bluuebunny/crossref_metadata_2025_split huggingface dataset:
GLP-1(9-36) mediates the glucagonostatic effect of GLP-1 by promiscuous activation of the glucagon receptor
Authors: Guida Claudia , Miranda Caroline , Asterholm Ingrid Wernstedt , Basco Davide , Benrick Anna , Chanclon Belen , Chibalina Margarita V. , Harris Matthew , Kellard Joely , McCulloch Laura J. , Real Joana , Rorsman Nils J.G. , Yeung Ho Yan , Reimann Frank , Shigeto Makoto , Clark Anne , Thorens Bernard , Rorsman Patrik , Ladds Graham , Ramracheya Reshma 
Published: October 2019

SummaryThe incretin hormone glucagon-like peptide 1(7-36) (GLP-1(7-36)) stimulates insulin and inhibits glucagon secretion. The mechanisms by which GLP-1 suppresses glucagon release are unclear as glucagon-secreting α-cells express GLP-1 receptors (GLP-1Rs) at very low levels. Here, we examine the underlying mechanisms. We find that both GLP-1(7-36) and its degradation product GLP-1(9-36) inhibit glucagon secretion at physiological (pM) concentrations. Whereas the effect of GLP-1(7-36) is sensitive to PKA inhibition, GLP-1(9-36) exerts its effect by a PKA-independent mechanism sensitive to pretreatment with pertussis. The glucagonostatic effects of both GLP-1(7-36) and (9-36) are retained in islets fromGlp1rknockout mice but only GLP-1(9-36) remains glucagonostatic in the presence of the DPP-4 (the peptidase catalyzing the formation of GLP-1(9-36)) inhibitor sitagliptin. Glucagon receptor (GCGR) antagonism specifically prevents the inhibitory effects of GLP-1(9-36) whilst not affecting that of GLP-1(7-36). We conclude that GLP-1(7-36) and GLP-1(9-36) regulate glucagon secretion via interaction with GLP-1R and GCGR, respectively.HighlightsGLP-1(7-36) and GLP-1(9-36) inhibit glucagon secretion from alpha-cellsGLP-1(7-36) and (9-36) retain glucagonostatic effect in Glp1r-/-isletsGLP-1(7-36) and (9-36) activate distinct signal transduction mechanismsGLP-1(7-36) acts via GLP-1R and GLP-1(9-36) via GCGR
Dynamics of genetic variation in Transcription Factors and its implications for the evolution of regulatory networks in Bacteria
Authors: Ali Farhan , Narain Seshasayee Aswin Sai 
Published: October 2019

AbstractThe evolution of bacterial regulatory networks has largely been explained at macroevolutionary scales through lateral gene transfer and gene duplication. Transcription factors (TF) have been found to be less conserved across species than their target genes (TG). This would be expected if TFs accumulate mutations faster than TGs. This hypothesis is supported by several lab evolution studies which found TFs, especially global regulators, to be frequently mutated. Despite these studies, the contribution of point mutations in TFs to the evolution of regulatory network is poorly understood. We tested if TFs show greater genetic variation than their TGs using whole-genome sequencing data from a large collection of E coli isolates. We found TFs to be less diverse, across natural isolates, due to their regulatory roles. TFs were enriched in mutations in multiple adaptive lab evolution studies but not in mutation accumulation. However, over long-term evolution, relative frequency of mutations in TFs showed a gradual decay after a rapid initial burst. Our results suggest that point mutations, conferring large-scale expression changes, may drive the early stages of adaptation but gene regulation is subjected to stronger purifying selection post adaptation.
Symbolic Information Flow Measurement (SIFM): A Software for Measurement of Information Flow Using Symbolic Analysis
Authors: Nebiu Dhurata , Kamberaj Hiqmet 
Published: October 2019

AbstractSymbolic Information Flow Measurement software is used to compute the information flow between different components of a dynamical system or different dynamical systems using symbolic transfer entropy. Here, the time series represents the time evolution trajectory of a component of the dynamical system. Different methods are used to perform a symbolic analysis of the time series based on the coarse-graining approach by computing the so-called embedding parameters. Information flow is measured in terms of the so-called average symbolic transfer entropy and local symbolic transfer entropy. Besides, a new measure of mutual information is introduced based on the symbolic analysis, called symbolic mutual information.
Angular momentum regulation may dictate the slip severity in young adults
Authors: Nazifi Mohammad Moein , Beschorner Kurt , Hur Pilwon 
Published: October 2019

