bluuebunny/crossref_metadata_2025_split huggingface dataset:
iterb-PPse: Identification of transcriptional terminators in bacterial by incorporating nucleotide properties into PseKNC
Authors: Fan Yongxian , Wang Wanru , Zhu Qingqi 
Published: January 2020

AbstractTerminator is a DNA sequence that give the RNA polymerase the transcriptional termination signal. Identifying terminators correctly can optimize the genome annotation, more importantly, it has considerable application value in disease diagnosis and therapies. However, accurate prediction methods are deficient and in urgent need. Therefore, we proposed a prediction method “iterb-PPse” for terminators by incorporating 47 nucleotide properties into PseKNC-Iand PseKNC-IIand utilizing Extreme Gradient Boosting to predict terminators based onEscherichia coliandBacillus subtilis. Combing with the preceding methods, we employed three new feature extraction methods K-pwm, Base-content, Nucleotidepro to formulate raw samples. The two-step method was applied to select features. When identifying terminators based on optimized features, we compared five single models as well as 16 ensemble models. As a result, the accuracy of our method on benchmark dataset achieved 99.88%, higher than the existing state-of-the-art predictor iTerm-PseKNC in 100 times five-fold cross-validation test. It’s prediction accuracy for two independent datasets reached 94.24% and 99.45% respectively. For the convenience of users, a software was developed with the same name on the basis of “iterb-PPse”. The open software and source code of “iterb-PPse” are available athttps://github.com/Sarahyouzi/iterb-PPse.
Ribosome association primes the stringent factor Rel for recruitment of deacylated tRNA to ribosomal A-site
Authors: Takada Hiraku , Roghanian Mohammad , Caballero-Montes Julien , Van Nerom Katleen , Jimmy Steffi , Kudrin Pavel , Trebini Fabio , Murayama Rikinori , Akanuma Genki , Garcia-Pino Abel , Hauryliuk Vasili 
Published: January 2020

ABSTRACTIn the Gram-positive Firmicute bacteriumBacillus subtilis, amino acid starvation induces synthesis of the alarmone (p)ppGpp by the multi-domain RelA/SpoT Homolog factor Rel. This bifunctional enzyme is capable of both synthesizing and hydrolysing (p)ppGpp. To detect amino acid deficiency, Rel monitors the aminoacylation status of the ribosomal A-site tRNA by directly inspecting the tRNA’s CCA end. Here we uncover the molecular mechanism of Rel-mediated stringent response. Off the ribosome, Rel assumes a ‘closed’ conformation which has predominantly (p)ppGpp hydrolysis activity. This state does not specifically inspect tRNA and the interaction is only moderately affected by tRNA aminoacylation. Once bound to the vacant ribosomal A-site, Rel assumes an ‘open’ conformation, which primes its TGS and Helical domains for specific recognition and recruitment of cognate deacylated tRNA to the ribosome. The tRNA locks Rel on the ribosome in a hyperactivated state that processively synthesises (p)ppGpp while the hydrolysis is suppressed. In stark contrast to non-specific tRNA interactions off the ribosome, tRNA-dependent Rel locking on the ribosome and activation of (p)ppGpp synthesis are highly specific and completely abrogated by tRNA aminoacylation. Binding pppGpp to a dedicated allosteric site located in the N-terminal catalytic domain region of the enzyme further enhances its synthetase activity.
Transcription factors involved in stem cell maintenance are downstream of Slug/Snail2 and repressed by TGF-β in bronchial basal stem/progenitor cells from COPD
Authors: de la Grange Pierre , Jolly Ariane , Courageux Charlotte , Brahim Chamseddine Ben , Leroy Pascale 
Published: January 2020

AbstractPatients with COPD have many anomalies in their airway epithelium, and their basal stem/progenitor cells show a decrease in self-renewal and differentiation potential. The objective of this study was to identify deregulations in the genetic program of COPD bronchial basal stem/progenitor cells that could account for their exhaustion. TGF-β is found at higher levels in the lungs of COPD subjects. It has been shown to play a role in stem/progenitor cell fate and also to regulate the expression of the EMT-inducing transcription factor Slug/Snail2. In contrast to other transcription factors of the Snail family, Slug is highly expressed in basal progenitor cells, the adult stem/progenitors of human airway epithelium. We aimed at identifying genes downstream of Slug that respond to TGF-β, and whose expression is deregulated in COPD airway basal stem/progenitor cells, and could account for the decrease in count and functional ability of these cells observed in COPD. For this, we knocked down Slug in primary bronchial basal progenitor cells from COPD and normal subjects and, among the genes downstream of Slug, we selected those responding to TGF-β and differentiation. We identified 5 genes coding for transcription factors involved in stem cell maintenance that are repressed downstream of Slug and by TGF-β in COPD but not normal basal progenitor cells. Our results bring a molecular perspective to the exhaustion of airway basal stem/progenitor cells observed in COPD by revealing that stem cell maintenance genes are repressed in these cells, with TGF-β and Slug being involved in this deregulation.
The TMJ disc is a common ancestral feature in all mammals, as evidenced by the presence of a rudimentary disc during monotreme development
Authors: Anthwal Neal , Tucker Abigail S 
Published: January 2020

