bluuebunny/crossref_metadata_2025_split huggingface dataset:
Divergent projections of the prelimbic cortex bidirectionally regulate active avoidance
Authors: Diehl Maria M. , Iravedra-García Jorge M. , Morán-Sierra Jonathan , Rojas-Bowe Gabriel , Gonzalez-Díaz Fabiola , Valentín-Valentín Viviana , Quirk Gregory J. 
Published: May 2020

AbstractThe prefrontal cortex (PFC) integrates incoming information to guide our actions. When motivation for food-seeking competes with avoidance, the PFC likely plays a role in selecting the optimal choice. In platform-mediated active avoidance, rats avoid a tone-signaled footshock by stepping onto a nearby platform, delaying access to sucrose pellets. This avoidance requires prelimbic (PL) prefrontal cortex, basolateral amygdala (BLA), and ventral striatum (VS). We previously showed that inhibitory tone responses of PL neurons correlate with avoidability of shock (Diehlet al., 2018). Here, we optogenetically modulated PL terminals in VS and BLA to identify PL outputs regulating avoidance. Photoactivating PL-VS projections reduced avoidance, whereas photoactivating PL-BLA projections increased avoidance. Moreover, photosilencing PL-BLA or BLA-VS projections reduced avoidance, suggesting that VS receives opposing inputs from PL and BLA. Bidirectional modulation of avoidance by PL projections to VS and BLA enables the animal to make appropriate decisions when faced with competing drives.
Database for drug metabolism and comparisons, NICEdrug.ch, aids discovery and design
Authors: MohammadiPeyhani Homa , Chiappino-Pepe Anush , Haddadi Kiandokht , Hafner Jasmin , Hadadi Noushin , Hatzimanikatis Vassily 
Published: May 2020

AbstractThe discovery of a drug requires over a decade of enormous research and financial investments—and still has a high risk of failure. To reduce this burden, we developed the NICEdrug.ch database, which incorporates 250,000 bio-active molecules, and studied their metabolic targets, fate, and toxicity. NICEdrug.ch includes a unique fingerprint that identifies reactive similarities between drug-drug and drug-metabolite pairs. We use NICEdrug.ch to evaluate inhibition and toxicity by the anticancer drug 5-fluorouracil, and suggest avenues to alleviate its side effects. Clustering based on this fingerprint in statins identified drugs for repurposing. We propose shikimate 3-phosphate for targeting liver-stage malaria with minimal impact on the human host cell. Finally, NICEdrug.ch suggests over 1,300 drugs and food molecules to target COVID-19 and explains their inhibitory mechanisms. The NICEdrug.ch database is accessible online to systematically identify the reactivity of small molecules and druggable enzymes with practical applications in lead discovery and drug repurposing.
Evidence for an apathy phenotype in aged mice
Authors: Jackson Megan G , Lightman Stafford L , Gilmour Gary , Marston Hugh , Robinson Emma S J 
Published: May 2020

AbstractApathy is widely reported in patients with neurological disorders or post viral infection but is also seen in otherwise-healthy aged individuals. This study investigated whether aged mice express behavioural and physiological changes indicative of an apathy phenotype. Using measures of motivation to work for reward, we found deficits in the progressive ratio task related to rate of responding. In an effort for reward task, aged mice were less willing to exert effort for high value reward. Aged mice exhibited reduced reward sensitivity and expressed lower measures of anxiety in the novelty supressed feeding test. In a test of cognition (novel object recognition) aged mice showed no impairments but activity was lower in a measure of exploration in a novel environment. Aged mice also showed an attenuated response to restraint stress with lower corticosterone and reduced paraventricular nucleus c-fos activation. Together, these data suggest aged mice show reduced goal-directed behaviour and reduced reward sensitivity and stress reactivity, reflective of emotional blunting and may be a suitable model for pre-clinical apathy research.
MINTyper: An outbreak-detection method for accurate and rapid SNP typing of clonal clusters with noisy long reads
Authors: Hallgren Malte B. , Overballe-Petersen Søren , Lund Ole , Hasman Henrik , Clausen Philip T. L. C. 
Published: May 2020

