bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consecutive treatments of methamphetamine promote the development of cardiac pathological symptoms in zebrafish
Authors: Zhang Jimmy , Nguyen Anh H. , Jilani Daniel , Torres Ramses Seferino Trigo , Schmiess-Heine Lauren , Le Tai , Xia Xing , Cao Hung 
Published: May 2023

AbstractChronic methamphetamine use, a widespread drug epidemic, has been associated with cardiac morphological and electrical remodeling, leading to the development of numerous cardiovascular diseases. While methamphetamine has been documented to induce arrhythmia, most results originate from clinical trials from users who experienced different durations of methamphetamine abuse, providing no documentation on the use of methamphetamine in standardized settings. Additionally, the underlying molecular mechanism on how methamphetamine affects the cardiovascular system remains elusive. A relationship was sought between cardiotoxicity and arrhythmia with associated methamphetamine abuse in zebrafish to identify and to understand the adverse cardiac symptoms associated with methamphetamine. Zebrafish were first treated with methamphetamine 3 times a week over a 2-week duration. Immediately after treatment, zebrafish underwent electrocardiogram (ECG) measurement using an in-house developed acquisition system for electrophysiological analysis. Subsequent analyses of cAMP expression and Ca2+regulation in zebrafish cardiomyocytes were conducted. cAMP is vital to development of myocardial fibrosis and arrhythmia, prominent symptoms in the development of cardiovascular diseases. Ca2+dysregulation is also a factor in inducing arrhythmias. During the first week of treatment, zebrafish that were administered with methamphetamine displayed a decrease in heart rate, which persisted throughout the second week and remained significantly lower than the heart rate of untreated fish. Results also indicate an increased heart rate variability during the early stage of treatment followed by a decrease in the late stage for methamphetamine-treated fish over the duration of the experiment, suggesting a biphasic response to methamphetamine exposure. Methamphetamine-treated fish also exhibited reduced QTc intervals throughout the experiment. Results from the cAMP and Ca2+assays demonstrate that cAMP was upregulated and Ca2+was dysregulated in response to methamphetamine treatment. Collagenic assays indicated significant fibrotic response to methamphetamine treatment. These results provide potential insight into the role of methamphetamine in the development of fibrosis and arrhythmia due to downstream effectors of cAMP.
Asymmetric conformations and lipid interactions shape the ATP-coupled cycle of a heterodimeric ABC transporter
Authors: Tang Qingyu , Sinclair Matt , Hasdemir Hale S. , Stein Richard , Karakas Erkan , Tajkhorshid Emad , Mchaourab Hassane 
Published: May 2023

AbstractTo illuminate the structural origin of catalytic asymmetry of heterodimeric ABC transporters and how it shapes the energetics of their conformational cycles, we used cryo-electron microscopy (cryo-EM), double electron-electron resonance spectroscopy (DEER), and molecular dynamics (MD) simulations, to capture and characterize conformational states of the heterodimeric ABC multidrug exporter BmrCD in lipid nanodiscs. In addition to multiple ATP- and substrate-bound inward-facing (IF) conformations, we obtained the structure of an occluded (OC) conformation wherein the unique extracellular domain (ECD) twists to partially open the extracellular gate. In conjunction with DEER analysis of the populations of these conformations, the structures reveal that ATP-powered isomerization entails changes in the relative symmetry of the BmrC and BmrD subunits that propagates from the transmembrane domain (TMD) to the nucleotide binding domain (NBD). The structures uncover asymmetric substrate and Mg2+binding which we hypothesize are required for triggering ATP hydrolysis preferentially in one of the nucleotide-binding sites. MD simulations demonstrated that multiple lipid molecules, identified from the cryo-EM density maps, differentially bind the IF versus the OC conformation thus modulating their relative stability. In addition to establishing how lipid interactions with BmrCD modulate the energy landscape, our findings are framed in a distinct transport model that highlights the role of asymmetric conformations in the ATP-coupled cycle with implications to the mechanism of ABC transporters in general.
Unveiling Liquid-Crystalline Lipids in the Urothelial Membrane through Cryo-EM
Authors: Yanagisawa Haruaki , Kita Yoshihiro , Oda Toshiyuki , Kikkawa Masahide 
Published: May 2023

