bluuebunny/crossref_metadata_2025_split huggingface dataset:
SELVa: Simulator of Evolution with Landscape Variation
Authors: Nabieva Elena , Bazykin Georgii A. 
Published: May 2019

Organisms evolve to increase their fitness, a process that may be described as climbing the fitness landscape. However, the fitness landscape of an individual site, i.e., the vector of fitness values corresponding to different variants at this site, can change with time due to changes in the environment or substitutions at other epistatically interacting sites. We present SELVa, the Simulator of Evolution with Landscape Variation, aimed at modeling the substitution process under a changing single position fitness landscape in a set of evolving lineages forming a phylogeny of arbitrary shape. Written in Java and distributed as an executable jar file, SELVa provides a flexible framework that allows the user to choose from a number of implemented rules governing landscape change.Availabilityhttps://github.com/bazykinlab/SELVa
StereoMate: 3D Stereological Automated Analysis of Biological Structures
Authors: West Steven J. , Bonboire Damien , Bennett David L 
Published: May 2019

AbstractTissue clearing methods offer great promise to understand tissue organisation, but also present serious technical challenges. Generating high quality tissue labelling, developing tools for demonstrably reliable and accurate extraction, and eliminating baises through stereological technique, will establish a high standard for 3D quantitative data from cleared tissue. These challenges are met with StereoMate, an open-source image analysis framework for immunofluorescent labelling in cleared tissue. The platform facilitates the development of image segmentation protocols with rigorous validation, and extraction of object-level data in an automated and stereological manner. Mouse dorsal root ganglion neurones were assessed to validate this platform, which revealed a profound loss and shift in neurone size, and loss of axonal input and synaptic terminations within the spinal dorsal horn following their injury. In conclusion, the StereoMate platform provides a general-purpose automated stereological analysis platform to generate rich and unbiased object-level datasets from immunofluorescent data.
GSAn: an alternative to enrichment analysis for annotating gene sets
Authors: Ayllon-Benitez Aaron , Bourqui Romain , Thébaut Patricia , Mougin Fleur 
Published: May 2019

AbstractThe revolution in new sequencing technologies, by strongly improving the production of omics data, is greatly leading to new understandings of the relations between genotype and phenotype. To interpret and analyze these massive data that are grouped according to a phenotype of interest, methods based on statistical enrichment became a standard in biology. However, these methods synthesize the biological information by a priori selecting the over-represented terms and may suffer from focusing on the most studied genes that represent a limited coverage of annotated genes within the gene set.To address these limitations, we developed GSAn, a novel gene set annotation Web server that uses semantic similarity measures to reduce a priori Gene Ontology annotation terms. The originality of this new approach is to identify the best compromise between the number of retained annotation terms that has to be drastically reduced and the number of related genes that has to be as large as possible. Moreover, GSAn offers interactive visualization facilities dedicated to the multi-scale analysis of gene set annotations. GSAn is available at: https://gsan.labri.fr.
Rapid adaptive evolution of scale-eating kinematics to a novel ecological niche
Authors: St. John Michelle E. , Holzman Roi , Martin Christopher H. 
Published: May 2019

AbstractThe origins of novel trophic specialization, in which organisms begin to exploit novel resources for the first time, may be explained by shifts in behavior such as foraging preferences or feeding kinematics. One way to investigate the behavioral mechanisms underlying ecological novelty is by comparing prey capture kinematics between groups. In this study, we investigated the contribution of kinematics to the origins of a novel ecological niche for scale-eating within a microendemic adaptive radiation of pupfishes on San Salvador Island, Bahamas. We compared prey capture kinematics across three species of pupfish while consuming shrimp and scales in the lab and found that scale-eating pupfish exhibited peak gape sizes that were twice as large as all other groups, but also attacked prey with a more obtuse angle between their lower jaw and suspensorium. We then investigated how this variation in feeding kinematics could explain scale-biting performance by measuring the surface area removed per strike from standardized gelatin cubes. We found that a combination of larger peak gape and more obtuse lower jaw and suspensorium angles resulted in 67% more surface area removed per strike, indicating that scale-eaters may reside on a performance optimum for scale-biting. We also measured feeding kinematics of F1 hybrids to test whether feeding performance could contribute to reproductive isolation between species and found that F1 hybrid kinematics and performance more closely resembled those of generalists, suggesting that they may have low fitness in the scale-eating niche. Ultimately, our results suggest that the evolution of strike kinematics in this radiation is an adaptation to the novel niche of scale-eating.
Overt attention towards appetitive cues enhances their subjective value, independent of orbitofrontal cortex activity
Authors: McGinty Vincent B. 
Published: May 2019

