Fracture Detection in Traumatic Pelvic CT Images

Fracture detection in pelvic bones is vital for patient diagnostic decisions and treatment planning in traumatic pelvic injuries. Manual detection of bone fracture from computed tomography (CT) images is very challenging due to low resolution of the images and the complex pelvic structures. Automated fracture detection from segmented bones can significantly help physicians analyze pelvic CT images and detect the severity of injuries in a very short period. This paper presents an automated hierarchical algorithm for bone fracture detection in pelvic CT scans using adaptive windowing, boundary tracing, and wavelet transform while incorporating anatomical information. Fracture detection is performed on the basis of the results of prior pelvic bone segmentation via our registered active shape model (RASM). The results are promising and show that the method is capable of detecting fractures accurately

Hemorrhage Detection and Segmentation in Traumatic Pelvic Injuries

Automated hemorrhage detection and segmentation in traumatic pelvic injuries is vital for fast and accurate treatment decision making. Hemorrhage is the main cause of deaths in patients within first 24 hours after the injury. It is very time consuming for physicians to analyze all Computed Tomography (CT) images manually. As time is crucial in emergence medicine, analyzing medical images manually delays the decision-making process. Automated hemorrhage detection and segmentation can significantly help physicians to analyze these images and make fast and accurate decisions. Hemorrhage segmentation is a crucial step in the accurate diagnosis and treatment decision-making process. This paper presents a novel rule-based hemorrhage segmentation technique that utilizes pelvic anatomical information to segment hemorrhage accurately. An evaluation measure is used to quantify the accuracy of hemorrhage segmentation. The results show that the proposed method is able to segment hemorrhage very well, and the results are promising

Overexpression of UV-DAMAGED DNA BINDING PROTEIN 1 links plant development and phytonutrient accumulation in high pigment-1 tomato

Fruits of tomato plants carrying the high pigment-1 mutations hp-1 and hp-1w are characterized by an increased number of plastids coupled with enhanced levels of functional metabolites. Unfortunately, hp-1 mutant plants are also typified by light-dependent retardation in seedling and whole-plant growth and development, which limits their cultivation. These mutations were mapped to the gene encoding UV-DAMAGED DNA BINDING PROTEIN 1 (DDB1) and, recently, fruit-specific RNA interference studies have demonstrated an increased number of plastids and enhanced carotenoid accumulation in the transgenic tomato fruits. However, whole-plant overexpression of DDB1, required to substantiate its effects on seedling and plant development and to couple them with fruit phenotypes, has heretofore been unsuccessful. In this study, five transgenic lines constitutively overexpressing normal DDB1 in hp-1 mutant plants were analysed. Eleven-day-old seedlings, representing these lines, displayed up to ∼73- and ∼221-fold overexpression of the gene in hypocotyls and cotyledons, respectively. This overexpression resulted in statistically significant reversion to the non-mutant developmental phenotypes, including more than a full quantitative reversion. This reversion of phenotypes was generally accompanied by correlated responses in chlorophyll accumulation and altered expression of selected light signalling genes: PHYTOCHROME A, CRYPTOCHROME 1, ELONGATED HYPOCOTYL 5, and the gene encoding CHLOROPHYLL A/B-BINDING PROTEIN 4. Cumulatively, these results provide the missing link between DDB1 and its effects on tomato plant development

Personizing the prediction of future susceptibility to a specific disease

A traceable biomarker is a member of a disease’s molecular pathway. A disease may be associated with several molecular pathways. Each different combination of these molecular pathways, to which detected traceable biomarkers belong, may serve as an indicative of the elicitation of the disease at a different time frame in the future. Based on this notion, we introduce a novel methodology for personalizing an individual’s degree of future susceptibility to a specific disease. We implemented the methodology in a working system called Susceptibility Degree to a Disease Predictor (SDDP). For a specific disease d, let S be the set of molecular pathways, to which traceable biomarkers detected from most patients of d belong. For the same disease d, let S′ be the set of molecular pathways, to which traceable biomarkers detected from a certain individual belong. SDDP is able to infer the subset S′′ ⊆{S-S′} of undetected molecular pathways for the individual. Thus, SDDP can infer undetected molecular pathways of a disease for an individual based on few molecular pathways detected from the individual. SDDP can also help in inferring the combination of molecular pathways in the set {S′+S′′}, whose traceable biomarkers collectively is an indicative of the disease. SDDP is composed of the following four components: information extractor, interrelationship between molecular pathways modeler, logic inferencer, and risk indicator. The information extractor takes advantage of the exponential increase of biomedical literature to automatically extract the common traceable biomarkers for a specific disease. The interrelationship between molecular pathways modeler models the hierarchical interrelationships between the molecular pathways of the traceable biomarkers. The logic inferencer transforms the hierarchical interrelationships between the molecular pathways into rule-based specifications. It employs the specification rules and the inference rules for predicate logic to infer as many as possible undetected molecular pathways of a disease for an individual. The risk indicator outputs a risk indicator value that reflects the individual’s degree of future susceptibility to the disease. We evaluated SDDP by comparing it experimentally with other methods. Results revealed marked improvement

