bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bayesian age‐period‐cohort prediction of lung cancer incidence in China
Authors: Chen Wan‐Qing , Zheng Rong‐Shou , Zeng Hong‐Mei 
Published: June 2011

AbstractBackground:  Lung cancer is one of the most common cancers in China. Estimation of future cancer trends is important for cancer control planning. The aim of this study was to examine the trend of lung cancer incidence from 1998 to 2007 and predict the lung cancer burden up to 2020 in China.Materials and methods:  Lung cancer incidence data were retrieved from the national cancer registration database from 1998 to 2007. Annual population projection for the same period was obtained from the National Statistics Bureau. The Bayesian Age‐Period‐Cohort Modeling and Prediction package (Institute of Biomedical Engineering, Imperial College, London, UK) was used to describe the trend of lung cancer incidence and to predict the incidence rate and number of cases until the year 2020.Results:  The crude incidence rates of lung cancer increased from 43.39 per 100 000 in 1998 to 51.25 per 100 000 in 2007. After age standardization, the incidence rates remained stable over the 10‐year period. The trends were mainly caused by aging, no obvious period effects and cohort effects were observed. Our projection showed that the age‐standardized lung cancer incidence rate would remain steady until 2020. The estimated number of new incident cases was predicted to increase to 693 727 in 2020.Conclusion:  The burden of lung cancer incidence is likely to continue increasing. Effective policies such as smoking cessation and environmental protection are imperative for lung cancer control and prevention.
High prevalence of hepatitis C virus infection in Airin district, Osaka, Japan: A hospital‐based study of 1162 patients
Authors: Yamaguchi Yasunori , Enomoto Masaru , Fujii Hideki , Tamori Akihiro , Sakaguchi Hiroki , Tanigawa Tetsuya , Watanabe Kenji , Fujiwara Yasuhiro , Arakawa Tetsuo , Harihara Shigeyoshi , Monna Takeyuki , Kawada Norifumi 
Published: June 2011

Aim:  The Airin district, located in Nishinari‐ku, Osaka, is known as Japan's largest slum area, and has the largest concentration of day laborers in the country. We conducted a large hospital‐based study to determine the prevalence of hepatitis C virus (HCV) infection in the district.Methods:  The subjects were 1162 men (mean age, 57 ± 9 years) admitted to the Osaka Socio‐Medical Center Hospital between April 2005 and March 2008. Their case records were retrospectively reviewed.Results:  Anti‐HCV antibodies were found in 218 (18.8%) patients; in contrast, only 24 (2.1%) patients had hepatitis B surface antigen. The prevalence of anti‐HCV antibodies was 59% among the 122 patients admitted for liver diseases and 14% among the 1040 patients with other diseases. Among 927 patients with normal alanine aminotransferase levels (≤40 IU/L), 128 (13.8%) had anti‐HCV antibodies. The prevalence of anti‐HCV antibodies increased with age significantly (P < 0.001). At least 33 of the 218 (15%) patients with anti‐HCV antibodies admitted to having a history of injection drug use. Interferon therapy was initiated in 26 patients (11 with genotype 1, 14 with genotype 2 and one unclassifiable), but only six completed their scheduled regimens. Hepatocellular carcinoma was diagnosed in 20 patients, but only seven had early‐stage disease in which curative treatment, such as surgical hepatectomy or percutaneous ablation, was indicated.Conclusion:  The prevalence of HCV infection in the Airin district is extremely higher than that in the Japanese general population. Patient education and strict action against illegal drug use are indispensable to prevent the spread of HCV infection from the district.
Sorting nexin 19 regulates the number of dense core vesicles in pancreatic β‐cells
Authors: Harashima Shin‐ichi , Horiuchi Takahiko , Wang Yu , Notkins Abner Louis , Seino Yutaka , Inagaki Nobuya 
Published: June 2011

