bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Esthetic Difference of Chinese Beauty Evaluated by Two Different Human Races Based on Three-Dimensional Average Face Analysis
Authors: Chen Cong , Chen Yutong , Li Qingyi , Kau Chung How 
Published: March 2019

Purpose:
The aim of this study was to establish a new method of facial soft tissue analysis based on 3dMDface system and to find the different esthetic preferences of Chinese beauties from the Chinese and Indian evaluators perspective.

Methods:
Three-dimensional facial images of 242 females and 168 males were evaluated and ranked by 8 Chinese and nine Indians using a 10-point visual analog scale (VAS). Total 120 subjects in 2 panels (from Chinese perspective and Indian perspective) including 30 male and 30 female faces with top 30 scores were analyzed with the “average face” method respectively. Then 17 linear measurements, 13 curve measurements and 14 ratios of 4 average faces were calculated and compared with the divine proportion.

Results:
Distinct differences were founded based on the average face analysis. Similar total facial types were preferred by both Chinese and Indian evaluators, while Indian evaluators preferred a wider male face with a protrusive lower lip. Delicate noses with lower nose ridge but protrusive lower lips in females were more acceptable by Indian evaluators. The differences of linear measurements were limited in 2.0 mm except the facial width, lower facial width, upper facial height and forehead height while curve measurements differ distinctly as the table shows. No ratios equal to the divine proportion were founded.

Conclusion:
The 3D Average face based on stereophotogrammetry is a feasible method to analyze the facial characters and discrepancy of esthetic preferences. Chinese and Indian evaluators have some certain differences when judging beauties. Attractive faces have some certain ratios but not the divine proportion.
Telescoping With Multiple Revolution Cranial Osteotomies in Patients With Simple Craniosynostosis
Authors: Caycedo Diego José , Betancourt Nadia Patricia , Cabal Marcela , Devia Rodriguez Raul , Santacruz Luís Fernando 
Published: March 2019

Abstract
Simple craniosynostosis is a cranial disease characterized by the premature closure of the cranial sutures, it develops during the first years of life and affects 1 in every 2000 to 2500 births worldwide (1). The cranial growth alteration occurs as parallel flattening to the compromised sutured with compensatory bulging in a perpendicular vector. Currently, The Suturectomy is the gold validated surgical treatment, that besides the dynamic Cranioplasties of multiples revolutions allows the design of bone flaps and therefore the correction of the secondary deformities caused by the synostosis. This multicenter descriptive study assessed a 20 series of cases (6 Plagiocephaly, 13 Scaphocephaly, 1 Brachycephaly) obtained in Cali, Colombia, that underwent surgery between January of 2014 and December of 2017, applying a Suturectomy surgery with additional telescoping of multiple revolution cranial osteotomies. The authors observe no clinical complications in the recruited patients regarding postoperative period of the described surgical technique (1, 90, and 180 days), thereby obtaining excellent outcomes on the maintained suture distraction focused on the assessment of the 3D reconstruction computed tomography scans.
Assessing the Performance of the De Novo Postoperative Stress Urinary Incontinence Calculator
Authors: Ross James H. , Carter-Brooks Charelle M. , Ruppert Kristine M. , Giugale Lauren E. , Shepherd Jonathan P. , Zyczynski Halina M. 
Published: March 2019

Objective
The aim of the study was to determine the performance of a previously published stress urinary incontinence (SUI) risk calculator in women undergoing minimally invasive or transvaginal apical suspensions.

Methods
Using a database of stress-continent women who underwent minimally invasive or transvaginal apical suspensions, we calculated 2 prediction risks for development of SUI within 12 months based on inclusion of a “prophylactic” midurethral sling at the time of prolapse surgery. Observed subjective and objective continence status was abstracted from medical records. Regression models were created for the outcome of de novo SUI to generate receiver operating curves. Concordance (c) indices were estimated for the overall and procedure subgroups to determine the calculator’s ability to discriminate between SUI outcomes.

Results
Analyses included 502 women. De novo SUI was observed in 23.5% of women. The mean ± SD calculated risk of de novo SUI if a sling was performed was 18.9% ± 13.9 at 12 months compared with 36.4% ± 8.3 without sling. The calculator’s discriminative ability for those with a planned sling was moderate (c-index = 0.55, P = 0.037). The calculator failed to discriminate continence outcomes when a sling was not planned in the overall group (c-index = 0.50, P = 0.799) and individual apical procedures.

