bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time decoding of 5 finger movements from 2 EMG channels for mixed reality human-computer interaction
Authors: McDermott Eric J. , Zwiener Thimm , Ziemann Ulf , Zrenner Christoph 
Published: October 2021

AbstractThe search for optimized forms of human-computer interaction (HCI) has intensified alongside the growing potential for the combination of biosignals with virtual reality (VR) and augmented reality (AR) to enable the next generation of personal computing. At the core, this requires decoding the user’s biosignals into digital commands. Electromyography (EMG) is a biosensor of particular interest due to the ease of data collection, the relatively high signal-to-noise-ratio, its non-invasiveness, and the ability to interpret the signal as being generated by (intentional) muscle activity. Here, we investigate the potential of using data taken from a simple 2-channel EMG setup to differentiate 5 distinct movements. In particular, EMG was recorded from two bipolar sensors over small hand muscles (extensor digitorum,flexor digitorum profundus) while a subject performed 50 trials of dorsal extension and return for each of the five digits. The maximum and the mean values across the trial were determined for each channel and used as features. A k-nearest neighbors (kNN) classification was performed and overall 5-class classification accuracy reached 94% when using the full trial’s time window, while simulated real-time classification reached 90.4% accuracy when using the constructed kNN model (k=3) with a 280ms sliding window. Additionally, unsupervised learning was performed and a homogeneity of 85% was achieved. This study demonstrates that reliable decoding of different natural movements is possible with fewer than one channel per class, even without taking into account temporal features of the signal. The technical feasibility of this approach in a real-time setting was validated by sending real-time EMG data to a custom Unity3D VR application through a Lab Streaming Layer to control a user interface. Further use-cases of gamification and rehabilitation were also examined alongside the integration of eye-tracking and gesture recognition for a sensor fusion approach to HCI and user intent.
Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging
Authors: Valle Andres Flores , Seelig Johannes D. 
Published: October 2021

ABSTRACTTwo-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion related intensity changes or motion artifacts cannot easily be separated from neural activity induced signals. While lateral motion within the focal plane can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected.Here, we develop an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using at least two simultaneously recorded focal planes, the algorithm separates motion related and neural activity induced changes in fluorescence intensity. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.
In Situ Surface-Directed Assembly of 2D Metal Nanoplatelets for Drug-Free Treatment of Antibiotic-Resistant Bacteria
Authors: Fathi Parinaz , Roslend Ayman , Alafeef Maha , Esch Mandy B. , Pan Dipanjan 
Published: October 2021

ABSTRACTThe development of antibiotic resistance among bacterial strains is a major global public health concern. To address this, drug-free antibacterial approaches are needed. High-touch surfaces in particular can serve as a means for the spread of bacteria and other pathogens from one infected person to another. Copper surfaces have long been known for their antibacterial properties. To further enhance the surface’s antibacterial properties, we used a one-step surface modification technique to assemble 2D copper chloride nanoplatelets directly onto copper surfaces such as copper tape, transmission electron microscopy (TEM) grids, electrodes, and granules. The nanoplatelets were formed using copper ions from the copper surfaces, enabling their direct assembly onto these surfaces in a one-step process that does not require separate nanoparticle synthesis. The synthesis of the nanoplatelets was confirmed with TEM, scanning electron microscopy, energy dispersive spectroscopy (EDS), x-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). Antibacterial properties of the surfaces with copper chloride nanoplatelets were demonstrated in multi-drug-resistant (MDR) E. coli. The presence of copper chloride nanoplatelets on the surface led to a marked improvement in antibacterial properties compared to the untreated copper surfaces. Surfaces with copper chloride nanoplatelets affected bacterial cell morphology, prevented bacterial cell division, reduced their viability, damaged bacterial deoxyribonucleic acid (DNA), and altered protein expression. In particular, proteins corresponding to cell division, DNA division, and mediation of copper toxicity were down-regulated. This work presents a robust method to directly assemble copper chloride nanoplatelets onto any copper surface to imbue it with improved antibacterial properties. To demonstrate that our method of particle generation can be used with other metal surfaces, we also demonstrate the synthesis of other metal-derived nanoarchitectures on a variety of metal surfaces.
Evolutionary Strategies Applied to Artificial Gene Regulatory Networks
Authors: Moreira André L. L. , Rennó-Costa César 
Published: October 2021

