bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting transfer RNA gene activity from sequence and genome context
Authors: Thornlow Bryan , Armstrong Joel , Holmes Andrew , Corbett-Detig Russell , Lowe Todd 
Published: June 2019

ABSTRACTTransfer RNA (tRNA) genes are among the most highly transcribed genes in the genome due to their central role in protein synthesis. However, there is evidence for a broad range of gene expression across tRNA loci. This complexity, combined with difficulty in measuring transcript abundance and high sequence identity across transcripts, has severely limited our collective understanding of tRNA gene expression regulation and evolution. We establish sequence-based correlates to tRNA gene expression and develop a tRNA gene classification method that does not require, but benefits from comparative genomic information, and achieves accuracy comparable to molecular assays. We observe that guanine+cytosine (G+C) content and CpG density surrounding tRNA loci is exceptionally well correlated with tRNA gene activity, supporting a prominent regulatory role of the local genomic context in combination with internal sequence features. We use our tRNA gene activity predictions in conjunction with a comprehensive tRNA gene ortholog set spanning 29 placental mammals to infer the frequency of changes to tRNA gene expression among orthologs. Our method adds an important new dimension to tRNA annotation and will help focus the study of natural tRNA variants. Its simplicity and robustness enables facile application to other clades and timescales, as well as exploration of functional diversification of tRNAs and other large gene families.
Machine-Learning Prediction of Comorbid Substance Use Disorders in ADHD Youth Using Swedish Registry Data
Authors: Zhang-James Yanli , Chen Qi , Kuja-Halkola Ralf , Lichtenstein Paul , Larsson Henrik , Faraone Stephen V 
Published: June 2019

AbstractBackgroundChildren with attention-deficit/hyperactivity disorder (ADHD) have a high risk for substance use disorders (SUDs). Early identification of at-risk youth would help allocate scarce resources for prevention programs.MethodsPsychiatric and somatic diagnoses, family history of these disorders, measures of socioeconomic distress and information about birth complications were obtained from the national registers in Sweden for 19,787 children with ADHD born between 1989-1993. We trained 1) cross-sectional machine learning models using data available by age 17 to predict SUD diagnosis between ages 18-19; and 2) a longitudinal model to predict new diagnoses at each age.ResultsThe area under the receiver operating characteristic curve (AUC) was 0.73 and 0.71 for the random forest and multilayer perceptron cross-sectional models. A prior diagnosis of SUD was the most important predictor, accounting for 25% of correct predictions. However, after excluding this predictor, our model still significantly predicted the first-time diagnosis of SUD during age 18-19 with an AUC of 0.67. The average of the AUCs from longitudinal models predicting new diagnoses one, two, five and ten years in the future was 0.63.ConclusionsSignificant predictions of at-risk co-morbid SUDs in individuals with ADHD can be achieved using population registry data, even many years prior to the first diagnosis. Longitudinal models can potentially monitor their risks over time. More work is needed to create prediction models based on electronic health records or linked population-registers that are sufficiently accurate for use in the clinic.
Kindlin Assists Talin to Promote Integrin Activation
Authors: Haydari Z. , Shams H. , Jahed Z. , Mofrad M.R.K. 
Published: June 2019

