bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrating genomics and metabolomics for scalable non-ribosomal peptide discovery
Authors: Behsaz Bahar , Bode Edna , Gurevich Alexey , Shi Yan-Ni , Grundmann Florian , Acharya Deepa , Caraballo-Rodríguez Andrés Mauricio , Bouslimani Amina , Panitchpakdi Morgan , Linck Annabell , Guan Changhui , Oh Julia , Dorrestein Pieter C. , Bode Helge B. , Pevzner Pavel A. , Mohimani Hosein 
Published: May 2021

AbstractNon-Ribosomal Peptides (NRPs) represent a biomedically important class of natural products that include a multitude of antibiotics and other clinically used drugs. NRPs are not directly encoded in the genome but are instead produced by metabolic pathways encoded bybiosynthetic gene clusters(BGCs). Since the existing genome mining tools predict many putative NRPs synthesized by a given BGC, it remains unclear which of these putative NRPs are correct and how to identify post-assembly modifications of amino acids in these NRPs in a blind mode, without knowing which modifications exist in the sample. To address this challenge, here we report NRPminer, a modification-tolerant tool for NRP discovery from large (meta)genomic and mass spectrometry datasets. We show that NRPminer is able to identify many NRPs from different environments, including four previously unreported NRP families from soil-associated microbes and NRPs from human microbiota. Furthermore, in this work we demonstrate the anti-parasitic activities and the structure of two of these NRP families using direct bioactivity screening and nuclear magnetic resonance spectrometry, illustrating the power of NRPminer for discovering bioactive NRPs.
Structure of the mature Rous sarcoma virus lattice reveals a role for IP6 in the formation of the capsid hexamer
Authors: Obr Martin , Ricana Clifton L. , Nikulin Nadia , Feathers Jon-Philip R. , Klanschnig Marco , Thader Andreas , Johnson Marc C. , Vogt Volker M. , Schur Florian K. M. , Dick Robert A. 
Published: May 2021

AbstractInositol hexakisphosphate (IP6) is an assembly cofactor for HIV-1. We report here that IP6 is also used for assembly of Rous sarcoma virus (RSV), a retrovirus from a different genus. IP6 is ~100-fold more potent at promoting RSV mature capsid protein (CA) assembly than observed for HIV-1 and removal of IP6 in cells reduces infectivity by 100-fold. Here, visualized by cryo-electron tomography and subtomogram averaging, mature capsid-like particles show an IP6-like density in the CA hexamer, coordinated by rings of six lysines and six arginines. Phosphate and IP6 have opposing effects on CA in vitro assembly, inducing formation of T = 1 icosahedrons and tubes, respectively, implying that phosphate promotes pentamer and IP6 hexamer formation. Subtomogram averaging and classification optimized for analysis of pleomorphic retrovirus particles reveal that the heterogeneity of mature RSV CA polyhedrons results from an unexpected, intrinsic CA hexamer flexibility. In contrast, the CA pentamer forms rigid units organizing the local architecture. These different features of hexamers and pentamers determine the structural mechanism to form CA polyhedrons of variable shape in mature RSV particles.
Generative modeling of single-cell time series with PRESCIENT enables prediction of cell trajectories with interventions
Authors: Yeo Grace Hui Ting , Saksena Sachit D. , Gifford David K. 
Published: May 2021

AbstractExisting computational methods that use single-cell RNA-sequencing (scRNA-seq) for cell fate prediction do not model how cells evolve stochastically and in physical time, nor can they predict how differentiation trajectories are altered by proposed interventions. We introduce PRESCIENT (Potential eneRgy undErlying Single Cell gradIENTs), a generative modeling framework that learns an underlying differentiation landscape from time-series scRNA-seq data. We validate PRESCIENT on an experimental lineage tracing dataset, where we show that PRESCIENT is able to predict the fate biases of progenitor cells in hematopoiesis when accounting for cell proliferation, improving upon the best-performing existing method. We demonstrate how PRESCIENT can simulate trajectories for perturbed cells, recovering the expected effects of known modulators of cell fate in hematopoiesis and pancreatic β cell differentiation. PRESCIENT is able to accommodate complex perturbations of multiple genes, at different time points and from different starting cell populations, and is available at https://github.com/gifford-lab/prescient.
Dimerization and oligomerization of DNA-assembled building blocks for controlled multi-motion in high-order architectures
Authors: Xin Ling , Duan Xiaoyang , Liu Na 
Published: May 2021