AbstractThe novel mammalian jaw joint, known in humans as the temporomandibular joint or TMJ, is cushioned by a fibrocartilage disc. This disc is secondarily absent in therian mammals that have lost their dentition, such as giant anteaters and some baleen whales. The disc is also absent in all monotremes. However, it is not known if the absence in monotremes is secondary to the loss of dentition, or if it is an ancestral absence. We use museum held platypus and echidna histological sections to demonstrate that the developing monotreme jaw joint forms a disc primordium that fails to mature and become separated from the mandibular condyle. We then show that monotreme developmental anatomy is similar to that observed in transgenic mouse mutants with reduced musculature. We therefore suggest that the absence of the disc on monotremes is a consequence of the changes in jaw musculature associated with the loss of adult teeth. Taken together, these data indicate that the ancestors of extant monotremes likely had a jaw joint disc, and that the disc evolved in the last common ancestor or all mammals.
Measuring social networks in primates: wearable sensors vs. direct observations
Authors: Gelardi Valeria , Godard Jeanne , Paleressompoulle Dany , Claidière Nicolas , Barrat Alain 
Published: January 2020

AbstractNetwork analysis represents a valuable and flexible framework to understand the structure of individual interactions at the population level in animal societies. The versatility of network representations is moreover suited to different types of datasets describing these interactions. However, depending on the data collection method, different pictures of the social bonds between individuals could a priori emerge. Understanding how the data collection method influences the description of the social structure of a group is thus essential to assess the reliability of social studies based on different types of data. This is however rarely feasible, especially for animal groups, where data collection is often challenging. Here, we address this issue by comparing datasets of interactions between primates collected through two different methods: behavioral observations and wearable proximity sensors. We show that, although many directly observed interactions are not detected by the sensors, the global pictures obtained when aggregating the data to build interaction networks turn out to be remarkably similar. Sensors data yield moreover a reliable social network already over short timescales and can be used for long term campaigns, showing their important potential for detailed studies of the evolution of animal social groups.
The npBAF to nBAF Chromatin Switch Regulates Cell Cycle Exit in the Developing Mammalian Cortex
Authors: Braun Simon MG , Petrova Ralitsa , Tang Jiong , Krokhotin Andrey , Miller Erik L , Tang Yitai , Panagiotakos Georgia , Crabtree Gerald R 
Published: January 2020

ABSTRACTNervous system development is orchestrated by tightly-regulated progenitor cell divisions, followed by differentiation at precise but varying times across different regions. As progenitors exit the cell cycle, they initiate a subunit switch of the mSWI/SNF or npBAF complex to generate neuron-specific nBAF complexes. These chromatin regulatory complexes play dosage-sensitive roles in neural development and are frequently mutated in neurodevelopmental disorders. Here we manipulated the timing of BAF subunit exchange in the developing mouse brain and find that deletion of the npBAF subunit BAF53a blocks progenitor proliferation, leading to impaired neurogenesis. We show that npBAF complexes regulate cell cycle progression by antagonizing Polycomb complexes to promote chromatin accessibility at cell cycle and NPC identity genes. Replacement of the actin-related protein, Actl6a (BAF53a) by the neuron-specific actin-related protein, Actl6b (BAF53b), but not other regulators of proliferation, rescues progenitors by promoting neuronal differentiation. We propose that the function of the npBAF to nBAF chromatin switch is to control progenitor cell cycle exit and promote synchronous neural differentiation.
Classification of emotions based on functional connectivity patterns of the human brain
Authors: Saarimäki Heini , Glerean Enrico , Smirnov Dmitry , Mynttinen Henri , Jääskeläinen Iiro P. , Sams Mikko , Nummenmaa Lauri 
Published: January 2020

