bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fatigue behavior of 3-D orthogonal woven composite with silane modification
Authors: Zhang Yi , Gao Xiaoping , Tao Nannan 
Published: April 2020

Abstract
As key part in wind turbine, the blade is a vital component for energy transformation. Fiber reinforced composite has advantage of light weight, large specific strength and specific stiffness, which has been used in wind turbine blade. In order to avoid delamination of conventional laminate and debonding between fiber and epoxy, the silane modification composite specimen reinforced with 3-D orthogonal woven fabric/epoxy was prepared using vacuum assisted resin transfer molding (VARTM) for blade. As for fatigue experiment, the critical stress levels corresponding to micro-crack initiation and failure of composite were obtained by combining of acoustic emission technology and quasi-bending experiment. The fatigue behavior of 3-D orthogonal woven composite with silane modification was experimental evaluated based on the minimum and maximum stress levels. The fatigue behavior, such as S-N curve, stress-strain behavior and stiffness degradation behavior were analyzed. The result will provide the basis for investigation of bending behavior with nondestructive tests and set of stress level in bending fatigue experiment.
Optical and electrical properties of refined carbon derived from industrial tea waste
Authors: Akgül Gökçen , Bıçakçı Saliha Nur 
Published: April 2020

AbstractThe utilization of nano- and well-ordered carbon materials such as graphene especially in carbon-based electrical devices and in energy storage areas is becoming important in terms of developing economical methods and reducing the dimensions of the electrical devices. These applied carbon materials are mostly originated from fossil sources which are diminishing. Hence, renewable carbon resources are gaining importance. Biomass is the single renewable carbon resource and can be refined to highly ordered carbon materials such as graphene by top to down methods. In this work, industrial tea waste biomass was converted to carbonized material by pyrolysis and refined by some further chemical treatments towards the ordered structured carbon. The newly derived refined carbon material was characterized by Raman, TGA, FTIR, SEM and XRD methods, and its optical and electrical properties were determined. The experimental results showed that the band gap energies of refined carbon derived from tea waste and reduced graphene oxide prepared in this study are in the similar level as 2.375 and 2.264 eV, respectively. Furthermore, the electrical conductivities are at the same stage as 3.16 and 3.28 × 10−4(1/Ω·cm) for reduced graphene oxide and refined carbon. The optically active and electrical conductive refined carbon material from biomass could be a proper carbon in energy related applications in terms of renewable and sustainable processing.
Self-assembled monolayer formation of pentamers-like molecules onto FCC(111) surfaces: the case of curcuminoids onto Au(111) surface
Authors: Cisternas E , dos Santos G J , Flores M , Vogel E E , Ramirez-Pastor A J 
Published: April 2020

Abstract
The adsorption of rigid straight electrically polarized pentamers over a FCC(111) surface is studied. The model was inspired by the deposition of 2-thiophene molecules over the Au(111) surface, which was previously characterized by experimental techniques and simulated under the frame of the density functional theory. We now obtain and report the charge distribution of the molecule which allows to propose a deposition model followed by Monte Carlo simulations over an ad-hoc lattice gas model. We show that for a certain value of the chemical potential there exists an isotropic-nematic phase transition which can explain the formation of a self-assembled monolayer like the one observed in the transmission electron microscopy images. An order parameter is defined to characterize the transition which presents a step-like behavior at a critical chemical potential value. The possible nature of the nematic transition in conjunction with an ergodicity breakdown is discussed as future work by means of statistical physics techniques.
Histological Description and Histopathology in Polypedilum sp. (Diptera: Chironomidae): A Potential Biomarker for the Impact of Mining on Tributaries
Authors: Grueso-Gilaberth Rosa N , Jaramillo-Timarán Keiner S , Ospina-Pérez Erika M , Richardi Vinicius S , Ossa-López Paula A , Rivera-Páez Fredy A 
Published: April 2020