AbstractIn living organisms, proteins are organized prevalently through a self-association mechanism to form dimers and oligomers, which often confer new functions at the intermolecular interfaces. Despite the progress on DNA-assembled artificial systems, endeavors have been largely paid to achieve monomeric nanostructures that mimic motor proteins for a single type of motion. Here, we demonstrate a DNA-assembled building block with rotary and walking modules, which can introduce new motion through dimerization and oligomerization. The building block is a chiral system, comprising two interacting gold nanorods to perform rotation and walking, respectively. Through dimerization, two building blocks can form a dimer to yield coordinated sliding. Further oligomerization leads to higher-order structures, containing alternating rotation and sliding dimer interfaces to impose structural twisting. Our hierarchical assembly scheme offers a design blueprint to construct DNA-assembled advanced architectures with high degrees of freedom to tailor the optical responses and regulate multi-motion on the nanoscale.
Genome-resolved metagenomics reveals role of iron metabolism in drought-induced rhizosphere microbiome dynamics
Authors: Xu Ling , Dong Zhaobin , Chiniquy Dawn , Pierroz Grady , Deng Siwen , Gao Cheng , Diamond Spencer , Simmons Tuesday , Wipf Heidi M.-L. , Caddell Daniel , Varoquaux Nelle , Madera Mary A. , Hutmacher Robert , Deutschbauer Adam , Dahlberg Jeffery A. , Guerinot Mary Lou , Purdom Elizabeth , Banfield Jillian F. , Taylor John W. , Lemaux Peggy G. , Coleman-Derr Devin 
Published: May 2021

AbstractRecent studies have demonstrated that drought leads to dramatic, highly conserved shifts in the root microbiome. At present, the molecular mechanisms underlying these responses remain largely uncharacterized. Here we employ genome-resolved metagenomics and comparative genomics to demonstrate that carbohydrate and secondary metabolite transport functionalities are overrepresented within drought-enriched taxa. These data also reveal that bacterial iron transport and metabolism functionality is highly correlated with drought enrichment. Using time-series root RNA-Seq data, we demonstrate that iron homeostasis within the root is impacted by drought stress, and that loss of a plant phytosiderophore iron transporter impacts microbial community composition, leading to significant increases in the drought-enriched lineage, Actinobacteria. Finally, we show that exogenous application of iron disrupts the drought-induced enrichment of Actinobacteria, as well as their improvement in host phenotype during drought stress. Collectively, our findings implicate iron metabolism in the root microbiome’s response to drought and may inform efforts to improve plant drought tolerance to increase food security.
Mitochondrial targeted meganuclease as a platform to eliminate mutant mtDNA in vivo
Authors: Zekonyte Ugne , Bacman Sandra R. , Smith Jeff , Shoop Wendy , Pereira Claudia V. , Tomberlin Ginger , Stewart James , Jantz Derek , Moraes Carlos T. 
Published: May 2021

AbstractDiseases caused by heteroplasmic mitochondrial DNA mutations have no effective treatment or cure. In recent years, DNA editing enzymes were tested as tools to eliminate mutant mtDNA in heteroplasmic cells and tissues. Mitochondrial-targeted restriction endonucleases, ZFNs, and TALENs have been successful in shifting mtDNA heteroplasmy, but they all have drawbacks as gene therapy reagents, including: large size, heterodimeric nature, inability to distinguish single base changes, or low flexibility and effectiveness. Here we report the adaptation of a gene editing platform based on the I-CreI meganuclease known as ARCUS®. These mitochondrial-targeted meganucleases (mitoARCUS) have a relatively small size, are monomeric, and can recognize sequences differing by as little as one base pair. We show the development of a mitoARCUS specific for the mouse m.5024C>T mutation in the mt-tRNAAla gene and its delivery to mice intravenously using AAV9 as a vector. Liver and skeletal muscle show robust elimination of mutant mtDNA with concomitant restoration of mt-tRNAAla levels. We conclude that mitoARCUS is a potential powerful tool for the elimination of mutant mtDNA.
Revealing the etching process of water-soluble Au25 nanoclusters at the molecular level
Authors: Cao Yitao , Liu Tongyu , Chen Tiankai , Zhang Bihan , Jiang De-en , Xie Jianping 
Published: May 2021

