bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hybrid composite based on conducting polymers and plasmonic nanomaterials applied to catalysis and sensing
Authors: Alanazi Ahmed T , Rice James H 
Published: June 2022

Abstract
Combining plasmonic and semiconductors offers significant potential in creating sensing and photocatalytic devices. Nanocomposites including both metals and semiconductors can control the charge states in the metals that can enhance catalysis activity along with plasmon-enhanced spectroscopy. Here we demonstrate the use of conducting polymer materials with plasmonic nanomaterials to boost up to five-fold plasmon-enhanced Raman scattering spectroscopy signal strength and support oxidation of target molecules through supporting charge transfer processes. This work demonstrates the use of conducting polymers as a semiconductor platform to support plasmonic catalysis and sensing.
Ageing meets kidney disease
Authors: Ortiz Alberto , Mattace-Raso Francesco , Soler María José , Fouque Denis 
Published: June 2022

Abstract
Chronic kidney disease (CKD) is defined as abnormalities of kidney structure or function, present for &gt;3 months, with implications for health. The most used diagnostic criteria are a urinary albumin: creatinine ratio ≥30 mg/g or an estimated glomerular filtration rate (eGFR) &lt;60 mL/min/1.73 m2. Either of these diagnostic thresholds is associated with adverse health outcomes. GFR decreases with age and the prevalence of CKD is highest in older adults; moreover, the presence of CKD is associated with an increased risk of all-cause and cardiovascular death related to accelerated ageing in all age ranges, and the absolute increase in risk is highest for those aged &gt;75 years. Indeed, premature death is a more common outcome than CKD progression to kidney failure requiring kidney replacement therapy. The progressive ageing of the world population contributes to the projection that CKD will become the second most common cause of death before the end of the century in countries with long life expectancy. The current collection of selected studies on kidney disease and ageing published in Age&Ageing, NDT and CKJ provides an overview of key topics, including cognitive decline, sarcopaenia, wasting and cardiovascular and non-cardiovascular morbidity and mortality, the management of kidney failure and gender differences in CKD progression.
Characterization, costs, cues and future perspectives of phenotypic plasticity
Authors: Schneider Hannah M 
Published: June 2022

AbstractBackgroundPlastic responses of plants to the environment are ubiquitous. Phenotypic plasticity occurs in many forms and at many biological scales, and its adaptive value depends on the specific environment and interactions with other plant traits and organisms. Even though plasticity is the norm rather than the exception, its complex nature has been a challenge in characterizing the expression of plasticity, its adaptive value for fitness and the environmental cues that regulate its expression.ScopeThis review discusses the characterization and costs of plasticity and approaches, considerations, and promising research directions in studying plasticity. Phenotypic plasticity is genetically controlled and heritable; however, little is known about how organisms perceive, interpret and respond to environmental cues, and the genes and pathways associated with plasticity. Not every genotype is plastic for every trait, and plasticity is not infinite, suggesting trade-offs, costs and limits to expression of plasticity. The timing, specificity and duration of plasticity are critical to their adaptive value for plant fitness.ConclusionsThere are many research opportunities to advance our understanding of plant phenotypic plasticity. New methodology and technological breakthroughs enable the study of phenotypic responses across biological scales and in multiple environments. Understanding the mechanisms of plasticity and how the expression of specific phenotypes influences fitness in many environmental ranges would benefit many areas of plant science ranging from basic research to applied breeding for crop improvement.
Accurate identification of bacteriophages from metagenomic data using Transformer
Authors: Shang Jiayu , Tang Xubo , Guo Ruocheng , Sun Yanni 
Published: June 2022

Abstract

Motivation
Bacteriophages are viruses infecting bacteria. Being key players in microbial communities, they can regulate the composition/function of microbiome by infecting their bacterial hosts and mediating gene transfer. Recently, metagenomic sequencing, which can sequence all genetic materials from various microbiome, has become a popular means for new phage discovery. However, accurate and comprehensive detection of phages from the metagenomic data remains difficult. High diversity/abundance, and limited reference genomes pose major challenges for recruiting phage fragments from metagenomic data. Existing alignment-based or learning-based models have either low recall or precision on metagenomic data.

