bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genome-wide coancestry reveals details of ancient and recent male-driven reticulation in baboons
Authors: Sørensen Erik F. , Harris R. Alan , Zhang Liye , Raveendran Muthuswamy , Kuderna Lukas F. K. , Walker Jerilyn A. , Storer Jessica M. , Kuhlwilm Martin , Fontsere Claudia , Seshadri Lakshmi , Bergey Christina M. , Burrell Andrew S. , Bergmann Juraj , Phillips-Conroy Jane E. , Shiferaw Fekadu , Chiou Kenneth L. , Chuma Idrissa S. , Keyyu Julius D. , Fischer Julia , Gingras Marie-Claude , Salvi Sejal , Doddapaneni Harshavardhan , Schierup Mikkel H. , Batzer Mark A. , Jolly Clifford J. , Knauf Sascha , Zinner Dietmar , Farh Kyle K.-H. , Marques-Bonet Tomas , Munch Kasper , Roos Christian , Rogers Jeffrey 
Published: May 2023

AbstractBaboons (genusPapio) are a morphologically and behaviorally diverse clade of catarrhine monkeys that have experienced hybridization between phenotypically and genetically distinct phylogenetic species. We used high coverage whole genome sequences from 225 wild baboons representing 19 geographic localities to investigate population genomics and inter-species gene flow. Our analyses provide an expanded picture of evolutionary reticulation among species and reveal novel patterns of population structure within and among species, including differential admixture among conspecific populations. We describe the first example of a baboon population with a genetic composition that is derived from three distinct lineages. The results reveal processes, both ancient and recent, that produced the observed mismatch between phylogenetic relationships based on matrilineal, patrilineal, and biparental inheritance. We also identified several candidate genes that may contribute to species-specific phenotypes.One-Sentence SummaryGenomic data for 225 baboons reveal novel sites of inter-species gene flow and local effects due to differences in admixture.
High-content microscopy reveals a morphological signature of bortezomib resistance
Authors: Kelley M.E. , Berman A.Y. , Stirling D.R. , Cimini B.A. , Han Y. , Singh S. , Carpenter A.E. , Kapoor T.M. , Way G.P. 
Published: May 2023

ABSTRACTDrug resistance is a challenge in anticancer therapy, particularly with targeted therapeutics and cytotoxic compounds. In many cases, cancers can be resistant to the drug prior to exposure, i.e., possess intrinsic drug resistance. However, we lack target-independent methods to anticipate resistance in cancer cell lines or characterize intrinsic drug resistance without a priori knowledge of its cause. We hypothesized that cell morphology could provide an unbiased readout of drug sensitivity prior to treatment. We therefore isolated clonal cell lines that were either sensitive or resistant to bortezomib, a well-characterized proteasome inhibitor and anticancer drug to which many cancer cells possess intrinsic resistance. We then measured high-dimensional single-cell morphology profiles using Cell Painting, a high-content microscopy assay. Our imaging- and computation-based profiling pipeline identified morphological features typically different between resistant and sensitive clones. These features were compiled to generate a morphological signature of bortezomib resistance, which correctly predicted the bortezomib treatment response in seven of ten cell lines not included in the training dataset. This signature of resistance was specific to bortezomib over other drugs targeting the ubiquitin-proteasome system. Our results provide evidence that intrinsic morphological features of drug resistance exist and establish a framework for their identification.
A leaky integrate-and-fire computational model based on the connectome of the entire adultDrosophilabrain reveals insights into sensorimotor processing
Authors: Shiu Philip K. , Sterne Gabriella R. , Spiller Nico , Franconville Romain , Sandoval Andrea , Zhou Joie , Simha Neha , Kang Chan Hyuk , Yu Seongbong , Kim Jinseop S. , Dorkenwald Sven , Matsliah Arie , Schlegel Philipp , Yu Szi-chieh , McKellar Claire E. , Sterling Amy , Costa Marta , Eichler Katharina , Jefferis Gregory S.X.E. , Murthy Mala , Bates Alexander Shakeel , Eckstein Nils , Funke Jan , Bidaye Salil S. , Hampel Stefanie , Seeds Andrew M. , Scott Kristin 
Published: May 2023

