bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mutation Rate Variations in the Human Genome are Encoded in DNA Shape
Authors: Liu Zian , Samee Md. Abul Hassan 
Published: January 2021

AbstractSingle nucleotide mutation rates have critical implications for human evolution and genetic diseases. Accurate modeling of these mutation rates has long remained an open problem since the rates vary substantially across the human genome. A recent model, however, explained much of the variation by considering higher order nucleotide interactions in the local (7-mer) sequence context around mutated nucleotides. Despite this model’s predictive value, we still lack a biophysically-grounded understanding of genome-wide mutation rate variations. DNA shape features are geometric measurements of DNA structural properties, such as helical twist and tilt, and are known to capture information on interactions between neighboring nucleotides within a local context. Motivated by this characteristic of DNA shape features, we used them to model mutation rates in the human genome. The DNA shape feature based models show up to 15% higher accuracy than the current nucleotide sequence-based models and pinpoint DNA structural properties predictive of mutation rates in the human genome. Further analyzing the mutation rates of individual positions of transcription factor (TF) binding sites in the human genome, we found a strong association between DNA shape and the position-specific mutation rates. The trend holds for hundreds of TFs and is even stronger in evolutionarily conserved regions. To our knowledge, this is the first attempt that demonstrates the structural underpinnings of nucleotide mutations in the human genome and lays the groundwork for future studies to incorporate DNA shape information in modeling genetic variations.
Spatial metabolomics using imaging mass spectrometry to identify the localization of asparaptine inAsparagus officinalis
Authors: Nakabayashi Ryo , Hashimoto Kei , Mori Tetsuya , Toyooka Kiminori , Sudo Hiroshi , Saito Kazuki 
Published: January 2021

AbstractSpatial metabolomics uses imaging mass spectrometry (IMS) to localize metabolites within tissue section. Here, we performed matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance-IMS (MALDI-FTICR-IMS) to identify the localization of asparaptine, a naturally occurring inhibitor of angiotensin-converting enzyme, in green spears of asparagus (Asparagus officinalis). Spatial metabolome data were acquired with an untargeted manner. Segmentation analysis using the data characterized tissue-type-dependent and - independent distribution patterns in cross-sections of asparagus spears. Moreover, asparaptine accumulated at high levels in developing lateral shoot tissues. Quantification of asparaptine in lateral shoots using liquid chromatography-tandem mass spectrometry (LC-MS/MS) validated the IMS analysis. These results provide valuable information for understanding the function of asparaptine in asparagus, and identify the lateral shoot as a potential region of interest for multiomic studies to examine gene-to-metabolite associations in asparaptine biosynthesis.
The dynamic trophic architecture of open-ocean protist communities revealed through machine-guided metatranscriptomics
Authors: Lambert B.S. , Groussman R.D. , Schatz M.J. , Coesel S.N. , Durham B.P. , Alverson A.J. , White A.E. , Armbrust E.V. 
Published: January 2021

AbstractIntricate networks of single-celled eukaryotes (protists) dominate carbon flow in the ocean. Their growth, demise, and interactions with other microorganisms drive the fluxes of biogeochemical elements through marine ecosystems. Mixotrophic protists are capable of both photosynthesis and ingestion of prey and are dominant components of open-ocean planktonic communities. Yet, the role of mixotrophs in elemental cycling is obscured by their capacity to act as primary producers or heterotrophic consumers depending on factors that remain largely uncharacterized. Here we introduce a machine learning model that can predict thein situnutritional mode of aquatic protists based on their patterns of gene expression. This approach leverages a public collection of protist transcriptomes as a training set to identify a subset of gene families whose transcriptional profiles predict trophic status. We applied our model to nearly 100 metatranscriptomes obtained during two oceanographic cruises in the North Pacific and found community-level and population-specific evidence that abundant open-ocean mixotrophic populations shift their predominant mode of nutrient and carbon acquisition in response to natural gradients in nutrient supply and sea surface temperature. In addition, metatranscriptomic data from ship-board incubation experiments revealed that abundant mixotrophic prymnesiophytes from the oligotrophic North Pacific subtropical gyre rapidly remodelled their transcriptome to enhance photosynthesis when supplied with limiting nutrients. Coupling the technique introduced here with experiments designed to reveal the mechanisms driving mixotroph physiology is a promising approach for understanding the ecology of mixotrophic populations in the natural environment.Significance statementMixotrophy is a ubiquitous nutritional strategy in marine ecosystems. Although our understanding of the distribution and abundance of mixotrophic plankton has improved significantly, the functional roles of mixotrophs are difficult to pinpoint, as mixotroph nutritional strategies are flexible and form a continuum between heterotrophy and phototrophy. We employ a machine learning-driven metatranscriptomic technique to assess the nutritional strategies of abundant planktonic populationsin situand demonstrate that mixotrophic populations play varying functional roles along physico-chemical gradients in the North Pacific Ocean, revealing a degree of physiological plasticity unique to aquatic mixotrophs. Our results highlight mechanisms that may dictate the flow of biogeochemical elements and the ecology of the North Pacific Ocean, one of the largest biogeographical provinces on Earth.
DNA-based copy number analysis confirms genomic evolution of PDX models
Authors: Hoge Anna C. H. , Getz Michal , Beroukhim Rameen , Golub Todd R. , Ha Gavin , Ben-David Uri 
Published: January 2021