ABSTRACTEvolution optimizes cellular behavior throughout sequential generations by selecting the successful individual cells in a given context. As gene regulatory networks (GRNs) determine the behavior of single cells by ruling the activation of different processes - such as cell differentiation and death - how GRNs change from one generation to the other might have a relevant impact on the course of evolution. It is not clear, however, which mechanisms that affect GRNs effectively favor evolution and how. Here, we use a population of computational robotic models controlled by artificial gene regulatory networks (AGRNs) to evaluate the impact of different genetic modification strategies in the course of evolution. The virtual agent senses the ambient and acts on it as a bacteria in different phototaxis-like tasks - orientation to light, phototaxis, and phototaxis with obstacles. We studied how the strategies of gradual and abrupt changes on the AGRNs impact evolution considering multiple levels of task complexity. The results indicated that a gradual increase in the complexity of the performed tasks is beneficial for the evolution of the model. Furthermore, we have seen that larger gene regulatory networks are needed for more complex tasks, with single-gene duplication being an excellent evolutionary strategy for growing these networks, as opposed to full-genome duplication. Studying how GRNs evolved in a biological environment allows us to improve the computational models produced and provide insights into aspects and events that influenced the development of life on earth.
Joint Alignment and Tree Inference
Authors: Pečerska Jūlija , Gil Manuel , Anisimova Maria 
Published: October 2021

AbstractMultiple sequence alignment and phylogenetic tree inference are connected problems that are often solved as independent steps in the inference process. Several attempts at doing simultaneous inference have been made, however currently the available methods are greatly limited by their computational complexity and can only handle small datasets. In this manuscript we introduce a combinatorial optimisation approach that will allow us to resolve the circularity of the problem and efficiently infer both alignments and trees under maximum likelihood.
Direct quantification of ligand-induced lipid and protein microdomains with distinctive signaling properties
Authors: Wirth Daniel , Paul Michael D. , Pasquale Elena B. , Hristova Kalina 
Published: October 2021

AbstractLipid rafts are known as highly ordered lipid domains that are enriched in saturated lipids such as the ganglioside GM1. While lipid rafts are believed to exist in cells and to serve as signaling platforms through their enrichment in signaling components, they have never been directly observed in the plasma membrane without treatments that artificially cluster GM1 into large lattices. Here we report that microscopic GM1-enriched domains can form, without lipid cross-linking, in the plasma membrane of live mammalian cells expressing the EphA2 receptor tyrosine kinase in response to its ligand ephrinA1-Fc. The GM1-enriched microdomains form concomitantly with EphA2-enriched microdomains, but only partially co-localize with them. To gain insight into how plasma membrane heterogeneity controls signaling, we quantify the degree of EphA2 segregation and study initial EphA2 signaling steps in both EphA2-enriched and EphA2-depleted domains. By measuring dissociation constants, we demonstrate that EphA2 oligomerization is the same in EphA2-enriched and -depleted domains. However, EphA2 interacts preferentially with its downstream effector SRC in EphA2-depleted domains. The ability to induce microscopic GM1-enriched domains in live cells using a ligand for a transmembrane receptor will give us unprecedented opportunities to study the biology of lipid rafts.
Niosome encapsulated doxycycline-hyclate for potentiation of acne therapy: formulation and characterization
Authors: Kashani-Asadi-Jafari Fatemeh , Hadjizadeh Afra 
Published: October 2021