Abstract
The Neotropical region has a wide aquatic biodiversity, which is affected by anthropogenic activities. Mining has caused a negative impact on these ecosystems, directly affecting benthic communities. Aquatic macroinvertebrates are effective bioindicators of water quality, especially Chironomidae larvae, since these show high species richness, abundance, and sensitivity to human activities. The genus Polypedilum is among the most representative of the family Chironomidae. Research on these species is focused on their abundance and dominance in water bodies. In addition, several studies have addressed alterations in the external morphology of some Chironomidae due to mining pollution (heavy metals). However, little is known about the effects of mining on the internal morphology of these species. This study provides the first histological description of different systems and organs of Polypedilum sp. larvae. Furthermore, we report histopathological alterations in larvae collected from two tributaries affected by mining, namely Toldafría and La Elvira streams located in the municipalities of Villamaría and Manizales (Caldas – Colombia). Our findings show target organs of mining pollution in a species of Polypedilum, which represent potential early-warning histopathological biomarkers with relevant implications for water quality monitoring.
Invited Commentary: Opportunities That Come With Studying the Co-Occurrence of Multiple Outcomes
Authors: Haneuse Sebastien , Schrag Deborah , Nevo Daniel 
Published: April 2020

Abstract
In almost all clinical settings, patients are at risk for multiple potential events and, in consultation with health-care providers, must weigh the potential benefits and harms across these events when making decisions. As researchers seek to build an evidence base to inform these decisions, they must contend with a choice as to how they will handle the different events. One approach, arguably the standard approach in the literature, is to consider the events individually by conducting analyses and publishing results for each one at a time. Doing so, however, fails to acknowledge or exploit the inherent multivariate nature of the data, represents a lost opportunity, and results in an evidence base that is not aligned with how clinical decision-making is actually performed. The article by Prentice et al. (Am J Epidemiol. 2020;189(9):972–981) in this issue of the Journal moves beyond this standard by illustrating recently developed methods that directly take advantage of information on the co-occurrence of multiple events. Moreover, their article highlights the role of modern methods in deriving additional information and insight from studies of multiple clinical outcomes by making full use of multivariate data, with the goal being to complement, not replace, existing methods.
Standardizing Discrete-Time Hazard Ratios With a Disease Risk Score
Authors: Richardson David B , Keil Alexander P , Edwards Jessie K , Kinlaw Alan C , Cole Stephen R 
Published: April 2020

Abstract
The disease risk score (DRS) is a summary score that is a function of a potentially large set of covariates. The DRS can be used to control for confounding by the covariates that went into estimation of the DRS and obtain a standardized estimate of an exposure’s effect on disease. However, to date, literature on the DRS has not addressed analyses that focus on estimation of survival or hazard functions, which are common in epidemiologic analyses of cohort data. Here, we propose a method for standardization of hazard ratios using the DRS in longitudinal analyses of the association between a binary exposure and an outcome. This approach to handling a potentially large set of covariates through a model-based approach to standardization may provide a useful tool for cohort analyses of hazard ratios and may be particularly well-suited to settings where an exposure propensity score is difficult to model. Simulations are used in this paper to illustrate the approach, and an empirical example is provided.
Icotinib Attenuates Monocrotaline-Induced Pulmonary Hypertension by Preventing Pulmonary Arterial Smooth Muscle Cell Dysfunction
Authors: Peng Li-Yao , Yu Min , Yang Ming-Xia , Liu Ping , Zhou Hong , Huang Wen , Kong Hui , Xie Wei-Ping 
Published: April 2020

Abstract

Background
Aberrant activation of epidermal growth factor receptor (EGFR) signaling pathway is associated with the pathogenesis of pulmonary hypertension (PH). However, the effect of icotinib, a first generation of EGFR tyrosine kinase inhibitor (EGFR-TKI), on PH remains to be elucidated.

Methods
PH rat model was established by a single intraperitoneal injection of monocrotaline (MCT, 60 mg/kg). Icotinib (15, 30, and 60 mg/kg/day) was administered by oral gavage from the day of MCT injection. After 4 weeks, hemodynamic parameters and histological changes of the pulmonary arterial vessels were assessed, and the phenotypic switching of pulmonary arterial smooth muscle cells (PASMCs) was determined in vivo. Moreover, the effects of icotinib (10 µM) on epidermal growth factor (EGF, 50 ng/ml)-stimulated proliferation, migration, and phenotypic switching of human PASMCs were explored in vitro.