Results
In this work, we adopt the state-of-the-art language model, Transformer, to conduct contextual embedding for phage contigs. By constructing a protein-cluster vocabulary, we can feed both the protein composition and the proteins’ positions from each contig into the Transformer. The Transformer can learn the protein organization and associations using the self-attention mechanism and predicts the label for test contigs. We rigorously tested our developed tool named PhaMer on multiple datasets with increasing difficulty, including quality RefSeq genomes, short contigs, simulated metagenomic data, mock metagenomic data and the public IMG/VR dataset. All the experimental results show that PhaMer outperforms the state-of-the-art tools. In the real metagenomic data experiment, PhaMer improves the F1-score of phage detection by 27%.
ResPAN: a powerful batch correction model for scRNA-seq data through residual adversarial networks
Authors: Wang Yuge , Liu Tianyu , Zhao Hongyu 
Published: June 2022

AbstractMotivationWith the advancement of technology, we can generate and access large-scale, high dimensional and diverse genomics data, especially through single-cell RNA sequencing (scRNA-seq). However, integrative downstream analysis from multiple scRNA-seq datasets remains challenging due to batch effects.ResultsIn this article, we propose a light-structured deep learning framework called ResPAN for scRNA-seq data integration. ResPAN is based on Wasserstein Generative Adversarial Network (WGAN) combined with random walk mutual nearest neighbor pairing and fully skip-connected autoencoders to reduce the differences among batches. We also discuss the limitations of existing methods and demonstrate the advantages of our model over seven other methods through extensive benchmarking studies on both simulated data under various scenarios and real datasets across different scales. Our model achieves leading performance on both batch correction and biological information conservation and maintains scalable to datasets with over half a million cells.Availability and implementationAn open-source implementation of ResPAN and scripts to reproduce the results can be downloaded from: https://github.com/AprilYuge/ResPAN.Supplementary informationSupplementary data are available at Bioinformatics online.
i6mA-Caps: a CapsuleNet-based framework for identifying DNA N6-methyladenine sites
Authors: Rehman Mobeen Ur , Tayara Hilal , Zou Quan , Chong Kil To 
Published: June 2022

AbstractMotivationDNA N6-methyladenine (6mA) has been demonstrated to have an essential function in epigenetic modification in eukaryotic species in recent research. 6mA has been linked to various biological processes. It’s critical to create a new algorithm that can rapidly and reliably detect 6mA sites in genomes to investigate their biological roles. The identification of 6mA marks in the genome is the first and most important step in understanding the underlying molecular processes, as well as their regulatory functions.ResultsIn this article, we proposed a novel computational tool called i6mA-Caps which CapsuleNet based a framework for identifying the DNA N6-methyladenine sites. The proposed framework uses a single encoding scheme for numerical representation of the DNA sequence. The numerical data is then used by the set of convolution layers to extract low-level features. These features are then used by the capsule network to extract intermediate-level and later high-level features to classify the 6mA sites. The proposed network is evaluated on three datasets belonging to three genomes which are Rosaceae, Rice and Arabidopsis thaliana. Proposed method has attained an accuracy of 96.71%, 94% and 86.83% for independent Rosaceae dataset, Rice dataset and A.thaliana dataset respectively. The proposed framework has exhibited improved results when compared with the existing top-of-the-line methods.Availability and implementationA user-friendly web-server is made available for the biological experts which can be accessed at: http://nsclbio.jbnu.ac.kr/tools/i6mA-Caps/.Supplementary informationSupplementary data are available at Bioinformatics online.
InterpolatedXY: a two-step strategy to normalize DNA methylation microarray data avoiding sex bias
Authors: Wang Yucheng , Gorrie-Stone Tyler J , Grant Olivia A , Andrayas Alexandria D , Zhai Xiaojun , McDonald-Maier Klaus D , Schalkwyk Leonard C 
Published: June 2022