AbstractFalls vastly affect the economy and the society with their high cost, injuries, and mortalities. Slipping is the main trigger for falling. Yet, individuals differ in their ability to recover from slips. Mild slippers can accommodate slips without falling, whereas severe slippers indicate inadequate or slow pre-or post-slip control that make them more prone to fall after a slip. Knowing the discrepancies in different kinematic and kinetic variables in mild and severe slippers helps pinpoint the adverse control responsible for severe slipping and falling. This study examined Center of Mass (COM) height, sagittal angular momentum (H), upper body kinematics, and the duration of single/double phase in mild and severe slippers for both normal walking and slipping to identify their differences and possible relationships. Possible causality of such relationships were also studied by observing the time-lead of the deviations. Twenty healthy young adults walked in a long walkway for several trials and were slipped unexpectedly. They were classified into mild and severe slippers based on their slip severity. No inter-group differences were observed in the upper extremity kinematics. It was found that mild and severe slippers do not differ in the studied variables during normal gait; however, they do show significant differences through slipping. Compared to mild slippers, sever slippers lowered their COM height following a slip, presented higherH, and shortened their single support phase (p-value<0.05 for all). Based on the time-lead observed inHover all other variables suggests that angular momentum may be the key variable in controlling slips.
Mutational load and the functional fraction of the human genome
Authors: Galeota-Sprung Benjamin , Sniegowski Paul , Ewens Warren 
Published: October 2019

AbstractThe fraction of the human genome that is functional is a question of both evolutionary and practical importance. Studies of sequence divergence have suggested that the functional fraction of the human genome is likely to be no more than ∼15%. In contrast, the ENCODE project, a systematic effort to map regions of transcription, transcription factor association, chromatin structure, and histone modification, assigned function to 80% of the human genome. In this paper we examine whether and how an analysis based on mutational load might set a limit on the functional fraction. In order to do so, we characterize the distribution of fitness of a large, finite, diploid population at mutation-selection equilibrium. In particular, if mean fitness is ∼1, the fitness of the fittest individual likely to occur cannot be unreasonably high. We find that at equilibrium, the distribution of log fitness has variance nus, where u is the per-base deleterious mutation rate, n is the number of functional sites (and hence incorporates the functional fraction f), and s is the selection coefficient of deleterious mutations. In a large (N = 109) reproducing population, the fitness of the fittest individual likely to exist is . These results apply to both additive and recessive fitness schemes. Our approach is different from previous work that compared mean fitness at mutation-selection equilibrium to the fitness of an individual who has no deleterious mutations; we show that such an individual is exceedingly unlikely to exist. We find that the functional fraction is not very likely to be limited substantially by mutational load, and that any such limit, if it exists, depends strongly on the selection coefficients of new deleterious mutations.
Comparative single-cell transcriptomics of complete insect nervous systems
Authors: Cocanougher Benjamin T. , Wittenbach Jason D. , Long Xi Salina , Kohn Andrea B. , Norekian Tigran P. , Yan Jinyao , Colonell Jennifer , Masson Jean-Baptiste , Truman James W. , Cardona Albert , Turaga Srinivas C. , Singer Robert H. , Moroz Leonid L. , Zlatic Marta 
Published: October 2019

SummaryMolecular profiles of neurons influence information processing, but bridging the gap between genes, circuits, and behavior has been very difficult. Furthermore, the behavioral state of an animal continuously changes across development and as a result of sensory experience. How behavioral state influences molecular cell state is poorly understood. Here we present a complete atlas of theDrosophilalarval central nervous system composed of over 200,000 single cells across four developmental stages. We developpolyseq, a python package, to perform cell-type analyses. We use single-molecule RNA-FISH to validate our scRNAseq findings. To investigate how internal state affects cell state, we optogentically altered internal state with high-throughput behavior protocols designed to mimic wasp sting and over activation of the memory system. We found nervous system-wide and neuron-specific gene expression changes. This resource is valuable for developmental biology and neuroscience, and it advances our understanding of how genes, neurons, and circuits generate behavior.
Efficient approaches for large scale GWAS studies with genotype uncertainty
Authors: Jørsboe Emil , Albrechtsen Anders 
Published: October 2019

