bluuebunny/crossref_metadata_2025_split huggingface dataset:
Inhibition of LRRK2 kinase activity promotes anterograde axonal transport and presynaptic targeting of α-synuclein
Authors: Brzozowski Charlotte F. , Hijaz Baraa A. , Singh Vijay , Gcwensa Nolwazi Z. , Kelly Kaela , Boyden Edward S. , West Andrew B. , Sarkar Deblina , Volpicelli-Daley Laura A. 
Published: October 2021

AbstractPathologic inclusions composed of α-synuclein called Lewy pathology are hallmarks of Parkinson’s Disease (PD). Dominant inherited mutations in leucine rich repeat kinase 2 (LRRK2) are the most common genetic cause of PD. Lewy pathology is found in the majority of individuals with LRRK2-PD, particularly those with the G2019S-LRRK2 mutation. Lewy pathology in LRRK2-PD associates with increased non-motor symptoms such as cognitive deficits, anxiety, and orthostatic hypotension. Thus, understanding the relationship between LRRK2 and α-synuclein could be important for determining the mechanisms of non-motor symptoms. In PD models, expression of mutant LRRK2 reduces membrane localization of α- synuclein, and enhances formation of pathologic α-synuclein, particularly when synaptic activity is increased. α-Synuclein and LRRK2 both localize to the presynaptic terminal. LRRK2 plays a role in membrane traffic, including axonal transport, and therefore may influence α-synuclein synaptic localization. This study shows that LRRK2 kinase activity influences α-synuclein targeting to the presynaptic terminal. We used the selective LRRK2 kinase inhibitors, MLi-2 and PF-06685360 (PF-360) to determine the impact of reduced LRRK2 kinase activity on presynaptic localization of α-synuclein. Expansion microscopy (ExM) in primary hippocampal cultures and the mouse striatum, in vivo, was used to more precisely resolve the presynaptic localization of α-synuclein. Live imaging of axonal transport of α-synuclein-GFP was used to investigate the impact of LRRK2 kinase inhibition on α-synuclein axonal transport towards the presynaptic terminal. Reduced LRRK2 kinase activity increases α-synuclein overlap with presynaptic markers in primary neurons, and increases anterograde axonal transport of α- synuclein-GFP. In vivo, LRRK2 inhibition increases α-synuclein overlap with glutamatergic, cortico-striatal terminals, and dopaminergic nigral-striatal presynaptic terminals. The findings suggest that LRRK2 kinase activity plays a role in axonal transport, and presynaptic targeting of α-synuclein. These data provide potential mechanisms by which LRRK2-mediated perturbations of α-synuclein localization could cause pathology in both LRRK2-PD, and idiopathic PD.
Aminoglycosides induce a bacterial senescent state that increases antibiotic tolerance in treatment-naïve cells
Authors: Meyer Christian T. , Bruni Giancarlo N. , Dodd Ben , Kralj Joel M. 
Published: October 2021

1.AbstractBacterial evolution of antibiotic resistance is facilitated by non-genetic resistance that increases drug tolerance, buying time for evolutionary innovation. Escherichia coli treated with aminoglycosides permanently lose the ability to divide within four hours, yet we discovered a majority of cells maintain membrane integrity and metabolic activity greater than two days post treatment - a bacterial senescent-like state. These cells, which we term zombies, exhibit dynamic gene expression and metabolomic profiles, even after irreversible exit from the cell cycle. Our data reveal zombies upregulate the phage shock protein pathway to maintain membrane integrity. Remarkably, though unable to form new colonies, zombies increase the antibiotic tolerance of treatment-naïve cells, implying chemical communication. Chemical supplementation and genetic knockouts show that zombies communicate with treatment-naïve cells by secreting indole. In summary, our study revealed a bacterial senescent-like state, induced by aminoglycosides, that decreases the antibiotic susceptibility of multiple bacterial species. Thus, E. coli zombies utilize paracrine signaling to promote non-genetic antibiotic tolerance.
Sex differences in behavioral responding and dopamine release during Pavlovian learning
Authors: Lefner Merridee J. , Dejeux Mariana I. , Wanat Matthew J. 
Published: October 2021