AbstractThe urothelium, a distinct epithelial tissue lining the urinary tract, serves as an essential component in preserving urinary tract integrity and thwarting infections. The asymmetric unit membrane (AUM), primarily composed of the uroplakin complex, constitutes a critical permeability barrier in fulfilling this role. However, the molecular architectures of both the AUM and the uroplakin complex have remained enigmatic due to the paucity of high-resolution structural data. In this study, we utilized cryo-electron microscopy to elucidate the three-dimensional structure of the uroplakin complex within the porcine AUM. While the global resolution achieved was 3.5 Å, we acknowledge that due to orientation bias, the resolution in the vertical direction was determined to be 6.3 Å. Our findings unveiled that the uroplakin complexes are situated within hexagonally arranged crystalline lipid membrane domains, rich in hexosylceramides. Moreover, our research rectifies a misconception in a previous model by confirming the existence of a domain initially believed to be absent, and pinpointing the accurate location of a crucialEscherichia colibinding site implicated in urinary tract infections. These discoveries offer valuable insights into the molecular underpinnings governing the permeability barrier function of the urothelium and the orchestrated lipid phase formation within the plasma membrane.
Phase-encoded fMRI tracks down brainstorms of natural language processing with sub-second precision
Authors: Lei Victoria Lai Cheng , Leong Teng Ieng , Leong Cheok Teng , Liu Lili , Choi Chi Un , Sereno Martin I. , Li Defeng , Huang Ruey-Song 
Published: May 2023

AbstractThe human language system interacts with cognitive and sensorimotor regions during natural language processing. However, where, when, and how these processes occur remain unclear. Existing noninvasive subtraction-based neuroimaging techniques cannot simultaneously achieve the spatial and temporal resolutions required to visualize ongoing information flows across the whole brain. Here we have developed phase-encoded designs to fully exploit the temporal information latent in functional magnetic resonance imaging (fMRI) data, as well as overcoming scanner noise and head-motion challenges during overt language tasks. We captured neural information flows as coherent waves traveling over the cortical surface during listening, reciting, and oral cross-language interpreting. The timing, location, direction, and surge of traveling waves, visualized as ‘brainstorms’ on brain ‘weather’ maps, reveal the functional and effective connectivity of the brain in action. These maps uncover the functional neuroanatomy of language perception and production and motivate the construction of finer-grained models of human information processing.
A marker chromosome in psychosis identifies glycine decarboxylase (GLDC) as a novel regulator of neuronal and synaptic function in the hippocampus
Authors: Kambali Maltesh , Li Yan , Unichenko Petr , Pliego Jessica Feria , Yadav Rachita , Liu Jing , McGuinness Patrick , Cobb Johanna G. , Wang Muxiao , Nagarajan Rajasekar , Lyu Jinrui , Vongsouthi Vanessa , Jackson Colin J. , Engin Elif , Coyle Joseph T. , Shin Jeaweon , Talkowski Michael E. , Homanics Gregg E. , Bolshakov Vadim Y. , Henneberger Christian , Rudolph Uwe 
Published: May 2023

AbstractThe biological significance of a small supernumerary marker chromosome that results in dosage alterations to chromosome 9p24.1, including triplication of theGLDCgene encoding glycine decarboxylase, in two patients with psychosis is unclear. In an allelic series of copy number variant mouse models, we identify that triplication ofGldcreduces extracellular glycine levels as determined by optical fluorescence resonance energy transfer (FRET) in dentate gyrus (DG) but not in CA1, suppresses long-term potentiation (LTP) in mPP-DG synapses but not in CA3-CA1 synapses, reduces the activity of biochemical pathways implicated in schizophrenia and mitochondrial bioenergetics, and displays deficits in prepulse inhibition, startle habituation, latent inhibition, working memory, sociability and social preference. Our results thus provide a link between a genomic copy number variation, biochemical, cellular and behavioral phenotypes, and further demonstrate that GLDC negatively regulates long-term synaptic plasticity at specific hippocampal synapses, possibly contributing to the development of neuropsychiatric disorders.
Classifying high-dimensional phenotypes with ensemble learning
Authors: Devine Jay , Kurki Helen K. , Epp Jonathan R. , Gonzalez Paula N. , Claes Peter , Hallgrímsson Benedikt 
Published: May 2023