AbstractThe forthcoming assembly of the adultDrosophila melanogastercentral brain connectome, containing over 125,000 neurons and 50 million synaptic connections, provides a template for examining sensory processing throughout the brain. Here, we create a leaky integrate-and-fire computational model of the entireDrosophilabrain, based on neural connectivity and neurotransmitter identity, to study circuit properties of feeding and grooming behaviors. We show that activation of sugar-sensing or water-sensing gustatory neurons in the computational model accurately predicts neurons that respond to tastes and are required for feeding initiation. Computational activation of neurons in the feeding region of theDrosophilabrain predicts those that elicit motor neuron firing, a testable hypothesis that we validate by optogenetic activation and behavioral studies. Moreover, computational activation of different classes of gustatory neurons makes accurate predictions of how multiple taste modalities interact, providing circuit-level insight into aversive and appetitive taste processing. Our computational model predicts that the sugar and water pathways form a partially shared appetitive feeding initiation pathway, which our calcium imaging and behavioral experiments confirm. Additionally, we applied this model to mechanosensory circuits and found that computational activation of mechanosensory neurons predicts activation of a small set of neurons comprising the antennal grooming circuit that do not overlap with gustatory circuits, and accurately describes the circuit response upon activation of different mechanosensory subtypes. Our results demonstrate that modeling brain circuits purely from connectivity and predicted neurotransmitter identity generates experimentally testable hypotheses and can accurately describe complete sensorimotor transformations.
Syndecan-4 is the Key Proteoglycan Mediating LPS-induced Sepsis-associated Lung Injury
Authors: Zhu Zhipeng , Ling Xiaoyan , Zhou Hongmei , Xie Junran 
Published: May 2023

AbstractThe occurrence of acute sepsis-associated lung injury (ALI) is closely related to vascular endothelial cell dysfunction, but the exact isoform of the functional syndecans (SDCs) located in the inner endothelial membrane of blood vessels and involved in regulating inflammation is not clear. The present study aimed to clarify whether SDC2 and/or 4 is involved in the inflammation process.Using the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) were extracted and analyzed. A bioinformatic analysis was conducted using R language, gene ontology (GO), and the Kyoto Encyclopedia of Genes and Genomes (KEGG) with the aim of predicting SDC2 and 4 expression levels. Subsequently, the expression profiles of these two proteins were examined after construction of a sepsis-associated ALI mmodel was constructed in both human lung vascular endothelial cells (HLVEC) and animal models under inflammatory conditions. Eventually, the transcription factors (TF) of SDC2/4 were predicted based on the available dataset, and their involvement in septic inflammation was indirectly assessed. The GSE 5883 microarray gene-chip data profile was found to be suitable for analyzing lipopolysaccharide (LPS)-induced endothelial inflammatory injury. After analyzing the DEGs, 224 and 102 genes were found to be up- and down-regulated, respectively. All DEGs were involved in modulating receptor ligand and signaling receptor activator activities, cytokine receptor binding in biological processes, such as responses to lipopolysaccharide (LPS) and molecules from bacterial origins, positive regulation of cell adhesion, and other functions. In the case of localization of cellular components, most DEGs were enriched in cytoplasmic ribonucleoprotein granules, transcription regulator complex, and membrane rafts and were involved in the tumor necrosis factor (TNF) signaling and cytokine receptor interaction pathways. When compared with the control group, SDC4 gene expression in the LPS group increased by 4.5-fold, and comparable results were found in terms of SDC2 gene expression. From an experimental aspect, SDC4 was found to be markedly up-regulated with respect to mRNA and protein expression levels in response to inflammatory injury; moreover, down-regulation of SDC4 could severely exacerbate inflammatory responses either in in vivo or in vitro models. Altogether, SDC4, rather than SDC2, was found to be involved in LPS-induced sepsis-associated ALI.
Host-Microbiome Associations in Saliva Predict COVID-19 Severity
Authors: Alqedari Hend , Altabtbaei Khaled , Espinoza Josh L. , Bin-Hasan Saadoun , Alghounaim Mohammad , Alawady Abdullah , Altabtabae Abdullah , AlJamaan Sarah , Devarajan Sriraman , AlShammari Tahreer , Ben Eid Mohammed , Matsuoka Michele , Jang Hyesun , Dupont Christopher L. , Freire Marcelo 
Published: May 2023

