bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiplicity of Galactic Cepheids from long-baseline interferometry
Authors: Gallenne A. , Kervella P. , Borgniet S. , Mérand A. , Pietrzyński G. , Gieren W. , Monnier J. D. , Schaefer G. H. , Evans N. R. , Anderson R. I. , Baron F. , Roettenbacher R. M. , Karczmarek P.
Published: January 2019

Aims. We aim at detecting and characterizing the main-sequence companions of a sample of known and suspected Galactic binary Cepheids. The long-term objective is to accurately and independently measure the Cepheid masses and distances.

Methods. We used the multi-telescope interferometric combiners CHARA/MIRC and VLTI/PIONIER to detect and measure the astrometric positions of the high-contrast companions orbiting 16 bright Galactic Cepheids. We made use of the CANDID algorithm to search for the companions and set detection limits from interferometric observations. We also present new high-precision radial velocity measurements which were used to fit radial pulsation and orbital velocities.

Results. We report the detection of the companions orbiting the Cepheids U Aql, BP Cir, and S Mus, possible detections for FF Aql, Y Car, BG Cru, X Sgr, V350 Sgr, and V636 Sco, while no component is detected around U Car, YZ Car, T Mon, R Mus, S Nor, W Sgr, and AH Vel. For U Aql and S Mus, we performed a preliminary orbital fit combining their astrometric measurements with newly obtained high-precision single-line radial velocities, providing the full set of orbital elements and pulsation parameters. Assuming the distance from a period-luminosity (P-L) relation for both Cepheids, we estimated preliminary masses of MU Aql = 4.97 ± 0.62 M⊙ and MS Mus = 4.63 ± 0.99 M⊙. For YZ Car, W Sgr, V350 Sgr, and V636 Sco, we revised the spectroscopic orbits using new high-precision radial velocities, while we updated the pulsation parameters for BP Cir, BG Cru, S Nor, and AH Vel. Our interferometric observations also provide measurements of the angular diameters, which can be used in a Baade-Wesselink type analysis.

Conclusions. We now have several astrometric detections of Cepheid companions. When radial velocities of the companions are available, such systems will provide accurate and independent masses and distances. Orbital parallaxes with an accuracy better than 5% will be particularly useful for a better calibration of the P-L relation. The final Gaia parallaxes will also be particularly helpful for single-line spectroscopic systems, where mass and distance are degenerate. Mass measurements are necessary for a better understanding of the age and evolution of Cepheids.
Adaptive Hybrid Blood Cell Image Segmentation
Authors: T Zalizam T. Muda , Rosalina Abdul Salam , Suzilah Ismail
Published: January 2019

Image segmentation is an important phase in the image recognition system. In medical imaging such as blood cell analysis, it becomes a crucial step in quantitative cytophotometry. Currently, blood cell images become predominantly valuable in medical diagnostics tools. In this paper, we present an adaptive hybrid analysis based on selected segmentation algorithms. Three designates common approaches, that are Fuzzy c-means, K-means and Mean-shift are adapted. Blood cell images that are infected with malaria parasites at various stages were tested. The most suitable method will be selected based on the lowest number of regions. The selected approach will be enhanced by applying Median-cut algorithm to further expand the segmentation process. The proposed adaptive hybrid method has shown a significant improvement in the number of regions.
Adapted Wavelet Transform for Twisted Blade Diagnosis in Multi Stage Rotor
Authors: Abdelrhman Ahmed M. , Leong M. Salman , Ali Y.H. , Ahmad Iftikhar , Georgantopoulou Christina G. , Ali Salah M.
Published: January 2019

This paper studies the diagnosis of twisted blade in a multi stages rotor system using adapted wavelet transform and casing vibration. The common detection method (FFT) is effective only if sever blade faults occurred while the minor faults usually remain undetected. Wavelet analysis as alternative technique is still unable to fulfill the fault detection and diagnosis accurately due to its inadequate time-frequency resolution. In this paper, wavelet is adapted and its time-frequency is improved. Experimental study was undertaken to simulate multi stages rotor system. Results showed that the adapted wavelet analysis is effective in twisted blade diagnosis compared to the conventional one.
Cluster Analysis for Automated Operational Modal Analysis: A Review
Authors: Hasan M. Danial A. , Ahmad Z. A. B. , Leong M. Salman , Hee L. M. , Haffizzi Md. Idris M.
Published: January 2019