AbstractLearning associations between cues and rewards requires the mesolimbic dopamine system. The dopamine response to cues signals differences in reward value in well-trained animals. However, these value-related dopamine responses are absent during early training sessions when cues signal differences in the reward rate. These findings suggest cue-evoked dopamine release conveys differences between outcomes only after extensive training, though it is unclear if this is unique to when cues signal differences in reward rate, or if this is also evident when cues signal differences in other value-related parameters such as reward size. To address this, we utilized a Pavlovian conditioning task in which one audio cue was associated with a small reward (one pellet) and another audio cue was associated with a large reward (three pellets). We performed fast-scan cyclic voltammetry to record changes in dopamine release in the nucleus accumbens of male and female rats throughout learning. While female rats exhibited higher levels of conditioned responding, a faster latency to respond, and elevated post-reward head entries relative to male rats, there were no sex differences in the dopamine response to cues. Multiple training sessions were required before cue-evoked dopamine release signaled differences in reward size. Reward-evoked dopamine release scaled with reward size, though females displayed lower reward-evoked dopamine responses relative to males. Conditioned responding related to the decrease in the peak reward-evoked dopamine response and not to cue-evoked dopamine release. Collectively these data illustrate sex differences in behavioral responding as well as in reward-evoked dopamine release during Pavlovian learning.
Sweet revenge: AtSWEET12 in plant defense against bacterial pathogens by apoplastic sucrose limitation
Authors: Fatima Urooj , Senthil-Kumar Muthappa 
Published: October 2021

ABSTRACTDepriving bacterial pathogens of sugars is a potential plant defense strategy. The relevance of SUGARS WILL EVENTUALLY BE EXPORTED TRANSPORTERS (SWEETs) in plant susceptibility to pathogens has been established, but their role in plant defense remains unknown. We identified Arabidopsis thaliana SWEETs (AtSWEETs) involved in defense against nonhost and host Pseudomonas syringae pathogens through reverse genetic screening of atsweet1–17 mutants. Double/triple mutant, complementation, and overexpression line analysis, and apoplastic sucrose estimation studies revealed that AtSWEET12 suppresses pathogen multiplication by limiting sucrose availability in the apoplast. Localization studies suggested that plant defense occurred via increased plasma membrane targeting of AtSWEET12 with concomitant AtSWEET11 protein reduction. Moreover, the heterooligomerization of AtSWEET11 and AtSWEET12 was involved in regulating sucrose transport. Our results highlight a PAMP-mediated defense strategy against foliar bacterial pathogens whereby plants control AtSWEET11-mediated sucrose efflux in the apoplast through AtSWEET12. We uncover a fascinating new mechanism of pathogen starvation as a broad-spectrum disease resistance mechanism in parallel with existing immune pathways.One sentence summaryThe transporter AtSWEET12 restricts bacterial pathogen multiplication by regulating sucrose availability to pathogens in the apoplast.
Predicting compound-protein interaction using hierarchical graph convolutional networks
Authors: Bui-Thi Danh , Rivière Emmanuel , Meysman Pieter , Laukens Kris 
Published: October 2021

AbstractMotivationConvolutional neural networks have enabled unprecedented breakthroughs in a variety of computer vision tasks. They have also drawn much attention from other domains, including drug discovery and drug development. In this study, we develop a computational method based on convolutional neural networks to tackle a fundamental question in drug discovery and development, i.e. the prediction of compound-protein interactions based on compound structure and protein sequence. We propose a hierarchical graph convolutional network (HGCN) to encode small molecules. The HGCN aggregates a molecule embedding from substructure embeddings, which are synthesized from atom embeddings. As small molecules usually share substructures, computing a molecule embedding from those common substructures allows us to learn better generic models. We then combined the HGCN with a one-dimensional convolutional network to construct a complete model for predicting compound-protein interactions. Furthermore we apply an explanation technique, Grad-CAM, to visualize the contribution of each amino acid into the prediction.ResultsExperiments using different datasets show the improvement of our model compared to other GCN-based methods and a sequence based method, DeepDTA, in predicting compound-protein interactions. Each prediction made by the model is also explainable and can be used to identify critical residues mediating the interaction.Availability and implementationhttps://github.com/banhdzui/cpi_hgcn.git
Predicting the Activities of Drug Excipients on Biological Targets using One-Shot Learning
Authors: Mi Xuenan , Shukla Diwakar 
Published: October 2021