AbstractEstablished evidence indicates that oral microbiota plays a crucial role in modulating host immune responses to viral infection. Following Severe Acute Respiratory Syndrome Coronavirus 2 – SARS-CoV-2 – there are coordinated microbiome and inflammatory responses within the mucosal and systemic compartments that are unknown. The specific roles that the oral microbiota and inflammatory cytokines play in the pathogenesis of COVID-19 are yet to be explored. We evaluated the relationships between the salivary microbiome and host parameters in different groups of COVID-19 severity based on their Oxygen requirement. Saliva and blood samples (n = 80) were collected from COVID-19 and from non-infected individuals. We characterized the oral microbiomes using 16S ribosomal RNA gene sequencing and evaluated saliva and serum cytokines using Luminex multiplex analysis. Alpha diversity of the salivary microbial community was negatively associated with COVID-19 severity. Integrated cytokine evaluations of saliva and serum showed that the oral host response was distinct from the systemic response. The hierarchical classification of COVID-19 status and respiratory severity using multiple modalities separately (i.e., microbiome, salivary cytokines, and systemic cytokines) and simultaneously (i.e., multi-modal perturbation analyses) revealed that the microbiome perturbation analysis was the most informative for predicting COVID-19 status and severity, followed by the multi-modal. Our findings suggest that oral microbiome and salivary cytokines may be predictive of COVID-19 status and severity, whereas atypical local mucosal immune suppression and systemic hyperinflammation provide new cues to understand the pathogenesis in immunologically naïve populations.Significance StatementThe oral mucosa is one of the first sites encountered by bacterial and viral infections, including SARS-CoV-2. It consists of a primary barrier occupied by a commensal oral microbiome. The primary function of this barrier is to modulate immunity and provide protection against invading infection. The occupying commensal microbiome is an essential component that influences the immune system’s function and homeostasis. The present study showed that the host oral immune response performs unique functions in response to SARS-CoV-2 when compared to systemic responses during the acute phase. We also demonstrated that there is a link between oral microbiome diversity and COVID-19 severity. Additionally, the salivary microbiome was predictive of not only disease status but also severity.
Endothelial specific reduction in Arf6 impairs insulin-stimulated vasodilation and skeletal muscle blood flow resulting in systemic insulin resistance
Authors: Islam Md Torikul , Cai Jinjin , Allen Shanena , Moreno Denisse G , Bloom Samuel I , Bramwell R Colton , Mitton Jonathan , Horn Andrew G , Zhu Weiquan , Donato Anthony J , Holland William L , Lesniewski Lisa A 
Published: May 2023

AbstractBackgroundMuch of what we know about insulin resistance is based on studies from metabolically active tissues such as liver, adipose tissue, and skeletal muscle. Emerging evidence suggests that the vascular endothelium plays a crucial role in systemic insulin resistance, however, the underlying mechanisms remain incompletely understood. ADP ribosylation factor 6 (Arf6) is a small GTPase that plays a critical role in endothelial cell (EC) function. Here, we tested the hypothesis that the deletion of endothelial Arf6 will result in systemic insulin resistance.MethodsWe used mouse models of constitutive EC-specific Arf6 deletion (Arf6f/-Tie2Cre) and tamoxifen inducible Arf6 knockout (Arf6f/fCdh5Cre). Endothelium-dependent vasodilation was assessed using pressure myography. Metabolic function was assessed using a battery of metabolic assessments including glucose- and insulin-tolerance tests and hyperinsulinemic-euglycemic clamps. A fluorescence microsphere-based technique was used to measure tissue blood flow. Intravital microscopy was used to assess skeletal muscle capillary density.ResultsEndothelial Arf6 deletion impaired insulin-stimulated vasodilation in white adipose tissue (WAT) and skeletal muscle feed arteries. The impairment in vasodilation was primarily due to attenuated insulin-stimulated nitric oxide (NO) bioavailability but independent of altered acetylcholine- or sodium nitroprusside-mediated vasodilation. In vitro Arf6 inhibition resulted in suppressed insulin stimulated phosphorylation of Akt and endothelial NO synthase. Endothelial cell-specific deletion of Arf6 also resulted in systematic insulin resistance in normal chow fed mice and glucose intolerance in high fat diet fed obese mice. The underlying mechanisms of glucose intolerance were reductions in insulin-stimulated blood flow and glucose uptake in the skeletal muscle and were independent of changes in capillary density or vascular permeability.ConclusionResults from this study support the conclusion that endothelial Arf6 signaling is essential for maintaining insulin sensitivity. Reduced expression of endothelial Arf6 impairs insulin-mediated vasodilation and results in systemic insulin resistance. These results have therapeutic implications for diseases that are associated with endothelial cell dysfunction and insulin resistance such as diabetes.
Role of sociodemographic, clinical, behavioral, and molecular factors in precision prevention of type 2 diabetes: a systematic review
Authors: Bodhini Dhanasekaran , Morton Robert W. , Santhakumar Vanessa , Nakabuye Mariam , Pomares-Millan Hugo , Clemmensen Christoffer , Fitzpatrick Stephanie L. , Guasch-Ferre Marta , Pankow James S. , Ried-Larsen Mathias , Franks Paul W. ,   ADA/EASD Precision Medicine in Diabetes Initiative, Tobias Deirdre K. , Merino Jordi , Mohan Viswanathan , Loos Ruth J.F. 
Published: May 2023

