bluuebunny/crossref_metadata_2025_split huggingface dataset:
Pitfalls and opportunities for applying PEER factors in single-cell eQTL analyses
Authors: Xue Angli , Yazar Seyhan , Neavin Drew , Powell Joseph E. 
Published: August 2022

AbstractUsing latent variables in gene expression data can help correct spurious correlations due to unobserved confounders and increase statistical power for expression Quantitative Trait Loci (eQTL) detection. Probabilistic Estimation of Expression Residuals (PEER) is a widely used statistical method that has been developed to remove unwanted variation and improve eQTL discovery power in bulk RNA-seq analysis. However, its performance has not been largely evaluated in single-cell eQTL data analysis, where it is becoming a commonly used technique. Potential challenges arise due to the structure of single-cell data, including sparsity, skewness, and mean-variance relationship. Here, we show by a series of analyses that this method requires additional quality control and data transformation steps on the pseudo-bulk matrix to obtain valid PEER factors. By using a population-scale single-cell cohort (OneK1K, N = 982), we found that generating PEER factors without further QC or transformation on the pseudo-bulk matrix could result in inferred factors that are highly correlated (Pearson’s correlation r = 0.626∼0.997). Similar spurious correlations were also found in PEER factors inferred from an independent dataset (induced pluripotent stem cells, N = 31). Optimization of the strategy for generating PEER factors and incorporating the improved PEER factors in the eQTL association model can identify 9.0∼23.1% more eQTLs or 1.7%∼13.3% more eGenes. Sensitivity analysis showed that the pattern of change between the number of eGenes detected and PEER factors fitted varied significantly for different cell types. In addition, using highly variable genes (e.g., top 2000) to generate PEER factors could achieve similar eGenes discovery power as using all genes but save considerable computational resources (∼6.2-fold faster). We provide diagnostic guidelines to improve the robustness and avoid potential pitfalls when generating PEER factors for single-cell eQTL association analyses.
Profiling genome-wide methylation in two maples: fine-scale approaches to detection with nanopore technology
Authors: McEvoy Susan L. , Grady Patrick G. S. , Pauloski Nicole , O’Neill Rachel J. , Wegrzyn Jill L. 
Published: August 2022

ABSTRACTDNA methylation is critical to the regulation of transposable elements and gene expression, and can play an important role in the adaptation of stress response mechanisms in plants. Traditional methods of methylation quantification rely on bisulfite conversion that can compromise accuracy. Recent advances in long-read sequencing technologies allow for methylation detection in real time. The associated algorithms that interpret these modifications have evolved from strictly statistical approaches to Hidden Markov Models and, recently, deep learning approaches. Much of the existing software focuses on methylation in the CG context, but methylation in other contexts is important to quantify, as it is extensively leveraged in plants. Here, we present methylation profiles for two maple species across the full range of 5mC sequence contexts using Oxford Nanopore Technologies (ONT) long-reads. Hybrid and reference-guided assemblies were generated for two newAceraccessions:Acer negundo(65x ONT and 111X Illumina) andAcer saccharum(93x ONT and 148X Illumina). The ONT reads generated for these assemblies were re-basecalled, and methylation detection was conducted in a custom pipeline with the publishedAcerreferences (PacBio assemblies) and hybrid assemblies reported herein to generate four epigenomes. Examination of the transposable element landscape revealed the dominance ofLTR Copiaelements and patterns of methylation associated with different classes of TEs. Methylation distributions were examined at high resolution across gene and repeat density and described within the broader angiosperm context, and more narrowly in the context of gene family dynamics and candidate nutrient stress genes.
Talin regulates steady-state tensional homeostasis to drive vascular morphodynamics and cancer
Authors: Nikolopoulou Pinelopi , Arapatzi Christina , Rouni Georgia , Mitrossilis Demosthenis , Gaitanis Anastasios , Anagnostopoulos Constantinos D. , Grammenoudi Sofia , Kostourou Vassiliki 
Published: August 2022