Conclusions
The SUI risk calculator is significantly limited in its ability to predict de novo SUI in our population of women planning minimally invasive apical suspensions. Refinements to the calculator model are needed to improve its utility in clinical practice.
WACS: Improving ChIP-seq Peak Calling by Optimally Weighting Controls
Authors: Awdeh Aseel , Turcotte Marcel , Perkins Theodore J. 
Published: March 2019

AbstractMotivationChromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq), initially introduced more than a decade ago, is widely used by the scientific community to detect protein/DNA binding and histone modifications across the genome. Every experiment is prone to noise and bias, and ChIP-seq experiments are no exception. To alleviate bias, the incorporation of control datasets in ChIP-seq analysis is an essential step. The controls are used to account for the background signal, while the remainder of the ChIP-seq signal captures true binding or histone modification. However, a recurrent issue is different types of bias in different ChIP-seq experiments. Depending on which controls are used, different aspects of ChIP-seq bias are better or worse accounted for, and peak calling can produce different results for the same ChIP-seq experiment. Consequently, generating “smart” controls, which model the non-signal effect for a specific ChIP-seq experiment, could enhance contrast and increase the reliability and reproducibility of the results.ResultsWe propose a peak calling algorithm, Weighted Analysis of ChIP-seq (WACS), which is an extension of the well-known peak caller MACS2. There are two main steps in WACS: First, weights are estimated for each control using non-negative least squares regression. The goal is to customize controls to model the noise distribution for each ChIP-seq experiment. This is then followed by peak calling. We demonstrate that WACS significantly outperforms MACS2 and AIControl, another recent algorithm for generating smart controls, in the detection of enriched regions along the genome, in terms of motif enrichment and reproducibility analyses.ConclusionThis ultimately improves our understanding of ChIP-seq controls and their biases, and shows that WACS results in a better approximation of the noise distribution in controls.
Unifying Gene Duplication, Loss, and Coalescence on Phylogenetic Networks
Authors: Du Peng , Ogilvie Huw A. , Nakhleh Luay 
Published: March 2019

AbstractStatistical methods were recently introduced for inferring phylogenetic networks under the multispecies network coalescent, thus accounting for both reticulation and incomplete lineage sorting. Two evolutionary processes that are ubiquitous across all three domains of life, but are not accounted for by those methods, are gene duplication and loss (GDL).In this work, we devise a three-piece model—phylogenetic network, locus network, and gene tree—that unifies all the aforementioned processes into a single model of how genes evolve in the presence of ILS, GDL, and introgression within the branches of a phylogenetic network. To illustrate the power of this model, we develop an algorithm for estimating the parameters of a phylogenetic network topology under this unified model. The algorithm consists of a set of moves that allow for stochastic search through the parameter space. The challenges with developing such moves stem from the intricate dependencies among the three pieces of the model. We demonstrate the application of the model and the accuracy of the algorithm on simulated as well as biological data.Our work adds to the biologist’s toolbox of methods for phylogenomic inference by accounting for more complex evolutionary processes.
Impact of in vivo protein folding probability on local fitness landscapes
Authors: Faber Matthew S. , Wrenbeck Emily E. , Azouz Laura R. , Steiner Paul J. , Whitehead Timothy A. 
Published: March 2019

AbstractIt is incompletely understood how biophysical properties like protein stability impact molecular evolution and epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. By contrast, nonspecific epistasis results when a mutation is influenced by a large number of non-local mutations. As most mutations are pleiotropic, the in vivo folding probability – governed by basal protein stability – is thought to determine activity-enhancing mutational tolerance, which implies that nonspecific epistasis is dominant. However, evidence exists for both specific and nonspecific epistasis as the prevalent factor, with limited comprehensive datasets to validate either claim. Using deep mutational scanning we probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE in which catalytic efficiencies are statistically indistinguishable but the enzyme variants have lower probabilities of folding in vivo. Local fitness landscapes show only slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific epistasis was predominant for the subset of mutations exhibiting positive sign epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon-dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes, and suggest that transcriptional-translational effects are an equally important determinant as stability in determining evolutionary outcomes.
Cell signalling stabilizes morphogenesis against noise
Authors: Hagolani Pascal , Zimm Roland , Marin-Riera Miquel , Salazar-Ciudad Isaac 
Published: March 2019