ABSTRACTNeural representations of value underlie many behaviors that are crucial for survival. Previously, we found that value representations in primate orbitofrontal cortex (OFC) are modulated by attention, specifically, by overt shifts of gaze towards or away from reward-associated visual cues (McGinty et al., 2016). Here, we investigate the influence of overt attention on behavior, by asking how gaze shifts correlate with reward anticipatory responses, and whether activity in OFC mediates this correlation. Macaque monkeys viewed Pavlovian-conditioned appetitive cues on a visual display, while the fraction of time they spent looking towards or away from the cues was measured using an eye tracker. Also measured during cue presentation were the monkeys’ reward anticipation, indicated by conditioned licking responses (CRs), and single neuron activity in OFC. In general, gaze allocation predicted subsequent licking responses: the longer the monkeys spent looking at a cue at a given time point in a trial, the more likely they were to produce an anticipatory CR later in that trial, as if the subjective value of the cue were increased. To address neural mechanisms, mediation analysis measured the extent to which the gaze-CR correlation could be statistically explained by the concurrently recorded firing of single OFC neurons. The resulting mediation effects were indistinguishable from chance. Therefore, while overt attention may increase the subjective value of reward-associated cues (as revealed by anticipatory behaviors), the underlying mechanism remains unknown, as does the functional significance of gaze-driven modulation of OFC value signals.
A humanness dimension to visual object coding in the brain
Authors: Contini Erika W. , Goddard Erin , Grootswagers Tijl , Williams Mark , Carlson Thomas 
Published: May 2019

AbstractNeuroimaging studies investigating human object recognition have largely focused on a relatively small number of object categories, in particular, faces, bodies, scenes, and vehicles. More recent studies have taken a broader focus, investigating hypothesised dichotomies, for example animate versus inanimate, and continuous feature dimensions, such as biologically similarity. These studies typically have used stimuli that are clearly identified as animate or inanimate, neglecting objects that may not fit into this dichotomy. We generated a novel stimulus set including standard objects and objects that blur the animate-inanimate dichotomy, for example robots and toy animals. We used MEG time-series decoding to study the brain’s emerging representation of these objects. Our analysis examined contemporary models of object coding such as dichotomous animacy, as well as several new higher order models that take into account an object’s capacity for agency (i.e. its ability to move voluntarily) and capacity to experience the world. We show that early brain responses are best accounted for by low-level visual similarity of the objects; and shortly thereafter, higher order models of agency/experience best explained the brain’s representation of the stimuli. Strikingly, a model of human-similarity provided the best account for the brain’s representation after an initial perceptual processing phase. Our findings provide evidence for a new dimension of object coding in the human brain – one that has a “human-centric” focus.
Genome-wide heritability analysis of severe malaria susceptibility and resistance reveals evidence of polygenic inheritance
Authors: Damena Delesa , Chimusa Emile R. 
Published: May 2019