AbstractIntegrin αIIbβ3 is a predominant type of integrin abundantly expressed on the surface of platelets and its activation regulates the process of thrombosis. Talin and kindlin are cytoplasmic proteins that bind to integrin and modulate its affinity for extracellular ligands. While the molecular details of talin-mediated integrin activation are known, the mechanism of kindlin involvement in this process remains elusive. Here, we demonstrate that the interplay between talin and kindlin promotes integrin activation. Our all-atomic molecular dynamics simulations on complete transmembrane and cytoplasmic domains of integrin αIIbβ3, talin1 F2/F3 subdomains, and kindlin2 FERM domain in an explicit lipid-water environment over microsecond timescale, unraveled the role of kindlin as an enhancer of the talin interaction with the membrane proximal region of β–integrin. The cooperation of kindlin with talin results in a complete disruption of salt bridges between R995 on αIIb and D723/E726 on β3. Furthermore, kindlin modifies the molecular mechanisms of inside-out activation by decreasing the crossing angle between transmembrane helices of integrin αIIb-β3, which eventually results in parallelization of integrin dimer. In addition, our control simulation featuring integrin in complex with kindlin reveals that kindlin binding is not sufficient for unclasping the inner membrane and outer membrane interactions of integrin dimer, thus ruling out the possibility of solitary action of kindlin in integrin activation.Statement of SignificanceUsing the newly solved crystal structure of kindlin, we investigated, for the first time, the molecular mechanism of kindlin-mediated integrin activation through simultaneous binding of talin and kindlin. We demonstrate in atomist details how kindlin cooperates with talin to promote the activation of integrin αIIb-β3.
The effect of insect cyanoglucosides on predation by domestic chicks
Authors: Cardoso Márcio Zikán 
Published: June 2019

AbstractCyanogenic insects release cyanide and other byproducts that are thought to make them unpalatable to would be predators. In fact, aposematic Heliconius butterflies and Zygaena moths are rejected by vertebrate predators. Nevertheless, there have been few studies testing the effect of cyanoglucosides on vertebrate predation. Here I report tests undertook with captive domestic chicks in order to evaluate the effect of two chemically diverse cyanoglucosides, linamarin and prunasin. In insects as well as plants, cyanoglucosides are stored in vacuoles and are enzymatically broken down when the tissue is disrupted as in the case of a predator attack. Linamarin is an aliphatic that releases cyanide and acetone upon breakdown, while prunasin is an aromatic cyanoglucoside that releases cyanide and benzaldehyde. Using concentrations that mimicked the average concentration of a Heliconius butterfly, supplemented by test with higher concentrations, I ran a series of trials with naïve chicks by offering prey laced with chemicals. I categorized prey acceptance and compared the behavior of the predators towards test and control larvae. Prey coated with cyanide and benzaldehyde were significantly rejected by the birds, while acetone did not elicit avoidance behavior. Intact cyanoglucosides apparently were not detected by the predators, presumably because of fast ingestion time or lack of enzymes to breakdown cyanoglucosides. The rejection of cyanide laced prey confirm the protective nature of cyanoglucosides against a vertebrate predator. Additionally, the rejection of the pungent but not toxic benzaldehyde suggests that some species that store aromatic cyanoglucosides could be detected via smell as well by taste. These results provide support for cyanoglucosides as defensive chemicals of aposematic lepidopterans and related arthropods.
ERO1α promotes hypoxic tumour progression and is associated with poor prognosis in pancreatic cancer
Authors: Gupta Nikhil , Park Jung Eun , Tse Wilford , Low Jee Keem , Kon Oi Lian , McCarthy Neil , Sze Siu Kwan 
Published: June 2019

AbstractPancreatic cancer is a leading cause of mortality worldwide due to difficulty detecting early-stage disease and our poor understanding of the mediators that drive the progression of hypoxic solid tumours. We, therefore, used a heavy isotope ‘pulse/trace’ proteomic approach to determine how hypoxia alters pancreatic tumour expression of proteins that confer treatment resistance, promote metastasis, and suppress host immunity. Using this method, we identified that hypoxia stress stimulates pancreatic cancer cells to rapidly translate proteins that enhance metastasis (NOTCH2, NCS1, CD151, NUSAP1), treatment resistant (ABCB6), immune suppression (NFIL3,WDR4), angiogenesis (ANGPT4, ERO1α, FOS), alter cell metabolic activity (HK2, ENO2), and mediate growth-promoting cytokine responses (CLK3, ANGPTL4). Database mining confirmed that elevated gene expression of these hypoxia-induced mediators is significantly associated with poor patient survival in various stages of pancreatic cancer. Among these proteins, the oxidoreductase enzyme ERO1α was highly sensitive to induction by hypoxia stress across a range of different pancreatic cancer cell lines and was associated with particularly poor prognosis in human patients. Consistent with these data, genetic deletion of ERO1α substantially reduced growth rates and colony formation in pancreatic cancer cells when assessed in a series of functional assays in vitro. Accordingly, when transferred into a mouse xenograft model, ERO1α-deficient tumour cells exhibited severe growth restriction and negligible disease progression in vivo. Together, these data indicate that ERO1α is potential prognostic biomarker and novel drug target for pancreatic cancer therapy.
The bounded rationality of probability distortion
Authors: Zhang Hang , Ren Xiangjuan , Maloney Laurence T. 
Published: June 2019

