bluuebunny/crossref_metadata_2025_split huggingface dataset:
Quantifying posterior effect size distribution of susceptibility loci by common summary statistics
Authors: Vsevolozhskaya Olga A. , Zaykin Dmitri V. 
Published: July 2019

AbstractTesting millions of SNPs in genetic association studies has become standard routine for disease gene discovery, followed by prioritization of the strongest signals based on the set of the smallest P-values. In light of recent re-evaluation of statistical practice, it has been suggested that P-values are unfit as summaries of statistical evidence. Despite this criticism, P-values are commonly used and are unlikely to be abandoned by practitioners. Moreover, P-values contain information that can be utilized to address the concerns about their flaws and misuse. We present a new method for utilizing evidence summarized by P-values for estimating odds ratio (OR) based on its approximate posterior distribution. In our method, only P-value, sample size, and standard deviation for log(OR) are needed as summaries of data, accompanied by a suitable prior distribution for log(OR) that can assume any shape. The parameter of interest, log(OR), is the only parameter with a specified prior distribution, hence our model is a mix of classical and Bayesian approaches. We show that our “Mix Bayes” (MB) method retains the main advantages of the Bayesian approach: it yields direct probability statements about hypotheses for OR and is resistant to biases caused by selection of top-scoring SNPs. MB enjoys greater flexibility than similarly inspired methods in the assumed distribution for the summary statistic and in the form of the prior for the parameter of interest. We illustrate our method by presenting interval estimates of effect size for reported genetic associations with lung cancer. Although we focus on OR, our method is not limited to this particular measure of effect size and can be used broadly for assessing reliability of findings in studies testing multiple predictors.
Evolutionary Analyses of RNA Editing and Amino Acid Recoding in Cephalopods
Authors: Wang Mingye (Christina) , Mohlhenrich Erik 
Published: July 2019

AbstractRNA editing is a post-transcriptional modification process that alters nucleotides of mRNA and consequently the amino acids of the translated protein without changing the original DNA sequence. In human and other mammals, amino acid recoding from RNA editing is rare, and most edits are non-adaptive and provide no fitness advantage (1). However, recently it was discovered that in soft-bodied cephalopods, which are exceptionally intelligent and include squid, octopus, and cuttlefish, RNA editing is widespread and positively selected (2). To examine the effects of RNA editing on individual genes, we developed a “diversity score” system that quantitatively assesses the amount of diversity generated in each gene, incorporating combinatorial diversity and the radicalness of amino acid changes. Using this metric, we compiled a list of top 100 genes across the cephalopod species that are most diversified by RNA editing. This list of candidate genes provides directions for future research into the specific functional impact of RNA editing in terms of protein structure and cellular function on individual proteins. Additionally, considering the connection of RNA editing to the nervous system, and the exceptional intelligence of cephalopod, the candidate genes may shed light to the molecular development of behavioral complexity and intelligence. To further investigate global influences of RNA editing on the transcriptome, we investigated changes in nucleotide composition and codon usage biases in edited genes and coleoid transcriptome in general. Results show that these features indeed correlate with editing and may correspond to causes or effects of RNA editing. In addition, we characterized the unusual RNA editing in cephalopods by analyzing ratio of radical to conservative amino acid substitutions (R/C) and distribution of amino acid recoding from editing. Our results show that compared to model organisms, editing in cephalopods have significantly decreased R/C ratio and distinct distribution of amino acid substitutions that favor conservative over radical changes, indicating selection at the amino acid level and providing a potential mechanism for the evolution of widespread RNA editing in cephalopods.
Attenuation of Motion Artifacts in fMRI using Discrete Reconstruction of Irregular fMRI Trajectories (DRIFT)
Authors: Parker David , Razlighi Qolamreza 
Published: July 2019