AbstractThe mechanical properties of the extracellular environment emerge as critical regulators of cellular functions. Cell mechanotransduction is mainly studied in vitro at initial stages of cell adhesion and very little is known about the mechanoresponses of cells with established tensional dynamics, resembling cells embedded in tissues. Here, we provide in vivo evidence that talin-dependent cell-matrix adhesions are global regulators of vascular mechanics and establish talin as an essential and required mechanosensor in neovessels and already developed tumours. At the molecular level, we demonstrate that talin exploits alternative mechanisms to dynamically-adjust the mechanical integrity of endothelial cells. Our mutational studies indicate a previously unknown role for the requirement of the talin-head in mechanosensing and demonstrate that the talin-head and the talin-rod alone are sufficient to maintain mechanical stability of endothelial cells. Overall, our results underpin the significance of mechanical signals in regulating vascular morphology in steady-state conditions and ultimately modulate cancer progression.Talin mechanosensing is required to maintain cell morphology and control developmental and tumour angiogenesis.
Ataxin-7 promotes Drosophila posterior follicle cell maturation by suppressing yorkie function
Authors: Badmos Hammed , Bennett Daimark 
Published: August 2022

AbstractAtaxin-7 is a key component of the Spt-Ada-Gcn5-acetyltransferase (SAGA) chromatin-modifying complex that anchors Non-stop/USP22, a deubiquitinase, to the complex, thereby helping to coordinate SAGA’s different activities. Recently, we found that non-stop is required in the Drosophila ovary for expression of Hippo signalling pathway components ex and mer, and polarisation of the actin cytoskeleton during collective epithelial cell migration. Here we show that in addition to being required for collective migration, Ataxin-7 plays an essential role in posterior follicle cells (PFCs) to control epithelial maturation and architecture, as well as body axis specification which depends on correct PFC differentiation. Loss of both the deubiquitinase and acetyltransferase modules of SAGA phenocopy loss of Ataxin-7 in PFCs, demonstrating a redundant requirement for SAGA’s enzymatic modules. Strikingly, loss of yorkie completely suppressed effects of Ataxin-7 loss-of-function in PFCs, indicating that the only essential function of Ataxin-7 in PFCs is to suppress yorkie function. This may have broad relevance to the roles of SAGA and Ataxin-7 in development and disease.
Anin cellsite-specific labeling methodology reveals conformational changes of proteins in bacteria
Authors: Shenberger Yulia , Gevorkyan-Airapetov Lada , Hirsch Melanie , Hofmann Lukas , Ruthstein Sharon 
Published: August 2022

AbstractGaining new structural information on proteins in their native cellular environments will shed light on many enzymatic reaction mechanisms and encourage the development of new therapeutic approaches. During the last decade,in cellelectron paramagnetic resonance (EPR) spectroscopy experiments have provided high-resolution data on conformational changes of proteins within the cell. However, one of the major obstacles of EPR spectroscopy is the spin-labeling process, which until now was performed only outside the cellular environment (i.e., exogenously). The spin-labeled protein is then injected into the cell, which limits the protein size and the cellular system that can be used. Here, we describe a new spin-labeling approach that can be applied to over-expressed proteins inEscherichia coli(i.e., endogenously). This approach uses a Cu(II) ion bound to a ligand, which has high affinity to a dHis site in the protein of interest. The presence of a nearby19F-phenylalanine residue can be exploited to verify that the Cu(II)-ligand indeed bound to the protein target. This new methodology allows for the study of any protein, regardless of size or the cellular system used.
Evaluation of resistance of human head lice to pyrethroid insecticides: a meta-analysis study
Authors: Abbasi Ebrahim , Daliri Salman , Yazdani Zahra , Mohseni Shokrollah , Mohammadyan Ghulamraza , Seyed Hosseini Seyedeh Niloofar , Haghighi Reza Nasiri 
Published: August 2022