AbstractEmbryonic development involves gene networks, extracellular signaling, cell behaviors (cell division, apoptosis, adhesion, etc.) and mechanical interactions. How should gene networks, extracellular signaling and cell behaviors be coordinated to lead to complex and robust morphologies?To explore this question, we randomly wired genes and cell behaviors into a huge number of networks in EmbryoMaker. EmbryoMaker is a general mathematical model of animal development that simulates how embryos change,i.e.how the 3D spatial position of cells change, over time due such networks. Real gene networks are not random. Random networks, however, allow an unbiased view on the requirements for complex and robust development.We found that the mere autonomous activation of cell behaviors, especially cell division and contraction, was able to lead to the development of complex morphologies. We also found that complex morphologies tend to be less robust to noise than simple morphologies. However, we found that morphologies that developed through extracellular signaling and complex gene networks were, on average, more robust to noise. This stabilization occurs when gene networks and extracellular signaling partition the embryo into different regions where cell behaviors are regulated in slightly different ways. Our results are consistent with theories proposing that morphological complexity arose in early metazoan evolution as a consequence of the cell bio-mechanics already present in protozoa and that robustness evolved by the co-option of gene networks and extracellular cell signaling.
Distance Measures for Tumor Evolutionary Trees
Authors: DiNardo Zach , Tomlinson Kiran , Ritz Anna , Oesper Layla 
Published: March 2019

AbstractIn recent years, there has been increased interest in studying cancer by using algorithmic methods to infer the evolutionary tree underlying a tumor’s developmental history. Quantitative measures that compare such trees are then vital to benchmarking these algorithmic tree inference methods, understanding the structure of the space of possible trees for a given dataset, and clustering together similar trees in order to evaluate inheritance patterns. However, few appropriate distance measures exist, and those that do exist have low resolution for differentiating trees or do not fully account for the complex relationship between tree topology and how the mutations that label that topology are inherited. Here we present two novel distance measures,CommonAncestorSetdistance (CASet) andDistinctlyInheritedSetComparison distance (DISC), that are specifically designed to account for the subclonal mutation inheritance patterns characteristic of tumor evolutionary trees. We apply CASet and DISC to two simulated and two breast cancer datasets and show that our distance measures allow for more nuanced and accurate delineation between tumor evolutionary trees than existing distance measures. Implementations of CASet and DISC are available at:https://bitbucket.org/oesperlab/stereodist.
Validation and characterization of a DNA methylation alcohol biomarker across the life course
Authors: Yousefi Paul Darius , Richmond Rebecca , Langdon Ryan , Ness Andrew , Liu Chunyu , Levy Daniel , Relton Caroline , Suderman Matthew , Zuccolo Luisa 
Published: March 2019

AbstractRecently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterize the drivers of this DNAm-Alc for the first time in independent populations. In N=1,049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of AUDIT score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding we examined how earlier vs. concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions. The stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.
MicroRNA levels in bone and blood change during bisphosphonate and teriparatide therapy in an animal model of postmenopausal osteoporosis
Authors: Kocijan Roland , Weigl Moritz , Skalicky Susanna , Geiger Elisabeth , Ferguson James , Leinfellner Gabriele , Heimel Patrick , Pietschmann Peter , Grillari Johannes , Redl Heinz , Hackl Matthias 
Published: March 2019

ABSTRACTMicroRNAs control the activity of a variety of genes that are pivotal to bone metabolism. Therefore, the clinical utility of miRNAs as biomarkers and drug targets for bone diseases certainly merits further investigation. This study describes the use of an animal model of postmenopausal osteoporosis to generate a comprehensive dataset on miRNA regulation in bone tissue and peripheral blood during bone loss and specifically anti-resorptive and osteo-anabolic treatment.Forty-two Sprague-Dawley rats were randomized to SHAM surgery (n=10) or ovariectomy (OVX, n=32). Eight weeks after surgery, OVX animals were further randomized to anti-resorptive treatment with zoledronate (n=11), osteo-anabolic treatment with teriparatide (n=11), or vehicle treatment (n=10). After 12 weeks of treatment, bone and serum samples were used for microRNA analysis using next-generation sequencing (NGS), mRNA levels using RT-qPCR, and bone microarchitecture analysis using nanoCT.Ovariectomy resulted in loss of trabecular bone, which was fully rescued using osteo-anabolic treatment, and partially rescued using anti-resorptive treatment. NGS revealed that both, anti-resorptive and anabolic treatment had a significant impact on miRNA levels in bone tissue and serum: out of 426 detected miRNAs, 46 miRNAs were regulated by teriparatide treatment an d 10 by zoledronate treatment (p-adj. < 0.1). Interestingly, teriparatide and zoledronate treatment were able to revert miRNA changes in tissue and serum of untreated OVX animals, such as the up-regulation of miR-203a-3p, a known osteo-inhibitory miRNA. We confirmed previously established mechanisms of miR-203a by analyzing its direct target Dlx5 in femoral head.Our data reveal a significant effect of ovariectomy-induced bone loss, as well as the two major types of anti-osteoporotic treatment on miRNA transcription in femoral head tissue. These changes are associated with altered activity of target genes relevant to bone formation, such as Dlx5. The observed effects of bone loss and treatment response on miRNA levels in bone are also reflected in the peripheral blood, suggesting the possibility of minimally-invasive monitoring of bone-derived miRNAs using liquid biopsies.HighlightsmicroRNA expression in bone tissue is altered by osteo-anabolic and anti-resorptive therapy in OVX rats.microRNA changes in untreated OVX rats are reverted by anti-osteoporotic therapy.miR-203a is up-regulated during bone loss and down-regulated following therapy.Bone tissue and serum levels of miR-203a are highly correlated.
A segregating human allele ofSPO11modeled in mice disrupts timing and amounts of meiotic recombination, causing oligospermia and a decreased ovarian reserve
Authors: Tran Tina N. , Schimenti John C. 
Published: March 2019