Recent developments in the field of modal-based damage detection and vibration-based monitoring have led to a renewed interest in automated procedures for the operational modal analysis (OMA). The development of automated operational modal analysis (OMA) procedures marked a fundamental step towards the elimination of any user intervention since traditional modal identification requires a lot of interaction by an expert user. A key for effective automation of OMA is depended on well- defined modal indicators for a clear indication about which modes are to be selected as the physical modes. In all modal analysis, the construction of stabilization diagrams is necessary in order to illustrate, and decide, if a mode is physical or not for predefined range of the model order. On the other hand, the use of stabilization diagram tools involves a large amount of user interaction, costly, time-consuming process and certainly unsuited for online applications. Therefore, the development of automatic procedures for the analysis of stabilization diagrams by resembling decision-making process of a human has been carried out in recent years. For the sake of clearness, the automation of the interpretation of stabilization diagrams can generally be divided into two steps in order to speed up the process: a) elimination of noise modes and b) clustering of physical modes in order to obtain the most representative values of the estimated parameters of each clustered mode. In recent years, several alternative procedures have been proposed for clustering techniques. Therefore, this review aims to provide relevant essential information on the recent developments of cluster analysis in automated OMA. A literature review of existing clustering algorithm has been carried out to find best practice criteria for automated modal parameter identification which involving the general concepts of these techniques as well as the pro and cons of applying these clustering techniques are also discussed and summarised.
Spatial Signature Method (SSM) Against XML Signature Wrapping Attacks
Authors: Saudi Madihah Mohd , Mohd Zaizi Nurzi Juana , Ahmed Sweese Khaled Juma , Bakar Azreena Abu
Published: January 2019

Living in cyber world with revolutionizes of Industrial 4.0, most of the users and organisations prefer to sell and buy products or services via website online transaction. This online transaction is done through a messaging protocol (SOAP) and signing entire SOAP (SESOAP) using Extensible Markup Language (XML). XML is implemented to secure the SOAP contents by applying the signing method called as XML Digital signature. However, the XML digital signature has issues related to XML signature wrapping (XSW) attacks specifically on Sibling Value Context and Sibling Order Context attacks. Therefore, this paper proposes an enhanced method called as Spatial Signature Method (SSM) which aims to resolve the limitation of SESOAP from the aspect of XSW attacks. It proposes new parameters for XML digital signature inspired by the concept of ratio and space in biotechnology to detect the XSW attacks. The experiment was conducted in a controlled lab by using the Ubuntu Linux system and PHP programming. Based on the comparison made with SESOAP and ID Referencing method (IDR), SSM has proven to defend against the XSW attacks. For the future work, the spatial signature method can be forged with more extensive spatial information for the digital signature and to integrate it with web services.
Review on Predictive Modelling Techniques for Identifying Students at Risk in University Environment
Authors: Nik Nurul Hafzan Mat Yaacob , Safaai Deris , Asiah Mat , Mohd Saberi Mohamad , Siti Syuhaida Safaai
Published: January 2019

Predictive analytics including statistical techniques, predictive modelling, machine learning, and data mining that analyse current and historical facts to make predictions about future or otherwise unknown events. Higher education institutions nowadays are under increasing pressure to respond to national and global economic, political and social changes such as the growing need to increase the proportion of students in certain disciplines, embedding workplace graduate attributes and ensuring that the quality of learning programs are both nationally and globally relevant. However, in higher education institution, there are significant numbers of students that stop their studies before graduation, especially for undergraduate students. Problem related to stopping out student and late or not graduating student can be improved by applying analytics. Using analytics, administrators, instructors and student can predict what will happen in future. Administrator and instructors can decide suitable intervention programs for at-risk students and before students decide to leave their study. Many different machine learning techniques have been implemented for predictive modelling in the past including decision tree, k-nearest neighbour, random forest, neural network, support vector machine, naïve Bayesian and a few others. A few attempts have been made to use Bayesian network and dynamic Bayesian network as modelling techniques for predicting at- risk student but a few challenges need to be resolved. The motivation for using dynamic Bayesian network is that it is robust to incomplete data and it provides opportunities for handling changing and dynamic environment. The trends and directions of research on prediction and identifying at-risk student are developing prediction model that can provide as early as possible alert to administrators, predictive model that handle dynamic and changing environment and the model that provide real-time prediction.
A data enlargement strategy for fault classification through a convolutional auto-encoder
Authors: Hao Cui , Kesheng Wang , Yu Li , Binyuan Yang , Qiang miao
Published: January 2019

The amount of data is of crucial to the accuracy of fault classification through machine learning techniques. In wind energy harvest industry, due to the shortage of faulty data obtained in real practice, together with ever changing operational conditions, fault detection and evaluation of wind turbine blade problems become intractable through conventional machine learning methods. In this paper, a modified unsupervised learning method, namely a convolutional auto-encoder based data enlargement strategy (ABE) is proposed for wind turbine blade fault classification. Limited simulation results for different levels of wind turbine icy blades are used for investigation. First, convolutional auto encoder is used to increase the amount of the data. Then, decision tree based xgboost tool, as an example, is used to demonstrate the effectiveness of data enlargement strategy for fault classification. The study shows that the proposed data enlargement strategy is an effective method to improve the fault classification accuracy through machine learning techniques.
Permission-based Analysis of Android Applications Using Categorization and Deep Learning Scheme
Authors: Hamidreza Alimardani , Mohammed Nazeh
Published: January 2019

As mobile devices grow in popularity, they have become indispensable in people's daily lives, keeping us connected to social networks, breaking news, and the entire Internet. While there are multiple competing platforms, Google's Android is currently the most popular operating system for mobile devices. This popularity has drawn attention of hackers as well. Thus far, research works have analysed Android permissions individually, which makes analysis complex and time consuming. In this work, we propose categorizing Android permissions based on Google's recommendation and perform LSTM analysis on data. The used datasets are Drebin and AndroZoo, which are the most complete and well-respected among research community. The experiment results show that LSTM achieved 91% of true positive rate.
Grid Convergence Analysis for MUSCL-based Numerical Scheme in Shockwave-containing Flows
Authors: Li Guangning , Bhatia Dinesh , Xu Min , Wang Jian
Published: January 2019