AbstractClassification is a fundamental task in biology used to assign members to a class. While linear discriminant functions have long been effective, advances in phenotypic data collection are yielding increasingly high-dimensional datasets with more classes, unequal class covariances, and non-linear distributions. Numerous studies have deployed machine learning techniques to classify such distributions, but they are often restricted to a particular organism, a limited set of algorithms, and/or a specific classification task. In addition, the utility of ensemble learning or the strategic combination of models has not been fully explored.We performed a meta-analysis of 33 algorithms across 20 datasets containing over 20,000 high-dimensional shape phenotypes using an ensemble learning framework. Both binary (e.g., sex, environment) and multi-class (e.g., species, genotype, population) classification tasks were considered. The ensemble workflow contains functions for preprocessing, training individual learners and ensembles, and model evaluation. We evaluated algorithm performance within and among datasets. Furthermore, we quantified the extent to which various dataset and phenotypic properties impact performance.We found that discriminant analysis variants and neural networks were the most accurate base learners on average. However, their performance varied substantially between datasets. Ensemble models achieved the highest performance on average, both within and among datasets, increasing average accuracy by up to 3% over the top base learner. Higher class R2values, mean class shape distances, and between– vs. within-class variances were positively associated with performance, whereas higher class covariance distances were negatively associated. Class balance and total sample size were not predictive.Learning-based classification is a complex task driven by many hyperparameters. We demonstrate that selecting and optimizing an algorithm based on the results of another study is a flawed strategy. Ensemble models instead offer a flexible approach that is data agnostic and exceptionally accurate. By assessing the impact of various dataset and phenotypic properties on classification performance, we also offer potential explanations for variation in performance. Researchers interested in maximizing performance stand to benefit from the simplicity and effectiveness of our approach made accessible via the R packagepheble.
Optimizing Cell Therapy by Sorting Cells with High Extracellular Vesicle Secretion
Authors: Koo Doyeon , Cheng Xiao , Udani Shreya , Zhu Dashuai , Li Junlang , Hall Brian , Tsubamoto Natalie , Hu Shiqi , Ko Jina , Cheng Ke , Di Carlo Dino 
Published: May 2023

AbstractCritical challenges remain in clinical translation of extracellular vesicle (EV)-based therapeutics due to the absence of methods to enrich cells with high EV secretion. Current cell sorting methods are limited to surface markers that are uncorrelated to EV secretion or therapeutic potential. We developed a nanovial technology for enrichment of millions of single cells based on EV secretion. This approach was applied to select mesenchymal stem cells (MSCs) with high EV secretion as therapeutic cells for improving treatment. The selected MSCs exhibited distinct transcriptional profiles associated with EV biogenesis and vascular regeneration and maintained high levels of EV secretion after sorting and regrowth. In a mouse model of myocardial infarction, treatment with high-secreting MSCs improved heart functions compared to treatment with low-secreting MSCs. These findings highlight the therapeutic importance of EV secretion in regenerative cell therapies and suggest that selecting cells based on EV secretion could enhance therapeutic efficacy.
Hybrid Raman spectroscopy and artificial neural network algorithm discriminatingmycobacterium bovisBCG and members of the ordermycobacteriales
Authors: Macgregor-Fairlie Michael , De Gomes Paulo , Weston Daniel , Rickard Jonathan James Stanley , Goldberg Oppenheimer Pola 
Published: May 2023