AbstractNeurophysiological and psychological models posit that emotions depend on connections across wide-spread corticolimbic circuits. While previous studies using pattern recognition on neuroimaging data have shown differences between various discrete emotions in brain activity patterns, less is known about the differences in functional connectivity. Thus, we employed multivariate pattern analysis on functional magnetic resonance imaging data (i) to develop a pipeline for applying pattern recognition in functional connectivity data, and (ii) to test whether connectivity signatures differ across emotions. Six emotions (anger, fear, disgust, happiness, sadness, and surprise) and a neutral state were induced in 16 participants using one-minute-long emotional narratives with natural prosody while brain activity was measured with functional magnetic resonance imaging (fMRI). We computed emotion-wise connectivity matrices both for whole-brain connections and for 10 previously defined functionally connected brain subnetworks, and trained an across-participant classifier to categorize the emotional states based on whole-brain data and for each subnetwork separately. The whole-brain classifier performed above chance level with all emotions except sadness, suggesting that different emotions are characterized by differences in large-scale connectivity patterns. When focusing on the connectivity within the 10 subnetworks, classification was successful within the default mode system and for all emotions. We conclude that functional connectivity patterns consistently differ across different emotions particularly within the default mode system.
Network Insights into Improving Drug Target Inference Algorithms
Authors: Wang Muying , Noh Heeju , Mochan Ericka , Shoemaker Jason E. 
Published: January 2020

AbstractTo improve the efficacy of drug research and development (R&D), a better understanding of drug mechanisms of action (MoA) is needed to improve drug discovery. Computational algorithms, such as ProTINA, that integrate protein-protein interactions (PPIs), protein-gene interactions (PGIs) and gene expression data have shown promising performance on drug target inference. In this work, we evaluated how network and gene expression data affect ProTINA’s accuracy. Network data predominantly determines the accuracy of ProTINA instead of gene expression, while the size of an interaction network or selecting cell/tissue-specific networks have limited effects on the accuracy. However, we found that protein network betweenness values showed high accuracy in predicting drug targets. Therefore, we suggested a new algorithm, TREAP (https://github.com/ImmuSystems-Lab/TREAP), that combines betweenness values and adjustedp-values for target inference. This algorithm has resulted in higher accuracy than ProTINA using the same datasets.
Harmonic-Balance Circuit Analysis for Electro-Neural Interfaces
Authors: Chen Zhijie Charles , Wang Bingyi , Palanker Daniel 
Published: January 2020

AbstractObjectiveAvoidance of the adverse electrochemical reactions at the electrode-electrolyte interface defines the voltage safety window and limits the charge injection capacity (CIC) of an electrode material. For an electrode that is not ideally capacitive, the CIC depends on the waveform of the stimulus. We study the modeling of the charge injection dynamics to optimize the waveforms for efficient neural stimulation within the electrochemical safety limits.ApproachThe charge injection dynamics at the electrode-electrolyte interface is typically characterized by the electrochemical impedance spectrum, and is often approximated by discrete-element circuit models. We compare the modeling of the complete circuit, including a non-linear driver such as a photodiode, based on the harmonic-balance (HB) analysis with the analysis based on various discrete element approximations. To validate the modeling results, we performed experiments with iridium-oxide electrodes driven by a current source with diodes in parallel, which mimics a photovoltaic circuit.Main resultsApplication of HB analysis based on a full impedance spectrum in frequency domain eliminates the complication of finding the discrete-element circuit model in traditional approaches. HB-based results agree with the experimental data better than the discrete-element circuit analysis. HB technique can be applied not only to demonstrate the circuit response to periodic stimulation, but also to describe the initial transient behavior when a burst waveform is applied.SignificanceHB-based circuit analysis accurately describes the dynamics of electrode-electrolyte interfaces and driving circuits for all pulsing schemes. This allows optimizing the stimulus waveform to maximize the CIC, based on the impedance spectrum alone.
Multimodal magnetic resonance imaging predicts regional amyloid- β burden in the brain
Authors: Rangarajan Anusha , Wu Minjie , Joseph Naomi , Karim Helmet T. , Laymon Charles , Tudorascu Dana , Cohen Annie , Klunk William , Aizenstein Howard J. 
Published: January 2020