AbstractExcipients are a major component of drugs and are used to improve drugs attributes such as stability and appearance. Excipients approved by Food and Drug Administration (FDA) are regarded as safe for human in allowed concentration, but their potential interaction with drug targets have not been investigated systematically, which might influence drug’s efficacy. Deep learning models have been used for identification of ligands that could bind to the drug targets. However, due to the limited available data, it is challenging to reliably estimate the likelihood of a ligand-protein interaction. One-shot learning techniques provide a potential approach to address this low-data problem as these techniques require only one or a few examples to classify the new data. In this study, we apply one-shot learning models on datasets that include ligands binding to G-Protein Coupled Receptors (GPCRs) and Kinases. The predicted results suggest that one-shot learning models could be used for predicting ligand-protein interaction and the models attain better performance when protein targets contain conserved binding pockets. The trained models are also used to predict interactions between excipients and drug targets, which provides a potential efficient strategy to explore the activities of drug excipients. We find that a large number of drug excipients could interact with biological targets and influence their function. The results demonstrate how one-shot learning models can be used to make accurate prediction for excipient-protein interactions and these methods could be used for selecting excipients with limited drug-protein interactions.
Development of coarse-grained model for a minimal stratum corneum lipid mixture
Authors: Shamaprasad Parashara , Moore Timothy C. , Xia Donna , Iacovella Christopher R. , Bunge Annette L. , McCabe Clare 
Published: October 2021

AbstractMolecular dynamics simulations of mixtures of the ceramide N-(tetracosanoyl)-sphingosine (NS), cholesterol, and a free fatty acid are performed to gain a molecular-level understanding of the structure of the lipids found in the stratum corneum layer of skin. A new coarse-grained model for cholesterol, developed using the multistate iterative Boltzmann inversion method, is compatible with previously developed coarse-grained forcefields for ceramide NS, free fatty acid, and water, and validated against atomistic simulations of these lipids using the CHARMM force field. Self-assembly simulations of multilayer structures using these coarse-grained force fields are performed, revealing that a large fraction of the ceramides adopt extended conformations, which cannot occur in the bilayer structures typically studied using simulation. Cholesterol fluidizes the membrane by promoting packing defects and it is observed that an increase in cholesterol content reduces the bilayer height, due to an increase in interdigitation of the C24 lipid tails, consistent with experimental observations. Through the use of a simple reverse-mapping procedure, a self-assembled coarse-grained multilayer system is used to construct an equivalent structure with atomistic resolution. Simulations of this atomistic structure are found to closely agree with experimentally derived neutron scattering length density profiles. Significant interlayer hydrogen bonding is observed in the inner layers of the atomistic multilayer structure that are not found in the outer layers in contact with water or in equivalent bilayer structures. These results identify several significant differences in the structure and hydrogen bonding of multilayer structures as compared to the more commonly studied bilayer systems, and, as such, highlight the importance of simulating multilayer structures for more accurate comparisons with experiment. These results also provide validation of the efficacy of the coarse-grained forcefields and the framework for multiscale simulation.
Perceived competition in agricultural lending: stylized facts and an agenda for future research
Authors: Kuethe Todd , Fiechter Chad , Oppedahl David 
Published: October 2021

PurposeThis study examines agricultural lending by commercial banks and the competition they face from the Farm Credit System (FCS) and non-traditional lenders, including merchants, dealers and other input suppliers.Design/methodology/approachWe construct a measure of commercial banks' perceived competition with FCS or non-traditional lenders using the individual responses to the Federal Reserve Bank of Chicago's Land Values and Credit Conditions Survey between 1999 and 2019. Through regression analysis of an unbalanced panel of survey responses, we present a number of stylized facts on the relationship between perceived competition and farm loan rate spreads, collateral requirements, loan delinquencies and expected lending volumes.FindingsOur analysis shows that the two sources of competition have very different effects on commercial bank lending terms, loan portfolio riskiness and expected loan volumes. With these results in mind, we offer a number of suggestions for future research.Originality/valueWe leverage the unique characteristics of the Land Values and Credit Conditions Survey to examine the competition with non-traditional lenders that cannot be observed using administrative data.
The effects of perceived luxury value on customer engagement and purchase intention in live streaming shopping
Authors: Yu Fan , Zheng Ran 
Published: October 2021