AbstractWe previously reported the genomic evolution of the copy number (CN) landscapes of patient-derived xenografts (PDXs) during their engraftment and passaging1. Woo et al. argue that the CN profiles of PDXs are highly conserved, and that the main conclusions of our paper are invalid due to our use of expression-based CN profiles2. Here, we reassess genomic evolution of PDXs using the DNA-based CN profiles reported by Woo et al. We find that the degree of genomic evolution in the DNA-based dataset of Woo et al. is similar to that which we had previously reported. While the overall Pearson’s correlation of CN profiles between primary tumors (PTs) and their derived PDXs is high (as reported in our original paper as well), a median of ~10% of the genome is differentially altered between PTs and PDXs across cohorts (range, 0% to 73% across all models). In 24% of the matched PT-PDX samples, over a quarter of the genome is differentially affected by CN alterations. Moreover, in matched analyses of PTs and their derived PDXs at multiple passages, later-passage PDXs are significantly less similar to their parental PTs than earlier-passage PDXs, indicative of genomic divergence. We conclude that genomic evolution of PDX models during model generation and propagation should not be dismissed, and that the phenotypic consequences of this evolution ought to be assessed in order to optimize the application of these valuable cancer models.
Fractal triads efficiently sample ecological diversity and processes across spatial scales
Authors: Simpson Elizabeth G. , Pearse William D. 
Published: January 2021

AbstractThe relative influence of ecological assembly processes, such as environmental filtering, competition, and dispersal, vary across spatial scales. Changes in phylogenetic and taxonomic diversity across environments provide insight into these processes, however, it is challenging to assess the effect of spatial scale on these metrics. Here, we outline a nested sampling design that fractally spaces sampling locations to concentrate statistical power across spatial scales in a study area. We test this design in northeast Utah, at a study site with distinct vegetation types (including sagebrush steppe and mixed conifer forest), that vary across environmental gradients. We demonstrate the power of this design to detect changes in community phylogenetic diversity across environmental gradients and assess the spatial scale at which the sampling design captures the most variation in empirical data. We find clear evidence of broad-scale changes in multiple features of phylogenetic and taxonomic diversity across aspect. At finer scales, we find additional variation in phylo-diversity, highlighting the power of our fractal sampling design to efficiently detect patterns across multiple spatial scales. Thus, our fractal sampling design and analysis effectively identify important environmental gradients and spatial scales that drive community phylogenetic structure. We discuss the insights this gives us into the ecological assembly processes that differentiate plant communities found in northeast Utah.
Cross-tissue single-cell transcriptomics reveals organizing principles of fibroblasts in health and disease
Authors: Buechler Matthew B. , Pradhan Rachana N. , Calviello Aslihan Karabacak , Muller Soren , Bourgon Richard , Turley Shannon. J. 
Published: January 2021

AbstractFibroblasts are non-hematopoietic structural cells that define the architecture of organs, support the homeostasis of tissue-resident cells and play key roles in fibrosis, cancer, autoimmunity and wound healing. Recent studies have described fibroblast heterogeneity within individual tissues. However, the field lacks a definition of fibroblasts at single-cell resolution across tissues in healthy and diseased organs. Here, we integrated single-cell RNA transcriptomic data from ~150,000 fibroblast cells derived from 16 steady- and 11 perturbed-state mouse organs into fibroblast atlases. These data revealed two universal fibroblast cell subtypes, marked by expression of Pi16 or Col15a1, in all tissues; it also revealed discrete subsets of five specialized fibroblast subtypes in steady-state tissues and three activated fibroblast subtypes in perturbed or diseased tissues. These subsets were transcriptionally shaped by microenvironmental context rather than tissue-type alone. Inference of fibroblast lineage structure from the murine steady-state and perturbed-state fibroblast atlases suggested that specialized and activated subtypes are developmentally related to universal tissue-resident fibroblasts. Analysis of human samples revealed that fibroblast subtypes found in mice are conserved between species, including universal fibroblasts and activated phenotypes associated with pathogenicity in human cancer, fibrosis, arthritis and inflammation. In sum, a cross-species and pan-tissue approach to transcriptomics at single-cell resolution enabled us to define the organizing principles of the fibroblast lineage in health and disease.
Membrane contact probability: an essential and predictive character for the structural and functional studies of membrane proteins
Authors: Wang Lei , Zhang Jiangguo , Wang Dali , Song Chen 
Published: January 2021