1AbstractIntroductionAssociation studies using genetic data from SNP-chip based imputation or low depth sequencing data provide a cost efficient design for large scale studies. However, these approaches provide genetic data with uncertainty of the observed genotypes. Here we explore association methods that can be applied to data where the genotype is not directly observed. We investigate how using different priors when estimating genotype probabilities affects the association results in different scenarios such as studies with population structure and varying depth sequencing data. We also suggest a method (ANGSD-asso) that is computational feasible for analysing large scale low depth sequencing data sets, such as can be generated by the non-invasive prenatal testing (NIPT) with low-pass sequencing.MethodsANGSD-asso’s EM model works by modelling the unobserved genotype as a latent variable in a generalised linear model framework. The software is implemented in C/C++ and can be run multi-threaded enabling the analysis of big data sets. ANGSD-asso is based on genotype probabilities, they can be estimated in various ways, such as using the sample allele frequency as a prior, using the individual allele frequencies as a prior or using haplotype frequencies from haplotype imputation. Using simulations of sequencing data we explore how genotype probability based method compares to using genetic dosages in large association studies with genotype uncertainty.Results & DiscussionOur simulations show that in a structured population using the individual allele frequency prior has better power than the sample allele frequency. If there is a correlation between genotype uncertainty and phenotype, then the individual allele frequency prior also helps control the false positive rate. In the absence of population structure the sample allele frequency prior and the individual allele frequency prior perform similarly. In scenarios with sequencing depth and phenotype correlation ANGSD-asso’s EM model has better statistical power and less bias compared to using dosages. Lastly when adding additional covariates to the linear model ANGSD-asso’s EM model has more statistical power and provides less biased effect sizes than other methods that accommodate genotype uncertainly, while also being much faster. This makes it possible to properly account for genotype uncertainty in large scale association studies.
Decoding age-related changes in the spatiotemporal neural processing of speech using machine learning
Authors: Mahmud Md Sultan , Ahmed Faruk , Al-Fahad Rakib , Moinuddin Kazi Ashraf , Yeasin Mohammed , Alain Claude , Bidelman Gavin M. 
Published: October 2019

ABSTRACTSpeech comprehension in noisy environments depends on complex interactions between sensory and cognitive systems. In older adults, such interactions may be affected, especially in those individuals who have more severe age-related hearing loss. Using a data-driven approach, we assessed the temporal (when in time) and spatial (where in the brain) characteristics of the cortex’s speech-evoked response that distinguish older adults with or without mild hearing loss. We used source montage to model scalp-recorded during a phoneme discrimination task conducted under clear and noise-degraded conditions. We applied machine learning analyses (stability selection and control) to choose features of the speech-evoked response that are consistent over a range of model parameters and support vector machine (SVM) classification to investigate the time course and brain regions that segregate groups and speech clarity. Whole-brain data analysis revealed a classification accuracy of 82.03% [area under the curve (AUC)=81.18%; F1-score 82.00%], distinguishing groups within ∼50 ms after speech onset (i.e., as early as the P1 wave).We observed lower accuracy of 78.39% [AUC=78.74%; F1-score=79.00%] and delayed classification performance when the speech token were embedded in noise, with group segregation at 60 ms. Separate analysis using left (LH) and right hemisphere (RH) regions showed that LH speech activity was better at distinguishing hearing groups than activity measured over the RH. Moreover, stability selection analysis identified 13 brain regions (among 1428 total spatiotemporal features from 68 regions) where source activity segregated groups with >80% accuracy (clear speech); whereas 15 regions were critical for noise-degraded speech to achieve a comparable level of group segregation (76% accuracy). Our results identify two core neural networks associated with complex speech perception in older adults and confirm a larger number of neural regions, particularly in RH and frontal lobe, are active when processing degraded speech information.
Functional Maturation of Human iPSC-based Cardiac Microphysiological Systems with Tunable Electroconductive Decellularized Extracellular Matrices
Authors: Tsui Jonathan H. , Leonard Andrea , Camp Nathan D. , Long Joseph T. , Nawas Zeid Y. , Chavanachat Rakchanok , Choi Jong Seob , Wolf-Yadlin Alejandro , Murry Charles E. , Sniadecki Nathan J. , Kim Deok-Ho 
Published: October 2019