AbstractEtching (often considered as decomposition) is one of the key considerations in the synthesis, storage, and application of metal nanoparticles. However, the underlying chemistry of their etching process still remains elusive. Here, we use real-time electrospray ionization mass spectrometry to study the reaction dynamics and size/structure evolution of all the stable intermediates during the etching of water-soluble thiolate-protected gold nanoclusters (Au NCs), which reveal an unusual “recombination” process in the oxidative reaction environment after the initial decomposition process. Interestingly, the sizes of NC species grow larger and their ligand-to-metal ratios become higher during this recombination process, which are distinctly different from that observed in the reductive growth of Au NCs (e.g., lower ligand-to-metal ratios with increasing sizes). The etching chemistry revealed in this study provides molecular-level understandings on how metal nanoparticles transform under the oxidative reaction environment, providing efficient synthetic strategies for new NC species through the etching reactions.
The IDEAL household energy dataset, electricity, gas, contextual sensor data and survey data for 255 UK homes
Authors: Pullinger Martin , Kilgour Jonathan , Goddard Nigel , Berliner Niklas , Webb Lynda , Dzikovska Myroslava , Lovell Heather , Mann Janek , Sutton Charles , Webb Janette , Zhong Mingjun 
Published: May 2021

AbstractThe IDEAL household energy dataset described here comprises electricity, gas and contextual data from 255 UK homes over a 23-month period ending in June 2018, with a mean participation duration of 286 days. Sensors gathered 1-second electricity data, pulse-level gas data, 12-second temperature, humidity and light data for each room, and 12-second temperature data from boiler pipes for central heating and hot water. 39 homes also included plug-level monitoring of selected electrical appliances, real-power measurement of mains electricity and key sub-circuits, and more detailed temperature monitoring of gas- and heat-using equipment, including radiators and taps. Survey data included occupant demographics, values, attitudes and self-reported energy awareness, household income, energy tariffs, and building, room and appliance characteristics. Linked secondary data comprises weather and level of urbanisation. The data is provided in comma-separated format with a custom-built API to facilitate usage, and has been cleaned and documented. The data has a wide range of applications, including investigating energy demand patterns and drivers, modelling building performance, and undertaking Non-Intrusive Load Monitoring research.
KASPar SNP genetic map of cassava for QTL discovery of productivity traits in moderate drought stress environment in Africa
Authors: Ewa Favour , Asiwe Joseph N. A. , Okogbenin Emmanuel , Ogbonna Alex C. , Egesi Chiedozie 
Published: May 2021

AbstractCassava is an important staple in Sub-Sahara Africa. While its production has rapidly expanded to the dry savannahs of the continent, productivity is low in this ecology due to drought by farmers, extending the growth cycle from 12 months to 18, and sometimes 24 months to ensure better harvests. Yield is a complex trait and often difficult to manipulate for genetic gain in conventional breeding. Unfortunately, the dearth of molecular tools for decades has hampered molecular breeding (MB) to improve cassava productivity. This study was conducted to explore KASpar SNPs to generate more molecular tools to enhance genetic dissection of elite African germplasm for improved cassava productivity in dry environments of Africa where molecular resources are highly limited for crop improvement. To aid molecular genetic analysis of traits, a linkage map covering 1582.8 cM with an average resolution of 3.69 cM was constructed using 505 polymorphic SNP markers distributed over 21 linkage groups. Composite interval mapping using 267 F1 progeny in initial QTL mapping identified 27 QTLs for productivity traits in the dry savannah of Nigeria. The availability of KASPar SNPs are anticipated to improve the implementation of MB for the development of high performing drought-tolerant cassava varieties in Africa.
Hypertonic stress modulates eNOS function through O-GlcNAc modification at Thr-866
Authors: Li Chang , He An , Guo Yongzheng , Yang Xiyang , Luo Minghao , Cheng Zhe , Huang Longxiang , Xia Yong , Luo Suxin 
Published: May 2021