ABSTRACTFor detection of clonal outbreaks in clinical settings, we present a complete pipeline that generates a SNP-distance matrix from a set of sequencing reads. Importantly, the program is able to handle a separate mix of both short reads from the Illumina sequencing platforms and long reads from Oxford Nanopore Technologies’ (ONT) platforms as input.MINTyper performs automated reference identification, alignment, alignment trimming, optional methylation masking and pairwise distance calculations. With this approach, we could rapidly and accurately cluster a set of DNA sequenced isolates, with a known epidemiological relationship to confirm the clustering. Functions were built to allow for both high-accuracy methylation-aware base-called MinION reads (hac_m Q10) and fast generated lower-quality reads (fast Q8) to be used, also in combination with Illumina data. With fast Q8 reads a higher number of base pairs were excluded from the calculated distance matrix, compared to the high-accuracy methylation-aware Q10 base-calling of ONT data. Nonetheless, when using different qualities of ONT data with corresponding input parameters, the clustering of isolates were nearly identical.
Mapping social reward and punishment processing in the human brain: A voxel-based meta-analysis of neuroimaging findings using the Social Incentive Delay task
Authors: Martins D. , Rademacher L. , Gabay A. S. , Taylor R. , Richey J. A. , Smith D. , Goerlich K. S. , Nawijn L. , Cremers H.R. , Wilson R. , Bhattacharyya S. , Paloyelis Y. 
Published: May 2020

ABSTRACTSocial incentives (rewards or punishments) motivate human learning and behaviour, and alterations in the brain circuits involved in the processing social incentives have been linked with several neuropsychiatric disorders. However, questions still remain about the exact neural substrates implicated in social incentive processing. Here, we conducted four Anisotropic Effect Size Signed Differential Mapping voxel-based meta-analyses of fMRI studies investigating the neural correlates of the anticipation and receipt of social rewards and punishments using the Social Incentive Delay task. We map the regions involved in each of these four processes in the human brain, identify decreases in the BOLD signal during the anticipation of both social reward and punishment avoidance that were missed in individual studies due to a lack of power, and characterise the effect size and direction of changes in the BOLD signal for each brain area. Our results provide a better understanding of the brain circuitry involved in social incentive processing and can inform hypotheses about potentially disrupted brain areas linked with dysfunctional social incentive processing during disease.HighlightsVoxel-based meta-analysis of the neural underpinnings of social incentive processingWe map the brain regions involved in the processing of social incentives in humansWe identify new regions missed in individual studies as a result of lack of powerOur work can inform research on pathological brain processing of social incentives
A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders
Authors: Torshizi Abolfazl Doostparast , Duan Jubao , Wang Kai 
Published: May 2020