AbstractIn decision-making under risk (DMR) participants’ choices are based on probability values systematically different from those that are objectively correct. Similar systematic distortions are found in tasks involving relative frequency judgments (JRF). These distortions limit performance in a wide variety of tasks and an evident question is, why do we systematically fail in our use of probability and relative frequency information?We propose a Bounded Log-Odds Model (BLO) of probability and relative frequency distortion based on three assumptions: (1)log-odds: probability and relative frequency are mapped to an internal log-odds scale, (2)boundedness: the range of representations of probability and relative frequency are bounded and the bounds change dynamically with task, and (3)variance compensation: the mapping compensates in part for uncertainty in probability and relative frequency values.We compared human performance in both DMR and JRF tasks to the predictions of the BLO model as well as eleven alternative models each missing one or more of the underlying BLO assumptions (factorial model comparison). The BLO model and its assumptions proved to be superior to any of the alternatives. In a separate analysis, we found that BLO accounts for individual participants’ data better than any previous model in the DMR literature.We also found that, subject to the boundedness limitation, participants’ choice of distortion approximately maximized the mutual information between objective task-relevant values and internal values, a form of bounded rationality.SignificanceStatementPeople distort probability in decision under risk and many other tasks. These distortions can be large, leading us to make markedly suboptimal decisions. There is no agreement on why we distort probability. Distortion changes systematically with task, hinting that distortions are dynamic compensations for some intrinsic “bound” on working memory. We first develop a model of the bound and the compensation process and then report an experiment showing that the model accounts for individual human performance in decision under risk and relative frequency judgments. Last, we show that the particular compensation in each experimental condition serve to maximize the mutual information between objective decision variables and their internal representations. We distort probability to compensate for our own working memory limitations.
Pre-existent adult sox10+cardiomyocytes contribute to myocardial regeneration in the zebrafish
Authors: Sande-Melón Marcos , Marques Inês J. , Galardi-Castilla María , Langa Xavier , Pérez-López María , Botos Marius , Guzmán-Martínez Gabriela , Ferreira-Francisco David Miguel , Pavlinic Dinko , Benes Vladimir , Bruggmann Remy , Mercader Nadia 
Published: June 2019

AbstractDuring heart regeneration in the zebrafish, fibrotic tissue is replaced by newly formed cardiomyocytes derived from pre-existing ones. It is unclear whether the heart is comprised of several cardiomyocyte populations bearing different capacity to replace lost myocardium. Here, usingsox10genetic fate mapping, we identified a subset of pre-existent cardiomyocytes in the adult zebrafish heart with a distinct gene expression profile that expanded massively after cryoinjury. Genetic ablation ofsox10+cardiomyocytes severely impaired cardiac regeneration revealing that they play a crucial role for heart regeneration.
Fine scale population structure linked to neutral divergence in the common sole (Solea solea), a marine fish with high dispersal capacity
Authors: Le Moan Alan , Jiménez-Mena Belén , Bekkevold Dorte , Hemmer-Hansen Jakob 
Published: June 2019