AbstractOne of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.
Molecular basis of ligand recognition and activation of human V2 vasopressin receptor
Authors: Zhou Fulai , Ye Chenyu , Ma Xiaomin , Yin Wanchao , Zhou Qingtong , He Xinheng , Zhang Xiaokang , Croll Tristan I. , Yang Dehua , Wang Peiyi , Xu H. Eric , Wang Ming-Wei , Jiang Yi 
Published: January 2021

AbstractThe V2 vasopressin receptor (V2R) is a class A G protein-coupled receptor (GPCR) and plays a vital role in controlling water homeostasis upon stimulation by the natural peptide arginine vasopressin (AVP). Thus, V2R has attracted intense interest as a drug target for diabetes insipidus, nocturia, and hyponatremia. However, how AVP recognizes and activates V2R remains elusive. Here, we report the 2.6 Å resolution structure of V2R bound to AVP and the stimulatory G protein Gs, determined by cryo-electron microscopy (cryo-EM). In this complex, AVP presents a unique cyclic conformation formed by an intramolecular disulfide bond and engages the orthosteric binding pocket of V2R in a ligand-specific mode. Comparison of the AVP–V2R–Gscomplex to previously reported Gs-coupled class A GPCRs reveals distinct structural features, including a smaller outward movement of TM5 and TM6 and the concomitant shift of Gsprotein. Our detailed structural analysis provides a framework for understanding AVP recognition and V2R activation, thereby offering a structural template for drug design targeting V2R.
The adaptive sliding mode control using improved genetic algorithm tuning PID controller for the planetary rover
Authors: Yuan Tiger , Guo Guanyou , Du Baiyu , Zhao Zhiping , Xu Weikai 
Published: January 2021

Purpose
The purpose of this paper is to resolve the problem of the dynamic response performance of the driving control system for a six-wheeled planetary rover. An adaptive sliding mode controller based on an improved genetic algorithm (IGA) to tune PID sliding surface parameters was used in the driving control system of the planetary rover.

Design/methodology/approach
First, the mathematical model of planetary rover driving control is established. Second, according to sliding mode variable structure control, an equivalent controller and a disturbance controller are constructed to solve the problem of a multi-disturbance nonlinear driving control system of planetary rovers and an IGA is used to tune PID parameters.

Findings
Simulation results show that the proposed control algorithm improves the accuracy of the driving control system and optimizes the smoothness of rover motion control.

Practical implications
The controller based on the IGA to tune PID sliding surface parameters has good self-adaptability and real-time controllability for the control object which is difficult to present a precise mathematical model.

Originality/value
The advanced control method is adopted to solve the uncertainty and external interference of planetary rovers in a complex environment. The mathematical model of the six-wheeled rover is established as the control object and the uncertainty and external disturbance of the model are considered. The controller based on IGA has good adaptability and real-time performance and the control algorithm can be used to drive robots in complex environments.
Formal credit usage and gender income gap: the case of farmers in Cambodia
Authors: Sam Vichet 
Published: January 2021

PurposeThe purpose of this article is to analyze the factors that drive gender income differences among farmers in Cambodia with a focus on the role of formal credit.Design/methodology/approachTo decompose the gender income gap, this article employs the Blinder–Oaxaca decomposition technique, while a two-stage least square (2SLS) regression is also employed to check the causal effect of formal credit usage on earnings.FindingsResults show a positive effect of formal credit on farmers' earnings and the gender gap in formal credit usage is not found. Despite that, formal credit still contributes to the gender earnings gap with a higher return to credit usage for male farmers. This can be due to the difference in the level of education, financial literacy and other dimensions in favor of men, allowing them to use credit more effectively than women.Research limitations/implicationsThe findings underline the importance of boosting general and financial education among female farmers in Cambodia. Meanwhile, the expansion of access to financial services for women must be accompanied by policies addressing gender gaps in other economic and social dimensions, so that women are able to reap the potential benefit of using those financial services.Originality/valueLack of research focuses on the link between the gender gap in the use of financial services and the gender income gap. The significant gender gap in returns to formal credit usage found in this study demonstrates that the benefits of gender equity in access to and usage of financial services also depend on the effects of other indicators that policymakers must be aware of.
The apprentice experience: the role of interpersonal attributes and people-related generic skills
Authors: Pagnoccolo Joe , Bertone Santina 
Published: January 2021