This paper investigated the influence of limiter functions widely utilized in MUSCL-type (Monotone Upstream-centred Schemes for Conservation Laws) upwind numerical schemes on the solution accuracy of shockwave-containing flows. An incident shock interacting with laminar boundary layer developed on a flat plate was numerically simulated with the in-house developed code. A mixed-order grid convergence study was performed to assess the spatial errors of different limiters in simulating the selected shockwave-containing flow on flat plate. The conclusions are that, limiter functions implemented in the current in-house code play the critical roles in accurately predicting shockwave-containing flows. The mixed-order error estimator based on grid convergence study was proved to be applicable to evaluate the spatial errors of shockwave-containing flows, where the shock could reduce the nominal second- or third-order accuracy to first-order. The mixed-order estimator is conservative in the sense that the actual error is less than the error estimated, in the examined case.
The Optimization of FDM 3D Printer’s Structure Based on Finite Element Analysis
Authors: Huang Zhenhai , Shi Tingchun , Yue Xiuyan
Published: January 2019

In view of the forming accuracy of the 3D printer, the paper, from the structure of the printer itself, discussed the influence on the precision of the printer via improving the structure of 3D printer. A typical 3D printer, such as a common type of FDM, was selected, and SOLIDWORKS software was used for solid modeling, after establishing the model, the finite element analysis was carried out on the whole structure model to obtain the deformation characteristics and the main vibration model of the printer. On the basis of finite element analysis, the influence of the level shaft bearing diameter, material properties and symmetry of the parts on the overall mechanical properties of the printer was discussed respectively. On this basis, the overall structure of the machine has been optimized and achieved remarkable results.
The effect of the particle size and magnetic moment of the Fe3O4 superparamagnetic beads on the sensitivity of biodetection
Authors: Zhang Yang , Xu Jie , Li Qiang , Cao Derang , Li Shandong
Published: January 2019

In recent years, the quantitative detection of biomolecules based on Giant magnetoresistive (GMR) sensors and magnetic nanoparticles have received continuous attention. Researchers try to improve the accuracy of detection by various methods, including using a more sensitive sensor, designing circuit to reduce system noise, and so on. In which, the intrinsic properties of magnetic labels, such as the particle size of labels is a vital aspect for the GMR biosensing technology. In this work, a series of Fe3O4 particles with average particle sizes from 80 to 580 nm were prepared for exploring the effect of particle size on the limit of detection (LOD). An ultra-low LOD of 0.1 ng/mL was obtained for small particles with average sizes from 80 to 200 nm detected by our home-made biodetection device. However, for the ones with large sizes from 330 to 580 nm, the LOD increases with the increase of particle size. The total magnetic moments of all particles attached on the sensor surface Σmm are calculated theoretically and compared with the experimental data of the normalized voltage ratio (Vnvr=|ΔV|/V0×100%) over particle size. It is found that not only the particle size but also the magnetic moment of particles affect the LOD of the concentration.
Mapping time series into complex networks based on equal probability division
Authors: Zhang Zelin , Xu Jinyu , Zhou Xiao
Published: January 2019

As effective representations of complex systems, complex networks have attracted scholarly attention for their many practical applications. They also represent a new tool for time series analysis. In order to characterize the underlying dynamic features, the structure of transformed networks should be encoded with the systematic evolution information that always hides behind the time series data. Thus, the way of mapping segments of the time series into nodes of the network is particularly crucial, but it is liable to be unstable under noise and missing values. In this paper, we propose a coarse-graining based on statistics of segments (CBS) founded complex network method, which can make it immune to interference to a certain degree. The time series is divided into many segments by a slide window, of which the width is determined by the multi-scale entropy of the data. We use a multi-dimensional symbol to represent the motion state of every segment. Due to the utilization of the distribution information of the fragments’ numerical characteristics, the coarse-graining process is self-adaptive to some extent. The complex network is then established based on the adjacent relations of the symbolic sequence. With our method, the differences in the network measurements between the periodic and chaotic motion is easily observable. Furthermore, we investigated the robustness of CBS by adding noise and missing values. We found that CBS is still valid, even with strong noise and 15% missing values, and simulation shows that it is more robust than the VG and LS approaches. By mapping a time series into a complex network, we provide a new tool for understanding the dynamic evolution mechanism of a complex system. This method has been applied in various fields, such as physics, engineering, medicine and economics. However, the interference of noise may greatly affects the reliability of judgment, which is based on the structures of transformed networks. An insufficient robustness is mostly to blame for the transformation from a time series to a symbolic sequence. In this paper, we suggest a new approach to the coarse-graining process which is self-adaptive for threshold choosing. Simulations show that even with strong disturbances, our network structure is easily distinguishable under different dynamic mechanisms.
Investigation of metal-nickel oxide contacts used for perovskite solar cell
Authors: Abdy Hamed , Aletayeb Arash , Kolahdouz Mohammadreza , Soleimani Ebrahim Asl
Published: January 2019

