bluuebunny/crossref_metadata_2025_split huggingface dataset:
Analysis and Modeling of Precipitation Intermittency by Compound Markov‐DARMA Models
Authors: Wiuff Rasmus 
Published: December 2019

AbstractIntermittency in precipitation is analyzed by a new class of stochastic models consisting of the product of two binary stochastic models. The ingoing models in these compound models are confined to a one‐parameter white noise model and either a first‐order or a second‐order autoregressive model, which is described by two or three parameters, respectively. The two resulting second‐order compound models have three and four parameters, respectively. Expressions of these parameters are derived, as well as equations with which to assess the parameters in the ingoing models based on the parameters in the compound models. The compound models are shown to differ considerably from the usual Markov models and discrete autoregressive moving average (DARMA) models. Daily binary precipitation time series from Copenhagen, Denmark, and Alice Springs, Australia, are analyzed by depicting the Markovian transition probabilities in probability trees with time lags of up to 5 days, resulting in 32 branches. Each tree is a kind of signature for the time series considered, but only a few of the branches, typically 3–4, are significant. Furthermore, the significant parts of the trees are rather skewed due to the intermittency of the precipitation process. This skewness makes the application of usual Markov and DARMA models less effective, whereas the new compound models better explain the observations. Based on one of the two new models, explicit but approximate expressions for the cumulative distribution (or the return period) of the durations of wet and dry spells are derived and compared to the observations from Copenhagen.
Sensitivity Analysis of Fully Distributed Parameterization Reveals Insights Into Heterogeneous Catchment Responses for Water Quality Modeling
Authors: Yang Xiaoqiang , Jomaa Seifeddine , Rode Michael 
Published: December 2019

AbstractSpatially distributed parameterization is preferable in capturing the heterogeneity of catchment properties and in allowing a better model representation of catchment responses. In hydrological modeling, sensitivity analysis is recommended to address the high‐dimensional parametric problems. However, less has been focused on water quality modeling, presumably due to the lack of suitable fully distributed models. Based on the newly developed mesoscale hydrological‐nitrate model, we investigated for the first time the spatially distributed sensitivity of nitrate model parameters and correlated the sensitivity indices with multiple catchment characteristics. The study was conducted in the highly heterogeneous Selke catchment, central Germany. Three nested catchments were defined based on the heterogeneous catchment responses (gauged by three nested stations). Results showed that parameters of soil denitrification, in‐stream denitrification, and in‐stream assimilatory uptake were the most sensitive parameters throughout the catchment. They all showed high spatial variability, which also varied when different gauging stations were considered. Spearman rank correlation indicated that the sensitivity of soil denitrification was controlled mainly by the relative limitations between the terrestrial hydrological transport capacity and the soil nitrate availability; the sensitivity of in‐stream processes was predominated by the spatial variability within the river network (e.g., the proximity to the gauging station), rather than the local biogeochemical factors. Based on the insights gained from the spatial sensitivity and correlation analyses, we suggested that an appropriate monitoring scheme is important in reflecting actual catchment responses, and a cautious statistical correlation is informative in benefiting future parameter regionalization of water quality models.
Limits on Groundwater‐Surface Water Fluxes Derived from Temperature Time Series: Defining Resolution‐Based Thresholds
Authors: Glose Thomas J. , Lowry Christopher S. , Hausner Mark B. 
Published: December 2019

AbstractHeat as a tracer is frequently used to quantify Darcy fluxes across the groundwater‐surface water interface. Often quantified through the analysis of diurnal or annual periodic temperature signals, these temperature time series methods rely on the advective transport of heat by flowing water perturbing the periodic conducted heat signal. Multiple methodologies have been developed that rely on temperature time series data collected from at least two unique depths a set distance apart. However, the lower limits at which these methods can no longer reliably quantify a Darcy flux are not well established. To examine these lower limits, synthetic temperature time series data were generated using a numerical model for various combinations of head gradients, sensor spacing, and thermal properties of the sediment. Darcy fluxes were subsequently quantified using the combined method and directly compared to prescribed Darcy fluxes. The dimensionless Péclet number, representing the ratio of advective to conductive heat flux, was used to establish threshold values at which the combined amplitude ratio and phase shift method was no longer able to reliably quantify a Darcy flux. The lowest recharge Darcy flux that can be quantified ranges from 0.07 to 0.2 m/day, dependent on the resolution of the sensor used to collect data, a narrower range than previously reported. When transitioning to a field setting, where the accuracy of Darcy fluxes is not known, a newly developed relationship between the true and inferred Péclet numbers can be used to evaluate quantified Darcy fluxes for accuracy.
Resolving Drivers of a Spatial Gradient in Evapotranspiration Through the Simulated Translocation of Landscape Factors
Authors: Jepsen S.M. , Harmon T.C. 
Published: December 2019