AbstractEven in the face of the COVID-19 pandemic, Tuberculosis (TB) continues to be a major public health problem and the 2nd biggest infectious cause of death worldwide. There is, therefore, an urgent need to develop effective TB diagnostic methods, which are cheap, portable, sensitive and specific. Raman spectroscopy is a potential spectroscopic technique for this purpose, however, so far, research efforts have focused primarily on the characterisation ofMycobacterium tuberculosisand other Mycobacteria, neglecting bacteria within the microbiome and thus, failing to consider the bigger picture. It is paramount to characterise relevant Mycobacteriales and develop suitable analytical tools to discriminate them from each other. Herein, through the combined use of Raman spectroscopy and the self-optimising Kohonen index network and further multivariate tools, we have successfully undertaken the spectral analysis ofMycobacterium bovisBCG,Corynebacterium glutamicumandRhodoccocus erythropolis. This has led to development of a useful tool set, which can readily discern spectral differences between these three closely related bacteria as well as generate a unique spectral barcode for each species. Further optimisation and refinement of the developed method will enable its application to other bacteria inhabiting the microbiome and ultimately lead to advanced diagnostic technologies, which can save many lives.
Glyceroglycolipids are essential forBurkholderia cenocepaciaintracellular survival by preventing phagolysosome acidification
Authors: Shropshire Holly , Guillonneau Richard , Han Zengsheng , Jones Rebekah A. , Ahmed Shadman , García-Romero Inmaculada , Aberdeen Isabel , Nezis Ioannis , Valvano Miguel A. , Scanlan David J. , Chen Yin 
Published: May 2023

AbstractBurkholderia cenocepaciais a problematic pathogen that infects people with cystic fibrosis and often causes fatal “cepacia syndrome”.B. cenocepaciainfection is difficult to treat due to the high intrinsic resistance of the bacterium to antimicrobials and its ability to survive in macrophages. In this study, we uncover a hitherto unknown aspect ofB. cenocepacia’s pathogenesis related to the formation of new glyceroglycolipids, which is required for intracellular survival. Using lipidomics, we observed thatB. cenocepaciacan produce three glyceroglycolipid species in phosphate deplete conditions using a PlcP-mediated lipid remodelling pathway originally discovered in soil and ocean-dwelling bacteria. While lipid remodelling as an adaptation strategy for environmental microbes to cope with the scarcity of phosphorus is known, its role in intracellular bacterial survival was not investigated. Using mammalian macrophages andGalleria mellonellalarvae as infection models, we showed that the mutant unable to perform membrane lipid remodelling (ΔplcP) could not establish infection. Unlike the wild type bacterium, the ΔplcPmutant did not replicate within macrophages and failed to prevent phagosome acidification. Comparative genomics analyses showed that this PlcP pathway is conserved in all pathogenicBurkholderiathat infect a variety of mammalian and plant hosts. Overall, our results indicate that membrane lipid remodelling plays an essential, yet previously overlooked, role in subverting host immunity.
The effects of team diversity on promoting sustainable luxury products
Authors: Quach Sara , Septianto Felix , Thaichon Park , Sung Billy 
Published: May 2023

PurposeThis research examines the effect of team diversity on customer behavior (purchase likelihood) associated with sustainable luxury products and further considers the mediating role of customer skepticism and the moderating role of the growth mindset in these relationships.Design/methodology/approachStudy 1 aims to confirm the direct effect of team diversity on purchase intention and the mediating effect of customer skepticism. Featuring a fictitious brand, Study 2 seeks to test the moderating effects of a growth mindset. This research recruits participants located in the USA who have shopping experiences with a luxury product.FindingsThe findings support the notion that team diversity can mitigate customers' skepticism while enhancing purchase likelihood. Moreover, this effect is stronger among those with a growth mindset. As such, the findings suggest that communicating the heterogeneous composition of team members can benefit sustainable luxury brands.Originality/valueUnderpinned by the signaling theory and incremental theory, this research examines the effects of team diversity on customer behavior (purchase likelihood) related to sustainable luxury products, as well as the role of customer skepticism (as a mediator) and a growth mindset (as a moderator) in these relationships. Thus, the findings broaden the current diversity research which has predominantly focused on team decision-making and performance.
The effect of corruption level in steering the business–government relations: evidence from 23 African countries
Authors: Tesfagebreal Mebrahtu , Chang Li , Tuo Siele Jean , Qian Yu 
Published: May 2023