Perovskite solar cells (PSCs) have been able to raise new hopes for a revolution in solar cell technology. However, there are many challenges which need to be resolved in order to reveal the true potential of this technology. An issue which should be addressed in designing PSCs is the metal-hole transporting material (HTM) contact’s property. One of the most promising inorganic HTMs for PSCs is Nickel oxide. Although NiO has been extensively studied in the literature, to the best of our knowledge metal-NiO junctions have never been studied experimentally. In this work, metal-NiO contacts have been investigated to indicate a novel route to choose proper metals in designing PSCs based on NiO as the HTM. Thus, NiO layers with four various metals have been fabricated and comprehensively explored. The contacts have been characterized using the transmission line method (TLM), and a contact resistivity ranging from about 2052 to 34 mΩ⋅cm2 was observed. I-V characteristics showed ohmic behavior in all metal-NiO cases. These results indicate that Fermi level pinning occurs at the valence band edge of the NiO. Further discussions resulted in suggesting Nickel as the most applicable candidate on NiO have been also included.
Pd Nanoparticles Incorporated Within a Zr-Based Metal–Organic Framework/Reduced Graphene Oxide Multifunctional Composite for Efficient Visible-Light-Promoted Benzyl Alcohol Oxidation
Authors: Li Ting , Tian Tian , Chen Fangyuan , Liu Xiang , Zhao Xiaohua
Published: January 2019

Metal–organic frameworks (MOFs) in photocatalysis oxidation reactions have been arousing great interest because of their unique properties. Zr-based MOFs (mainly 1,4-dicarboxybenzene MOF (UiO-66)) appear to be very attractive candidates. In this study, a Pd@UiO-66/reduced graphene oxide (rGO) nanocomposite was successfully prepared via a facile solvothermal method and was characterised by several techniques, including field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), x-ray diffraction (XRD), nitrogen adsorption–desorption isotherms, and photoluminescence (PL) spectroscopy. Subsequently, the as-obtained Pd@UiO-66/rGO composite was used as a photocatalyst for the selective oxidation of benzyl alcohol to benzaldehyde with O2 under visible light irradiation (>420nm); it exhibited superior photocatalytic activity due to the synergistic effect of coupling Pd nanoparticles (NPs) with UiO-66 and rGO. Importantly, the Pd@UiO-66/rGO composite showed high stability and considerable recyclability to preserve most of its initial photocatalytic activity after five cycles of the oxidation reaction.
Unemployment sequences and the risk of poverty: from counting duration to contextualizing sequences
Authors: Pohlig Matthias
Published: January 2019

Research has consistently shown that unemployment is a strong predictor for income poverty. So far, most studies have focused on the duration of unemployment to account for differences in income poverty. However, this practice may mistreat trajectories which conform less to the norm of continuous full-time employment before unemployment. In this article, I first develop a generalized framework which contextualizes unemployment sequences according to duration as well as timing and order. Second, I apply a sequence analysis to longitudinal data from five European welfare states—Austria, the Netherlands, Poland, Spain, and Sweden—using the European Union Statistics on Income and Living Conditions. Thereby, I construct a typology of unemployment sequences which includes some non-standard types of unemployment sequences. These sequences contain inactivity, part-time employment and self-employment spells and have an increased poverty risk. Thus, the sequence-based framework and the sequence analysis are able to contextualize unemployment sequences better than the conventional measure of unemployment duration.
Vitamin D and childhood asthma: causation and contribution to disease activity
Authors: Litonjua Augusto A.
Published: January 2019

Purpose of review

To review the literature of the past 18 months (April 2017 through September, 2018) relating to vitamin D and childhood asthma.

Recent findings

A combined analysis of two clinical trials of maternal vitamin D supplementation trials showed a significant protective effect of vitamin D supplementation trials in the primary prevention of asthma and recurrent wheeze up to age 3 years. Secondary analyses from these trials have also suggested that initial maternal vitamin D status could affect the response to supplementation during pregnancy, with the biggest protective effect in children born to mothers with initial 25hydroxyvitamin D (25OHD) levels of at least 30 ng/ml. A postnatal, 6-month vitamin D supplementation trial in black, premature babies showed a 34% decreased risk of recurrent wheezing at 1 year among the infants who received supplementation. An individual patient data meta-analysis of published clinical trials concluded that vitamin D supplementation decreased the risk of asthma exacerbations in those with 25OHD levels less than 10 ng/ml. Results of observational analyses on primary prevention of asthma and in prevention of exacerbations remain mixed, with the bulk of the evidence suggesting that there is a protective effect of higher vitamin D levels.