AbstractAims/Introduction:  Insulinoma‐associated protein 2 (IA‐2) regulates insulin secretion and the number of dense core vesicles (DCV). However, the mechanism of regulation of DCV number by IA‐2 is unknown. We examined the effect of sorting nexin 19 (SNX19), an IA‐2 interacting protein, on insulin secretion and the number of dense core vesicles (DCV).Materials and Methods:  Stable SNX19 knockdown (SNX19KD) MIN6, a mouse pancreatic β‐cell line, and stable SNX19‐reintroduced SNX19KD MIN6 were established. Quantification of DCV, and lysosomes was carried out using electron micrographs. The half‐life of DCV was detected by pulse‐chase experiment.Results:  Insulin secretion and content were decreased in stable SNX19KD MIN6 cells compared with those in control MIN6 cells. Electron micrographs showed that DCV number in SNX19KD cells was decreased by approximately 75% and that DCV size was decreased by approximately 40% compared with those in control cells, respectively. Furthermore, when SNX19 was reintroduced in SNX19KD cells, insulin content, insulin secretion and DCV number were increased. The half‐life of DCV was decreased in SNX19KD cells, but was increased in SNX19KD cells in which SNX19 was reintroduced. The number of lysosomes and the activity of lysosome enzyme cathepsin D were increased by approximately threefold in SNX19KD cells compared with those in control cells. In contrast, they were decreased to approximately half to one‐third in SNX19‐reintroduced SNX19KD cells.Conclusions:  SNX19 regulates the number of DCV and insulin content by stabilizing DCV in β‐cells. (J Diabetes Invest, doi: 10.1111/j.2040‐1124.2011.00138.x, 2012)
Association of human papillomavirus with denture wearing
Authors: Saini Rajan , Osman Nurainina Binti , Ismail Mazian , Sobri Farini Mohd , Tang Thean Hock , Santhanam Jacinta 
Published: June 2011

AbstractAim:  To determine the prevalence of human papillomavirus in the oral cavity of denture wearers.Methods:  Swabs were collected from 72 denture wearers and 72 controls (non‐denture wearers) to obtain DNA. Amplification of the β‐globin gene was performed by polymerase chain reaction to check the integrity of extracted DNA. The presence of human papillomavirus in the DNA sample was detected by nested polymerase chain reaction.Results:  The prevalence of human papillomavirus was found to be significantly higher in the oral cavity of denture wearers (38/72, 52.8%) than in the controls (17/72, 23.6%; odds ratio = 3.612, confidence interval = 1.771/7.385, P = <0.001). When adjusted for variables, including age, sex, ethnicity, and smoking habit, human papillomavirus was still found to be significantly associated with denture wearing, with an adjusted odds of 3.2 (P = 0.008). No association of human papillomavirus positivity was found with denture variables, including denture type, denture material type, duration of denture wearing, and denture hygiene (P > 0.05). Low‐risk human papillomavirus types were found to be more frequent in both groups.Conclusions:  The prevalence of human papillomavirus in the oral cavity of denture wearers was found to be significantly higher compared to controls; however, it was mainly low‐risk types.
How safe is mist netting? evaluating the risk of injury and mortality to birds
Authors: Spotswood Erica N. , Goodman Kari Roesch , Carlisle Jay , Cormier Renée L. , Humple Diana L. , Rousseau Josée , Guers Susan L. , Barton Gina G. 
Published: June 2011