AbstractO-GlcNAcylation, an energy-sensitive posttranslational modification, can regulate the activity of endothelial nitric oxide synthase (eNOS). Previous studies found that Thr866 is the key site for low-glucose-mediated regulation of eNOS O-GlcNAc. However, it is not known whether this activity functions through the Thr866 site concomitant with other physical and chemical factors. Therefore, we first explored the effects of physical and chemical factors on eNOS O-GlcNAc and its Thr866 site. In this study, hypertonic stress, hyperthermia and hydrogen peroxide all increased the expression levels of eNOS O-GlcNAc, whereas hypoxia and high levels of alcohol had no effect. on the expression levels of eNOS O-GlcNAc; by contrast, low pH led to a decrease in eNOS O-GlcNAc levels. Notably, eNOS O-GlcNAc protein levels were unchanged after Thr866 site mutation only under hypertonic conditions, suggesting that hypertonic stress may act through the Thr866 site. Upon exploring the mechanism of hypertonic stress on eNOS O-GlcNAc activity and function, we found that hypertonic stress can upregulate the expression of O-linked N-acetylglucosamine (GlcNAc) transferase (OGT), which is dependent on AMPK. When AMPK was knocked out, the upregulation of OGT expression and increased O-GlcNAc modifications induced by hypertonic stress were reversed.
Rotating flow assessment of magnetized mixture fluid suspended with hybrid nanoparticles and chemical reactions of species
Authors: Khan Noor Saeed , Shah Qayyum , Sohail Arif , Ullah Zafar , Kaewkhao Attapol , Kumam Poom , Zubair Seema , Ullah Naeem , Thounthong Phatiphat 
Published: May 2021

AbstractThe current study characterizes the effects of Hall current, Arrhenius activation energy and binary chemical reaction on the rotating flow of hybrid nanofluid in two double disks. By the use of suitable similarity transformations, the system of partial differential equations and boundary conditions for hybrid nanofluid are transformed to ordinary differential equations which are solved through optimal homotopy analysis method. The intensified magnetic field and hybrid nanofluid performances are represented in three dimensional model with flow, heat and mass transfer. Radial velocity decreases and tangential velocity increases with the Hall parameter. Temperature rises with high values of rotation parameter while it decreases with the Prandtl number. Nanoparticles concentration enhances with the increments in Arrhenius activation energy parameter and stretching parameter due to lower disk. There exists a close and favorable harmony in the results of present and published work.
Intuitive real-time control strategy for high-density myoelectric hand prosthesis using deep and transfer learning
Authors: Tam Simon , Boukadoum Mounir , Campeau-Lecours Alexandre , Gosselin Benoit 
Published: May 2021

AbstractMyoelectric hand prostheses offer a way for upper-limb amputees to recover gesture and prehensile abilities to ease rehabilitation and daily life activities. However, studies with prosthesis users found that a lack of intuitiveness and ease-of-use in the human-machine control interface are among the main driving factors in the low user acceptance of these devices. This paper proposes a highly intuitive, responsive and reliable real-time myoelectric hand prosthesis control strategy with an emphasis on the demonstration and report of real-time evaluation metrics. The presented solution leverages surface high-density electromyography (HD-EMG) and a convolutional neural network (CNN) to adapt itself to each unique user and his/her specific voluntary muscle contraction patterns. Furthermore, a transfer learning approach is presented to drastically reduce the training time and allow for easy installation and calibration processes. The CNN-based gesture recognition system was evaluated in real-time with a group of 12 able-bodied users. A real-time test for 6 classes/grip modes resulted in mean and median positive predictive values (PPV) of 93.43% and 100%, respectively. Each gesture state is instantly accessible from any other state, with no mode switching required for increased responsiveness and natural seamless control. The system is able to output a correct prediction within less than 116 ms latency. 100% PPV has been attained in many trials and is realistically achievable consistently with user practice and/or employing a thresholded majority vote inference. Using transfer learning, these results are achievable after a sensor installation, data recording and network training/fine-tuning routine taking less than 10 min to complete, a reduction of 89.4% in the setup time of the traditional, non-transfer learning approach.
Sofosbuvir plus Ribavirin is effective for HCV elimination in people living with HIV from rural area of China
Authors: Chen Liyu , Du Lingyao , Kang Shuang , Ma Fanghua , Li Changmin , He Min , Bai Lang , Tang Hong 
Published: May 2021