AbstractAcne is the pilosebaceous units’ disorder. The most important cause of acne is the colonization of bacteria in the follicles. Among antibiotics, doxycycline-hyclate kills a wide range of bacteria. To prevent oral administration’s side effects, overcome the barriers of conventional topical treatment, and improve the therapeutic effectiveness, doxycycline-hyclate was loaded into four niosomal formulations with different percentages of constituents (span 60 and cholesterol) prepared by the thin-film hydration method. Then, one of the four formulations with the most appropriate particle size of 362.88 ± 13.05 nm to target the follicles, percentage of drug entrapment efficiency of 56.3 ± 2.1%, in vitro drug release of 54.93 ± 1.99% after 32 hours, and the lowest permeation of the drug through the Wistar rat skin, was selected. Then, its toxicity on human dermal fibroblasts (HDF) by MTT method after 72 hours, its antibacterial activity against the main acne-causing bacteria via antibiogram test, and its effect on Wistar rat skin drug deposition were measured. Improved cell viability, increased antibacterial activity, and an approximately three-fold increase in drug deposition were the optimal niosomal formulation features relative to the free drug. Overall, this study demonstrated the ability of nano-niosomes containing doxycycline-hyclate to treat skin acne.
Sex Differences in Brain Tumor Glutamine Metabolism Reveal Sex-Specific Vulnerabilities to Treatment
Authors: Sponagel Jasmin , Jones Jill K. , Frankfater Cheryl , Zhang Shanshan , Tung Olivia , Cho Kevin , Tinkum Kelsey L. , Gass Hannah , Nunez Elena , Spitz Douglas R. , Chinnaiyan Prakash , Schaefer Jacob , Patti Gary J. , Graham Maya S. , Mauguen Audrey , Grkovski Milan , Dunphy Mark P. , Krebs Simone , Luo Jingqin , Rubin Joshua B. , Ippolito Joseph E. 
Published: October 2021

SummarySex differences in normal metabolism are well described, but whether they persist in cancerous tissue is unknown. We assessed metabolite abundance in glioblastoma surgical specimens and found that male glioblastomas are enriched for amino acids, including glutamine. Using PET imaging, we found that gliomas in male patients exhibit significantly higher glutamine uptake. These sex differences were well-modeled in murine transformed astrocytes, in which male cells imported and metabolized more glutamine and were more sensitive to glutaminase 1 (GLS1) inhibition. The sensitivity to GLS1 inhibition in males was driven by their dependence on glutamine-derived glutamate for α-ketoglutarate synthesis and TCA cycle replenishment. Females were resistant to GLS1 inhibition through greater pyruvate carboxylase-mediated TCA cycle replenishment. Thus, clinically important sex differences exist in targetable elements of metabolism. Recognition of sex-biased metabolism is an opportunity to improve treatments for all patients through further laboratory and clinical research.
All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons
Authors: Sarangi Vivekananda , Jang Yeongjun , Suvakov Milovan , Bae Taejeong , Fasching Liana , Sekar Shobana , Tomasini Livia , Mariani Jessica , Vaccarino Flora M. , Abyzov Alexej 
Published: October 2021

AbstractAccurate discovery of somatic mutations in a cell is a challenge that partially lays in immaturity of dedicated analytical approaches. Approaches comparing cell’s genome to a control bulk sample miss common mutations, while approaches to find such mutations from bulk suffer from low sensitivity. We developed a tool, All2, which enables accurate filtering of mutations in a cell from exhaustive comparison of cells’ genomes to each other without data for bulk(s). Based on all pair-wise comparisons, every variant call (point mutation, indel, and structural variant) is classified as either a germline variant, mosaic mutation, or false positive. As All2 allows for considering dropped-out regions, it is applicable to whole genome and exome analysis of cloned and amplified cells. By applying the approach to a variety of available data, we showed that its application reduces false positives, enables sensitive discovery of high frequency mutations, and is indispensable for conducting high resolution cell lineage tracing. All2 is freely available at https://github.com/abyzovlab/All2.
SPF: A Spatial and Functional Data Analytic Approach to cell Imaging data
Authors: Vu Thao , Wrobel Julia , Bitler Benjamin G. , Schenk Erin L. , Jordan Kimberly R. , Ghosh Debashis 
Published: October 2021