AbstractMotivationData normalization is an essential step to reduce technical variation within and between arrays. Due to the different karyotypes and the effects of X chromosome inactivation, females and males exhibit distinct methylation patterns on sex chromosomes; thus, it poses a significant challenge to normalize sex chromosome data without introducing bias. Currently, existing methods do not provide unbiased solutions to normalize sex chromosome data, usually, they just process autosomal and sex chromosomes indiscriminately.ResultsHere, we demonstrate that ignoring this sex difference will lead to introducing artificial sex bias, especially for thousands of autosomal CpGs. We present a novel two-step strategy (interpolatedXY) to address this issue, which is applicable to all quantile-based normalization methods. By this new strategy, the autosomal CpGs are first normalized independently by conventional methods, such as funnorm or dasen; then the corrected methylation values of sex chromosome-linked CpGs are estimated as the weighted average of their nearest neighbors on autosomes. The proposed two-step strategy can also be applied to other non-quantile-based normalization methods, as well as other array-based data types. Moreover, we propose a useful concept: the sex explained fraction of variance, to quantitatively measure the normalization effect.Availability and implementationThe proposed methods are available by calling the function ‘adjustedDasen’ or ‘adjustedFunnorm’ in the latest wateRmelon package (https://github.com/schalkwyk/wateRmelon), with methods compatible with all the major workflows, including minfi.Supplementary informationSupplementary data are available at Bioinformatics online.
Ab-CoV: a curated database for binding affinity and neutralization profiles of coronavirus-related antibodies
Authors: Rawat Puneet , Sharma Divya , Prabakaran R , Ridha Fathima , Mohkhedkar Mugdha , Janakiraman Vani , Gromiha M Michael 
Published: June 2022

AbstractSummaryWe have developed a database, Ab-CoV, which contains manually curated experimental interaction profiles of 1780 coronavirus-related neutralizing antibodies. It contains more than 3200 datapoints on half maximal inhibitory concentration (IC50), half maximal effective concentration (EC50) and binding affinity (KD). Each data with experimentally known three-dimensional structures are complemented with predicted change in stability and affinity of all possible point mutations of interface residues. Ab-CoV also includes information on epitopes and paratopes, structural features of viral proteins, sequentially similar therapeutic antibodies and Collier de Perles plots. It has the feasibility for structure visualization and options to search, display and download the data.Availability and implementationAb-CoV database is freely available at https://web.iitm.ac.in/bioinfo2/ab-cov/home.Supplementary informationSupplementary data are available at Bioinformatics online.
Topological analysis as a tool for detection of abnormalities in protein–protein interaction data
Authors: Nowakowska Alicja W , Kotulska Malgorzata 
Published: June 2022

AbstractMotivationProtein–protein interaction datasets, which can be modeled as networks, constitute an essential layer in multi-omics approach to biomedical knowledge. This representation gives insight into molecular pathways, help to uncover novel potential drug targets or predict a therapy outcome. Nevertheless, the data that constitute such systems are frequently incomplete, error-prone and biased by scientific trends. Implementation of methods for detection of such shortcomings could improve protein–protein interaction data analysis.ResultsWe performed topological analysis of three protein–protein interaction networks (PPINs) from IntAct Molecular Database, regarding cancer, Parkinson’s disease (two most common subjects in PPINs analysis) and Human Reference Interactome. The data collections were shown to be often biased by scientific interests, which highly impact the networks structure. This may obscure correct systematic biological interpretation of the protein–protein interactions and limit their application potential. As a solution to this problem, we propose a set of topological methods for the bias detection, which performed in the first step provides more objective biological conclusions regarding protein–protein interactions and their multi-omics consequences.Availability and implementationA user-friendly tool Extensive Tool for Network Analysis (ETNA) is available on https://github.com/AlicjaNowakowska/ETNA. The software includes a graphical Colab notebook: https://githubtocolab.com/AlicjaNowakowska/ETNA/blob/main/ETNAColab.ipynb.Contactalicja.nowakowska@pwr.edu.pl or malgorzata.kotulska@pwr.edu.plSupplementary informationSupplementary data are available at Bioinformatics online.
Full spectrum of vitamin D immunomodulation in multiple sclerosis: mechanisms and therapeutic implications
Authors: Galoppin Manon , Kari Saniya , Soldati Sasha , Pal Arindam , Rival Manon , Engelhardt Britta , Astier Anne , Thouvenot Eric 
Published: June 2022