Evidence continues to accumulate that vitamin D supplementation helps to prevent the development of asthma and recurrent wheeze in early life, and may also help in the management of asthma. The level(s) of circulating vitamin D that maximizes these effects remains to be identified.
Symptom-based patient-reported outcomes in adults with eosinophilic esophagitis: value for treatment monitoring and randomized controlled trial design
Authors: Safroneeva Ekaterina , Schoepfer Alain M.
Published: January 2019

Purpose of review

In adults with eosinophilic esophagitis (EoE), a chronic, inflammatory immune-mediated condition of the esophagus, both inflammation and fibrosis are likely associated with symptom generation. Therefore, assessing symptom-based patient-reported outcomes (PROs), defined by US Food and Drug Administration as ‘any report of the status of a patient's health condition that comes directly from the patients, without interpretation of the patient's response by a clinician or anyone else’, is important in the context of trials and observational studies of emerging therapies.

Recent findings

For purposes of treatment monitoring, lack of symptoms does not predict the absence of biologic inflammation; hence, endoscopy with esophageal biopsies should be performed to check for residual inflammation. Lack of inflammation does not predict lack of symptoms, and the presence of subepithelial fibrosis cannot be excluded. No published instrument currently measures the frequency of dysphagia described all possible ways, strategies of living with this symptom and various pain types. In randomized controlled trials, in which symptom response was detected using validated PRO measures, only modest decreases in symptom scores were observed.

Accessing full EoE symptom spectrum and optimizing PRO measures remains a challenge that should be tackled to reliably assess response to existing and emerging therapies.
Fostering Transformative Learning in a Social Pediatrics Research Summer Studentship
Authors: Talarico Susanna , Zubairi Mohammad , Daneman Denis , Punnett Angela , Martimianakis Maria Athina (Tina)
Published: January 2019

Problem

Teaching future doctors the skills necessary to address health disparities is a challenge for medical educators. In response, the authors developed and implemented the Social Pediatrics Research Summer Studentship (SPReSS) program for medical students at the University of Toronto.

Approach

The curriculum incorporated research and clinical placements into a formal seminar series. Participating students were required to complete a research project and to write a reflection describing a situation that challenged their thinking. The authors and curriculum developers applied transformative learning principles not only to facilitate critical reflection and learning in the students but also as an innovative approach to program development and evaluation. The authors conducted a thematic analysis of the reflections of 23 students participating in the program in June and July 2013, 2014, and 2015 to evaluate the SPReSS program.

Outcomes

The analysis revealed students’ empathic responses to marginalized patients, and these responses acted as triggers for critical reflection. Students described feeling empowered to act as advocates and wrote that these feelings were reinforced through faculty members’ role modeling. According to their reflections, students found the program both challenging and rewarding, particularly the integration of the clinical and research experiences which made broader sociopolitical phenomena introduced through assigned readings and seminar discussions concrete.

Next Steps

The authors are exploring models, including a fourth-year selective or multiyear longitudinal experience, to support more students. They also hope to involve more community partners and to evaluate long-term outcomes of participants.
Confirming the Presence of Unrecognized Meniscal Injuries on Magnetic Resonance Imaging in Pediatric and Adolescent Patients With Anterior Cruciate Ligament Tears
Authors: Munger Alana M. , Gonsalves Nicholas R. , Sarkisova Natalya , Clarke Emily , VandenBerg Curtis D. , Pace J. Lee
Published: January 2019

Background:

Prior research has shown decreased accuracy of meniscal injury detection using magnetic resonance imaging (MRI) for anterior cruciate ligament (ACL)-deficient adult patients as well as ACL-deficient pediatric and adolescent patients. The objectives of this study were the following: (1) assess the diagnostic ability of MRI in detecting meniscal injuries for pediatric and adolescent patients undergoing arthroscopic ACL reconstruction and (2) characterize the unrecognized meniscal injuries.

Methods:

The sensitivity, specificity, positive predictive value, and negative predictive value of meniscal tears (medial, lateral, or both) on MRI were calculated for the 107 patients in this cohort. Fisher exact tests were used to compare event frequencies between medial meniscal (MM) and lateral meniscal (LM) tears. One-way analysis of variance tests were performed to compare event rates between the location and type of unrecognized meniscal tears.

Results:

The median age of the cohort was 15 (range: 7 to 18). The sensitivity, specificity, positive predictive value, and negative predictive value of MRI in detecting meniscal tears (medial, lateral, or both) in ACL-deficient pediatric and adolescent patients was 62.3%, 68.4%, 78.2%, and 50.0%, respectively. There were 26 (24.3%) cases in which a meniscal injury was not detected on MRI, but was discovered arthroscopically (MM: 5 knees, LM: 20 knees, both: 1 knee). These unrecognized meniscal injuries were more commonly the LM than the MM (77.8%, P-value=0.100), a vertical/longitudinal tear type (77.8%, P-value <0.001), and located in the posterior horn (74.1%, P-value <0.001).

Conclusions:

In this ACL-deficient pediatric and adolescent cohort, there were 26 (24.3%) patients with unrecognized meniscal injuries. A vertical tear in the posterior horn was the most commonly unrecognized meniscal injury, supporting the findings of prior research postulating that the location and configuration of a tear influence the accuracy of MRI in detecting these injuries. More research is needed to investigate strategies to improve the detection of meniscal tears in pediatric and adolescent patients preoperatively. These findings have implications with regard to patient counseling, operative planning, anticipatory guidance with regard to postoperative rehabilitation, recovery expectations, and surgical outcomes.