AbstractHuman induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) offer tremendous potential for use in engineering human tissues for regenerative therapy and drug screening. However, differentiated cardiomyocytes are phenotypically immature, reducing assay reliability when translatingin vitroresults to clinical studies and precluding hiPSC-derived cardiac tissues from therapeutic usein vivo. To address this, we have developed hybrid hydrogels comprised of decellularized porcine myocardial extracellular matrix (dECM) and reduced graphene oxide (rGO) to provide a more instructive microenvironment for proper cellular and tissue development. A tissue-specific protein profile was preserved post-decellularization, and through the modulation of rGO content and degree of reduction, the mechanical and electrical properties of the hydrogels could be tuned. Engineered heart tissues (EHTs) generated using dECM-rGO hydrogel scaffolds and hiPSC-derived cardiomyocytes exhibited significantly increased twitch forces at 14 days of culture and had increased the expression of genes that regulate contractile function. Similar improvements in various aspects of electrophysiological function, such as calcium-handling, action potential duration, and conduction velocity, were also induced by the hybrid biomaterial. We also demonstrate that dECM-rGO hydrogels can be used as a bioink to print cardiac tissues in a high-throughput manner, and these tissues were utilized to assess the proarrhythmic potential of cisapride. Action potential prolongation and beat interval irregularities was observed in dECM-rGO tissues at clinical doses of cisapride, indicating that the enhanced maturation of these tissues corresponded well with a capability to produce physiologically relevant drug responses.
Surviving in high stress environments: Physiological and molecular responses of lobe coral indicate nearshore adaptations to anthropogenic stressors
Authors: Tisthammer Kaho H , Timmins-Schiffman Emma , Seneca Francois O , Nunn Brook L , Richmond Robert H 
Published: October 2019

ABSTRACTCorals in nearshore marine environments are increasingly exposed to reduced water quality, which is the primary local threat to Hawaiian coral reefs. It is unclear if corals surviving in such conditions have adapted to withstand sedimentation, pollutants, and other environmental stressors. Lobe coral populations from Maunalua Bay, Hawaii showed clear genetic differentiation between the ’polluted, high-stress’ nearshore site and the ’lower-stress’ offshore site. To understand the driving force of the observed genetic partitioning, reciprocal transplant and common-garden experiments were conducted to assess phenotypic differences between these two populations. Physiological responses were significantly different between the populations, revealing more stress-resilient traits in the nearshore corals. Changes in protein profiles between the two populations highlighted the inherent differences in the cellular metabolic processes and activities; nearshore corals did not significantly alter their proteome between the sites, while offshore corals responded to nearshore transplantation with increased abundances of proteins associated with detoxification, antioxidant defense, and regulation of cellular metabolic processes. The response differences across multiple phenotypes between the populations suggest local adaptation of nearshore corals to reduced water quality. Our results provide insight into coral’s adaptive potential and its underlying processes, and reveal potential protein biomarkers that could be used to predict resiliency.
Overnight caloric restriction prior to cardiac arrest and resuscitation leads to improved survival and neurological outcome in a rodent model
Authors: Azadian Matine , Tian Guilian , Bazrafkan Afsheen , Maki Niki , Rafi Masih , Desai Monica , Otarola Ieeshiah , Zaher Shuhab , Khan Ashar , Suri Yusuf , Wang Minwei , Steward Oswald , Akbari Yama 
Published: October 2019