ABSTRACTA major challenge in medical genetics is to characterize variants of unknown significance (VUS), so as to better understand underlying causes of disease and design customized treatments. Infertility has presented an especially difficult challenge with respect to not only determining if a given patient has a genetic basis, but also to identify the causative genetic factor(s). Though genome sequencing can identify candidate variants, in silico predictions of causation are not always sufficiently reliable so as to be actionable. Thus, experimental validation is crucial. Here, we describe the phenotype of mice containing a nonsynonymous (proline-to-threonine at position 306) change inSpo11, corresponding to human SNP rs185545661. SPO11 is a topoisomerase-like protein that is essential for meiosis because it induces DNA double stranded breaks (DSBs) that stimulate pairing and recombination of homologous chromosomes.Although both male and femaleSpo11P306T/P306Tmice were fertile, they had reduced sperm and oocytes, respectively. Spermatocyte chromosomes exhibited synapsis defects (especially between the X and Y chromosomes), elevated apoptotic cells, persistent markers of DSBs, and most importantly, fewer Type 1 crossovers that causes some chromosomes to have none.Spo11P306T/−mice were sterile and made fewer meiotic DSBs thanSpo11+/−animals, suggesting that theSpo11P306Tallele is a hypomorph and likely is delayed in making sufficient DSBs in a timely fashion. If the consequences are recapitulated in humans, it would predict phenotypes of premature ovarian failure, reduced sperm counts, and possible increased number of aneuploid gametes. These results emphasize the importance of deep phenotyping in order to accurately assess the impact of VUSs in reproduction genes.
An approximate full-likelihood method for inferring selection and allele frequency trajectories from DNA sequence data
Authors: Stern Aaron J. , Wilton Peter R. , Nielsen Rasmus 
Published: March 2019

AbstractMost current methods for detecting natural selection from DNA sequence data are limited in that they are either based on summary statistics or a composite likelihood, and as a consequence, do not make full use of the information available in DNA sequence data. We here present a new importance sampling approach for approximating the full likelihood function for the selection coefficient. The method treats the ancestral recombination graph (ARG) as a latent variable that is integrated out using previously published Markov Chain Monte Carlo (MCMC) methods. The method can be used for detecting selection, estimating selection coefficients, testing models of changes in the strength of selection, estimating the time of the start of a selective sweep, and for inferring the allele frequency trajectory of a selected or neutral allele. We perform extensive simulations to evaluate the method and show that it uniformly improves power to detect selection compared to current popular methods such as nSL and SDS, under various demographic models and can provide reliable inferences of allele frequency trajectories under many conditions. We also explore the potential of our method to detect extremely recent changes in the strength of selection. We use the method to infer the past allele frequency trajectory for a lactase persistence SNP (MCM6) in Europeans. We also study a set of 11 pigmentation-associated variants. Several genes show evidence of strong selection particularly within the last 5,000 years, includingASIP,KITLG, andTYR. However, selection onOCA2/HERC2seems to be much older and, in contrast to previous claims, we find no evidence of selection onTYRP1.Author summaryCurrent methods to study natural selection using modern population genomic data are limited in their power and flexibility. Here, we present a new method to infer natural selection that builds on recent methodological advances in estimating genome-wide genealogies. By using importance sampling we are able to efficiently estimate the likelihood function of the selection coefficient. We show our method improves power to test for selection over competing methods across a diverse range of scenarios, and also accurately infers the selection coefficient. We also demonstrate a novel capability of our model, using it to infer the allele’s frequency over time. We validate these results with a study of a lactase persistence SNP in Europeans, and also study a set of 11 pigmentation-associated variants.