PurposeNowadays, more and more Chinese consumers purchase luxury goods on live streaming platforms. However, the existing literature rarely focuses on this emerging phenomenon. This article attempts to construct a theoretical model based on the perceived value theory to explain this phenomenon.Design/methodology/approachIn total, 354 online questionnaires are collected, and the partial least square structural equation model is used to analyze the model empirically.FindingsThe results show that consumers' perceived luxury values (financial value, functional value, individual value and social value) have a significant and positive effect on customer engagement, which further leads to purchase intention.Originality/valueIn view of fact that there is a big difference between luxury goods and nonluxury goods, yet the existing literature rarely distinguishes between luxury goods and nonluxury goods in the context of live streaming shopping, this article attempts to use perceived value theory to examine consumers' luxury purchase intentions in live streaming shopping and explores whether customer engagement is a mediating mechanism of perceived luxury values that influences purchase intention in live streaming.
The shape of creaminess: consumers expected and perceived rounded chocolates as creamier than squared
Authors: Yudi Furukita Baptista Iuri , Carvalho Fabiana , Efraim Priscilla , de Souza Silveira Paulo Túlio , Behrens Jorge 
Published: October 2021

PurposeResearch on cross-modal sensory interactions has shown that visual aspects of food can influence consumer's expectation and perception of taste, mouthfeel and liking. This paper aims to investigate the effects of a rounded (“bouba”) and a squared (“kiki”) shape on expected and perceived sweetness, bitterness, creaminess and liking of chocolates.Design/methodology/approachBrazilian consumers (N = 230) divided into two groups of 115 individuals each evaluated five chocolates containing 30, 40, 50, 60 and 70% of cocoa. One of the groups evaluated all formulations in the rounded shape and the other in the squared shape. Results were analysed with mixed multivariate analysis of variance (mixed-MANOVA) between shapes, repeated-measures MANOVA between pre- and post-tasting and Pearson's correlation analysis was performed between liking ratings and sweetness, bitterness and creaminess confirmation/disconfirmation.FindingsThe study found significant effects (p < 0.05) of shape on expected and perceived creaminess but not on other attributes; of cocoa percentage (30, 40, 50, 60 and 70%) on all four attributes; and time (pre- and post-tasting) on sweetness, bitterness and liking but not creaminess. Finally, it found significant negative correlations between the creaminess difference indices and the liking ratings for the 30, 50 and 60% chocolates.Originality/valueThis study reports that consumers may expect and perceive chocolates as creamier in a rounded shape than in an angular shape and that if the expectation of creaminess is not confirmed by sensory perception, acceptability may be negatively affected.
Impact of I4.0 technologies and their interoperability on performance: future pathways for supply chain resilience post-COVID-19
Authors: Frederico Guilherme F. , Kumar Vikas , Garza-Reyes Jose Arturo , Kumar Anil , Agrawal Rohit 
Published: October 2021