AbstractNumerous studies reported motion as the most detrimental source of noise and artifacts in functional magnetic resonance imaging (fMRI). Different approaches have been proposed and used to attenuate the effect of motion on fMRI data, including both prospective and retrospective (post-processing) techniques. However, each type of motion (e.g. translation versus rotation or in-plane versus out-of-plane) has a distinct effect on the MR signal, which is not fully understood nor appropriately modeled in the field. In addition, effects of the same motion can be substantially different depending on when it occurs during the pulse sequence (e.g. RF excitation, gradient encoding, or k-space read-out). Thus, each distinct kind of motion and the time of its occurrence may require a unique approach to be optimally corrected. Therefore, we start with an investigation of the effects of different motions on the MR signal based on the Bloch equation. We then simulate their unique effects with a comprehensive fMRI simulator. Our results indicate that current motion correction methods fail to completely address the motion problem. Retrospective techniques such as spatial realignment can correct for between-volume misalignment, but fail to address within volume contamination and spin-history artifacts. Because of the steady state nature of the fMRI acquisition, spin-history artifacts arising from over/under excitation during slice-selection causes the motion artifacts to contaminate MR signal even after cessation of motion, which makes it challenging to be corrected retrospectively. Prospective motion correction has been proposed to prevent spin-history artifacts, but fails to address motion artifacts during k-space readout. In this article, we propose a novel method to remove these artifacts: Discrete reconstruction of irregular fMRI trajectory (DRIFT). Our method calculates the exact displacement of k-space recording due to motion at each dwell time and retrospectively corrects each slice of the fMRI volume using an inverse nonuniform Fourier transform. We evaluate our proposed methods using simulated data as well as fMRI data collected from a rotating phantom inside a 3T Siemens Prisma scanner. We conclude that a hybrid approach with both prospective and retrospective components are essentially required for optimal removal of motion artifacts from the fMRI data.
Functional divergence of two duplicatedFertilization Independent Endospermgenes in rice with respect to seed development
Authors: Pan Meiyao , Cheng Xiaojun , Zhiguo E , Niu Baixiao , Chen Chen 
Published: July 2019

AbstractFertilization Independent Endosperm (FIE) is an essential member of Polycomb Repression Complex 2 (PRC2) that plays important roles in the developmental regulation of plants.OsFIE1andOsFIE2are twoFIEhomologs in the rice genome. Here, we showed thatOsFIE1probably duplicated fromOsFIE2after the origin of the tribe Oryzeae, but has a specific expression pattern and methylation landscape. During evolution,OsFIE1underwent a less intensive purifying selection than didOsFIE2. The mutantosfie1produced smaller seeds and displayed reduced dormancy, indicating thatOsFIE1predominantly functions in late seed development. Ectopic expression ofOsFIE1, but notOsFIE2, was deleterious to vegetative growth in a dosage-dependent manner. The newly evolved N-terminal tail of OsFIE1 was probably not the cause of the adverse effects on vegetative growth. The CRISPR/Cas9-derived mutantosfie2exhibited impaired cellularization of the endosperm, which suggested thatOsFIE2is indispensable for early seed development as a positive regulator of cellularization. Autonomous endosperm was observed in bothOsFIE2+−andosfie1/OsFIE2+−but at a very low frequency. Although OsFIE1-PRC2 exhibited H3K27me3 methyltransferase ability in plants, OsFIE1-PRC2 is likely to be less important for development in rice than is OsFIE2-PRC2. Our findings revealed the functional divergence ofOsFIE1andOsFIE2and shed light on their distinct evolution following duplication.
Retroconversion of estrogens into androgens by bacteriaviaa cobalamin-mediated methylation
Authors: Wang Po-Hsiang , Chen Yi-Lung , Wei Sean Ting-Shyang , Wu Kan , Lee Tzong-Huei , Wu Tien-Yu , Chiang Yin-Ru 
Published: July 2019

AbstractSteroid estrogens modulate physiology and development of vertebrates. Biosynthesis of C18estrogens from C19androgens by the O2-dependent aromatase is thought to be irreversible. Here, we report a denitrifyingDenitratisomasp. strain DHT3 capable of catabolizing estrogens or androgens anaerobically. Strain DHT3 genome contains a polycistronic gene clusteremtABCDdifferentially transcribed under estrogen-fed conditions.emtABCDencodes a cobalamin-dependent methyltransferase system conserved among estrogen-utilizing anaerobes;emtA-disrupted strain DHT3 can catabolize androgens but not estrogens. These data, along with the observed androgen production in estrogen-fed strain DHT3 cultures, indicate the occurrence of a cobalamin-mediated estrogen methylation to form androgens. Consistently, the estrogen conversion into androgens in strain DHT3 cell-extracts requires methylcobalamin and is inhibited by propyl-iodide, a specific inhibitor of cobalamin-dependent enzymes. The identification of the cobalamin-mediated estrogen methylation thus represents an unprecedented metabolic link between cobalamin and steroid metabolism and suggests that retroconversion of estrogens into androgens occurs in the biosphere.
Mutational Crosstalk between Nuclear Driver Genes and Mitochondrial DNA in Gingivobuccal Oral Cancer
Authors: Palodhi Arindam , Sarkar Soumi , Maitra Arindam 
Published: July 2019