AbstractThe Baltic Sea provides a classical example of how an environmental gradient is associated with the distribution of marine species. Here, numerous genetic studies have revealed clear patterns of population structuring linked to the physical features of the gradient itself. Nevertheless, it remains difficult to distinguish clearly between the different micro-evolutionary processes that shape these structured populationsin situ. The common sole (Solea solea) is a benthic flatfish that rarely occurs within the Baltic Sea, but that exhibits a clear genetic break between populations from the North Sea – Baltic Sea transition zone and the remainder of the Atlantic Ocean. Here, we aim to evaluate the extent to which natural selection is involved in the observed patterns of divergence of sole populations occurring in the transition zone by comparing them with population structures of other flatfish species that have successfully colonized the Baltic Sea. By using several thousand of ddRAD-derived SNPs, we identified a fine-scale pattern of isolation-by-distance (IBD) of sole populations in the region. However, despite strong biological similarities among the flatfishes compared here, the sole IBD was, by far, the lowest detected across the transition zone. While selection was inferred to strongly influence all other flatfishes evolutionary histories, the analytical inference on the sole demographic history suggests that this fine-scale IBD is mainly maintained by neutral processes due to low effective population size of sole in the transition zone and asymmetrical gene flow. Our work contributes to a growing body of evidence suggesting that the strength of the different micro-evolutionary processes is species-specific, even when species occur in the same environment.
Integrating population genetics to define conservation units from the core to the edge ofRhinolophus ferrumequinumwestern range
Authors: Tournayre Orianne , Pons Jean-Baptiste , Leuchtmann Maxime , Leblois Raphael , Piry Sylvain , Filippi-Codaccioni Ondine , Loiseau Anne , Duhayer Jeanne , Garin Inazio , Mathews Fiona , Puechmaille Sébastien , Charbonnel Nathalie , Pontier Dominique 
Published: June 2019

AbstractThe greater horseshoe bat(Rhinolophus ferrumequinum)is among the most widespread bat species in Europe but it has experienced severe declines, especially in Northern Europe. This species is listed Near Threatened in the EuropeanIUCN Red List of Threatened Animalsand it is considered to be highly sensitive to human activities and particularly to habitat fragmentation. Therefore, understanding the population boundaries and demographic history of populations of this species is of primary importance to assess relevant conservation strategies. In this study, we used 17 microsatellite markers to assess the genetic diversity, the genetic structure and the demographic history ofR. ferrumequinumcolonies in the Western European part of its distribution. We found high levels of genetic diversity and large population size on the European mainland and lower estimates in England and Northern France. Analyses of clustering and isolation by distance showed a barrier effect of the Channel and potentially of the Mediterranean Sea onR. ferrumequinumbat dispersal. Conversely, we could not reveal any gene flow disruption from both sides of the Western Pyrenees. These results provide important information to improve the delineation ofR. ferrumequinummanagement units in its western range. We suggest that a large management unit corresponding to the European mainland population must be considered. Particular attention should be given to mating territories as they seem to play a key role in maintaining the high levels of genetic mixing between colonies. Smaller management units corresponding to English and Northern France colonies must also be implemented. These insular or peripheral colonies could be at higher risk of extinction in a near future.
Balancing Model-Based and Memory-Free Action Selection under Competitive Pressure
Authors: Kikumoto Atsushi , Mayr Ulrich 
Published: June 2019

AbstractIn competitive situations, winning depends on selecting actions that surprise the opponent. Such unpredictable action can be generated based on representations of the opponent’s strategy and choice history (model-based counter-prediction) or by choosing actions in a memory-free, stochastic manner. Across five different experiments using a variant of a matching-pennies game with simulated and human opponents we found that people toggle between these two strategies, using model-based selection used when recent wins signal the appropriateness of the current model, but reverting to stochastic selection following losses. Also, after wins, feedback-related, mid-frontal EEG activity reflected information about the opponent’s global and local strategy, and predicted upcoming choices. After losses, this activity was nearly absent—indicating that the internal model is suppressed after negative feedback. We suggest that the mixed-strategy approach allows negotiating two conflicting goals: (1) exploiting the opponent’s deviations from randomness while (2) remaining unpredictable for the opponent.
New mechanism-based inhibitors of aspartate transcarbamoylase for anticancer drug development
Authors: Lei Zhen , Wang Nan , Wang Biying , Lu Zhifang , Tan Hongwei , Zheng Jimin , Jia Zongchao 
Published: June 2019