PurposeThis study aims to investigate the impact of I4.0 technologies and their interoperability on supply chains (SCs) performance and how the integration of such technologies and their interoperability can create pathways for SCs resilience post-COVID-19. This is of paramount importance in the context of COVID-19 as the investigation around I4.0 technologies may provide relevant insights on how SCs may better respond to unexpected situations like the current pandemic with the use of digital technologies.Design/methodology/approachA survey research method was designed based on some constructs extracted from the literature regarding the main disruptive technologies, interoperability, elements of supply chains processes (SCPs) performance such as integration, collaboration, transparency, efficiency, responsiveness and profitability. The data were collected from March to July 2020 from different regions of the world when the peak of the first wave of the pandemic had occurred. The survey resulted in 115 valid responses. The study used a combination of descriptive, correlation and multiple regression methods to analyse the data.FindingsThe study indicates that disruptive technologies significantly impact SCPs performance (integration, collaboration, responsiveness and transparency) and their resilience. The findings did not support the notion that these technologies improve the efficiency of SCs, a significant contrast to the existing literature. Our findings also refute the existing understanding that interoperability moderates the impact of disruptive technologies on SCPs performance and enhancing the resilience of SCs. However, the findings show that the integration of I4.0 technologies and their interoperability has a positive impact on SCPs profitability.Research limitations/implicationsThe findings strongly advocate that this integration plays an important role in improving SC performance, and a future pathway of SC resiliency post-COVID-19. Considering that the I4.0 trend will impact SCs in the coming years, this study brings a relevant contribution to researchers and practitioners.Originality/valueThis study makes a unique contribution by investigating a novel causal relationship between the main elements (I4.0 technologies, interoperability, processes performance and strategic outcomes) related to the SC in this new context.
Experimental research on improving the wear resistance and anti-friction properties of drill pipe joints
Authors: Huang Zhiqiang , Yin Zhongquan , Wu Wei 
Published: October 2021

Purpose
The purpose of this study is to solve the oil drill pipe joints and casing excessive wear problems and to improve the drill pipe joint-casing wear resistance and anti-friction properties.

Design/methodology/approach
On the surface of the drill pipe joints using oxyacetylene flame bead weld (BW) wear-resistant welding wire ARNCO-100XTTM prepares welding layer, high-velocity oxygen fuel (HVOF) Cr3C275-NiCr25 prepares coating and subsonic flame spray and remelt (SFSR) Ni60 prepares coating, then comparing and analyzing the friction and wear of the three types of wear-resistant layers and the casing under the condition of 1.8 g/cm3 mud drilling fluid lubrication. The wear resistance and anti-friction performance of the drill pipe joints were evaluated based on the wear situation, finally revealing its friction and wear mechanisms.

Findings
Three types of wear-resistant layers can improve the surface wear resistance of drill pipe joints, the wear-resistant layer and the substrate are well combined and the welding layers and coating are both dense and uniform. The wear resistance of the HVOF-Cr3C275-NiCr25 coating is 10.9 times that of the BW-ARNCO-100XTTM weld layer, and the wear resistance of the SFSR-Ni60 weld layer is 2.45 times that of the BW-ARNCO-100XTTM weld layer. The anti-friction properties of SFSR-Ni60 welding layer is the best, followed by HVOF-Cr3C275-NiCr25 coating, and the anti-friction properties of BW-ARNCO-100XTTM welding layer is the worst among the three.

Originality/value
The research results of this paper have great practical value in the process and material of improving the wear resistance and anti-friction performance of the drill pipe joint casing.
Considering the corporeal to facilitate research to practice transitions
Authors: Goltz Sonia , Sotirin Patty 
Published: October 2021

PurposeThe authors suggest that the research-to-practice gap, such as that found in evidence-based management, is due in part to a lack of attention to embodied knowledge. The recommendation is for change agents to bring attention to embodied knowing when implementing change based on research. The purpose of the paper is to address the research-to-practice gap.Design/methodology/approachThis is a conceptual paper that considers limitations of the predominant approach to considering the research-to-practice gap. The literature on phenomenology, feminist theory, and learning theory form the basis for exploring these challenges as well as possible solutions for transcending the research-to-practice gap.FindingsStrategic opportunities for introducing increased corporeal understanding are advanced. The suggestions address the research-to-practice gap at three critical stages of research-based change initiatives. These include making embodied knowledge integral to change initiatives in framing research, reducing resistance, and increasing acceptance. Among the specific strategies discussed are attending to tacit knowledge when considering the change, embracing the embrained body including attending to kinesthetic resistance and starting with the body to increase acceptance when implementing change.Originality/valueThere has been very little previous attention to the corporeal in management research and practice, including in the organizational change literature. This paper not only increases this discussion significantly but also provides suggestions for how to move forward in practice.