Level of Evidence:

Level IV.
High-Risk Human Papillomavirus E6/E7 mRNA Is Rarely Detected in Nonanogenital Cutaneous Squamous Cell Carcinoma: An RNA In Situ Hybridization–Based Tissue Microarray Study
Authors: Fujimoto Masakazu , Matsuzaki Ibu , Takahashi Yuichi , Iwahashi Yoshifumi , Warigaya Kenji , Kojima Fumiyoshi , Jinnin Masatoshi , Murata Shin-ichi
Published: January 2019

High-risk human papillomavirus (HR-HPV) is known to play an oncogenic role in squamous cell carcinoma (SCC) at certain anatomical sites, namely the uterine cervix, oropharynx, and anogenital skin. However, the association between HR-HPV and nonanogenital cutaneous SCC (CSCC) remains controversial. In this study, we addressed this controversy by performing HR-HPV E6/E7 mRNA in situ hybridization (ISH) on 243 CSCC samples. A cocktail of E6/E7 mRNA ISH probes, recognizing 18 HR-HPV genotypes, was applied to a tissue microarray of paraffin-embedded sections of 154 invasive and 89 in situ CSCC specimens. The anatomical sites of CSCC included the head and neck (n = 100), extremities (n = 100), trunk (n = 25), and anogenitalia (n = 18). We also investigated the correlation between the p16 expression and HR-HPV status by immunohistochemistry. The results of HR-HPV E6/E7 mRNA ISH showed that 5.8% (14/243) of all CSCC samples were positive for HR-HPV, including 66.7% (12/18) of the anogenital and only 0.9% (2/225) of the nonanogenital CSCC samples (P < 0.01). For the detection of diffuse p16 expression by immunohistochemistry, the sensitivity was 100% (14/14 HR-HPV–positive CSCC samples), and the specificity was 72.1% (165/229 HR-HPV–negative specimens). Thus, HR-HPV E6/E7 mRNA was rarely detected in nonanogenital CSCC, making it unlikely that the virus contributes to the pathogenesis of this malignancy. In addition, p16 immunoreactivity has a limited value as a surrogate marker for transcriptionally active HR-HPV in nonanogenital CSCC.
Hailey–Hailey–Like Pattern of Acantholysis on the Scalp Should Raise the Possibility of Incipient Pemphigus Vulgaris
Authors: Gottesman Silvija P. , Abedi Syed M. , Rosen Jason R. , Gottlieb Geoffrey J.
Published: January 2019

Hailey–Hailey disease (familial benign chronic pemphigus) is a genodermatosis with a typical clinical presentation of macerated plaques involving intertriginous areas of the body and affects multiple family members. Epidermal acanthosis, incipient, and completed acantholysis of many of the spinous keratinocytes of the epidermis and foci of dyskeratosis are well-recognized histologic findings. We have observed solitary lesions on the “scalp” of patients having a Hailey–Hailey–like pattern, and not the suprabasilar clefting of pemphigus represents the first manifestation of pemphigus vulgaris, which was confirmed with direct immunofluorescence in all our patients.
The effects of genetic variants related to insulin metabolism pathways and the interactions with lifestyles on colorectal cancer risk
Authors: Jung Su Yon , Zhang Zuo-Feng
Published: January 2019

Objectives:

Genetic variants in metabolic signaling pathways may interact with lifestyle factors, such as dietary fatty acids, influencing postmenopausal colorectal cancer (CRC) risk, but these interrelated pathways are not fully understood.

Methods:

In this study, we examined 54 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I/insulin traits and their signaling pathways and lifestyle factors in relation to postmenopausal CRC, using data from 6,539 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies. By employing a two-stage random survival forest analysis, we evaluated the SNPs and lifestyle factors by ranking them according to their predictive value and accuracy for CRC.

Results:

We identified four SNPs (IRS1 rs1801123, IRS1 rs1801278, AKT2 rs3730256, and AKT2 rs7247515) and two lifestyle factors (age and percentage calories from saturated fatty acids) as the top six most influential predictors for CRC risk. We further examined interactive effects of those factors on cancer risk. In the individual SNP analysis, no significant association was observed, but the combination of the four SNPs, age, and percentage calories from saturated fatty acid (≥11% per day) significantly increased the risk of CRC in a gene and lifestyle dose-dependent manner.

Conclusions:

Our findings provide insight into gene–lifestyle interactions and will enable researchers to focus on individuals with risk genotypes to promote intervention strategies. Our study suggests the careful use of data on potential genetic targets in clinical trials for cancer prevention to reduce the risk for CRC in postmenopausal women.
Quality of Care and Preventive Screening Use in the CareFirst Patient-Centered Medical Home Program
Authors: Kicinger Iwona M. , Cuellar Alison , Helmchen Lorens A. , Gimm Gilbert , Want Jay , Kells Bradley J. , Nichols Len M.
Published: January 2019