AbstractWhile interest toward caloric restriction (CR) in various models of brain injury has increased in recent decades, studies have predominantly focused on the benefits of chronic or intermittent CR. The effects of ultra-short, including overnight, CR on acute ischemic brain injury, however, are not well studied. Here, we show that overnight caloric restriction (75% over 14 h) prior to asphyxial cardiac arrest and resuscitation (CA) improves survival and neurological recovery, including complete prevention of neurodegeneration in multiple regions of the brain. We also show that overnight CR normalizes stress-induced hyperglycemia, while significantly decreasing insulin and glucagon production and increasing corticosterone and ketone body production. The benefits seen with ultra-short CR appear independent of Sirtuin 1 (SIRT-1) and brain-derived neurotrophic factor (BDNF) expression, which have been strongly linked to neuroprotective benefits seen in chronic CR. Further exploration into the precise mechanisms involved in ultra-short CR may have significant translational implications. These findings are also of importance to basic sciences research as we demonstrate that minor, often-overlooked alterations to pre-experimental dietary procedures can significantly affect results, and by extension, research homogeneity and reproducibility, especially in acute ischemic brain injury models.
The genome of Mekong tiger perch (Datnioides undecimradiatus) provides insights into the phylogenic position of Lobotiformes and biological conservation
Authors: Sun Shuai , Wang Yue , Du Xiao , Li Lei , Hong Xiaoning , Huang Xiaoyun , Zhang He , Zhang Mengqi , Fan Guangyi , Liu Xin , Liu Shanshan 
Published: October 2019

AbstractMekong tiger perch (Datnioides undecimradiatus) is one ornamental fish and a vulnerable species, which belongs to order Lobotiformes. Here, we report a ∼595 Mb D. undecimradiatus genome, which is the first whole genome sequence in the order Lobotiformes. Based on this genome, the phylogenetic tree analysis suggested that Lobotiformes and Sciaenidae are closer than Tetraodontiformes, resolving a long-time dispute. We depicted the pigment synthesis pathway in Mekong tiger perch and result confirmed that this pathway had evolved from the shared whole genome duplication. We also estimated the demographic history of Mekong tiger perch, showing the effective population size suffered a continuous reduction possibly related to the contraction of immune-related genes. Our study provided a reference genome resource for the Lobotiformes, as well as insights into the phylogeny of Eupercaria and biological conservation.
Detection of AmpC β-lactamases in Escherichia coli using different screening agars
Authors: den Drijver Evert , Verweij Jaco J. , Verhulst Carlo , Soer Joke , Veldman Kees , Rossen John W. , Kooistra-Smid A.M.D. (Mirjam) , Kluytmans van den Bergh Marjolein F. Q. , Kluytmans Jan A. J. W. 
Published: October 2019

AbstractThe aim of this study was to determine the performance of both cefotaxime and ceftazidime containing agars on the specificity and sensitivity for chromosomal AmpC-hyperproducing and plasmid AmpC harboring Escherichia coli compared to ESBL-producing E. coli and E. coli without ESBL, pAmpC or cAmpC hyperproduction. Second, we evaluated the influence of adding cefoxitin to these agars for detection of both chromosomal AmpC-hyperproducing and plasmid AmpC harboring E. coli.Four different homemade screening agars with cefotaxime (1mg/L), ceftazidime (1mg/L), cefotaxime (1mg/L) with cefoxitin (8mg/L), and ceftazidime (1mg/L) with cefoxitin (8mg/L) were compared to each other for the identification of AmpC producing E. coli. A total of 40 isolates with plasmid encoded AmpC β-lactamases, 40 isolates with alterations in the promoter/attenuator region of the AmpC gene leading to hyperproduction of the β-lactamase, 40 isolates with ESBL genes and 39 isolates lacking both a AmpC and ESBL genotype were used to test the four agars.The sensitivity and specificity were 100% (95% confidence interval (95% CI) 96.1% to 100%) and 48.1% (95% CI 38.6%-60.2%), respectively, for the cefotaxime agar; 100% (95% CI 96.1% to 100%) and 49.41% (95% CI 39.8%-61.4%), respectively, for the ceftazidime agar; 96.3% (95% CI 89.1% to 99.2%) and 77.2% (95% CI 66.7%-85.2%) respectively, for the cefotaxime with cefoxitin agar; 98.8% (95% CI) 92.6% to 99.6%) and 81.0% (95% CI 70.9%-88.3%) respectively, for the ceftazidime agar with cefoxitin. The main reason for false-positive results were ESBL-harboring strains that grew on various agars; therefore, the specificity of each agar reported here was influenced mainly by the proportion of ESBL isolates tested. In conclusion addition of cefoxitin to cefotaxime and ceftazidime containing agars had little influence on sensitivity, but increased specificity for the detection of AmpC in E. coli.