Results
Icotinib significantly reduced the right ventricular systolic pressure and right ventricle hypertrophy index in rats with MCT-induced PH. Moreover, icotinib improved MCT-induced pulmonary vascular remodeling. The expression of contractile marker (smooth muscle 22 alpha (SM22α)) and synthetic markers (osteopontin (OPN) and vimentin) in pulmonary artery was restored by icotinib treatment. In vitro, icotinib suppressed EGF-induced PASMCs proliferation and migration. Meanwhile, icotinib inhibited EGF-induced downregulation of α-smooth muscle actin and SM22α and upregulation of OPN and Collagen I in PASMCs, suggesting that icotinib could inhibit EGF-induced phenotypic switching of PASMCs. Mechanistically, these effects of icotinib were associated with the inhibition of EGFR-Akt/ERK signaling pathway.

Conclusions
Icotinib can attenuate MCT-induced pulmonary vascular remodeling and improve PH. This effect of icotinib might be attributed to preventing PASMC dysfunction by inhibiting EGFR-Akt/ERK signaling pathway.
Hyperalgesia after a Drinking Episode in Young Adult Binge Drinkers: A Cross-Sectional Study
Authors: You Dokyoung S , Hahn Hunter A , Welsh Thomas H , Meagher Mary W 
Published: April 2020

Abstract

Aims
Rodent studies propose potential mechanisms linking excessive drinking and pain hypersensitivity (hyperalgesia), such that stress hormones (i.e. epinephrine and cortisol) mediate induction and maintenance of alcohol withdrawal-induced hyperalgesia. The first aim of this study was to examine whether hyperalgesia would occur within 48 h after a drinking episode in healthy young adult binge drinkers. The second was to examine whether stress hormones and negative effect would be associated with binge drinking or alcohol withdrawal-associated hyperalgesia.

Methods
A cross-sectional experiment was conducted in five groups with naturally occurring drinking (mean age = 19.6, range 18–29 years): abstainers (n = 43, 54% female), moderate drinkers with (n = 50, 50% female) or without recent drinking (i.e. within 48 h, n = 23, 26% female) and binge drinkers with (n = 36, 58% female) or without recent drinking (n = 25, 44% female). All types of drinkers endorsed drinking about 2–3 times a month and 2–3 years of drinking history.

Results
Muscle pressure pain thresholds were significantly lower in the binge group with recent drinking compared to other groups, but cutaneous mechanical and heat pain thresholds were not significantly different across the five groups. Basal epinephrine levels were significantly higher in binge groups regardless of recent drinking, but cortisol and negative effect were not significantly different across the five groups.

Conclusions
This is the first study to show that alcohol withdrawal-associated muscle hyperalgesia may occur in healthy episodic binge drinkers with only 2–3 years of drinking history, and epinephrine may play a role in binge drinking-associated hyperalgesia.
Complications of Cosmetic Surgery Tourism: Case Series and Cost Analysis
Authors: Venditto Chelsea , Gallagher Margaret , Hettinger Patrick , Havlik Robert , Zarb Rakel , Argenta Anne , Doren Erin , Sanger James , Klement Kristen , Dzwierzynski William , LoGiudice John , Jensen John 
Published: April 2020

Abstract

Background
Cosmetic surgery tourism is increasing exponentially. Patients seek cosmetic procedures within the United States and abroad, lured by lower cost procedures, shorter waiting lists, and affordable airfare and hotel accommodations. Unfortunately, operations are often performed by non–board-certified plastic surgeons, sometimes not even by plastic surgeons. Preoperative counseling, frequently limited to a video-chat with an office secretary, provides inadequate discussion regarding potential complications. Postoperative care is careless and rarely involves the operating surgeon. Complications are frequent, with management falling into the hands of plastic surgeons unfamiliar with the patient’s care. Furthermore, the physician, rather than the patient or hospital, faces the largest cost burden.