AbstractA number of studies using the so‐called space‐for‐time substitution (STS) approach have predicted that climate warming of snow‐influenced watersheds would result in alarming increases in long‐term ET and concurrent decreases in runoff. This empirical approach implicitly assumes that any spatial covariation of factors across the landscape would remain fixed in time, that is, the “covariance‐stationarity” assumption. A better understanding of this assumption, in terms of what it means and how it affects predictions, is needed to assess the implications of STS predictions. To address this, we examined the influence of the covariance‐stationarity assumption on STS predictions of long‐term ET in response to warming. We did this by simulating changes in ET resulting from elevational transfers of factors in ways that emulate STS. This approach was applied to the upper San Joaquin River, a snow‐influenced watershed in the Sierra Nevada, USA. Predicted increases in ET from STS including the covariance‐stationarity assumption were 3–7 times greater than STS treating air temperature as an independent factor, over most of the higher elevations. Based on results from a factorial analysis, these differences were attributed primarily to the pedologic gradient across elevation, which transitions from loamy Alfisol soils at lower elevations to sandy Entisol/Inceptisol soils and exposed bedrock at upper elevations. The covariance‐stationarity assumption does not seem realistic for soil and air temperature over timescales of projected climate. Therefore, the confounding of these factors in the STS approach can substantially overestimate the sensitivity of long‐term ET to air temperature.
Identification of novel FBN1 variations implicated in congenital scoliosis
Authors: Lin Mao , Zhao Sen , Liu Gang , Huang Yingzhao , Yu Chenxi , Zhao Yanxue , Wang Lianlei , Zhang Yuanqiang , Yan Zihui , Wang Shengru , Liu Sen , Liu Jiaqi , Ye Yongyu , Chen Yaping , Yang Xu , Tong Bingdu , Wang Zheng , Yang Xinzhuang , Niu Yuchen , Li Xiaoxin , Wang Yipeng , Su Jianzhong , Yuan Jian , Zhao Hengqiang , Zhang Shuyang , Qiu Guixing ,   on behalf of the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) study, Qiu Guixing , Wu Zhihong , Zhang Jianguo , Wu Nan , Wang Shengru , Liu Jiaqi , Liu Sen , Zuo Yuzhi , Liu Gang , Zhang Yuanqiang , Yu Chenxi , Zhao Sen , Wang Lianlei , Zhao Yanxue , Yan Zihui , Yang Xinzhuang , Zhao Hengqiang , Niu Yuchen , Li Xiaoxin , Lin Mao , Ikegawa Shiro , Zhang Jianguo , Wu Zhihong , Wu Nan 
Published: December 2019

AbstractCongenital scoliosis (CS) is a form of scoliosis caused by congenital vertebral malformations. Genetic predisposition has been demonstrated in CS. We previously reported that TBX6 loss-of-function causes CS in a compound heterozygous model; however, this model can explain only 10% of CS. Many monogenic and polygenic CS genes remain to be elucidated. In this study, we analyzed exome sequencing (ES) data of 615 Chinese CS from the Deciphering Disorders Involving Scoliosis and COmorbidities (DISCO) project. Cosegregation studies for 103 familial CS identified a novel heterozygous nonsense variant, c.2649G>A (p.Trp883Ter) in FBN1. The association between FBN1 and CS was then analyzed by extracting FBN1 variants from ES data of 574 sporadic CS and 828 controls; 30 novel variants were identified and prioritized for further analyses. A mutational burden test showed that the deleterious FBN1 variants were significantly enriched in CS subjects (OR = 3.9, P = 0.03 by Fisher’s exact test). One missense variant, c.2613A>C (p.Leu871Phe) was recurrent in two unrelated CS subjects, and in vitro functional experiments for the variant suggest that FBN1 may contribute to CS by upregulating the transforming growth factor beta (TGF-β) signaling. Our study expanded the phenotypic spectrum of FBN1, and provided nove insights into the genetic etiology of CS.
A novel CDK9 inhibitor increases the efficacy of venetoclax (ABT-199) in multiple models of hematologic malignancies
Authors: Phillips Darren C. , Jin Sha , Gregory Gareth P. , Zhang Qi , Xue John , Zhao Xiaoxian , Chen Jun , Tong Yunsong , Zhang Haichao , Smith Morey , Tahir Stephen K. , Clark Rick F. , Penning Thomas D. , Devlin Jennifer R. , Shortt Jake , Hsi Eric D. , Albert Daniel H. , Konopleva Marina , Johnstone Ricky W. , Leverson Joel D. , Souers Andrew J. 
Published: December 2019