AbstractIntroductionPediculosis is one of the most common annoying infections caused by insects in humans. Pyrethroids are one of the main insecticides used to treat this infection. But recently, due to the resistance of lice to this group of insecticides, its therapeutic effects have been affected. Based on this, the present study was conducted to investigating the prevalence of resistance to treatment against these insecticides in the world in the form of a meta-analysis.MethodsThis study was conducted as a meta-analysis on the prevalence of treatment resistance in human head lice against pyrethroid insecticides in the world. Based on this, all articles published without a time limit until the end of June 2022 in PubMed/MEDLINE, Web of Science (ISI), Scopus, and Google Scholar databases were extracted and using random effects model statistical methods in the meta-analysis, Cochrane, Index I2 and funnel plot were analyzed by STATA software.ResultsTwenty studies were included in the meta-analysis process. According to this the prevalence of resistance to pyrethroid insecticides in human head lice was estimated at 59% (CI95%: 50% to 68%). Among pyrethroid insecticides, the highest prevalence of resistance to treatment against permethrin insecticide was 65%. Regarding the prevalence of resistance by year, the prevalence before 2004 was estimated at 33%, but after 2015, this rate reached 82%. Also, the prevalence of resistance to treatment was estimated at 68% using genetic diagnosis methods and 43% using clinical diagnosis methods.ConclusionMore than half of human head lice are resistant to pyrethroid insecticides. Based on this, it is recommended that before using this treatment method to treat human head lice infestation, the prevalence of resistance to treatment in that area should be investigated and if the prevalence of resistance is high, alternative or combined treatment methods should be used.
Use of Systems Thinking and Group Model Building Methods to Understand Patterns of Continuous Glucose Monitoring Use Among Older Adults with Type 1 Diabetes
Authors: Kahkoska Anna R. , Smith Cambray , Young Laura A. , Lich Kristen Hassmiller 
Published: August 2022

AbstractA growing number of older adults (ages 65+ years) live with Type 1 diabetes, yet little is known about the complex dynamics that promote use of diabetes technology, such as continuous glucose monitoring (CGM), in this age group. We used systems thinking and methods from group model building (GMB), a participatory approach to system dynamics modeling, to collect data from older adults with Type 1 diabetes and their caregivers through group workshops and individual validation interviews. Data were integrated into a causal loop diagram of the “system” of factors associated with CGM uptake and use, including the clinical and psychosocial outcomes of use and interactions with caregiver and healthcare system factors. We describe the study design, recruitment, GMB and interview procedures, participant feedback, and lessons learned. The study demonstrates feasibility, acceptability, and the value of GMB to engage older adult stakeholders in sophisticated and rigorous research about key determinants of complex health outcomes over time.
Decomposing neural circuit function into information processing primitives
Authors: Voges Nicole , Hausmann Johannes , Brovelli Andrea , Battaglia Demian 
Published: August 2022

ABSTRACTCognitive functions arise from the coordinated activity of neural populations distributed over large-scale brain networks. However, it is challenging to understand and measure how specific aspects of neural dynamics translate into operations of information processing, and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms–such as self-sustained or propagating activity and nonlinear summation of inputs–do not directly give rise to high-level functions. Nevertheless, they already implement simple transformations of the information carried by neural activity.Here, we propose that distinct neural circuit functions, such as stimulus representation, working memory, or selective attention stem from different combinations and types of low-level manipulations of information, or information processing primitives. To test this hypothesis, we combine approaches from information theory with computational simulations of canonical neural circuits involving one or more interacting brain regions that emulate well-defined cognitive functions. More specifically, we track the dynamics of information emergent from dynamic patterns of neural activity, using suitable quantitative metrics to detect where and when information is actively buffered (“active information storage”), transferred (“information transfer”) or non-linearly merged (“information modification”), as possible modes of low-level processing. We find that neuronal subsets maintaining representations in working memory or performing attention-related gain modulation are signaled by their boosted involvement in operations of active information storage or information modification, respectively.Thus, information dynamics metrics, beyond detectingwhichnetwork units participate in cognitive processing, also promise to specifyhow and whenthey do it, i.e., through which type of primitive computation, a capability that may be exploited for the parsing of actual experimental recordings.
Race to survival during antibiotic breakdown determines the minimal surviving population size
Authors: Geyrhofer Lukas , Ruelens Philip , Farr Andrew D. , Pesce Diego , de Visser J. Arjan G.M. , Brenner Naama 
Published: August 2022