AbstractThe variability in the effectiveness of type 2 diabetes (T2D) preventive interventions highlights the potential to identify the factors that determine treatment responses and those that would benefit the most from a given intervention. We conducted a systematic review to synthesize the evidence to support whether sociodemographic, clinical, behavioral, and molecular characteristics modify the efficacy of dietary or lifestyle interventions to prevent T2D. Among the 80 publications that met our criteria for inclusion, the evidence was low to very low to attribute variability in intervention effectiveness to individual characteristics such as age, sex, BMI, race/ethnicity, socioeconomic status, baseline behavioral factors, or genetic predisposition. We found evidence, albeit low certainty, to support conclusions that those with poorer health status, particularly those with prediabetes at baseline, tend to benefit more from T2D prevention strategies compared to healthier counterparts. Our synthesis highlights the need for purposefully designed clinical trials to inform whether individual factors influence the success of T2D prevention strategies.
Autophagy is a cell-intrinsic driver of neural stem cell quiescence in hippocampal dentate gyrus development
Authors: Calatayud-Baselga Isabel , Casares-Crespo Lucía , Franch-Ibáñez Carmina , Guijarro-Nuez José , Sanz Pascual , Mira Helena 
Published: May 2023

AbstractNeurogenesis in the adult mammalian brain relies on the lifelong persistence of quiescent neural stem cell (NSC) reservoirs. Little is known about the mechanisms that lead to the initial establishment of NSC quiescence during development. Here, we show that protein aggregates and autophagy machinery components accumulate in quiescent NSCs and that pharmacological blockade of autophagy disrupts quiescence. Conversely, increasing autophagy through AMPK/ULK1 activation instructs the acquisition of the quiescent state. Selective ablation ofAtg7, a critical gene for autophagosome formation, in hippocampal radial-glia like NSCs at early and late postnatal stages compromises the initial acquisition and maintenance of quiescence during the formation of the dentate gyrus SGZ niche. Therefore, we demonstrate that autophagy is cell-intrinsically required to establish radial glia-like NSC quiescence during hippocampal development. Our results uncover a fundamental role of autophagy in the transition of developmental NSCs into their dormant adult form, paving the way for studies directed at further understanding the mechanisms of stem cell niche formation and maintenance in the mammalian brain.
ICT adoption and youth employment in Nigeria's agricultural sector
Authors: Osabohien Romanus 
Published: May 2023