ABSTRACTObjectiveEstimating SNP-heritability (h2g) of severe malaria/resistance and its distribution across the genome might shed new light in to the underlying biology.MethodWe investigated h2g of severe malaria susceptibility and resistance from genome-wide association study (GWAS) dataset (sample size =11, 657). We partitioned the h2g in to chromosomes, allele frequencies and annotations. We further examined none-cell type specific and cell type specific enrichments from GWAS-summary statistics.ResultsWe estimated the h2g of severe malaria at 0.21 (se=0.05, p=2.7×10−5), 0.20 (se =0.05, p=7.5×10−5) and 0.17 (se =0.05, p= 7.2×10−4) in Gambian, Kenyan and Malawi populations, respectively. The h2g attributed to the GWAS significant SNPs and the well-known sickle cell (HbS) variant was approximately 0.07 and 0.03, respectively. We prepared African population reference panel and obtained comparable h2g estimate (0.21 (se = 0.02, p< 1×10−5)) from GWAS-summary statistics meta-analysed across the three populations. Partitioning analysis from raw genotype data showed significant enrichment of h2g in protein coding genic SNPs while summary statistics analysis suggests pattern of enrichment in multiple categories.ConclusionWe report for the first time that the heritability of malaria susceptibility and resistance is largely ascribed by common SNPs and the causal variants are overrepresented in protein coding regions of the genome. Overall, our results suggest that malaria susceptibility and resistance is a polygenic trait. Further studies with larger sample sizes are needed to better understand the underpinning genetics of resistance and susceptibility to severe malaria.
The effect of network thresholding and weighting on structural brain networks in the UK Biobank
Authors: Buchanan Colin R. , Bastin Mark E. , Ritchie Stuart J. , Liewald David C. , Madole James , Tucker-Drob Elliot M. , Deary Ian J. , Cox Simon R. 
Published: May 2019

AbstractWhole-brain structural networks can be constructed using diffusion MRI and probabilistic tractography. However, measurement noise and the probabilistic nature of the tracking procedure result in an unknown proportion of spurious white matter connections. Faithful disentanglement of spurious and genuine connections is hindered by a lack of comprehensive anatomical information at the network-level. Therefore, network thresholding methods are widely used to remove ostensibly false connections, but it is not yet clear how different thresholding strategies affect basic network properties and their associations with meaningful demographic variables, such as age. In a sample of 3,153 generally healthy volunteers from the UK Biobank Imaging Study (aged 44—77 years), we constructed 85 × 85 node whole-brain structural networks and applied two principled network thresholding approaches (consistency and proportional thresholding). These were applied over a broad range of threshold levels across six alternative network weightings (streamline count, fractional anisotropy, mean diffusivity and three novel weightings from neurite orientation dispersion and density imaging) and for four common network measures (mean edge weight, characteristic path length, network efficiency and network clustering coefficient). We compared network measures against age associations and found that the most commonly-used level of proportional-thresholding from the literature (retaining 68.7% of all possible connections) yielded significantly weaker age-associations (0.070 ≤ |β| ≤ 0.406) than the consistency-based approach which retained only 30% of connections (0.140 ≤ |β| ≤ 0.409). However, we determined that the stringency of the threshold was a stronger determinant of the network-age association than the choice of threshold method and the two thresholding approaches identified a highly overlapping set of connections (ICC = 0.84) when matched at a plausible level of network sparsity (70%). Generally, more stringent thresholding resulted in more age-sensitive network measures in five of the six network weightings, except at the highest levels of sparsity (>90%), where crucial connections were then removed. At two commonly-used threshold levels, the age-associations of the connections that were discarded (mean β ≤ |0.068|) were significantly smaller in magnitude than the corresponding age-associations of the connections that were retained (mean β ≤ |0.219|, p < 0.001, uncorrected). Given histological evidence of widespread degeneration of structural brain connectivity with increasing age, these results indicate that stringent thresholding methods may be most accurate in identifying true white matter connections.
Targeted brain tumor radiotherapy using an Auger emitter
Authors: Pirovano Giacomo , Jannetti Stephen A. , Carter Lukas M. , Sadique Ahmad , Kossatz Susanne , Guru Navjot , De Souza Franca Paula Demetrio , Maeda Masatomo , Zeglis Brian M. , Lewis Jason S. , Humm John L. , Reiner Thomas 
Published: May 2019