AbstractA common strategy used by bacteria to resist antibiotics is enzymatic degradation or modification. Such a collective mechanism also enhances the survival of nearby cells, an effect that increases with the number of bacteria that are present. Collective resistance is of clinical significance, yet a quantitative understanding at the population level is lacking. Here we develop a general theoretical framework of collective resistance under antibiotic degradation. Our modeling reveals that population survival crucially depends on the ratio of timescales of two processes: the rates of population death and antibiotic removal. However, it is insensitive to molecular, biological and kinetic details of the underlying processes that give rise to these timescales. Another important aspect for this ‘race to survival’ is the degree of ‘cooperativity’, which is related to the permeability of the cell wall for antibiotics and enzymes. These observations motivate a coarse-grained, phenomenological model and simple experimental assay to measure the dose-dependent minimal surviving population size. From this model, two dimensionless parameters can be estimated, representing the population’s race to survival and single-cell resistance. Our simple model may serve as reference for more complex situations, such as heterogeneous bacterial communities.
Torsion angles to map and visualize the conformational space of a protein
Authors: Ginn Helen Mary 
Published: August 2022

1AbstractPresent understanding of protein structure dynamics trails behind that of static structures. A torsionangle based approach, called representation of protein entities (RoPE), derives an interpretable conformational space which correlates with data collection temperature, resolution and reaction coordinate. For more complex systems, atomic coordinates fail to separate functional conformational states, which are still preserved by torsion angle-derived space. This indicates that torsion angles are often a more sensitive and biologically relevant descriptor for protein conformational dynamics than atomic coordinates.
Regioselective control of biocatalytic C–H activation and halogenation
Authors: Kissman Elijah N. , Neugebauer Monica E. , Sumida Kiera H. , Swenson Cameron V. , Sambold Nicholas A. , Marchand Jorge A. , Millar Douglas C. , Chang Michelle C.Y. 
Published: August 2022

ABSTRACTBiocatalytic C–H activation has the potential to merge enzymatic and synthetic strategies for bond formation. FeII/αKG-dependent halogenases are particularly distinguished for their ability both to control selective C-H activation as well as to direct group transfer of a bound anion along a reaction axis separate from oxygen rebound, enabling the development of new transformations. In this context, we elucidate the basis for selectivity of enzymes that perform selective halogenation to yield 4-Cl-lysine (BesD), 5-Cl-lysine (HalB), and 4-Cl-ornithine (HalD), allowing us to probe how regioselectivity and chain length selectivity are achieved. We now report the crystal structure of the HalB and HalD, revealing the key role of the substrate-lid in positioning the substrate for C4 vs C5 chlorination and recognition of lysine vs ornithine. Targeted engineering of the substrate-binding lid further demonstrates that these selectivities can be altered or switched, showcasing the potential to develop halogenases for biocatalytic applications.
Rhometa: Population recombination rate estimation from metagenomic read datasets
Authors: Krishnan Sidaswar , DeMaere Matthew Z. , Beck Dominik , Ostrowski Martin , Seymour Justin R. , Darling Aaron E. 
Published: August 2022

AbstractBacterial evolution is influenced by the exchange of genetic information between species through a process referred to as recombination. The rate of recombination is a useful measure for the adaptive capacity of a bacterial population. We introduce Rhometa (https://github.com/sid-krish/Rhometa), a new software package to determine recombination rates from shotgun sequencing reads of metagenomes.It extends the composite likelihood approach for population recombination rate estimation and enables the analysis of modern short-read datasets. We evaluated Rhometa over a broad range of sequencing depths and complexities, using simulated and real experimental short-read data aligned to external reference genomes. In simulated datasets, the deviation from the expected value decreased as the number of genomes increased and we show that 80 genomes are sufficient to reduce these variations below 30%. Testing on an S. pneumoniae transformation experiment dataset we show that Rhometa accurately estimate the expected levels of recombination in a real world dataset.
Testing the nexus between reward system, job condition and employee retention through intervening role of employee engagement among nursing staff
Authors: Kamselem Kaltume Mohammed , Nuhu Muhammad Shaheer , Lawal Kamaldeen A.A , Liman Amina Muhammad , Abdullahi Mohammed Sani 
Published: August 2022