AbstractMCL-1 is one of the most frequently amplified genes in cancer, facilitating tumor initiation and maintenance and enabling resistance to anti-tumorigenic agents including the BCL-2 selective inhibitor venetoclax. The expression of MCL-1 is maintained via P-TEFb-mediated transcription, where the kinase CDK9 is a critical component. Consequently, we developed a series of potent small-molecule inhibitors of CDK9, exemplified by the orally active A-1592668, with CDK selectivity profiles that are distinct from related molecules that have been extensively studied clinically. Short-term treatment with A-1592668 rapidly downregulates RNA pol-II (Ser 2) phosphorylation resulting in the loss of MCL-1 protein and apoptosis in MCL-1-dependent hematologic tumor cell lines. This cell death could be attenuated by either inhibiting caspases or overexpressing BCL-2 protein. Synergistic cell killing was also observed between A-1592668 or the related analog A-1467729, and venetoclax in a number of hematologic cell lines and primary NHL patient samples. Importantly, the CDK9 inhibitor plus venetoclax combination was well tolerated in vivo and demonstrated efficacy superior to either agent alone in mouse models of lymphoma and AML. These data indicate that CDK9 inhibitors could be highly efficacious in tumors that depend on MCL-1 for survival or when used in combination with venetoclax in malignancies dependent on MCL-1 and BCL-2.
CHIMGEN: a Chinese imaging genetics cohort to enhance cross-ethnic and cross-geographic brain research
Authors:   for the CHIMGEN Consortium, Xu Qiang , Guo Lining , Cheng Jingliang , Wang Meiyun , Geng Zuojun , Zhu Wenzhen , Zhang Bing , Liao Weihua , Qiu Shijun , Zhang Hui , Xu Xiaojun , Yu Yongqiang , Gao Bo , Han Tong , Yao Zhenwei , Cui Guangbin , Liu Feng , Qin Wen , Zhang Quan , Li Mulin Jun , Liang Meng , Chen Feng , Xian Junfang , Li Jiance , Zhang Jing , Zuo Xi-Nian , Wang Dawei , Shen Wen , Miao Yanwei , Yuan Fei , Lui Su , Zhang Xiaochu , Xu Kai , Zhang Long Jiang , Ye Zhaoxiang , Yu Chunshui 
Published: December 2019

AbstractThe Chinese Imaging Genetics (CHIMGEN) study establishes the largest Chinese neuroimaging genetics cohort and aims to identify genetic and environmental factors and their interactions that are associated with neuroimaging and behavioral phenotypes. This study prospectively collected genomic, neuroimaging, environmental, and behavioral data from more than 7000 healthy Chinese Han participants aged 18–30 years. As a pioneer of large-sample neuroimaging genetics cohorts of non-Caucasian populations, this cohort can provide new insights into ethnic differences in genetic-neuroimaging associations by being compared with Caucasian cohorts. In addition to micro-environmental measurements, this study also collects hundreds of quantitative macro-environmental measurements from remote sensing and national survey databases based on the locations of each participant from birth to present, which will facilitate discoveries of new environmental factors associated with neuroimaging phenotypes. With lifespan environmental measurements, this study can also provide insights on the macro-environmental exposures that affect the human brain as well as their timing and mechanisms of action.
Resting-state functional connectivity in women with PMDD
Authors: Petersen Nicole , Ghahremani Dara G. , Rapkin Andrea J. , Berman Steven M. , Wijker Noor , Liang Letty , London Edythe D. 
Published: December 2019

Abstract
Background
Premenstrual dysphoric disorder (PMDD) is an understudied, debilitating disorder of women. Given evidence for prefrontal cortical and limbic dysfunction in PMDD, we compared intrinsic connectivity of the executive control network (ECN), default mode network (DMN), and amygdala in women with PMDD vs. controls.