AbstractThe importance of cell type-specific gene expression in disease-relevant tissues is increasingly recognized in genetic studies of complex diseases. However, the vast majority of gene expression studies are conducted on bulk tissues, necessitating computational approaches to infer biological insights on cell type-specific contribution to diseases. Several computational methods are available for cell type deconvolution (that is, inference of cellular composition) from bulk RNA-Seq data, but cannot impute cell type-specific expression profiles. We hypothesize that with external prior information such as single cell RNA-seq (scRNA-seq) and population-wide expression profiles, it can be a computationally tractable and identifiable to estimate both cellular composition and cell type-specific expression from bulk RNA-Seq data. Here we introduce CellR, which addresses cross-individual gene expression variations by employing genome-wide tissue-wise expression signatures from GTEx to adjust the weights of cell-specific gene markers. It then transforms the deconvolution problem into a linear programming model while taking into account inter/intra cellular correlations, and uses a multi-variate stochastic search algorithm to estimate the expression level of each gene in each cell type. Extensive analyses on several complex diseases such as schizophrenia, Alzheimer’s disease, Huntington’s disease, and type 2 diabetes validated efficiency of CellR, while revealing how specific cell types contribute to different diseases. We conducted numerical simulations on human cerebellum to generate pseudo-bulk RNA-seq data and demonstrated its efficiency in inferring cell-specific expression profiles. Moreover, we inferred cell-specific expression levels from bulk RNA-seq data on schizophrenia and computed differentially expressed genes within certain cell types. Using predicted gene expression profile on excitatory neurons, we were able to reproduce our recently published findings on TCF4 being a master regulator in schizophrenia and showed how this gene and its targets are enriched in excitatory neurons. In summary, CellR compares favorably (both accuracy and stability of inference) against competing approaches on inferring cellular composition from bulk RNA-seq data, but also allows direct imputation of cell type-specific gene expression, opening new doors to re-analyze gene expression data on bulk tissues in complex diseases.
Alterations of multiple alveolar macrophage states in chronic obstructive pulmonary disease
Authors: Baßler Kevin , Fujii Wataru , Kapellos Theodore S. , Horne Arik , Reiz Benedikt , Dudkin Erika , Lücken Malte , Reusch Nico , Osei-Sarpong Collins , Warnat-Herresthal Stefanie , Wagner Allon , Bonaguro Lorenzo , Günther Patrick , Pizarro Carmen , Schreiber Tina , Becker Matthias , Händler Kristian , Wohnhaas Christian T. , Baumgartner Florian , Köhler Meike , Theis Heidi , Kraut Michael , Wadsworth Marc H. , Hughes Travis K. , Ferreira Humberto J. G. , Schulte-Schrepping Jonas , Hinkley Emily , Kaltheuner Ines H. , Geyer Matthias , Thiele Christoph , Shalek Alex K. , Feißt Andreas , Thomas Daniel , Dickten Henning , Beyer Marc , Baum Patrick , Yosef Nir , Aschenbrenner Anna C. , Ulas Thomas , Hasenauer Jan , Theis Fabian J. , Skowasch Dirk , Schultze Joachim L. 
Published: May 2020

AbstractDespite the epidemics of chronic obstructive pulmonary disease (COPD), the cellular and molecular mechanisms of this disease are far from being understood. Here, we characterize and classify the cellular composition within the alveolar space and peripheral blood of COPD patients and control donors using a clinically applicable single-cell RNA-seq technology corroborated by advanced computational approaches for: machine learning-based cell-type classification, identification of differentially expressed genes, prediction of metabolic changes, and modeling of cellular trajectories within a patient cohort. These high-resolution approaches revealed: massive transcriptional plasticity of macrophages in the alveolar space with increased levels of invading and proliferating cells, loss of MHC expression, reduced cellular motility, altered lipid metabolism, and a metabolic shift reminiscent of mitochondrial dysfunction in COPD patients. Collectively, single-cell omics of multi-tissue samples was used to build the first cellular and molecular framework for COPD pathophysiology as a prerequisite to develop molecular biomarkers and causal therapies against this deadly disease.
Mfd regulates RNA polymerase association with hard-to-transcribe regionsin vivo, especially those with structured RNAs
Authors: Ragheb Mark N. , Merrikh Christopher , Browning Kaitlyn , Merrikh Houra 
Published: May 2020

