A spline-based regression parameter set for creating customized DARTEL MRI brain templates from infancy to old age.
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ABSTRACT:
SUBMITTER: Wilke M
PROVIDER: S-EPMC5752094 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundWe wished to produce a single reference gene set for honey bee (Apis mellifera). Our motivation was twofold. First, we wished to obtain an improved set of gene models with increased coverage of known genes, while maintaining gene model quality. Second, we wished to provide a single official gene list that the research community could further utilize for consistent and comparable analyses and functional annotation.ResultsWe created a consensus gene set for honey bee (Apis mellifera) using GLEAN, a new algorithm that uses latent class analysis to automatically combine disparate gene prediction evidence in the absence of known genes. The consensus gene models had increased representation of honey bee genes without sacrificing quality compared with any one of the input gene predictions. When compared with manually annotated gold standards, the consensus set of gene models was similar or superior in quality to each of the input sets.ConclusionMost eukaryotic genome projects produce multiple gene sets because of the variety of gene prediction programs. Each of the gene prediction programs has strengths and weaknesses, and so the multiplicity of gene sets offers users a more comprehensive collection of genes to use than is available from a single program. On the other hand, the availability of multiple gene sets is also a cause for uncertainty among users as regards which set they should use. GLEAN proved to be an effective method to combine gene lists into a single reference set.
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Project description:We present an overhang-based DNA block shuffling method to create a customized random DNA library with flexible sequence design and length. Our method enables the efficient and seamless assembly of short DNA blocks with dinucleotide overhangs through a simple ligation process. Next generation sequencing analysis of the assembled DNA library revealed that ligation was accurate, directional and unbiased. This straightforward DNA assembly method should fulfill the versatile needs of both in vivo and in vitro functional screening of random peptides and RNA created with a desired amino acid and nucleotide composition, as well as making highly repetitive gene constructs that are difficult to synthesize de novo.
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Project description:BACKGROUND:To evaluate and establish a digital workflow for the custom designing and 3D printing of mouth opening tongue-depressing (MOTD) stents for patients receiving radiotherapy for head and neck cancer. METHODS:We retrospectively identified 3 patients who received radiation therapy (RT) for primary head and neck cancers with MOTD stents. We compared two methods for obtaining the digital impressions of patients' teeth. The first method involved segmentation from computed tomography (CT) scans, as previously established by our group, and the second method used 3D scanning of the patients' articulated stone models that were made during the conventional stent fabrication process. Three independent observers repeated the process to obtain digital impressions which provided data to design customized MOTD stents. For each method, we evaluated the time efficiency, dice similarity coefficient (DSC) for reproducibility, and the 3D printed stents' accuracy. For the 3D scanning method, we evaluated the registration process using manual and automatic approaches. RESULTS:For all patients, the 3D scanning method demonstrated a significant advantage over the CT scanning method in terms of time efficiency with over 60% reduction in time consumed (p?<?0.0001) and reproducibility with significantly higher DSC (p?<?0.001). The printed stents were tested over the articulated dental stone models, and the trueness of fit and accuracy of dental anatomy was found to be significantly better for MOTD stents made using the 3D scanning method. The automated registration showed higher accuracy with errors <?0.001?mm compared to manual registration. CONCLUSIONS:We developed an efficient workflow for custom designing and 3D-printing MOTD radiation stents. This workflow represents a considerable improvement over the CT-derived segmentation method. The application of this rapid and efficient digital workflow into radiation oncology practices can expand the use of these toxicity sparing devices to practices that do not currently have the support to make them.
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Project description:Penalized regression methods that perform simultaneous model selection and estimation are ubiquitous in statistical modeling. The use of such methods is often unavoidable as manual inspection of all possible models quickly becomes intractable when there are more than a handful of predictors. However, automated methods usually fail to incorporate domain-knowledge, exploratory analyses, or other factors that might guide a more interactive model-building approach. A hybrid approach is to use penalized regression to identify a set of candidate models and then to use interactive model-building to examine this candidate set more closely. To identify a set of candidate models, we derive point and interval estimators of the probability that each model along a solution path will minimize a given model selection criterion, for example, Akaike information criterion, Bayesian information criterion (AIC, BIC), etc., conditional on the observed solution path. Then models with a high probability of selection are considered for further examination. Thus, the proposed methodology attempts to strike a balance between algorithmic modeling approaches that are computationally efficient but fail to incorporate expert knowledge, and interactive modeling approaches that are labor intensive but informed by experience, intuition, and domain knowledge. Supplementary materials for this article are available online.
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Project description:PurposeHemodynamic atlases can add to the pathophysiological understanding of cardiac diseases. This study proposes a method to create hemodynamic atlases using 4D Flow magnetic resonance imaging (MRI). The method is demonstrated for kinetic energy (KE) and helicity density (Hd ).Materials and methodsThirteen healthy subjects underwent 4D Flow MRI at 3T. Phase-contrast magnetic resonance cardioangiographies (PC-MRCAs) and an average heart were created and segmented. The PC-MRCAs, KE, and Hd were nonrigidly registered to the average heart to create atlases. The method was compared with 1) rigid, 2) affine registration of the PC-MRCAs, and 3) affine registration of segmentations. The peak and mean KE and Hd before and after registration were calculated to evaluate interpolation error due to nonrigid registration.ResultsThe segmentations deformed using nonrigid registration overlapped (median: 92.3%) more than rigid (23.1%, P < 0.001), and affine registration of PC-MRCAs (38.5%, P < 0.001) and affine registration of segmentations (61.5%, P < 0.001). The peak KE was 4.9 mJ using the proposed method and affine registration of segmentations (P?=?0.91), 3.5 mJ using rigid registration (P < 0.001), and 4.2 mJ using affine registration of the PC-MRCAs (P < 0.001). The mean KE was 1.1 mJ using the proposed method, 0.8 mJ using rigid registration (P < 0.001), 0.9 mJ using affine registration of the PC-MRCAs (P < 0.001), and 1.0 mJ using affine registration of segmentations (P?=?0.028). The interpolation error was 5.2?±?2.6% at mid-systole, 2.8?±?3.8% at early diastole for peak KE; 9.6?±?9.3% at mid-systole, 4.0?±?4.6% at early diastole, and 4.9?±?4.6% at late diastole for peak Hd . The mean KE and Hd were not affected by interpolation.ConclusionHemodynamic atlases can be obtained with minimal user interaction using nonrigid registration of 4D Flow MRI.Level of evidence2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1389-1399.
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