AbstractVitamin D deficiency has been associated with the risk of multiple sclerosis, disease activity and progression. Results from in vitro experiments, animal models and analysis of human samples from randomized controlled trials provide comprehensive data illustrating the pleiotropic actions of Vitamin D on the immune system. They globally result in immunomodulation by decreasing differentiation of effector T and B cells while promoting regulatory subsets. Vitamin D also modulates innate immune cells such as macrophages, monocytes and dendritic cells, and acts at the level of the blood–brain barrier reducing immune cell trafficking. Vitamin D exerts additional activity within the central nervous system reducing microglial and astrocytic activation. The immunomodulatory role of Vitamin D detected in animal models of multiple sclerosis has suggested its potential therapeutic use for treating multiple sclerosis. In this review, we focus on recent published data describing the biological effects of Vitamin D in animal models of multiple sclerosis on immune cells, blood–brain barrier function, activation of glial cells and its potential neuroprotective effects. Based on the current knowledge, we also discuss optimization of therapeutic interventions with Vitamin D in patients with multiple sclerosis, as well as new technologies allowing in-depth analysis of immune cell regulations by vitamin D.
Cortico-cerebellar audio-motor regions coordinate self and other in musical joint action
Authors: Kohler Natalie , Novembre Giacomo , Gugnowska Katarzyna , Keller Peter E , Villringer Arno , Sammler Daniela 
Published: June 2022

AbstractJoint music performance requires flexible sensorimotor coordination between self and other. Cognitive and sensory parameters of joint action—such as shared knowledge or temporal (a)synchrony—influence this coordination by shifting the balance between self-other segregation and integration. To investigate the neural bases of these parameters and their interaction during joint action, we asked pianists to play on an MR-compatible piano, in duet with a partner outside of the scanner room. Motor knowledge of the partner’s musical part and the temporal compatibility of the partner’s action feedback were manipulated. First, we found stronger activity and functional connectivity within cortico-cerebellar audio-motor networks when pianists had practiced their partner’s part before. This indicates that they simulated and anticipated the auditory feedback of the partner by virtue of an internal model. Second, we observed stronger cerebellar activity and reduced behavioral adaptation when pianists encountered subtle asynchronies between these model-based anticipations and the perceived sensory outcome of (familiar) partner actions, indicating a shift towards self-other segregation. These combined findings demonstrate that cortico-cerebellar audio-motor networks link motor knowledge and other-produced sounds depending on cognitive and sensory factors of the joint performance, and play a crucial role in balancing self-other integration and segregation.
Visual recognition in rhesus monkeys requires area TE but not TEO
Authors: Eldridge Mark A G , Pearl Jonah E , Fomani Grace P , Masseau Evan C , Fredericks J Megan , Chen Gang , Richmond Barry J 
Published: June 2022

Abstract
The primate visual system is often described as a hierarchical feature-conjunction pathway, whereby each level represents an increasingly complex combination of image elements, culminating in the representation of whole coherent images in anterior inferior temporal cortex. Although many models of the ventral visual stream emphasize serial feedforward processing (Poggio et al. 2012; Yamins and DiCarlo 2016) anatomical studies show connections that bypass intermediate areas and that feedback to preceding areas (Distler et al. 1993; Kravitz et al. 2011). Prior studies on visual discrimination and object transforms also provide evidence against a strictly feed-forward serial transfer of information between adjacent areas (Kikuchi and Iwai 1980; Weiskrantz and Saunders 1984; Kar and DiCarlo 2021). Thus, we sought to investigate whether behaviorally relevant propagation of visual information is as strictly sequential as sometimes supposed. We compared the accuracy of visual recognition after selective removal of specific subregions of inferior temporal cortex—area TEO, area TE, or both areas combined. Removal of TEO alone had no detectable effect on recognition memory, whereas removal of TE alone produced a large and significant impairment. Combined removal of both areas created no additional deficit relative to removal of TE alone. Thus, area TE is critical for rapid visual object recognition, and detailed image-level visual information can reach area TE via a route other than through TEO.
A case report of Enterobacter cloacae endocarditis in a patient with a history of cotton fever
Authors: Tarabanis Constantine , Zhang Ruina , Grossman Kelsey , Kaul Christina , Lorin Jeffrey D 
Published: June 2022