Objectives
The authors sought to explore their institution’s experience treating complications of cosmetic tourism and investigate associated costs.

Methods
The retrospective review of 16 patients treated for complications related to cosmetic surgery tourism plus cost analysis revealed a substantial discrepancy between money saved by undergoing surgery abroad and massive costs accrued to treat surgical complications.

Results
The most common complication was infection, often requiring surgery or IV antibiotics on discharge. Mean cost per patient was $26,657.19, ranging from $392 (single outpatient visit) to $154,700.79 (prolonged admission and surgery). Overall, the hospital retained 63% of billed charges, while physicians retained only 9%. The greatest amount paid by any single patient was $2635.00 by a patient with private insurance.

Conclusions
Cosmetic tourism has severe medical repercussions for patients and complications that burden hospitals, physicians, and the US medical system. Physicians treating the complications suffer the greatest financial loss.

Level of Evidence: 4
Sequoya: multiobjective multiple sequence alignment in Python
Authors: Benítez-Hidalgo Antonio , Nebro Antonio J , Aldana-Montes José F 
Published: April 2020

Abstract

Motivation
Multiple sequence alignment (MSA) consists of finding the optimal alignment of three or more biological sequences to identify highly conserved regions that may be the result of similarities and relationships between the sequences. MSA is an optimization problem with NP-hard complexity (non-deterministic polynomial-time hardness), because the time needed to find optimal alignments raises exponentially along with the number of sequences and their length. Furthermore, the problem becomes multiobjective when more than one score is considered to assess the quality of an alignment, such as maximizing the percentage of totally conserved columns and minimizing the number of gaps. Our motivation is to provide a Python tool for solving MSA problems using evolutionary algorithms, a nonexact stochastic optimization approach that has proven to be effective to solve multiobjective problems.

Results
The software tool we have developed, called Sequoya, is written in the Python programming language, which offers a broad set of libraries for data analysis, visualization and parallelism. Thus, Sequoya offers a graphical tool to visualize the progress of the optimization in real time, the ability to guide the search toward a preferred region in run-time, parallel support to distribute the computation among nodes in a distributed computing system, and a graphical component to assist in the analysis of the solutions found at the end of the optimization.

Availability and implementation
Sequoya can be freely obtained from the Python Package Index (pip) or, alternatively, it can be downloaded from Github at https://github.com/benhid/Sequoya.

Supplementary information
Supplementary data are available at Bioinformatics online.
LeafCutterMD: an algorithm for outlier splicing detection in rare diseases
Authors: Jenkinson Garrett , Li Yang I , Basu Shubham , Cousin Margot A , Oliver Gavin R , Klee Eric W 
Published: April 2020

Abstract

Motivation
Next-generation sequencing is rapidly improving diagnostic rates in rare Mendelian diseases, but even with whole genome or whole exome sequencing, the majority of cases remain unsolved. Increasingly, RNA sequencing is being used to solve many cases that evade diagnosis through sequencing alone. Specifically, the detection of aberrant splicing in many rare disease patients suggests that identifying RNA splicing outliers is particularly useful for determining causal Mendelian disease genes. However, there is as yet a paucity of statistical methodologies to detect splicing outliers.

Results
We developed LeafCutterMD, a new statistical framework that significantly improves the previously published LeafCutter in the context of detecting outlier splicing events. Through simulations and analysis of real patient data, we demonstrate that LeafCutterMD has better power than the state-of-the-art methodology while controlling false-positive rates. When applied to a cohort of disease-affected probands from the Mayo Clinic Center for Individualized Medicine, LeafCutterMD recovered all aberrantly spliced genes that had previously been identified by manual curation efforts.

Availability and implementation
The source code for this method is available under the opensource Apache 2.0 license in the latest release of the LeafCutter software package available online at http://davidaknowles.github.io/leafcutter.