AbstractGlioblastoma multiforme is a highly aggressive form of brain cancer whose location, tendency to infiltrate healthy surrounding tissue, and heterogeneity significantly limit survival, with scant progress having been made in recent decades.123I-MAPi (Iodine-123 Meitner-Auger PARP1 inhibitor) is a precise therapeutic tool composed of a PARP1 inhibitor radiolabeled with an Auger- and gamma-emitting iodine isotope. Here, the PARP inhibitor, which binds to the DNA repair enzyme PARP1, specifically targets cancer cells, sparing healthy tissue, and carries a radioactive payload within reach of the cancer cells’ DNA. The high relative biological efficacy of Auger electrons within their short range of action is leveraged to inflict DNA damage and cell death with high precision. The gamma ray emission of123I-MAPi allows for the imaging of tumor progression and therapy response, and for patient dosimetry calculation. Here we demonstrated the efficacy and specificity of this small molecule radiotheranostic in a complex preclinical model.In vitroandin vivostudies demonstrate high tumor uptake and a prolonged survival in mice treated with123I-MAPi when compared to vehicle controls. Different methods of drug delivery were investigated to develop this technology for clinical applications, including convection enhanced delivery (CED) and intrathecal injection. Taken together, these results represent the first full characterization of an Auger-emitting PARP inhibitor, demonstrate a survival benefit in mouse models of GBM, and confirm the high potential of123I-MAPi for clinical translation.One Sentence SummaryA novel PARP1-targeted Auger radiotherapeutic shows translational potential as a theranostic tool for imaging and killing cancer cells, resulting in tumor delineation and prolonged survival in a glioblastoma model.
Connecting Concepts in the Brain by Mapping Cortical Representations of Semantic Relations
Authors: Zhang Yizhen , Han Kuan , Worth Robert , Liu Zhongming 
Published: May 2019

AbstractIn the brain, the semantic system is thought to store concepts. However, little is known about how it connects different concepts and infers semantic relations. To address this question, we collected hours of functional magnetic resonance imaging data from human subjects listening to natural stories. We developed a predictive model of the voxel-wise response and further applied it to thousands of new words. Our results suggest that both semantic categories and relations are represented by spatially overlapping cortical patterns, instead of anatomically segregated regions. Semantic relations that reflect conceptual progression from concreteness to abstractness are represented by cortical patterns of activation in the default mode network and deactivation in the frontoparietal attention network. We conclude that the human brain uses distributed networks to encode not only concepts but also relationships between concepts. In particular, the default mode network plays a central role in semantic processing for abstraction of concepts.
Long non-coding RNAGRASLNDenhances chondrogenesis via suppression of interferon type II signaling pathway
Authors: Huynh Nguyen P.T. , Gloss Catherine C. , Lorentz Jeremiah , Tang Ruhang , Brunger Jonathan M. , McAlinden Audrey , Zhang Bo , Guilak Farshid 
Published: May 2019

AbstractLong non-coding RNAs (lncRNAs) play critical roles in regulating gene expression and cellular processes; however, their roles in musculoskeletal development, disease, and regeneration remain poorly understood. Here, we identified a novel lncRNA, Glycosaminoglycan Regulatory ASsociated Long Non-coDing RNA (GRASLND) as a regulator of mesenchymal stem cell (MSC) chondrogenesis, and we investigated its basic molecular mechanism and its potential application towards regenerative medicine.GRASLND,a primate-specific lncRNA, is upregulated during MSC chondrogenesis and appears to act directly downstream of SRY-Box 9 (SOX9), but not Transforming Growth Factor Beta 3 (TGF-β3). Utilizing the established model of pellet formation for MSC chondrogenesis, we showed that the silencing ofGRASLNDresulted in lower accumulation of cartilage-like extracellular matrix, whileGRASLNDoverexpression, either via transgene ectopic expression or by endogenous activation via CRISPR, significantly enhanced cartilage matrix production.GRASLNDacts to inhibit interferon gamma (IFN-γ) by binding to Eukaryotic Initiation Factor-2 Kinase EIF2AK2. We further demonstrated thatGRASLNDexhibits a protective effect in engineered cartilage against interferon type II across different sources of chondroprogenitor cells. Our results indicate an important role ofGRASLNDin regulating stem cell chondrogenesis, as well as its therapeutic potential in the treatment of cartilage-related diseases, such as osteoarthritis.SignificanceLong non-coding RNAs (lncRNAs) play critical roles in gene regulation and cellular physiology; however, the role of lncRNAs in controlling stem cell chondrogenesis remains to be determined. Here, we utilized next generation sequencing of adult stem cell chondrogenesis to identify a set of potential lncRNA candidates involved in this process. We identified lncRNA Glycosaminoglycan Regulatory ASsociated Long Non-coDing RNA (GRASLND) and characterized its molecular mechanism of action. We described a novel role ofGRASLNDin positive regulation of chondrogenesis via its inhibition of type II interferon. Importantly, we showed that overexpression ofGRASLNDaugments stem cell chondrogenesis, providing a promising approach to enhancing stem cell chondrogenesis and cartilage regeneration.
Time-dependent Canonical Correlation Analysis for Multilevel Time Series
Authors: Cao Xuefei , Ke Jun , Sandstede Björn , Luo Xi 
Published: May 2019