Methods
Thirty-six women (18 PMDD, 18 control) participated in fMRI during the follicular and luteal phases of the menstrual cycle. At each time, resting-state functional connectivity was evaluated both before and after participants performed an emotion regulation task. The ECN was identified using independent components analysis, and connectivity of left and right amygdala seeds was also evaluated.

Results
Nonparametric permutation testing identified a cluster in the left middle temporal gyrus (MTG) with significantly stronger connectivity to the left ECN in women with PMDD vs. controls in all four fMRI sessions. Women with PMDD exhibited no difference in functional connectivity between menstrual cycle phases. Amygdala connectivity did not differ between the groups but differed significantly with menstrual phase, with left amygdala connectivity to cingulate cortex being significantly stronger during the follicular vs. luteal phase. Right amygdala connectivity to the middle frontal gyrus was also stronger during the follicular vs. luteal phase, with no group differences. These findings suggest that women with PMDD have different intrinsic network dynamics in the left executive control network compared to healthy controls.
Comprehensive detection of recurring genomic abnormalities: a targeted sequencing approach for multiple myeloma
Authors: Yellapantula Venkata , Hultcrantz Malin , Rustad Even H. , Wasserman Ester , Londono Dory , Cimera Robert , Ciardiello Amanda , Landau Heather , Akhlaghi Theresia , Mailankody Sham , Patel Minal , Medina-Martinez Juan Santiago , Arango Ossa Juan Esteban , Levine Max Fine , Bolli Niccolo , Maura Francesco , Dogan Ahmet , Papaemmanuil Elli , Zhang Yanming , Landgren Ola 
Published: December 2019

AbstractRecent genomic research efforts in multiple myeloma have revealed clinically relevant molecular subgroups beyond conventional cytogenetic classifications. Implementing these advances in clinical trial design and in routine patient care requires a new generation of molecular diagnostic tools. Here, we present a custom capture next-generation sequencing (NGS) panel designed to identify rearrangements involving the IGH locus, arm level, and focal copy number aberrations, as well as frequently mutated genes in multiple myeloma in a single assay. We sequenced 154 patients with plasma cell disorders and performed a head-to-head comparison with the results from conventional clinical assays, i.e., fluorescent in situ hybridization (FISH) and single-nucleotide polymorphism (SNP) microarray. Our custom capture NGS panel had high sensitivity (>99%) and specificity (>99%) for detection of IGH translocations and relevant chromosomal gains and losses in multiple myeloma. In addition, the assay was able to capture novel genomic markers associated with poor outcome such as bi-allelic events involving TP53. In summary, we show that a multiple myeloma designed custom capture NGS panel can detect IGH translocations and CNAs with very high concordance in relation to FISH and SNP microarrays and importantly captures the most relevant and recurrent somatic mutations in multiple myeloma rendering this approach highly suitable for clinical application in the modern era.
The paternal and maternal genetic history of Vietnamese populations
Authors: Macholdt Enrico , Arias Leonardo , Duong Nguyen Thuy , Ton Nguyen Dang , Van Phong Nguyen , Schröder Roland , Pakendorf Brigitte , Van Hai Nong , Stoneking Mark 
Published: December 2019

AbstractVietnam exhibits great cultural and linguistic diversity, yet the genetic history of Vietnamese populations remains poorly understood. Previous studies focused mostly on the majority Kinh group, and thus the genetic diversity of the many other groups has not yet been investigated. Here we analyze complete mtDNA genome sequences and ~2.3 Mb sequences of the male-specific portion of the Y chromosome from the Kinh and 16 minority populations, encompassing all five language families present in Vietnam. We find highly variable levels of diversity within and between groups that do not correlate with either geography or language family. In particular, the Mang and Sila have undergone recent, independent bottlenecks, while the majority group, Kinh, exhibits low levels of differentiation with other groups. The two Austronesian-speaking groups, Giarai and Ede, show a potential impact of matrilocality on their patterns of variation. Overall, we find that isolation, coupled with limited contact involving some groups, has been the major factor influencing the genetic structure of Vietnamese populations, and that there is substantial genetic diversity that is not represented by the Kinh.
PINK1 phosphorylates ubiquitin predominantly in astrocytes
Authors: Barodia Sandeep K. , McMeekin Laura J. , Creed Rose B. , Quinones Elijah K. , Cowell Rita M. , Goldberg Matthew S. 
Published: December 2019