AbstractAspartate transcarbamoylase (ATCase) is a key enzyme which regulates and catalyzes the second step ofde novopyrimidine synthesis in all organisms.E. coliATCase is a prototypic enzyme regulated by both product feedback and substrate cooperativity, whereas human ATCase is a potential anticancer target. Through structural and biochemical analyses, we revealed that R167/130’s loop region in ATCase serves as a gatekeeper for the active site, playing a new and unappreciated role in feedback regulation. Based on virtual compound screening simultaneously targeting the new regulatory region and active site of human ATCase, two compounds were identified to exhibit strong inhibition of ATCase activity, proliferation of multiple cancer cell lines, and growth of xenograft tumors. Our work has not only revealed a previously unknown regulatory region of ATCase that helps explain feedback regulation, but also successfully guided the identification of new ATCase inhibitors for anticancer drug development using a dual-targeting strategy.
Personalized Therapy Design for Liquid Tumors via Optimal Control Theory
Authors: Angaroni Fabrizio , Graudenzi Alex , Rossignolo Marco , Maspero Davide , Calarco Tommaso , Piazza Rocco , Montangero Simone , Antoniotti Marco 
Published: June 2019

ABSTRACTOne of the key challenges in current cancer research is the development of reliable methods for the definition of personalized therapeutic strategies, based on increasingly available experimental data on single patients. To this end, methods from control theory can be effectively employed on patient-specific pharmacokinetic and pharmacodynamic models to generate robust data-driven experimental hypotheses.Here we introduce the Control Theory for Therapy Design (CT4TD) theoretical framework for the generation of optimized personalized therapeutic strategies in cancer patients, based on optimal control theory and population dynamics modeling. The CT4TD framework can help clinicians in designing patient-specific therapeutic regimens, with the specific goal of optimizing the efficacy of the cure while reducing the costs, especially in terms of toxicity and adverse effects. CT4TD can be used at the time of the diagnosis in order to set optimized personalized therapies to reach selected target drug concentrations. Furthermore, if longitudinal data on patients under treatment are available, our approach introduces the possibility of adjusting the therapy with the explicit goal of minimizing the tumor burden measured in each case.As a case study, we present the application of CT4TD to Imatinib administration in Chronic Myeloid Leukemia, in which we show that the optimized therapeutic strategies are extremely diversified among patients, and display improvements with respect to the currently employed regimes. Interestingly, we prove that much of the variance in therapeutic response observed among patients is due to the individual differences in pharmacokinetics, rather than in pharmacodynamics.
Numerical cognition based on precise counting with a single spiking neuron
Authors: Rapp Hannes , Nawrot Martin Paul , Stern Merav 
Published: June 2019

AbstractInsects are able to solve basic numerical cognition tasks. We show that estimation of numerosity can be realized and learned by a single spiking neuron with an appropriate synaptic plasticity rule. This model can be efficiently trained to detect arbitrary spatio-temporal spike patterns on a noisy and dynamic background with high precision and low variance. When put to test in a task that requires counting of visual concepts in a static image it required considerably less training epochs than a convolutional neural network to achieve equal performance. When mimicking a behavioral task in free flying bees that requires numerical cognition the model reaches a similar success rate in making correct decisions. We propose that using action potentials to represent basic numerical concepts with a single spiking neuron is beneficial for organisms with small brains and limited neuronal resources.