Summary1. The capture of birds using mist nets is a widely utilized technique for monitoring avian populations. While the method is assumed to be safe, very few studies have addressed how frequently injuries and mortalities occur and the associated risks have not been formally evaluated.2. We quantified the rates of mortality and injury at 22 banding organizations in the United States and Canada and used capture data from five organizations to determine what kinds of incidents occur most frequently. Analyses focused on passerines and near‐passerines, but other groups were included. We evaluated whether body mass, age, sex, mist net mesh size, month and time of day or frequency of capture are related to the risk or type of incident. We also compared the recapture histories over time between birds that were injured and those that were never injured for 16 species.3. The average rate of injury was 0·59%, while mortality was 0·23%. Birds captured frequently were less at risk to incident. Body mass was positively correlated with incident and larger birds were at greater risk to predation, leg injuries, broken legs, internal bleeding and cuts, while smaller birds were more prone to stress, tangling‐related injuries and wing strain. Rates of incident varied among species, with some at greater risk than others. We found no evidence for increased mortality over time of injured birds compared with uninjured birds.4. We provide the first comprehensive evaluation of the risks associated with mist netting. Our results indicate that (1) injury and mortality rates below one percent can be achieved during mist netting and (2) injured birds are likely to survive in comparable numbers to uninjured birds after release. While overall risks are low, this study identified vulnerable species and traits that may increase a bird’s susceptibility to incident that should be considered in banding protocols aimed at minimizing injury and mortality. Projects using mist nets should monitor their performance and compare their results to those of other organizations.
MOTMOT: models of trait macroevolution on trees
Authors: Thomas Gavin H. , Freckleton Robert P. 
Published: June 2011

Summary1. Models of trait macroevolution on trees (MOTMOT) is a new software package that tests for variation in the tempo and mode of continuous character evolution on phylogenetic trees. MOTMOT provides tools to fit a range of models of trait evolution with emphasis on variation in the rate of evolution between clades and character states.2. We introduce a new method, trait MEDUSA, to identify the location of major changes in the rate of evolution of continuous traits on phylogenetic trees. We demonstrate trait MEDUSA and the other main functions of MOTMOT, using body size of Anolis lizards.3. MOTMOT is open source software written in the R language and is freely available from CRAN (http://cran.r‐project.org/web/packages/).
Developing procedural flexibility: Are novices prepared to learn from comparing procedures?
Authors: Rittle‐Johnson Bethany , Star Jon R. , Durkin Kelley 
Published: June 2011

Background.  A key learning outcome in problem‐solving domains is the development of procedural flexibility, where learners know multiple procedures and use them appropriately to solve a range of problems (e.g., Verschaffel, Luwel, Torbeyns, & Van Dooren, 2009). However, students often fail to become flexible problem solvers in mathematics. To support flexibility, teaching standards in many countries recommend that students be exposed to multiple procedures early in instruction and be encouraged to compare them.Aims.  We experimentally evaluated this recommended instructional practice for supporting procedural flexibility during a classroom lesson, relative to two alternative conditions. The alternatives reflected the common instructional practice of delayed exposure to multiple procedures, either with or without comparison of procedures.Sample.  Grade 8 students from two public schools (N= 198) were randomly assigned to condition. Students had not received prior instruction on multi‐step equation solving, which was the topic of our lessons.Method.  Students learned about multi‐step equation solving under one of three conditions in math class for about 3 hr. They also completed a pre‐test, post‐test, and 1‐month‐retention test on their procedural knowledge, procedural flexibility, and conceptual knowledge of equation solving.Results.  Novices who compared procedures immediately were more flexible problem solvers than those who did not, even on a 1‐month retention test. Although condition had limited direct impact on conceptual and procedural knowledge, greater flexibility was associated with greater knowledge of both types.Conclusions.  Comparing procedures can support flexibility in novices and early introduction to multiple procedures may be one important reason.
General knowledge monitoring as a predictor of in‐class exam performance
Authors: Hartwig Marissa K. , Was Chris A. , Isaacson Randy M. , Dunlosky John 
Published: June 2011

Background. Current theories of self‐regulated learning predict a positive link between student monitoring accuracy and performance: students who more accurately monitor their knowledge of a particular set of materials are expected to more effectively regulate their subsequent study of those materials, which in turn should lead to higher test performance.Aims. The present study further explored the link between monitoring accuracy and performance by investigating whether monitoring of one set of materials would predict performance on a different set of materials.Sample. The participants were college students (N= 379) enrolled in an educational psychology course.Method. Students’ monitoring accuracy was measured at the start of the semester; the monitoring task involved materials that were not related to class content (i.e., general knowledge vocabulary) and that were related to class content (i.e., terms from educational psychology). Target performance was students’ scores on the final exam.Results. Monitoring accuracy significantly predicted student performance on the final exam, even when the monitoring task and final test were based on materials from different content domains. Also, the class‐related (vs. unrelated) materials in the monitoring task did not improve the predictive validity of monitoring accuracy, suggesting a limited role for domain specificity in the relationship between monitoring skill and performance.Conclusions. This study establishes a critical link between general monitoring accuracy and exam performance within a classroom setting.
2D/3D fetal cardiac dataset segmentation using a deformable model
Authors: Dindoyal Irving , Lambrou Tryphon , Deng Jing , Todd‐Pokropek Andrew 
Published: June 2011

