16 research outputs found
Multi-objective Optimization of Supercritical Water Gasification of Leftover Brazilian Ginseng Roots After Phytochemical Recovery Steps
Use of Gumbel and Weibull functions to model extreme values of diameter distributions in forest stands
Identification of regulatory variants associated with genetic susceptibility to meningococcal disease
Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA - a NF-kB subunit, master regulator of the response to infection - under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes
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Theoretical and empirical advancements in presenteeism research
Fully automated nipple detection in 3D breast ultrasound images
Nipple position provides useful diagnostic informations in reading automated 3D breast ultrasound (ABUS) images. The identification of nipples is required to localize and determine the quadrants of breast lesions. Additionally, the nipple position serves as an effective landmark to register an ABUS image to other imaging modalities, such as digital mammography, breast magnet resonance imaging (MRI), or tomosynthesis. Nevertheless, the presence of speckle noise induced by interference waves and variant imaging directions in ultrasonography poses challenges to the task. In this work, we propose a fast and automated algorithm to detect nipples in 3D breast ultrasound images. The method fully takes advantages of the consistent characteristics of ultrasonographic signals observed at nipples and employs a multi-scale Laplacian-based blob detector to eventually identify nipple positions. The accuracy of the proposed method was tested on 113 ABUS images, resulting in a distance error of 6.6±8.9 mm (mean ±std)
A hybrid method towards automated nipple detection in 3D breast ultrasound images
In clinical work-up of breast cancer, nipple position is an important marker to locate lesions. Moreover, it serves as an effective landmark to register a 3D automated breast ultrasound (ABUS) images to other imaging modalities, e.g., X-ray mammography, tomosynthesis or magnetic resonance imaging (MRI). However, the presence of speckle noises caused by the interference waves and variant imaging directions poses challenges to automatically identify nipple positions. In this work, a hybrid fully automatic method to detect nipple positions in ABUS images is presented. The method extends the multi-scale Laplacian-based method that we proposed previously, by integrating a specially designed Hessian-based method to locate the shadow area beneath the nipple and areola. Subsequently, the likelihood maps of nipple positions generated by both methods are combined to build a joint-likelihood map, where the final nipple position is extracted. To validate the efficiency and robustness, the extended hybrid method was tested on 926 ABUS images, resulting in a distance error of 7.08±10.96 mm (mean±standard deviation)
Attempt to Determine the Prevalence of Two Inborn Errors of Primary Bile Acid Synthesis: Results of a European Survey
Objective: Inborn errors of primary bile acid (BA) synthesis are genetic cholestatic disorders leading to accumulation of atypical BA with deficiency of normal BA. Unless treated with primary BA, chronic liver disease usually progresses to cirrhosis and liver failure before adulthood. We sought to determine the prevalence of 2 common disorders, 3β-hydroxy-Δ 5-C 27-steroid dehydrogenase (3β-HSD) and Δ 4-3-oxosteroid-5β-reductase (Δ 4-3-oxoR) deficiencies and to describe current diagnostic and treatment strategies among different European paediatric hepatology centres. Methods: A total of 52 clinical paediatric centres were approached and 39 centres in 21 countries agreed to participate in the Web-based survey. The survey comprised questions regarding general information, number of cases, diagnostic, and therapeutic management. Results: Seventeen centres located in 11 countries reported patients with inborn errors in primary BA synthesis, 22 centres never had cases diagnosed. In total, we could identify 63 patients; 55 with 3β-HSD and 8 with Δ 4-3-oxoR deficiency in 21 countries. The minimum estimated combined prevalence of these diseases was 1.13 cases per 10 million (0.99 and 0.14 for 3β-HSD and Δ 4-3-oxoR deficiencies, respectively). The surveyed colleagues indicated their main challenges to be the rarity of diseases and the lack of convenient laboratory facilities nearby. Conclusion: We have identified the largest cohort of patients with 3β-HSD or Δ 4-3-oxoR deficiency described so far. These diseases are likely underdiagnosed mainly due to unawareness of their existence and the lack of laboratory facilities