Supplementary information
Supplementary data are available at Bioinformatics online.
Testing hypotheses about the microbiome using the linear decomposition model (LDM)
Authors: Hu Yi-Juan , Satten Glen A 
Published: April 2020

AbstractMotivationMethods for analyzing microbiome data generally fall into one of two groups: tests of the global hypothesis of any microbiome effect, which do not provide any information on the contribution of individual operational taxonomic units (OTUs); and tests for individual OTUs, which do not typically provide a global test of microbiome effect. Without a unified approach, the findings of a global test may be hard to resolve with the findings at the individual OTU level. Further, many tests of individual OTU effects do not preserve the false discovery rate (FDR).ResultsWe introduce the linear decomposition model (LDM), that provides a single analysis path that includes global tests of any effect of the microbiome, tests of the effects of individual OTUs while accounting for multiple testing by controlling the FDR, and a connection to distance-based ordination. The LDM accommodates both continuous and discrete variables (e.g. clinical outcomes, environmental factors) as well as interaction terms to be tested either singly or in combination, allows for adjustment of confounding covariates, and uses permutation-based P-values that can control for sample correlation. The LDM can also be applied to transformed data, and an ‘omnibus’ test can easily combine results from analyses conducted on different transformation scales. We also provide a new implementation of PERMANOVA based on our approach. For global testing, our simulations indicate the LDM provided correct type I error and can have comparable power to existing distance-based methods. For testing individual OTUs, our simulations indicate the LDM controlled the FDR well. In contrast, DESeq2 often had inflated FDR; MetagenomeSeq generally had the lowest sensitivity. The flexibility of the LDM for a variety of microbiome studies is illustrated by the analysis of data from two microbiome studies. We also show that our implementation of PERMANOVA can outperform existing implementations.Availability and implementationThe R package LDM is available on GitHub at https://github.com/yijuanhu/LDM in formats appropriate for Macintosh or Windows.Contactyijuan.hu@emory.eduSupplementary informationSupplementary data are available at Bioinformatics online.
Learning context-aware structural representations to predict antigen and antibody binding interfaces
Authors: Pittala Srivamshi , Bailey-Kellogg Chris 
Published: April 2020

Abstract

Motivation
Understanding how antibodies specifically interact with their antigens can enable better drug and vaccine design, as well as provide insights into natural immunity. Experimental structural characterization can detail the ‘ground truth’ of antibody–antigen interactions, but computational methods are required to efficiently scale to large-scale studies. To increase prediction accuracy as well as to provide a means to gain new biological insights into these interactions, we have developed a unified deep learning-based framework to predict binding interfaces on both antibodies and antigens.

Results
Our framework leverages three key aspects of antibody–antigen interactions to learn predictive structural representations: (i) since interfaces are formed from multiple residues in spatial proximity, we employ graph convolutions to aggregate properties across local regions in a protein; (ii) since interactions are specific between antibody–antigen pairs, we employ an attention layer to explicitly encode the context of the partner; (iii) since more data are available for general protein–protein interactions, we employ transfer learning to leverage this data as a prior for the specific case of antibody–antigen interactions. We show that this single framework achieves state-of-the-art performance at predicting binding interfaces on both antibodies and antigens, and that each of its three aspects drives additional improvement in the performance. We further show that the attention layer not only improves performance, but also provides a biologically interpretable perspective into the mode of interaction.

Availability and implementation
The source code is freely available on github at https://github.com/vamships/PECAN.git.
Incidence of Pelvic Inflammatory Disease Associated With Mycoplasma genitalium Infection: Evidence Synthesis of Cohort Study Data
Authors: Lewis Joanna , Horner Paddy J , White Peter J 
Published: April 2020

Abstract
We synthesized evidence from the POPI sexual-health cohort study and estimated that 4.9% (95% credible interval, .4–14.1%) of Mycoplasma genitalium infections in women progress to pelvic inflammatory disease versus 14.4% (5.9–24.6%) of chlamydial infections. For validation, we predicted PID rates in 4 age groups that agree well with surveillance data.