AbstractRNA polymerase (RNAP) encounters various roadblocks during transcription. These obstacles can impede RNAP movement, influence transcription, ultimately necessitating the activity of RNAP associated factors. One such factor is the bacterial protein Mfd; a highly conserved DNA translocase and evolvability factor that interacts with RNAP. Although Mfd is thought to function primarily in the repair of DNA lesions that stall RNAP, increasing evidence suggests that it may also be important for transcription regulation. However, this is yet to be fully characterized.To shed light on Mfd’sin vivofunctions, we identified the chromosomal regions where it associates. We analyzed Mfd’s impact on RNAP association and transcription regulation genome-wide. We found that Mfd represses RNAP association at many chromosomal regions. We found that these regions show increased RNAP pausing, suggesting that they are hard-to-transcribe. Interestingly, we noticed that the majority of the regions where Mfd regulates transcription contain highly structured regulatory RNAs. The RNAs identified regulate a myriad of biological processes, ranging from metabolism, to tRNA regulation, to toxin-antitoxin (TA) functions. We found that transcription regulation by Mfd, at least at some TA loci, is critical for cell survival. Lastly, we found that Mfd promotes mutagenesis in at least one toxin gene, suggesting that its function in regulating transcription may promote evolution of certain TA systems, and other regions containing strong RNA secondary structures. We conclude that Mfd is an RNAP co-factor that is important, and at times critical, for transcription regulation at hard-to-transcribe regions, especially those that express structured regulatory RNAs.SignificanceThe bacterial DNA translocase Mfd binds to stalled RNAPs and is generally thought to facilitate transcription-coupled DNA repair. Most of our knowledge about Mfd is based on data from biochemical studies. However, little is known about Mfd’s function in living cells, especially in the absence of exogenous DNA damage. Here, we show that Mfd modulates RNAP association and alters transcription at a variety of chromosomal loci, especially those containing highly structured, regulatory RNAs. As such, this work improves our understanding of Mfd’s function in living cells, and assigns it a new function as a transcription regulator.
Multifractality Nature of Microtubule Dynamic Instability Process
Authors: Rezania Vahid , Sudirga Ferry C. , Tuszynski Jack A. 
Published: May 2020

AbstractThe irregularity of growing and shortening patterns observed experimentally in microtubules reflects a dynamical system that fluctuates stochastically between assembly and disassembly phases. The observed time series of microtubule lengths have been extensively analyzed to shed light on structural and dynamical properties of microtubules. Here, for the first time, Multifractal Detrended Fluctuation analysis (MFDFA) has been employed to investigate the multifractal and topological properties of both experimental and simulated microtubule time series. We find that the time dependence of microtubule length possesses true multifractal characteristics and cannot be described by monofractal distributions. Based on the multifractal spectrum profile, a set of multifractal indices have been calculated that can be related to the level of dynamical activities of microtubules. We also show that the resulting multifractal spectra for the simulated data might not be comparable with experimental data.Statement of SignificanceMicrotubules are some of the most important subcellular structures involved in a multitude of functions in all eukaryotic cells. In addition to their cylindrical geometry, their polymerization/depolymerization dynamics, termed dynamic instability, is unique among all protein polymers. In this paper we demonstrate that there is a very specific mathematical representation of microtubule growth and shrinkage time series in terms of multifractality. We further show that using this characteristic, one can distinguish real experimental data from synthetic time series generated from computer simulations.
Motion opponency examined throughout visual cortex with multivariate pattern analysis of fMRI data
Authors: Silva Andrew E. , Thompson Benjamin , Liu Zili 
Published: May 2020

AbstractThis study explores how the human brain solves the challenge of flicker noise in motion processing. Despite providing no useful directional motion information, flicker is common in the visual environment and exhibits omnidirectional motion energy which is processed by low-level motion detectors. Models of motion processing propose a mechanism called motion opponency that reduces the processing of flicker noise. Motion opponency involves the pooling of local motion signals to calculate an overall motion direction. A neural correlate of motion opponency has been observed in human area MT+/V5 using fMRI, whereby stimuli with perfectly balanced motion energy constructed from dots moving in counter-phase elicit a weaker BOLD response than non-balanced (in-phase) motion stimuli. Building on this previous work, we used multivariate pattern analysis to examine whether the patterns of brain activation elicited by motion opponent stimuli resemble the activation elicited by flicker noise across the human visual cortex. Robust multivariate signatures of opponency were observed in V5 and in V3A. Our results support the notion that V5 is centrally involved in motion opponency and in the reduction of flicker noise during visual processing. Furthermore, these results demonstrate the utility of powerful multivariate analysis methods in revealing the role of additional visual areas, such as V3A, in opponency and in motion processing more generally.HighlightsOpponency is demonstrated in multivariate and univariate analysis of V5 data.Multivariate fMRI also implicates V3A in motion opponency.Multivariate analyses are useful for examining opponency throughout visual cortex.
Viral-Induced Alternative Splicing of Host Genes Promotes Influenza Replication
Authors: Thompson Matthew G , Dittmar Mark , Mallory Michael J , Bhat Prasanna , Ferretti Max B. , Fontoura Beatriz MA , Cherry Sara , Lynch Kristen W. 
Published: May 2020