AbstractThe tumor microenvironment (TME), which characterizes the tumor and its surroundings, plays a critical role in understanding cancer development and progression. Recent advances in imaging techniques enable researchers to study spatial structure of the TME at a single-cell level. Investigating spatial patterns and interactions of cell subtypes within the TME provides useful insights into how cells with different biological purposes behave, which may consequentially impact a subject’s clinical outcomes. We utilize a class of well-known spatial summary statistics, the K-function and its variants, to explore inter-cell dependence as a function of distances between cells. Using techniques from functional data analysis, we introduce an approach to model the association between these summary spatial functions and subject-level outcomes, while controlling for other clinical scalar predictors such as age and disease stage. In particular, we leverage the additive functional Cox regression model (AFCM) to study the nonlinear impact of spatial interaction between tumor and stromal cells on overall survival in patients with non-small cell lung cancer, using multiplex immunohistochemistry (mIHC) data. The applicability of our approach is further validated using a publicly available Multiplexed Ion beam Imaging (MIBI) triple-negative breast cancer dataset.
easyfm: An easy software suite for file manipulation of Next Generation Sequencing data on desktops
Authors: Jung Hyungtaek , Jeon Brendan , Ortiz-Barrientos Daniel 
Published: October 2021

AbstractStoring and manipulating Next Generation Sequencing (NGS) file formats is an essential but difficult task in biological data analysis. The easyfm (easy file manipulation) toolkit (https://github.com/TaekAndBrendan/easyfm) makes manipulating commonly used NGS files more accessible to biologists. It enables them to perform end-to-end reproducible data analyses using a free standalone desktop application (available on Windows, Mac and Linux). Unlike existing tools (e.g. Galaxy), the Graphical User Interface (GUI)-based easyfm is not dependent on any high-performance computing (HPC) system and can be operated without an internet connection. This specific benefit allow easyfm to seamlessly integrate visual and interactive representations of NGS files, supporting a wider scope of bioinformatics applications in the life sciences.Author summaryThe analysis and manipulation of NGS data for understanding biological phenomena is an increasingly important aspect in the life sciences. Yet, most methods for analysing, storing and manipulating NGS data require complex command-line tools in HPC or web-based servers and have not yet been implemented in comprehensive, easy-to-use software. This is a major hurdle preventing more general application in the field of NGS data analysis and file manipulation. Here we present easyfm, a free standalone Graphical User Interface (GUI) software with Python support that can be used to facilitate the rapid discovery of target sequences (or user’s interest) in NGS datasets for novice users. For user-friendliness and convenience, easyfm was developed with four work modules and a secondary GUI window (herein secondary window), covering different aspects of NGS data analysis (mainly focusing on FASTA files), including post-processing, filtering, format conversion, generating results, real-time log, and help. In combination with the executable tools (BLAST+ and BLAT) and Python, easyfm allows the user to set analysis parameters, select/extract regions of interest, examine the input and output results, and convert to a wide range of file formats. To help augment the functionality of existing web-based and command-line tools, easyfm, a self-contained program, comes with extensive documentation (hosted at https://github.com/TaekAndBrendan/easyfm) including a comprehensive step-by-step guide.
The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution
Authors: Böndel Katharina B. , Samuels Toby , Craig Rory J. , Ness Rob W. , Colegrave Nick , Keightley Peter D. 
Published: October 2021