AbstractSomatic alterations in nuclear and mitochondrial genomes are known to play important role in the initiation and progress of tumours. However, crosstalk between these two genomic components in tumours have not been well investigated till date. We have excavated evidence of such crosstalk in gingivobuccal oral cancer. We have identified significant correlation between somatic mutations in nuclear driver genes and mitochondrial genes in 89 gingivobuccal oral cancer patients. Strong positive correlation between nuclear driver genes CASP8, NOTCH1, USP9X, TRPM3 and mitochondrial genes has been observed. Patients having mutations in nuclear driver genes except TP53, were also shown to harbour higher mitochondrial mutation load. TP53 mutations were shown to be negatively correlated with somatic mutations in mitochondrial 12S rRNA and ATP6. Also, TP53 mutations were negatively correlated with mutations in NOTCH1, HRAS and USP9X. We have identified a number of nuclear genes coexpressed with mitochondrial genes, although their association with tumorigenesis could not be established. Our observations suggest that in the absence of mutations in TP53, mutations in mtDNA and other driver genes might aid in the progression of cancer in a complementary fashion.
Serotonergic treatment normalizes midbrain dopaminergic neuron increase after periaqueductal gray stimulation-induced anticipatory fear in a rat model
Authors: Tan Shawn Zheng Kai , Temel Yasin , Chan Ariel Yovela , Mok Andrea Tsz Ching , Perucho Jose Angelo Udal , Blokland Arjan , Acquili Luca , Lim Wei Ling , Lim Lee Wei 
Published: July 2019

AbstractBackgroundElectrical stimulation of the dorsolateral periaqueductal gray (dlPAG) in rats has been shown to elicit panic-like behaviour and can be a useful tool for modelling anticipatory fear and agoraphobia.MethodsIn this study, we further analysed our previous data on the effects of escitalopram (a selective serotonin reuptake inhibitor, SSRI) and buspirone (a 5-HT1A receptor partial agonist) on dlPAG-induced anticipatory fear behaviour in a rat model using freezing as a measure. We then used tyrosine hydroxylase (TH) immunohistochemistry to probe the effects on dopaminergic neurons.ResultsAlthough acute treatment of escitalopram, but not buspirone, was effective in reducing anticipatory freezing behaviour, chronic administrations of both drugs were comparably effective. We found that the number of dopaminergic neurons in the ventral tegmental area (VTA) was lowered in both chronic buspirone and escitalopram groups. We showed a strong correlation between the number of dopaminergic neurons and freezing in the VTA. We further showed positive correlations between dopaminergic neurons in the VTA and substantia nigra pars compacta in escitalopram and buspirone groups, respectively.LimitationsAlthough our data strongly hint to a role of dopaminergic mechanisms in the dlPAG induced fear response, more in-depth studies with larger sample sizes are needed to understand the neuronal mechanisms underlying the interactions between serotonergic drugs and dopaminergic cell number and fear behavior.ConclusionChronic treatment with an SSRI and a 5-HT1A agonist decrease the number of dopaminergic neurons in the VTA. These effects seem to be associated with reduced dlPAG-induced anticipatory freezing behaviour.Key PointsChronic treatment of escitalopram and buspirone was effective in reducing dlPAG induced anticipatory freezing behaviour.The number of dopaminergic neurons in the ventral tegmental area (VTA) was lowered in both chronic buspirone and escitalopram groups and was correlated to freezing.We found positive correlations between dopaminergic neurons in the VTA and substantia nigra pars compacta in escitalopram and buspirone groups, respectively.
Mathematical modeling of the role of α-synuclein and dopamine in cell death in Parkinson’s disease provides the molecular basis to the toxicity of different point mutations
Authors: Saxena Gourvendu , Khandelwal Utkarsh , Doble Mukesh 
Published: July 2019