Purpose:To segment the fetal heart in order to facilitate the 3D assessment of the cardiac function and structure.Methods:Ultrasound acquisition typically results in drop‐out artifacts of the chamber walls. The authors outline a level set deformable model to automatically delineate the small fetal cardiac chambers. The level set is penalized from growing into an adjacent cardiac compartment using a novel collision detection term. The region based model allows simultaneous segmentation of all four cardiac chambers from a user defined seed point placed in each chamber.Results:The segmented boundaries are automatically penalized from intersecting at walls with signal dropout. Root mean square errors of the perpendicular distances between the algorithm's delineation and manual tracings are within 2 mm which is less than 10% of the length of a typical fetal heart. The ejection fractions were determined from the 3D datasets. We validate the algorithm using a physical phantom and obtain volumes that are comparable to those from physically determined means. The algorithm segments volumes with an error of within 13% as determined using a physical phantom.Conclusions:Our original work in fetal cardiac segmentation compares automatic and manual tracings to a physical phantom and also measures inter observer variation.
A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology
Authors: Wang Zhiyue J. , Seo Youngseob , Chia Jonathan M. , Rollins Nancy K. 
Published: June 2011

Purpose:To propose a quality assurance procedure for routine clinical diffusion tensor imaging (DTI) using the widely available American College of Radiology (ACR) head phantom.Methods:Analysis was performed on the data acquired at 1.5 and 3.0 T on whole body clinical MRI scanners using the ACR phantom and included the following: (1) the signal‐to‐noise ratio (SNR) at the center and periphery of the phantom, (2) image distortion by EPI readout relative to spin echo imaging, (3) distortion of high‐b images relative to the b = 0 image caused by diffusion encoding, and (4) determination of fractional anisotropy (FA) and mean diffusivity (MD) measured with region‐of‐interest (ROI) and pixel‐based approaches. Reproducibility of the measurements was assessed by five repetitions of data acquisition on each scanner.Results:The SNR at the phantom center was approximately half of that near the periphery at both 1.5 and 3 T. The image distortion by the EPI readout was up to 7 mm at 1.5 T and 10 mm at 3 T. The typical distortion caused by eddy currents from diffusion encoding was on the order of 0.5 mm. The difference between ROI‐based and pixel‐based MD quantification was 1.4% at 1.5 T and 0.3% at 3 T. The ROI‐based MD values were in close agreement (within 2%) with the reference values. The ROI‐based FA values were approximately a factor of 10 smaller than pixel‐based values and less than 0.01. The measurement reproducibility was sufficient for quality assurance (QA) purposes.Conclusions:This QA approach is simple to perform and evaluates key aspects of the scanner performance for DTI data acquisition using a widely available phantom.
Modeling diffusion‐weighted MRI as a spatially variant Gaussian mixture: Application to image denoising
Authors: Gonzalez Juan Eugenio Iglesias , Thompson Paul M. , Zhao Aishan , Tu Zhuowen 
Published: June 2011