AbstractCanonical Correlation Analysis is a technique in multivariate data analysis for finding linear projections that maximize the correlation between two groups of variables. The correlations are typically defined without accounting for the serial correlations between observations, a typical setting for time series data. To understand the coupling dynamics and temporal variations between the two time-varying sources, we introduce the time-dependent canonical correlation analysis (TDCCA), a method for inferring time-dependent canonical vectors from multilevel time series data. A convex formulation of the problem is proposed, which leverages the singular value decomposition (SVD) characterization of all solutions of the CCA problem. We use simulated datasets to validate the proposed algorithm. Moreover, we propose a novel measure, canonical correlation variation as another way to assess the dynamic pattern of brain connections and we apply it to a real resting state fMRI dataset to study the aging effects on brain connectivity. Additionally, we explore our proposed method in a task-related fMRI to detect the temporal dynamics due to different motor tasks. We show that, compared to extant methods, the TDCCA-based approach not only detect temporal changes but also improves feature extraction. Together, this paper contributes broadly to new computational methodologies in understanding multilevel time series.
TheC. elegansTubby homolog dynamically modulates olfactory cilia membrane morphogenesis and phospholipid composition
Authors: DiTirro Danielle , Philbrook Alison , Rubino Kendrick , Sengupta Piali 
Published: May 2019

ABSTRACTPlasticity in sensory signaling is partly mediated via regulated trafficking of signaling molecules to and from primary cilia. Tubby-related proteins regulate ciliary protein transport; however, their roles in remodeling of cilia properties are not fully understood. We find that theC. elegansTUB-1 Tubby homolog regulates membrane morphogenesis and signaling protein transport in specialized sensory cilia. In particular, TUB-1 is essential for sensory signaling-dependent reshaping of olfactory cilia morphology. We show that compromised sensory signaling alters cilia membrane phosphoinositide composition via TUB-1-dependent trafficking of a PIP5 kinase. TUB-1 regulates localization of this lipid kinase at the cilia base in part via localization of the AP-2 adaptor complex subunit DPY-23. Our results describe new functions for Tubby proteins in the dynamic regulation of cilia membrane lipid composition, morphology, and signaling protein content, and suggest that this conserved family of proteins plays a critical role in mediating cilia structural and functional plasticity.
Global mistranslation facilitates sampling of beneficial mutations under stress
Authors: Samhita Laasya , Raval Parth K , Agashe Deepa 
Published: May 2019

ABSTRACTMistranslation is typically deleterious, but can sometimes be beneficial. Although a specific mistranslated protein can confer a short-term benefit in a particular environment, the prevalence of high global mistranslation rates remains puzzling given the large overall cost. Here, we show that generalized mistranslation enhances earlyE. colisurvival under various forms of DNA damage, because it leads to early activation of the DNA damage-induced SOS response. Mistranslating cells therefore maintain larger populations, facilitating later sampling of critical beneficial mutations. Thus, under DNA damage, both basal and induced mistranslation (through genetic or environmental means) increase the number of genetically resistant and phenotypically persistent cells. Surprisingly, mistranslation also increases survival at high temperature. This wide-ranging stress resistance relies on Lon protease, which is revealed as a key effector that induces the SOS response in addition to alleviating proteotoxic stress. The new links between error-prone protein synthesis, DNA damage, and generalised stress resistance indicate surprising coordination between intracellular stress responses, and suggest a novel hypothesis to explain high global mistranslation rates.