ABSTRACTDifferent types of α-synuclein and non-β-amyloid component (NAC) peptides have been shown to induce cell death, with varying degree of toxicity, in various in vitro experiments. Oxidative stress has also been associated and proved to be involved in the pathogenesis of neuronal cell death in Parkinson’s disease. Oxidative stress has been shown to accelerate the aggregation of α-synuclein in vitro and in resent studies α-synuclein has been shown to increase oxidative stress. Thus it seems like a vicious cycle, one promoting the other.In this present work we have modeled the α-synuclein pathway to increase cytoplasmic Dopamine concentration, and thereby increasing the Reactive Oxygen Species (ROS) level of the cell, which consequently results in cell death. This model relates the α-synuclein concentration with the fractional cell survival and provides insight of crucial reaction(s) of α-synuclein which promote cell death. It predicts the toxicity of the type of α-synuclein and also explains the pattern of cell death with increasing concentration of α-synuclein. First we modeled a part of the pathway i.e. from dopamine to cell death. The results were compared with experimental data available for PC12 neuronal cell line. Then modeling of full pathway was done and the results were compared with experimental data available for Human neuroblastoma SH-SY5Y cells. It is predicted from this model that higher the auto catalysis of dopamine, higher is the cell death. Interestingly, the model predicts that NAC (1-18) not only hinders the vesicles coming from Endoplasmic Reticulum, to fuse with Golgi bodies, but also reduces the synthesis of Dopamine and the formation of vesicles from Endoplasmic Reticulum. The model is generalized and can predict the toxicity of any protein which impedes the early secretary pathway in dopaminergic cells and also the cell survival pattern with increasing concentration of the protein.
MicroRNA clusters integrate evolutionary constraints on expression and target affinities: the miR-6/5/4/286/3/309 cluster in Drosophila leg development
Authors: Qu Zhe , Yiu Wing Chung , Yip Ho Yin , Nong Wenyan , Yu Clare W.C. , Lee Ivy H.T. , Wong Annette Y.P. , Wong Nicola W.Y. , Cheung Fiona K.M. , Chan Ting Fung , Lau Kwok Fai , Zhong Silin , Chu Ka Hou , Tobe Stephen S. , Ferrier David E.K. , Bendena William G. , Hui Jerome H.L. 
Published: July 2019

AbstractA striking feature of microRNAs is that they are often clustered in the genomes of animals. The functional and evolutionary consequences of this clustering remain obscure. Here, we investigated a microRNA cluster miR-6/5/4/286/3/309 that is conserved across drosophilid lineages. Small RNA sequencing revealed expression of this microRNA cluster in Drosophila melanogaster leg discs, and conditional overexpression of the whole cluster resulted in leg appendage shortening. Transgenic overexpression lines expressing different combinations of microRNA cluster members were also constructed. Expression of individual microRNAs from the cluster resulted in a normal wild-type phenotype, but either the expression of several ancient microRNAs together (miR-5/4/286/3/309) or more recently evolved clustered microRNAs (miR-6-1/2/3) can recapitulate the phenotypes generated by the whole-cluster overexpression. Screening of transgenic fly lines revealed down-regulation of leg patterning gene cassettes in generation of the leg-shortening phenotype. Furthermore, cell transfection with different combinations of microRNA cluster members revealed a suite of downstream genes targeted by all cluster members, as well as complements of targets that are unique for distinct microRNAs. Considering together the microRNA targets and the evolutionary ages of each microRNA in the cluster demonstrates the importance of microRNA clustering, where new members can reinforce and modify the selection forces on both the cluster regulation and the gene regulatory network of existing microRNAs.
The impact of genistein supplementation on tendon functional properties and gene expression in estrogen deficient rats
Authors: Carroll Chad C. , Patel Shivam H. , Simmons Jessica , Gordon Ben DH. , Olson Jay F. , Chemelewski Kali , Saw Shannon , Hale Taben M. , Howden Reuben , Sabbaghi Arman 
Published: July 2019

