approach was extensively evaluated on diverse test sets and compared with the state-of-the-art cyclic peptide docking program AutoDock CrankPep (ADCP). On a benchmark dataset of 18 cyclic peptide-protein complexes, HPEPDOCK2.0 obtained a native contact fraction of above 0.5 for 61% of the cases when the top prediction was considered, compared with 39% for ADCP. On a larger test set of 25 cyclic peptide-protein complexes, HPEPDOCK2.0 yielded a success rate of 44% for the top prediction, compared with 20% for ADCP. In addition, HPEPDOCK2.0 was also validated on two other test sets of 10 and 11 complexes with apo and predicted receptor structures, respectively. HPEPDOCK2.0 is computationally efficient and the average running time for docking a cyclic peptide is about 34 min on a single CPU core, compared with 496 min for ADCP. HPEPDOCK2.0 will facilitate the study of the interaction between cyclic peptides and proteins and the development of therapeutic cyclic peptide drugs.Availability and implementationhttp://huanglab.phys.hust.edu.cn/hpepdock/.Supplementary informationSupplementary data are available at Bioinformatics online.
GenBank as a source to monitor and analyze Host-Microbiome data
Authors: Ramanan Vivek , Mechery Shanti , Sarkar Indra Neil 
Published: July 2022

AbstractMotivationMicrobiome datasets are often constrained by sequencing limitations. GenBank is the largest collection of publicly available DNA sequences, which is maintained by the National Center of Biotechnology Information (NCBI). The metadata of GenBank records are a largely understudied resource and may be uniquely leveraged to access the sum of prior studies focused on microbiome composition. Here, we developed a computational pipeline to analyze GenBank metadata, containing data on hosts, microorganisms and their place of origin. This work provides the first opportunity to leverage the totality of GenBank to shed light on compositional data practices that shape how microbiome datasets are formed as well as examine host–microbiome relationships.ResultsThe collected dataset contains multiple kingdoms of microorganisms, consisting of bacteria, viruses, archaea, protozoa, fungi, and invertebrate parasites, and hosts of multiple taxonomical classes, including mammals, birds and fish. A human data subset of this dataset provides insights to gaps in current microbiome data collection, which is biased towards clinically relevant pathogens. Clustering and phylogenic analysis reveals the potential to use these data to model host taxonomy and evolution, revealing groupings formed by host diet, environment and coevolution.Availability and implementationGenBank Host-Microbiome Pipeline is available at https://github.com/bcbi/genbank_holobiome. The GenBank loader is available at https://github.com/bcbi/genbank_loader.Supplementary informationSupplementary data are available at Bioinformatics online.
In Search of Social justice-informed Services: A Research Agenda for the Study of Resistance to Neo-managerialism
Authors: Timor-Shlevin Shachar , Hermans Koen , Roose Rudi 
Published: July 2022

Abstract
One of the main characteristics of social work is the fundamental tension between the profession’s conservative and critical rationales. In the last three decades, this tension has informed the development of critical resistance to the deprofessionalisation effects of neo-managerial rationality, which establishes cost reduction and fiscal accountability as the basis for professional practice. However, the theoretical conceptualisation of such critical resistance is caught between minor and major operations, both of which are considered insufficient. Addressing this gap, this article builds on the theoretical framework of radical incrementalism to develop a research agenda for the future study of resistance processes, which we conceptualise as operating in the middle range of a power exertion scale, between minor and major forms of operation. We portray the operation of resistance in the middle range of such a power exertion scale and offer a research agenda that includes relevant research directions and methodological considerations. In this way, the article suggests new ways of understanding, conceptualising and operating resistance to enable further development of the social justice-informed professionalisation of social work.
Fear conditioning as a pathogenic mechanism in the postural tachycardia syndrome
Authors: Norcliffe-Kaufmann Lucy , Palma Jose-Alberto , Martinez Jose , Camargo Celeste , Kaufmann Horacio 
Published: July 2022

Abstract
Despite its increasing recognition and extensive research, there is no unifying hypothesis on the pathophysiology of the postural tachycardia syndrome. In this cross-sectional study, we examined the role of fear conditioning and its association with tachycardia and cerebral hypoperfusion on standing in 28 patients with postural tachycardia syndrome (31 ± 12 years old, 25 females) and 21 matched controls. We found that patients had higher somatic vigilance (P = 0.0167) and more anxiety (P &lt; 0.0001). They also had a more pronounced anticipatory tachycardia right before assuming the upright position in a tilt-table test (P = 0.015), a physiological indicator of fear conditioning to orthostasis. While standing, patients had faster heart rate (P &lt; 0.001), higher plasma catecholamine levels (P = 0.020), lower end-tidal CO2 (P = 0.005) and reduced middle cerebral artery blood flow velocity (P = 0.002). Multi-linear logistic regression modelling showed that both epinephrine secretion and excessive somatic vigilance predicted the magnitude of the tachycardia and the hyperventilation. These findings suggest that the postural tachycardia syndrome is a functional disorder in which standing may acquire a frightful quality, so that even when experienced alone it may elicit a fearful conditioned response. Heightened somatic anxiety is associated with and may predispose to a fear-conditioned hyperadrenergic state when standing. Our results have therapeutic implications.