AbstractPurposeThis study investigated the effects of reward system (RS) and job conditions (JC) on employee retention (ER). In particular, this study addressed the mediating effect of employee engagement (EE) on the relationship between RS, JC and ER.Design/methodology/approachThis paper employed descriptive survey approach and the unit of analysis consisted of public hospital nursing staff. Data were collected using questionnaires with a sample of 370 nurse respondents. Structural equation modelling with Smart-Partial Least Squares (PLS) 3.3.8 was used in a statistical analysis.FindingsThe results revealed that RS and JC significantly related to ER. The study also showed the direct effect of RS and JC on EE. These findings indicate that (EE) has a partial mediating role in the relationship between RS, JC and ER.Practical implicationsThe study offers important policy insights for public nursing stakeholders who seek to increase retention of skills among their nursing staff. The findings are also crucial because they may help the health sector improve their ER strategies, especially in dynamic and competitive business situations where organisations are challenged to retain personnel from a limited skilled workforce.Originality/valueThe findings of this study contribute to the literature on retention of nursing employees by enhancing the understanding of the influences of EE, RS and JC on ER among public hospitals.
Family- and non-family-related reasons for entrepreneurial exits
Authors: Koładkiewicz Izabela Anna , Kaciak Eugene , Wojtyra-Perlejewska Marta 
Published: August 2022

PurposeThis study examines the family- and non-family-related reasons that may determine the choice of the anticipated entrepreneurial exit strategy (exit intention).Design/methodology/approachThe study is based on a survey of 267 owner-managers of micro-and small-sized firms in Poland and focuses on their exit intentions (rather than actual actions) as precursors to entrepreneurial exit. Structural equation modelling (SEM) was used to test the hypotheses.FindingsThe results show that family-related reasons may encourage entrepreneurs to choose the stewardship strategy over the financial harvest or voluntary cessation strategies, while non-family-related reasons such as maintaining financial independence and health may encourage the choice of the financial harvest or the voluntary cessation strategy.Originality/valueThis research contributes to both the entrepreneurial exit literature and psychological ownership theory by demonstrating the potential relevance of psychological ownership in the selection of exit strategies.
Cluster dynamics and firms’ strategies – an integrative framework
Authors: Ostapenko Svitlana , Africano Ana Paula , Meneses Raquel 
Published: August 2022

PurposeThis study aims to systematise the links between firms’ strategies (corporate and business) and the cluster dynamics (through the cluster life cycle [CLC] perspective) and propose an integrative framework bridging firms’ strategic behaviour and cluster dynamics (CLC).Design/methodology/approachThe methodology used is an integrative literature review, which provides a distinctive form of research.FindingsThe study identifies several links between firms’ strategies (corporate and business) and the cluster dynamics (CLC), namely: (1) firms’ strategies as a triggering factor of cluster evolution; (2) firms’ strategies and path's decline; (3) firms’ strategies and cluster’s renewal; (4) resilience strategies and the cluster life cycle; and (5) cluster’s features and firms’ strategies.Research limitations/implicationsThis study contributes to developing strategic management theory and cluster theory by bridging firms' strategies and cluster dynamics (CLC). It proposes a new conceptualisation of the impact of cluster dynamics on firms' strategic choices – firstly, it proposes a specific approach to identify the CLC; and secondly, it develops an integrative framework model that relates firms' strategies and each stage of the CLC. These are theoretical tools relevant for further advancements in this area of research, as they can be applied in studies of different clusters for validation, something that was not done.Practical implicationsThe integrative framework is expected to be helpful to company managers, allowing them to design better strategies that account for dynamic cluster environments.Originality/valueThis study aims to fill this gap in the literature by systematising the links between firms' strategies (corporate and business) and the cluster dynamics (CLC).