ABSTRACTPurposeTendinopathy risk increases with menopause. The phytoestrogen genistein prevents collagen loss during estrogen deficiency [ovariectomy (OVX)]. The influence of genistein on tendon function and extracellular matrix (ECM) regulation are not well known. We determined the impact of genistein on tendon function and examined potential mechanisms by which genistein alters tendon ECM.Materials and MethodsEight-week-old rats (n=42) were divided into three groups: intact, OVX, or OVX-genistein (6mg/kg/day) for 6-weeks. Tail fascicles were assessed with a Deben tensile stage. Achilles tendon mRNA expression was determined with digital droplet PCR. Tendon-derived fibroblasts were also treated with genistein in the presence of estrogen receptor (ER) antagonists.ResultsCompared to intact, stress tended to be lower in untreated OVX rats (p=0.022). Further, modulus and energy density were greater in genistein-treated rats (p<0.05) compared to intact. Neither OVX nor genistein altered expression of Col1a1, Col3a1, Casp3, Casp8, Mmp1a, Mmp2, or Mmp9 (p>0.05). Compared to intact, Tnmd and Esr1 expression was greater and Pcna and Timp1 expression lower in OVX rats (p<0.05). Genistein treatment returned Tnmd, Pcna, and Timp1 to levels of Intact-Vehicle (p<0.05), but did not alter Scx or Esr1 (p>0.05). Several β-catenin/Wnt signaling related molecules were not altered by OVX or genistein (p>0.05).In vitro, genistein blunted cell proliferation but not via ERs.ConclusionsOur findings demonstrate that genistein improves tendon function. Genistein inhibits cell proliferationin vitrobut not via ER. The effect of genisteinin vivowas predominately on genes related to cell proliferation rather than collagen remodeling.
Multifaceted adaptation of the neural decision process with prior knowledge of time constraints and stimulus probability
Authors: Kelly Simon P. , Corbett Elaine A. , O’Connell Redmond G. 
Published: July 2019

AbstractWhen selecting actions in response to noisy sensory stimuli, the brain can exploit prior knowledge of time constraints, stimulus discriminability and stimulus probability to hone the decision process. Although behavioral models typically explain such effects through adjustments to decision criteria only, the full range of underlying neural process adjustments remains to be established. Here, we draw on human neurophysiological signals reflecting decision formation to construct and constrain a multi-tiered model of prior-informed motion discrimination, in which a motor-independent representation of cumulative evidence feeds build-to-threshold motor signals that receive additional dynamic urgency and bias signal components. The neurally-informed model not only provides a superior quantitative fit to prior-biased behavior across three distinct task regimes (easy, time-pressured and weak evidence), but also reveals adjustments to evidence accumulation rate, urgency rate, and the timing of accumulation onset and motor execution which go undetected or are discrepant in more standard diffusion-model analysis of behavior.
Alignment of LC-MS Profiles by Neighbor-wise Compound-specific Graphical Time Warping with Misalignment Detection
Authors: Wu Chiung-Ting , Herrington David M. , Wang Yizhi , Ebbels Timothy , Karaman Ibrahim , Wang Yue , Yu Guoqiang 
Published: July 2019

AbstractMotivationLiquid chromatography - mass spectrometry (LC-MS) is a standard method for proteomics and metabolomics analysis of biological samples. Unfortunately, it suffers from various changes in the retention times (RT) of the same compound in different samples, and these must be subsequently corrected (aligned) during data processing. Classic alignment methods such as in the popular XCMS package often assume a single time-warping function for each sample. Thus, the potentially varying RT drift for compounds with different masses in a sample is neglected in these methods. Moreover, the systematic change in RT drift across run order is often not considered by alignment algorithms. Therefore, these methods cannot completely correct misalignments. For a large-scale experiment involving many samples, the existence of misalignment becomes inevitable and concerning.ResultsHere we describe an integrated reference-free profile alignment method, neighbor-wise compound-specific Graphical Time Warping (ncGTW), that can detect misaligned features and align profiles by leveraging expected RT drift structures and compound-specific warping functions. Specifically, ncGTW uses individualized warping functions for different compounds and assigns constraint edges on warping functions of neighboring samples. Validated with both realistic synthetic data and internal quality control samples, ncGTW applied to two large-scale metabolomics LC-MS datasets identifies many misaligned features and successfully realigns them. These features would otherwise be discarded or uncorrected using existing methods. The ncGTW software tool is developed currently as a plug-in to the XCMS package.Availability and ImplementationAn R package of ncGTW is freely available at https://github.com/ChiungTingWu/ncGTW. A detailed user’s manual and a vignette are provided within the package.Contactyuewang@vt.edu, yug@vt.eduSupplementary informationSupplementary data are available at Bioinformatics online.