Despite their value, comprehensive diabetes care and screening for common cancers remain underutilized. We examined the association between participation in a patient-centered medical home (PCMH) program with strong financial incentives and receipt of preventive care in the first 5 years after program launch. Using multivariate regression analysis, we compared outcomes for adults under the care of participating primary care providers (PCPs) with adults under the care of nonparticipating PCPs. Outcomes were breast, cervical and colorectal cancer screenings, and elements of diabetes care. The analytic sample included 818,623 adults living in Maryland, Virginia, or the District of Columbia, and enrolled with CareFirst for at least 1 year during 2010–2015. By Year 5, enrollees in the intervention group were 7.9 (95% confidence interval [CI]: 2.8–13.0), 6.1 (95% CI: 1.4–10.7), 3.1 (95% CI: 2.1–4.0), and 7.6 (95% CI: 7.0–8.2) percentage points more likely to undergo HbA1c tests, nephropathy examinations, breast, and cervical cancer screenings, respectively. We found no significant change in the propensity to receive colorectal cancer screening or an eye examination. Our study shows that a PCMH program with strong financial incentives can raise the provision of preventive care but could require additional adjustment.
Alerting Wisely: Reducing Inappropriate Blood Chemistry Panel Orders Using a Clinical Decision Support Tool
Authors: Anderson Jonathan W. , Greenwood Mark R. , Borsato Gisele G. , Kuttler Kathryn G.
Published: January 2019

The Choosing Wisely (CW) initiative provides recommendations for healthcare providers, aimed at reducing unnecessary or inappropriate tests and procedures. A clinical decision support (CDS) alert in the electronic health record was developed to reflect organizational CW guidelines regarding blood chemistry panel ordering in the primary care setting. An interrupted time series design was used to analyze the weekly proportion of inappropriate blood chemistry panel orders prior to and after implementation of the CDS alert in treatment and control groups. Implementation of the CDS alert significantly decreased the average weekly proportion of inappropriate blood chemistry panels from 28.64% to 15.69% in the treatment group (p < .001). Apart from other efforts implemented simultaneously to reduce inappropriate lab ordering, the CDS alert produced a significant reduction in inappropriate lab ordering. We conclude that CDS alerts can be an effective strategy for healthcare organizations seeking to more closely adhere to CW guidelines.
Triage of Mild Head-Injured Intoxicated Patients Could Be Aided by Use of an Electroencephalogram-Based Biomarker
Authors: Michelson Edward , Huff J. Stephen , Garrett John , Naunheim Rosanne
Published: January 2019

Objective: Drug and alcohol (DA)–related emergency department (ED) visits represent an increasing fraction the head-injured population seen in the ED. Such patients present a challenge to the evaluation of head injury and determination of need for computed tomographic (CT) scan and further clinical path. This effort examined whether an electroencephalogram (EEG)-based biomarker could aid in reducing unnecessary CT scans in the intoxicated ED population. Method: This is a retrospective secondary study of an independent prospective US Food and Drug Administration validation trial that demonstrated the efficacy of (1) an automatic Structural Injury Classifier for the likelihood of injury visible on a CT (CT+) and (2) an EEG-based Brain Function Index to assess functional impairment in minimally impaired, head-injured adults presenting within 3 days of injury. Impact on the biomarker performance in patients who presented with or without DA was studied. Results: Structural Injury Classifier sensitivity was not significantly impacted by the presence of DA. Although specificity decreased, it remained several times higher than obtained using standard CT decision rules. Furthermore, the potential to reduce the number of unnecessary scans by approximately 30% was demonstrated when the Structural Injury Classifier was integrated into CT clinical triage. The Brain Function Index was demonstrated to be independent of the presence of DA. Conclusion: This EEG-based assessment technology used to identify the likelihood of structural or functional brain injury in mildly head-injured patients represents an objective way to aid in triage patients with DA on presentation, with the potential to decrease overscanning while not sacrificing sensitivity to injuries visible on CT.
Cryptococcosis-Associated Immune Reconstitution Inflammatory Syndrome Is Associated With Dysregulation of IL-7/IL-7 Receptor Signaling Pathway in T Cells and Monocyte Activation
Authors: Akilimali Ngomu Akeem , Muema Daniel M. , Specht Charles , Chang Christina C. , Moosa Mahomed-Yunus S. , Levitz Stuart M. , Lewin Sharon R. , French Martyn A. , Ndung'u Thumbi
Published: January 2019

Background:

Systemic levels of interleukin (IL)-7 at antiretroviral therapy (ART) initiation have previously been shown to be predictive of HIV-linked paradoxical cryptococcosis-associated immune reconstitution inflammatory syndrome (C-IRIS). We therefore explored IL-7/IL-7 receptor (IL-7/IL-7R) signaling pathway dysfunction, with related alterations in immune function, as a mechanism underlying C-IRIS.

Method:

HIV-infected patients with cryptococcal meningitis who experienced C-IRIS (n = 27) were compared with CD4+ T-cell count-matched counterparts without C-IRIS (n = 27), after antifungal therapy and pre-ART initiation. Flow cytometry was used to assess T-cell and monocyte phenotypes and functions.