Abstract

Background
Cotton fever is a self-limited, febrile syndrome occurring after the injection of trace amounts of drugs, in particular heroin, extracted from reused cotton filters. It is characterized by non-specific findings, such as fever, tachycardia, and leucocytosis. The leading pathophysiologic explanation suggests it is the result of direct inoculation of the bloodstream with endotoxins from Gram-negative bacilli of the genus Enterobacter, known to colonize all parts of the cotton plant. Only one prior case report has suggested cotton fever as a potential risk factor of infective endocarditis (IE).

Case summary
We describe a case of a 57-year-old patient with a history of intravenous heroin use complicated by self-reported episodes of cotton fever. His presentation was notable for Enterobacter cloacae IE with bilateral septic pulmonary emboli. Transthoracic echocardiography findings included new tricuspid regurgitation and two mobile echodensities on the right atrial implantable cardioverter defibrillator (ICD) lead. Despite broad antibiotic coverage and extraction of the ICD leads, the patient passed away from septic shock.

Discussion
The present case report is only the second published report of endocarditis in a patient with a history of cotton fever. In both cases, bacteria of the Enterobacter genus were isolated in patients’ blood cultures. This evidence supports the endotoxin theory as the leading pathophysiologic explanation for cotton fever and suggests cotton fever as a risk factor for Gram-negative IE. In the inpatient setting it informs proper antibiotic coverage, whereas in the outpatient setting it supports harm reduction interventions in the form of sterile cotton balls.
The role of peptidoglycan hydrolases in the formation and toxicity ofPseudomonas aeruginosamembrane vesicles
Authors: Chen Yi-Chi , Kalawong Ratchara , Toyofuku Masanori , Eberl Leo 
Published: June 2022

AbstractBacterial membrane vesicles (MVs) have been reported to kill other bacteria. In the case of Pseudomonas aeruginosa the bactericidal activity has been attributed to an unidentified 26 kDa peptidoglycan (PG) hydrolase that is associated with MVs and gives rise to a lytic band on zymograms using murein sacculi as substrate. In this study, we employed a proteomics approach to show that this PG hydrolase is the AmphD3 amidase. The analysis of an amphD3 mutant as well as of an AmphD3 overexpression derivative revealed that this enzyme is not required for the bactericidal activity of P. aeruginosa MVs but is involved in cell wall recycling and thus protects the cell against PG damage. Another 23 kDa PG hydrolase, which we observed on zymograms of SOS-induced MVs, was identified as the endolysin Lys, which triggers explosive cell lysis but is shown to be dispensable for MV-mediated killing. We conclude that the lytic activities observed on zymograms do not correlate with the bactericidal potential of MVs. We demonstrate that P. aeruginosa MVs are enriched for several autolysins, suggesting that the predatory activity of MVs depends on the combined action of different murein hydrolases.
Methods to monitor bacterial growth and replicative rates at the single-cell level
Authors: Marro Florian C , Laurent Frédéric , Josse Jérôme , Blocker Ariel J 
Published: June 2022

Abstract
The heterogeneity of bacterial growth and replicative rates within a population was proposed a century ago notably to explain the presence of bacterial persisters. The term “growth rate” at the single-cell level corresponds to the increase in size or mass of an individual bacterium while the “replicative rate” refers to its division capacity within a defined temporality. After a decades long hiatus, recent technical innovative approaches allow population growth and replicative rates heterogeneity monitoring at the single-cell level resuming in earnest. Among these techniques, the oldest and widely used is time-lapse microscopy, most recently combined with microfluidics. We also discuss recent fluorescence dilution methods informing only on replicative rates and best suited. Some new elegant single cell methods so far only sporadically used such as buoyant mass measurement and stable isotope probing have emerged. Overall, such tools are widely used to investigate and compare the growth and replicative rates of bacteria displaying drug-persistent behaviors to that of bacteria growing in specific ecological niches or collected from patients. In this review, we describe the current methods available, discussing both the type of queries these have been used to answer and the specific strengths and limitations of each method.