AbstractPeople living with HIV (PLWH) bear higher prevalence of HCV coinfection. An accessible directly acting antivirals regimen with less drug–drug interaction with antiretroviral therapy (ART) is urgently needed in source limited regions. We aimed to assess the efficacy and safety of SOF + RBV for 24 weeks regimen in HIV–HCV coinfected patients in Liangshan Prefecture, China. PLWH under ART from China’s national free antiretroviral treatment project (CNFATP) and diagnosed with treatment-naïve HCV infection were enrolled. SOF + RBV was administrated for 24 weeks and patients were followed for ≥ 12 weeks. The efficacy and safety were analyzed and related factors were explored. 58 patients completed 24 weeks of SOF + RBV and had all tests done. Genotype prevalence in this population was G3 44.8% (n = 26), G6 31.0% (n = 18) and G1 17.2% (n = 10) respectively. 52/58 (89.7%) patients achieved SVR12 while 10.3% experienced therapeutic failure. However, SVR12 was neither significantly different between groups of different gender, age, transmission routines, CD4+ cell count, HIV infection duration, ART duration and HBsAg prevalence nor influenced by HCV viral load, genotypes and hepatic stiffness. The regimen was well-tolerated without any serious AEs or AEs leading to treatment adjustment or discontinuation reported. PLWH in Liangshan showed a high prevalence of HCV coinfection with GT3 and GT6 as the most frequent genotypes. SOF + RBV for 24 weeks could achieve good SVR12 in this population and was well-tolerated. It has great potential to be generalized in coinfected population in source-limited regions.
Deep learning of material transport in complex neurite networks
Authors: Li Angran , Barati Farimani Amir , Zhang Yongjie Jessica 
Published: May 2021

AbstractNeurons exhibit complex geometry in their branched networks of neurites which is essential to the function of individual neuron but also brings challenges to transport a wide variety of essential materials throughout their neurite networks for their survival and function. While numerical methods like isogeometric analysis (IGA) have been used for modeling the material transport process via solving partial differential equations (PDEs), they require long computation time and huge computation resources to ensure accurate geometry representation and solution, thus limit their biomedical application. Here we present a graph neural network (GNN)-based deep learning model to learn the IGA-based material transport simulation and provide fast material concentration prediction within neurite networks of any topology. Given input boundary conditions and geometry configurations, the well-trained model can predict the dynamical concentration change during the transport process with an average error less than 10% and $$120 \sim 330$$

120
∼
330

times faster compared to IGA simulations. The effectiveness of the proposed model is demonstrated within several complex neurite networks.
Hydrogel with silver nanoparticles synthesized by Mimosa tenuiflora for second-degree burns treatment
Authors: Martínez-Higuera Aaron , Rodríguez-Beas César , Villalobos-Noriega Jesús Mauro Adolfo , Arizmendi-Grijalva Abraham , Ochoa-Sánchez Carlos , Larios-Rodríguez Eduardo , Martínez-Soto Juan Manuel , Rodríguez-León Ericka , Ibarra-Zazueta Cristina , Mora-Monroy Roberto , Borbón-Nuñez Hugo Alejandro , García-Galaz Alfonso , Candia-Plata María del Carmen , López-Soto Luis Fernando , Iñiguez-Palomares Ramón 
Published: May 2021

AbstractIn this work we use Mimosa tenuiflora (MtE) extracts as reducing agents to synthesize silver nanoparticles (AgMt NPs) which were characterized by DPPH and Total Polyphenols Assays, UV–visible, X-ray diffractometer (XRD), high-resolution transmission electron microscopy (HRTEM), X-ray photoelectron spectroscopy (XPS) and Thermogravimetric analysis (TGA). AgMt NPs possess average sizes of 21 nm and fcc crystalline structure, it was also confirmed that the MtE is present in the AgMt NPs even after the cleaning protocol applied. Subsequently, carbopol hydrogels were made and the MtE and the synthesized AgMt NPs were dispersed in different gels (MtE-G and AgMt NPs-G, respectively) at 100 µg/g concentration. The gels were characterized by UV–Vis, IR, and rheology. Antimicrobial tests were performed using Staphylococcus aureus and Escherichia coli. Burn wound healing was evaluated in a second-degree burn injury on a Wistar rats model for 14 days and additional skin biopsies were examined with histopathological analysis. Gel with commercial silver nanoparticles (Ag NPs) was prepared and employed as a control on the biological assays. Hydrogel system containing silver nanoparticles synthesized with Mimosa tenuiflora (AgMt NPs-G) is a promising therapeutic strategy for burn wound healing, this due to bactericidal and anti-inflammatory effects, which promotes a more effective recovery (in percentage terms) by damaged area.