Results:

Proportions of IL-7R+ CD4+ or CD8+ T cells correlated positively with CD4+ T-cell counts and proportions of central memory and naive CD4+ and CD8+ T-cell pre-ART (all r > 0.50 and P < 0.05); however, the former negatively correlated with CD4+ T-cell counts fold-increase on ART in non–C-IRIS but not C-IRIS patients. Higher frequencies of activated monocytes (CD14+CD86+ or CD14+HLA-DR+; P ≤ 0.038) were also observed in C-IRIS compared with non–C-IRIS patients, and those who failed to clear cryptococci from cerebrospinal fluid before ART had higher levels of activated monocytes (CD14+HLA-DR+, P = 0.017) compared with those who cleared. In multivariate regression, CD14+HLA-DR+ monocytes were independently associated with C-IRIS [hazard ratio = 1.055 (1.013–1.098); P = 0.009].

Conclusion:

In contrast to non–C-IRIS patients, C-IRIS patients displayed a lack of association between proportions of IL-7R+ T cells and several markers of T-cell homeostasis. They also exhibited higher monocyte activation linked to cerebrospinal fluid cryptococcal culture positivity before ART. These data suggest a role for IL-7/IL-7R signaling pathway dysregulation in the pathogenesis of C-IRIS, possibly linked to monocyte activation and residual pathogen burden before ART.
Validation of the American College of Surgeons National Surgical Quality Improvement Program Risk Model for Patients Undergoing Panniculectomy
Authors: Suresh Visakha , Levites Heather , Peskoe Sarah , Hein Rachel , Avashia Yash , Erdmann Detlev
Published: January 2019

Purpose

Panniculectomy procedures have been reported to significantly improve quality of life, increase mobility, and improve hygiene in patients with a significant pannus formation. The primary aims of this study were to determine which preoperative risk factors may be used to differentiate postoperative complication rate among patient cohorts and to validate utilization of the American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) risk calculator in patients undergoing panniculectomies.

Methods

This retrospective study included all patients who underwent a panniculectomy procedure at our institution from 2005 to 2016. Baseline characteristics, preoperative risk factors, medical comorbidities, and postoperative complications were collected via retrospective chart review.

Results

Two hundred sixty-four patients who underwent a panniculectomy were identified. The odds ratios of any postoperative complication were 8.26, 7.76, and 16.6 for patients with classes 1, 2, and 3 obesity, respectively (P < 0.05). Statistical modeling was utilized to evaluate the predictive performance of the ACS-NSQIP Surgical Risk Calculator. We calculated the C-statistic for the ACS-NSQIP model to be only 0.61, indicating that although the model is associated with the risk of complication, it does not have a strong predictive value for this particular procedure.

Discussion

This study is one of the first to characterize postoperative complication rate based on extremum of body mass index for panniculectomy patients. Our results show that the utilization of the ACS-NSQIP Risk Calculator in this particular patient population underestimates the complication risk as a whole, which may necessitate the future development of a separate risk assessment model for this procedure.
Improving the Reliability of V-Wave Responses in the Soleus Muscle
Authors: Mendonca Goncalo V. , Teodósio Carolina , Mouro Miguel , Freitas Sandro , Mil-Homens Pedro , Pezarat-Correia Pedro , Vila-Chã Carolina
Published: January 2019

Purpose:

The V wave is an electrophysiologic variant of the H reflex that is evoked with supramaximal stimulus intensity. In this study, we explored whether the between-day reliability of V-wave normalized amplitude varies as a function of the number of intrasession measurement trials. We also determined whether the reliability of the V wave improves after the exclusion of the initial testing trials.

Methods:

Eighteen healthy, young participants (10 men and 8 women) were included in this study. Test–retest reliability was assessed using intraclass correlation coefficients and the standard error of the measurement (1.96*SEM).

Results:

The intraclass correlation coefficient values of the V-wave normalized amplitude increased in a progressive fashion with the inclusion of more than two measurement trials (from 0.41 to 0.75). The 1.96*SEM scores also decreased from 12.47% to 7.60% after calculating the V-wave normalized amplitude from five versus two measurement trials. After excluding the first two trials from V-wave calculations, the intraclass correlation coefficient and the 1.96*SEM score attained values of 0.88 and 6.54%, respectively.

Conclusions:

Our findings indicate that the test–retest reliability of the V-wave response increases in a progressive fashion with more than two intrasession measurement trials (up to five trials). It also shows that to ensure maximal reliability, the first two measurement trials should be discarded from V-wave computations.
Enhancing breakpoint resolution with deep segmentation model: a general refinement method for read-depth based structural variant callers
Authors: Zhang Yao-zhong , Imoto Seiya , Miyano Satoru , Yamaguchi Rui
Published: January 2019

Motivation

For short-read sequencing, read-depth based structural variant (SV) callers are difficult to find single-nucleotide-resolution breakpoints due to the bin-size limitation.

Results

In this paper, we present RDBKE to enhance the breakpoint resolution of read-depth SV callers using deep segmentation model UNet. We show that UNet can be trained with a small amount of data and applied for breakpoint enhancement both in-sample and cross-sample. On both simulation and real data, RDBKE significantly increases the number of SVs with more precise breakpoints.

Availability

source code of RDBKE is available athttps://github.com/yaozhong/deepIntraSV

Contact

yaozhong@ims.u-tokyo.ac.jp