PurposeThis research explores the training experiences of Australian apprentices in the workplace with a focus on workplace relationships and their link to interpersonal attributes and people-related generic skills among apprentices.Design/methodology/approachQualitative research is conducted, and the authors analysed interview data from 20 apprentices (17 men, three women; average age 25 years) who came from a range of industries and trade sectors.FindingsThese findings revealed common themes around the importance of communication, emotional direct cognition, self-awareness and teamwork during training on the job. This suggests that interpersonal attributes are central to apprentices' practices within their training experiences.Research limitations/implicationsThe findings indicate a need for greater emphasis on the development of interpersonal attributes in training both on the job and within training packages.Practical implicationsThe paper extends the literature on the role of interpersonal skills in the apprentice experience, presents information about young people's challenges in training and points to further investigations needed to explore this phenomenon.Originality/valueAn authentic detailed account is presented of apprentices' interpersonal attributes and people-related generic skills in their training experiences.
The role of brand love on bank customers' perceptions of corporate social responsibility
Authors: Amegbe Hayford , Dzandu Michael D. , Hanu Charles 
Published: January 2021

PurposeThe lovemarks theory (love and respect) is fairly new to the marketing literature and is now gaining much attention among marketing scholars. The study examined how brand love and brand respect moderate the relationship between corporate social responsibility (CSR), trust (TRUS), satisfaction (SAT) and loyalty (LOY) among bank customers in an emerging/and or a developing country's context.Design/methodology/approachA quantitative survey approach was used. Data from a total of 769 banking customers, containing demographic and psychographic measures were used.FindingsThis study tested six (6) hypotheses. The results confirmed the moderating role of brand respect on the relationship between CSR and TRUS in the banking sector. Also, our results reveal that BLOV moderates the relationship between SAT and LOY. The rest of our hypotheses did not confirm any significant relationship between them.Research limitations/implicationsLike any academic exercise, this study also has some limitations. The hypotheses tested for brand love on bank customers' perceptions of CSR were based on a country study. The implication of brand love for CSR may be the same or vary in different country contexts.Practical implicationsThe study provides managers of banks and managers of financial institutions a better understanding of how love and respect could play a role in their loyalty program and how to incorporate these new constructs into the already known constructs such as satisfaction, trust and loyalty.Originality/valueThis study is unique because it quantitatively examined the relationships between well-researched constructs corporate social responsibility (CSR), trust (TRUS), satisfaction (SAT) on loyalty (LOY) as well as examining these constructs with a fairly new constructs brand love (BLOV) and respect (BRES) in a single study.
DLC-coated spur gears – part I: friction reduction
Authors: Schwarz Andreas , Ebner Martin , Lohner Thomas , Stahl Karsten , Bobzin Kirsten , Brögelmann Tobias , Kalscheuer Christian , Thiex Matthias 
Published: January 2021

Purpose
This paper aims to address the influence of diamond-like carbon (DLC) coatings on the frictional power loss of spur gears. It shows potentials for friction and bulk temperature reduction in industrial use. From a scientific point of view, the thermal insulation effect on fluid friction is addressed, which lowers viscosity in the gear contact due to increasing contact temperature.

Design/methodology/approach
Thermal insulation effect is analyzed in detail by means of the heat balance and micro thermal network of thermal elastohydrodynamic lubrication contacts. Preliminary results at a twin-disk test rig are summarized to categorize friction and bulk temperature reduction by DLC coatings. Based on experiments at a gear efficiency test rig, the frictional power losses and bulk temperatures of DLC-coated gears are investigated, whereby load, speed, oil temperature and coatings are varied.

Findings
Experimental investigations at the gear efficiency test rig showed friction and bulk temperature reduction for all operating conditions of DLC-coated gears compared to uncoated gears. This effect was most pronounced for high load and high speed. A reduction of the mean gear coefficient of friction on average 25% and maximum 55% was found. A maximum reduction of bulk temperature of 15% was observed.

Practical implications
DLC-coated gears show a high potential for reducing friction and improving load-carrying capacity. However, the industrial implementation is restrained by the limited durability of coatings on gear flanks. Therefore, a further and overall consideration of key durability factors such as substrate material, pretreatment, coating parameters and gear geometry is necessary.

Originality/value
Thermal insulation effect of DLC coatings was shown by theoretical analyses and experimental investigations at model test rigs. Although trial tests on gears were conducted in literature, this study proves the friction reduction by DLC-coated gears for the first time systematically in terms of various operating conditions and coatings.

Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0257/