SummaryThe distribution of fitness effects (DFE) for new mutations is fundamental for many aspects of population and quantitative genetics. In this study, we have inferred the DFE in the single-celled alga Chlamydomonas reinhardtii by estimating changes in the frequencies of 254 spontaneous mutations under experimental evolution and equating the frequency changes of linked mutations with their selection coefficients. We generated seven populations of recombinant haplotypes by crossing seven independently derived mutation accumulation lines carrying an average of 36 mutations in the homozygous state to a mutation-free strain of the same genotype. We then allowed the populations to evolve under natural selection in the laboratory by serial transfer in liquid culture. We observed substantial and repeatable changes in the frequencies of many groups of linked mutations, and, surprisingly, as many mutations were observed to increase as decrease in frequency. We developed a Bayesian Monte Carlo Markov Chain method to infer the DFE. This computes the likelihood of the observed distribution of changes of frequency, and obtains the posterior distribution of the selective effects of individual mutations, while assuming a two-sided gamma distribution of effects. We infer that the DFE is a highly leptokurtic distribution, and that approximately equal proportions of mutations have positive and negative effects on fitness. This result is consistent with what we have observed in previous work on a different C. reinhardtii strain, and suggests that a high fraction of new spontaneously arisen mutations are advantageous in a simple laboratory environment.
Host diversity and behavior determine patterns of interspecies transmission and geographic diffusion of avian Influenza A subtypes among North American wild reservoir species
Authors: Hicks Joseph T. , Friedman Kimberly , Qiu Xueting , Kim Do-Kyun , Hixson James E. , Krauss Scott , Webby Richard J. , Webster Robert G. , Bahl Justin 
Published: October 2021

ABSTRACTWild birds can carry avian influenza viruses (AIV), including those with pandemic or panzootic potential, long distances. Even though AIV has a broad host range, few studies account for host diversity when estimating AIV spread. We analyzed AIV genomic sequences from North American wild birds, including 303 newly sequenced isolates, to estimate interspecies transmission and geographic diffusion patterns among multiple co-circulating subtypes. Our results show high transition rates within Anseriformes and Charadriiformes, but limited transitions between these orders. Patterns of interspecies transmission were positively associated with breeding habitat range overlap, and negatively associated with host genetic distance. Distance between regions (negative correlation) and summer temperature at origin (positive correlation) were strong predictors of diffusion. Taken together, this study demonstrates that host diversity and ecology can determine evolutionary processes that underlie AIV natural history and spread. Understanding these processes can provide important insights for effective control of AIV.
Managed culls mean extinction for a marine mammal population when combined with extreme climate impacts
Authors: Davis Katrina J 
Published: October 2021

AbstractHuman actions led to the worldwide decline of marine mammal populations in the 18th–19th centuries. However, the global uptake in protective legislation during the 20th century has recently allowed many marine mammal populations to recover. This positive trend is particularly true of pinnipeds (e.g., seals and sea lions), whose recovering populations are increasingly in conflict with fisheries. Many fisheries organisations call for managed culls of sea lion populations to reduce competition for target fish species as well as damage to catch and fishing gear through operational interactions. However, despite widespread perceptions that sea lion populations are generally increasing, to-date culls have been considered or implemented without quantitative evidence of their impacts on seal lion population viability. This knowledge gap is particularly concerning given the expected increase in extreme climate conditions, such as extreme El Niño events, which together with culls could push sea lion populations in some parts of the world into the extinction vortex. In this analysis, I develop and parameterise stochastic matrix population models of the South American sea lion (Otaria flavescens) to project the impact of (1) three cull scenarios with different intensity and temporal frequency targeting adult females, (2) extreme El Niño events whose frequency is modelled using a Markovian transition matrix, (3) and the interaction of culls and extreme climate events on population dynamics. I focus on the Chilean population of O. flavescens, where recent increases in sea lion numbers have triggered widespread conflict with small-scale fisheries, and where sea lion populations will increasingly be affected by extreme El Niño conditions. I find that sea lion populations decline below minimum viable population sizes under all scenarios involving culls and extreme climate events. By explicitly considering parameter uncertainty, this approach is a call to action for future research to focus on collecting stage-specific, annual population data to reduce uncertainty regarding marine mammal vital rates.