PurposeThis paper argues that through information and communication technology (ICT) adoption, the youth will be engaged in all nodes of the agricultural value chains, thereby improving the level of employment and reducing post-harvest losses. The study examines the determinants of ICT adoption among the youth. In addition, it estimates the impact of ICT adoption on youth employment in agriculture towards the actualisation of the Sustainable Development Goals (SDGs), particularly SDG-8, to promote inclusive and sustainable economic growth, productive employment and decent work for all.Design/methodology/approachThe study engages data from Wave 4 (2018/2019) of the Living Standards Measurement Study – Integrated Surveys on Agriculture (LSMS-ISA). The logit regression, the propensity score matching and the inverse probability weighted regression adjustment are used as the estimation techniques.FindingsThe study underscores that educational level, access to electricity, location, age and income are significant determinants of ICT adoption among the youth. The findings also show that the youth's average weekly engagement in agricultural activities is about 24 h. In addition, the result reveals that ICT adoption can increase youth agricultural employment by approximately 21%. The mean difference indicates that those with access to ICT participate in agricultural activities more than their counterparts without ICT access by 29.46%.Research limitations/implicationsOne of the limitations of the study is that some of the variables such as insecurity, social protection/safety nets, that may have a significant influence on youth agricultural participation where not included in the model due to data constraint. As a recommendation for further studies, given data availability, such variables should be considered when examining youth-agricultural employment nexus.Practical implicationsSince ICT adoption has a significant impact on agricultural employment, this study proposes improved infrastructure facilities such as reliable power supply, lowering the cost of mobile and data subscriptions and better education facilities should be prioritised at all localities. This will enable the youth to embrace agriculture and help improve their socioeconomic welfare and livelihood.Originality/valueUsing Wave 4 of the LSMS-ISA, logit regression, propensity score matching and the inverse probability weighted regression adjustment, makes this study one of the very few to examine the impact of ICT adoption on agricultural employment among the youth in Nigeria. It implies that this study has provided empirical evidence and expanded the frontiers of knowledge on the extent to which ICT adoption influences youth agricultural employment in Nigeria.
Channel attention-based spatial-temporal graph neural networks for traffic prediction
Authors: Wang Bin , Gao Fanghong , Tong Le , Zhang Qian , Zhu Sulei 
Published: May 2023

PurposeTraffic flow prediction has always been a top priority of intelligent transportation systems. There are many mature methods for short-term traffic flow prediction. However, the existing methods are often insufficient in capturing long-term spatial-temporal dependencies. To predict long-term dependencies more accurately, in this paper, a new and more effective traffic flow prediction model is proposed.Design/methodology/approachThis paper proposes a new and more effective traffic flow prediction model, named channel attention-based spatial-temporal graph neural networks. A graph convolutional network is used to extract local spatial-temporal correlations, a channel attention mechanism is used to enhance the influence of nearby spatial-temporal dependencies on decision-making and a transformer mechanism is used to capture long-term dependencies.FindingsThe proposed model is applied to two common highway datasets: METR-LA collected in Los Angeles and PEMS-BAY collected in the California Bay Area. This model outperforms the other five in terms of performance on three performance metrics a popular model.Originality/value(1) Based on the spatial-temporal synchronization graph convolution module, a spatial-temporal channel attention module is designed to increase the influence of proximity dependence on decision-making by enhancing or suppressing different channels. (2) To better capture long-term dependencies, the transformer module is introduced.
Using green and ESG assets to achieve post-COVID-19 environmental sustainability
Authors: Hasan Md. Bokhtiar , Rashid Md Mamunur , Hossain Md. Naiem , Rahman Mir Mahmudur , Amin Md. Ruhul 
Published: May 2023

PurposeThis research explores the spillovers and portfolio implications for green bonds and environmental, social and governance (ESG) assets in the context of the rapidly expanding trend in green finance investments and the need for a green recovery in the post-COVID-19 era.Design/methodology/approachThis study utilizes Diebold and Yilmaz’s (2014) spillover method and portfolio strategies (hedge ratio, optimal weights and hedging effectiveness) for the data starting from February 29, 2012, to March 14, 2022.FindingsThe study’s findings reveal that the lower volatility spillover is evidenced between the green bonds and ESG stocks during tranquil and turbulent periods (e.g. COVID-19 and Russia-Ukraine War). Furthermore, hedging costs are lower both in normal times and during economic slumps. Investing the bulk of the funds in green bonds makes it possible to achieve maximum hedging effectiveness between the S&P green bond (GB) and the S&P 500 ESG.Practical implicationsBoth investors and policymakers may use these findings to make wise investment and policy choices to achieve post-COVID environmental sustainability.Originality/valueUnlike previous research, this is the first to explore the interconnectedness among the major global and country-specific green bonds and ESG assets. The major findings of this study about the lower volatility spillovers and hedging costs between green bonds and ESG assets during the tranquil and turbulent periods may contribute to the post-COVID investment portfolio for environmental sustainability.