PurposeThe purpose of this paper is to investigate the effect of corruption level in steering the business–government relations (BGRs) in developing countries. It also examines the moderating effect of firm size.Design/methodology/approachUsing robust tobit and probit models, this study tests the response behavior of 9787 firms from 23 African countries to their government's policy and regulations and the direct effect of corruption control level in their response decisions. The authors also perform several other additional analyses to ensure the robustness of the findings, including change analysis, two-stage model and recursive bivariate model.FindingsThe result shows that corruption level is among the significant factors that drive BGRs exponentially. The finding points out that, there is a strong alliance of business and government in more corrupt countries. Moreover, the impact of corruption level exacerbates when the firm is bigger.Research limitations/implicationsManagers should focus more on activities that create long-term sustainable advantage. Valuable time of the senior managers should not waste on negotiating government policies to earn a short term advantages.Practical implicationsIt is evident that legal and transparent government alliances can lead to economic rent for firms. However, it is important to note that any alliance based on corruption and illegality is short-lived and ultimately detrimental to long-term prosperity. Therefore, it is crucial for firms to prioritize ethical business practices and build relationships with governments that prioritize transparency and accountability.Social implicationsGiven the detrimental impact of corruption on economic progress, it is crucial for Africa policy-makers to prioritize reforms aimed at reducing its adverse effect. By implementing ethical and transparent business practices, countries can attract more investment and promote economic growth.Originality/valueThis study contributes to the existing literature on the passive form of political connectivity/activity and to what extend corruption level affect the political activities of firms.
Enhancing supply chain resilience in SMEs: the role of business and political ties
Authors: Alghababsheh Mohammad 
Published: May 2023

PurposeThe COVID-19 pandemic outbreak has created disruptions across the supply chain that are beyond the resources of small and medium-sized enterprises (SMEs) to effectively deal with. This study aims to examine the idea that top managers' business and political ties can play direct roles in enhancing SCR in SMEs during COVID-19 by providing access to valuable resources. The study further investigates integrative capability as an underlying mechanism through which the effects of business and political ties can be transformed into enhanced SCR.Design/methodology/approachResponses from 217 SMEs in the country of Jordan were received via an online survey. The measurement and structural models were tested using the partial least squares structural equation modelling (PLS-SEM) technique.FindingsThe study found that business and political ties are positively related to SCR. However, integrative capability fully mediates the relationship between business ties and SCR, whereas it partially mediates the relationship between political ties and SCR.Research limitations/implicationsThe study examined only the direct and indirect impacts of business and political ties on SCR. It could be extended by exploring the conditions under which they influence SCR.Originality/valueThe study explicates the role of top managers' business and political ties on improving SCR in a developing country context. It further examines the mediating role of integrative capability in the relationships between business and political ties and SCR.
Multi-fidelity surrogate-based optimization for microfluidic concentration gradient generator design
Authors: Yang Haizhou , Hong Seong Hyeon , Qian Yu , Wang Yi 
Published: May 2023

PurposeThis paper aims to present a multi-fidelity surrogate-based optimization (MFSBO) method for computationally accurate and efficient design of microfluidic concentration gradient generators (µCGGs).Design/methodology/approachCokriging-based multi-fidelity surrogate model (MFSM) is constructed to combine data with varying fidelities and computational costs to accelerate the optimization process and improve design accuracy. An adaptive sampling approach based on parallel infill of multiple low-fidelity (LF) samples without notably adding computation burden is developed. The proposed optimization framework is compared with a surrogate-based optimization (SBO) method that relies on data from a single source, and a conventional multi-fidelity adaptive sampling and optimization method in terms of the convergence rate and design accuracy.FindingsThe results demonstrate that proposed MFSBO method allows faster convergence and better designs than SBO for all case studies with 49% more reduction in the objective function value on average. It is also found that parallel infill (MFSBO-4) with four LF samples, enables more robust, efficient and accurate designs than conventional multi-fidelity infill (MFSBO-1) that only adopts one LF sample during each iteration for more complex optimization problems.Originality/valueA MFSM based on cokriging method is constructed to utilize data with varying fidelities, accuracies and computational costs for µCGG design. A parallel infill strategy based on multiple infill criteria is developed to accelerate the convergence and improve the design accuracy of optimization. The proposed methodology is proved to be a feasible method for µCGG design and its computational efficiency is verified.