AbstractLoss-of-function mutations in PINK1 are causally linked to recessively inherited Parkinson’s disease (PD), with marked loss of dopaminergic neurons in the substantia nigra that are required for normal movement. PINK1 is a nuclear-encoded mitochondrial-targeted kinase that phosphorylates a conserved serine at amino acid 65 (pS65) in ubiquitin as well as Parkin, another gene with loss-of-function mutations linked to recessive parkinsonism. The steady-state levels of PINK1 protein are very low, even in cells that express PINK1, because PINK1 is normally targeted for degradation after mitochondrial import by a process that is dependent upon mitochondrial membrane potential. Dissipation of the mitochondrial membrane potential with ionophores, such as CCCP and valinomycin, causes the accumulation of PINK1 on the outer mitochondrial membrane, a marked increase of pS65-ubiquitin and the recruitment of Parkin, which targets dysfunctional mitochondria for degradation by autophagy. While the high penetrance of PINK1 mutations establish its critical function for maintaining neurons, the activity of PINK1 in primary neurons has been difficult to detect. Mounting evidence implicates non-neuronal cells, including astrocytes and microglia, in the pathogenesis of both idiopathic and inherited PD. Herein we used both western analysis and immunofluorescence of pS65-ubiquitin to directly compare the activity of PINK1 in primary neurons, astrocytes, microglia, and oligodendrocyte progenitor cells cultured from the brains of wild-type (WT) and PINK1 knockout (KO) rat pups. Our findings that PINK1-dependent ubiquitin phosphorylation is predominantly in astrocytes supports increased priority for research on the function of PINK1 in astrocytes and the contribution of astrocyte dysfunction to PD pathogenesis.
Calculating energy derivatives for quantum chemistry on a quantum computer
Authors: O’Brien Thomas E. , Senjean Bruno , Sagastizabal Ramiro , Bonet-Monroig Xavier , Dutkiewicz Alicja , Buda Francesco , DiCarlo Leonardo , Visscher Lucas 
Published: December 2019

AbstractModeling chemical reactions and complicated molecular systems has been proposed as the “killer application” of a future quantum computer. Accurate calculations of derivatives of molecular eigenenergies are essential toward this end, allowing for geometry optimization, transition state searches, predictions of the response to an applied electric or magnetic field, and molecular dynamics simulations. In this work, we survey methods to calculate energy derivatives, and present two new methods: one based on quantum phase estimation, the other on a low-order response approximation. We calculate asymptotic error bounds and approximate computational scalings for the methods presented. Implementing these methods, we perform geometry optimization on an experimental quantum processor, estimating the equilibrium bond length of the dihydrogen molecule to within $$0.014$$0.014 Å of the full configuration interaction value. Within the same experiment, we estimate the polarizability of the H$${}_{2}$$2 molecule, finding agreement at the equilibrium bond length to within $$0.06$$0.06 a.u. ($$2 \%$$2% relative error).
Mapping dynamic QTL dissects the genetic architecture of grain size and grain filling rate at different grain-filling stages in barley
Authors: Du Binbin , Wang Qifei , Sun Genlou , Ren Xifeng , Cheng Yun , Wang Yixiang , Gao Song , Li Chengdao , Sun Dongfa 
Published: December 2019

AbstractGrain filling is an important growth process in formation of yield and quality for barley final yield determination. To explore the grain development behavior during grain filling period in barley, a high-density genetic map with 1962 markers deriving from a doubled haploid (DH) population of 122 lines was used to identify dynamic quantitative trait locus (QTL) for grain filling rate (GFR) and five grain size traits: grain area (GA), grain perimeter (GP), grain length (GL), grain width (GW) and grain diameter (GD). Unconditional QTL mapping is to detect the cumulative effect of genetic factors on a phenotype from development to a certain stage. Conditional QTL mapping is to detect a net effect of genetic factors on the phenotype at adjacent time intervals. Using unconditional, conditional and covariate QTL mapping methods, we successfully detected 34 major consensus QTLs. Moreover, certain candidate genes related to grain size, plant height, yield, and starch synthesis were identified in six QTL clusters, and individual gene was specifically expressed in different grain filling stages. These findings provide useful information for understanding the genetic basis of the grain filling dynamic process and will be useful for molecular marker-assisted selection in barley breeding.