AbstractViral infection induces the expression of numerous host genes that impact the outcome of infection. Here we show that infection of human lung epithelial cells with Influenza A virus (IAV) also induces a broad program of alternative splicing of host genes. While these splicing-regulated genes are not enriched for canonical regulators of viral infection, we find that many of these genes do impact replication of IAV. Moreover, specific inhibition of the IAV-induced splicing in several cases also attenuates viral infection. We further show that approximately a quarter of the IAV-induced splicing events are regulated by hnRNP K, a host protein that required for efficient splicing of the IAV M transcript in nuclear speckles. Notably, we find that hnRNP K accumulates in nuclear speckles upon IAV infection, which is likely to alter the accessibility of hnRNP K for host transcripts thereby leading to a program of host splicing changes that promote IAV replication.
Further biochemical profiling ofHypholoma fascicularemetabolome reveals its chemogenetic diversity
Authors: Al-Salihi Suhad A.A. , Bull Ian , Al-Salhi Raghad A. , Gates Paul J. , Salih Kifah , Bailey Andy M. , Foster Gary D. 
Published: May 2020

AbstractThere is a desperate need in continuing the search for natural products with novel mechanism to battle the constant increase of microbial drug resistance. Previously mushroom forming fungi were neglected as a source of novel antibiotics, due to the difficulties associated with their culture preparation and genetic tractability. However, modern fungal molecular and synthetic biology tools, renewed the interest in exploring mushroom fungi for novel therapeutics. The aim of this study was to have a comprehensive picture of nine basidiomycetes secondary metabolites (SM), screen their biological and chemical properties to describe the genetic pathways associated with their production.H. fascicularerevealed to be highly active antagonistic species, with antimicrobial activity against three different microorganisms -Bacillus subtilis, Escherichia coliandSaccharomyces cerevisiae-. Extensive genomic comparison and chemical analysis using analytical chromatography, led to the characterisation of more than 15 variant biosynthetic gene clusters and the first identification of a potent antibacterial metabolite-3, 5-dichloromethoxy benzoic acid (3, 5-D)-in this species, for which a biosynthetic gene cluster was predicted. This work demonstrates the great potential of mushroom forming fungi as a reservoir of bioactive natural products which are currently unexplored, and that access to their genomic data and structural diversity natural products via utilizing modern computational analysis and efficient chemical methods, could accelerate the development and applications of such distinct molecules in both pharmaceutical and agrochemical industry.
The Caribbean-Hispanic Alzheimer’s Brain Transcriptome Reveals Ancestry-Specific Disease Mechanisms
Authors: Felsky Daniel , Sariya Sanjeev , Santa-Maria Ismael , French Leon , Schneider Julie A. , Bennett David A. , Mayeux Richard , De Jager Philip L. , Tosto Giuseppe 
Published: May 2020

AbstractEthnicity impacts Alzheimer’s disease risk, especially among Caribbean-Hispanics. We report the first RNA-sequencing analysis of brain tissue from 45 Alzheimer’s disease and control Caribbean-Hispanics. Data were compared with two independent samples of non-Hispanic Caucasians (total n=729). By identifying and characterizing those genes with ancestry- and region-specific expression patterns in Alzheimer’s disease, we reveal molecular insights that may help explain epidemiological disparities in this understudied aging population.