AbstractAlzheimer’s disease (AD) is the most common cause of dementia and identifying early markers of this disease is important for prevention and treatment strategies. Amyloid -βprotein deposition is one of the earliest detectable pathological changes in AD. But in-vivo detection of amyloid -βusing positron emission tomography (PET) is hampered by high cost and limited geographical accessibility. These factors can become limiting when PET is used to screen large numbers of subjects into prevention trials when only a minority are expected to be amyloid- β - positive. Structural MRI is advantageous; as it is relatively inexpensive and more accessible. Thus it could be widely used in large studies, even when frequent or repetitive imaging is necessary. We used a machine learning, pattern recognition, approach using intensity-based features from individual and combination of MR modalities (T1 weighted, T2 weighted, T2 fluid attenuated inversion recovery [FLAIR], susceptibility weighted imaging) to predict voxel-level amyloid- β in the brain. The MR- amyloidβrelation was learned within each subject and generalized across subjects using subject–specific features (demographic, clinical, and summary MR features). When compared to other modalities, combination of T1-weighted, T2-weighted FLAIR, and SWI performed best in predicting the amyloid- β status as positive or negative. T2- weighted performed the best in predicting change in amyloid- β over two timepoints. Overall, our results show feasibility of amyloid- β prediction by MRI.
Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort
Authors: Lv Jinglei , Di Biase Maria , Cash Robin F. H. , Cocchi Luca , Cropley Vanessa , Klauser Paul , Tian Ye , Bayer Johanna , Schmaal Lianne , Cetin-Karayumak Suheyla , Rathi Yogesh , Pasternak Ofer , Bousman Chad , Pantelis Christos , Calamante Fernando , Zalesky Andrew 
Published: January 2020

AbstractBackgroundThe heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology.MethodsFor each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n=195). Individuals with schizophrenia (n=322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual.ResultsCompared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region, whereas 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59±2%, p<0.001). Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r=-0.17, p=0.006).ConclusionsAnatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.
The relationship between eDNA particle concentration and organism abundance in nature is strengthened by allometric scaling
Authors: Yates M.C , Glaser D. , Post J. , Cristescu M.E. , Fraser D.J. , Derry A.M. 
Published: January 2020

AbstractOrganism abundance is a critical parameter in ecology, but its estimation is often challenging. Approaches utilizing eDNA to indirectly estimate abundance have recently generated substantial interest. However, preliminary correlations observed between eDNA concentration and abundance in nature are typically moderate in strength with significant unexplained variation. Here we apply a novel approach to integrate allometric scaling coefficients into models of eDNA concentration and organism abundance. We hypothesize that eDNA particle production scales non-linearly with mass, with scaling coefficients < 1. Wild populations often exhibit substantial variation in individual body size distributions; we therefore predict that the distribution of mass across individuals within a population will influence population-level eDNA production rates. To test our hypothesis, we collected standardized body size distribution and mark-recapture abundance data using whole-lake experiments involving nine populations of brook trout. We correlated eDNA concentration with three metrics of abundance: density (individuals/ha), biomass (kg/ha), and allometrically scaled mass (ASM) (∑(individual mass0.73)/ha). Density and biomass were both significantly positively correlated with eDNA concentration (adj. R2= 0.59 and 0.63, respectively), but ASM exhibited improved model fit (adj. R2= 0.78). We also demonstrate how estimates of ASM derived from eDNA samples in ‘unknown’ systems can be converted to biomass or density estimates with additional size structure data. Future experiments should empirically validate allometric scaling coefficients for eDNA production, particularly where substantial intraspecific size distribution variation exists. Incorporating allometric scaling may improve predictive models to the extent that eDNA concentration may become a reliable indicator of abundance in nature.
Life trajectories towards suicide: developmental role and specificities of adolescence
Authors: Notredame Charles-Edouard , Chawky Nadia , Beauchamp Guy , Vaiva Guillaume , Séguin Monique 
Published: January 2020

AbstractObjectiveConsidering that adolescence is a crucial period of allostatic maturation, we aimed at testing whether it represents a breakpoint in adversity trajectories to suicide and, relatedly, whether life trajectories of adolescents who died by suicide differ from those of adult counterparts.MethodIn 303 individuals who died by suicide, a panel of experts derived longitudinal burden of adversity ratings from extensive clinical interviews conducted with informants. Piecewise Joint Latent Class Models allowed to identify patterns of adversity trajectories and test the introduction of breakpoints in life-paths. The classes inferred from the optimal model were compared in terms of socio-demographics, psychopathology and nature of experienced events.ResultsThe most accurate model derived 2 trajectory patterns with a breakpoint in early adolescence. In the first class (n = 43 individuals), the burden of adversity increased steadily from birth to death, which occurred on average at 23 (SE = 1.29). In the second class (n = 259), where individuals died on average at 43 years (SE = 0.96), the burden of adversity followed a similar trajectory during infancy but stabilized between ages 10 and 14 years and rebounded at about 25. The classes differed in terms of childhood family stability, occurrence of dependent events, distal exposure to suicide and intra-family sexual victimization.ConclusionAlthough subject to inherent limitations of the retrospective designs, our results encourage clinicians and researchers to pay greater attention to the diathetic maturation processes occurring during adolescence when considering suicidal behaviors in young people.