Purpose:This work describes a spatially variant mixture model constrained by a Markov random field to model high angular resolution diffusion imaging (HARDI) data. Mixture models suit HARDI well because the attenuation by diffusion is inherently a mixture. The goal is to create a general model that can be used in different applications. This study focuses on image denoising and segmentation (primarily the former).Methods:HARDI signal attenuation data are used to train a Gaussian mixture model in which the mean vectors and covariance matrices are assumed to be independent of spatial locations, whereas the mixture weights are allowed to vary at different lattice positions. Spatial smoothness of the data is ensured by imposing a Markov random field prior on the mixture weights. The model is trained in an unsupervised fashion using the expectation maximization algorithm. The number of mixture components is determined using the minimum message length criterion from information theory. Once the model has been trained, it can be fitted to a noisy diffusion MRI volume by maximizing the posterior probability of the underlying noiseless data in a Bayesian framework, recovering a denoised version of the image. Moreover, the fitted probability maps of the mixture components can be used as features for posterior image segmentation.Results:The model‐based denoising algorithm proposed here was compared on real data with three other approaches that are commonly used in the literature: Gaussian filtering, anisotropic diffusion, and Rician‐adapted nonlocal means. The comparison shows that, at low signal‐to‐noise ratio, when these methods falter, our algorithm considerably outperforms them. When tractography is performed on the model‐fitted data rather than on the noisy measurements, the quality of the output improves substantially. Finally, ventricle and caudate nucleus segmentation experiments also show the potential usefulness of the mixture probability maps for classification tasks.Conclusions:The presented spatially variant mixture model for diffusion MRI provides excellent denoising results at low signal‐to‐noise ratios. This makes it possible to restore data acquired with a fast (i.e., noisy) pulse sequence to acceptable noise levels. This is the case in diffusion MRI, where a large number of diffusion‐weighted volumes have to be acquired under clinical time constraints.
Parallel fuzzy connected image segmentation on GPU
Authors: Zhuge Ying , Cao Yong , Udupa Jayaram K. , Miller Robert W. 
Published: June 2011

Purpose:Image segmentation techniques using fuzzy connectedness (FC) principles have shown their effectiveness in segmenting a variety of objects in several large applications. However, one challenge in these algorithms has been their excessive computational requirements when processing large image datasets. Nowadays, commodity graphics hardware provides a highly parallel computing environment. In this paper, the authors present a parallel fuzzy connected image segmentation algorithm implementation on NVIDIA's compute unified device Architecture (cuda) platform for segmenting medical image data sets.Methods:In the FC algorithm, there are two major computational tasks: (i) computing the fuzzy affinity relations and (ii) computing the fuzzy connectedness relations. These two tasks are implemented ascuda kernels and executed on GPU. A dramatic improvement in speed for both tasks is achieved as a result.Results:Our experiments based on three data sets of small, medium, and large data size demonstrate the efficiency of the parallel algorithm, which achieves a speed‐up factor of 24.4x, 18.1x, and 10.3x, correspondingly, for the three data sets on the NVIDIA Tesla C1060 over the implementation of the algorithm on CPU, and takes 0.25, 0.72, and 15.04 s, correspondingly, for the three data sets.Conclusions:The authors developed a parallel algorithm of the widely used fuzzy connected image segmentation method on the NVIDIA GPUs, which are far more cost‐ and speed‐effective than both cluster of workstations and multiprocessing systems. A near‐interactive speed of segmentation has been achieved, even for the large data set.
Reflection modeling in ultraviolet phototherapy
Authors: Grimes David Robert , Robbins Chris , Martin Colin J. , Phanco Graeme , O'Hare Neil John 
Published: June 2011

Purpose:Ultraviolet phototherapy is a widely used treatment which has exceptional success with a variety of skin conditions. Over‐exposure to ultraviolet radiation (UVR) can however be detrimental and cause side effects such as erythema, photokeratisis, and even skin cancer. Quantifying patient dose is therefore imperative to ensure biologically effective treatment while minimizing negative repercussions. A dose model for treatment would be valuable in achieving these ends.Methods:Prior work by the authors concentrated on modeling the output of the lamps used in treatment and it was found a line source model described the output from the sources to a high degree. In practice, these lamps are surrounded by reflective anodized aluminum in patient treatment cabins and this work extends the model to quantify specular reflections from these planes on patient dose.Results:The extension of the model to allow for reflected images in addition to tube output shows a remarkably good fit to the actual data measured.Conclusions:The reflection model yields impressive accuracy and is a good basis for full UVR cabin modeling.