Nonlinear partial differential equations and applications: Gene expression profiling of isogenic cells with different TP53 gene dosage reveals numerous genes that are affected by TP53 dosage and identifies CSPG2 as a direct target of p53

TP53 does not fully comply with the Knudson model [Knudson, A. G., Jr. (1971) Proc. Natl. Acad. Sci. USA 68, 820–823] in that a reduction of constitutional expression of p53 may be sufficient for tumor predisposition . This finding suggests a gene-dosage effect for p53 function. To determine whether TP53 gene dosage affects the transcriptional regulation of target genes, we performed oligonucleotide-array gene expression analysis by using human cells with wild-type p53 (p53 +/+), or with one (p53 +/−), or both (p53 −/−) TP53 alleles disrupted by homologous recombination. We identified 35 genes whose expression is significantly correlated to the dosage of TP53. These genes are involved in a variety of cellular processes including signal transduction, cell adhesion, and transcription regulation. Several of them are involved in neurogenesis and neural crest migration, developmental processes in which p53 is known to play a role. Motif search analysis revealed that of the genes highly expressed in p53 +/+ and +/− cells, several contain a putative p53 consensus binding site (bs), suggesting that they could be directly regulated by p53. Among those genes, we chose CSPG2 (which encodes versican) for further study because it contains a bona fide p53 bs in its first intron and its expression highly correlates with TP53 dosage. By using in vitro and in vivo assays, we showed CSPG2 to be directly transactivated by p53. In conclusion, we developed a strategy to demonstrate that many genes are affected by TP53 gene dosage for their expression. We report several candidate genes as potential downstream targets of p53 in nonstressed cells. Among them, CSPG2 is validated as being directly transactivated by p53. Our method provides a useful tool to elucidate additional mechanisms by which p53 exerts its functions

Preliminary Numerical and Experimental Analysis of the Spallation Phenomenon

The spallation phenomenon was studied through numerical analysis using a coupled Lagrangian particle tracking code and a hypersonic aerothermodynamics computational fluid dynamics solver. The results show that carbon emission from spalled particles results in a significant modification of the gas composition of the post shock layer. Preliminary results from a test-campaign at the NASA Langley HYMETS facility are presented. Using an automated image processing of high-speed images, two-dimensional velocity vectors of the spalled particles were calculated. In a 30 second test at 100 W/cm2 of cold-wall heat-flux, more than 1300 particles were detected, with an average velocity of 102 m/s, and most frequent observed velocity of 60 m/s

Agronomic performance and transcriptional analysis of carotenoid biosynthesis in fruits of transgenic HighCaro and control tomato lines under field conditions

Genetic manipulation of carotenoid biosynthesis in higher plants has been the objective of a number of biotechnology programs, e.g. the Golden Rice Program. However, tomato (Solanumlycopersicum L.), which naturally accumulates lycopene in fruits, has attracted the attention of many groups who have manipulated it to increase or diversify carotenoid accumulation. One of the most significant achievements was “HighCaro (HC),” a transgenic tomato plant constitutively expressing the tomato lycopene beta-cyclase (tLcy-b), that produces orange fruits due to the complete conversion of lycopene to β-carotene. In this article we report the results of a field trial conducted in Metaponto (Italy) on HC and on two control genotypes to evaluate the stability of the transgenic trait and their yield performances. Transcriptional regulation of eight genes involved in carotenogenesis was assayed by quantitative real-time PCR (qRT-PCR) analysis on fruits collected at four distinct development stages. Statistical analysis results demonstrated that in field conditions the transgene maintained its ability to induce the conversion of lycopene to β-carotene. Moreover, agronomic performances and fruit quality in the transgenic line were not impaired by this metabolic disturbance. Results of qRT-PCR analysis suggested that transcription of PSY-1, PDS and ZDS genes were developmentally regulated in both genotypes. Unexpectedly, Lcy-b expression in transgenic fruits was also developmentally regulated, despite the fact that the gene was driven by a constitutive promoter. Our data provide evidence that in photosynthetic cells a strict and aspecific mechanism controls the level of transcripts until the onset of chromoplasts differentiation, at which point a gene-specific control on transcription takes place

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

<p>Abstract</p> <p>Background</p> <p>Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server.</p> <p>Results</p> <p>MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only.</p> <p>Conclusions</p> <p>An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at <url>http://www.metnetonline.org/api</url>.</p

RBF-TSS: Identification of Transcription Start Site in Human Using Radial Basis Functions Network and Oligonucleotide Positional Frequencies

Accurate identification of promoter regions and transcription start sites (TSS) in genomic DNA allows for a more complete understanding of the structure of genes and gene regulation within a given genome. Many recently published methods have achieved high identification accuracy of TSS. However, models providing more accurate modeling of promoters and TSS are needed. A novel identification method for identifying transcription start sites that improves the accuracy of TSS recognition for recently published methods is proposed. This method incorporates a metric feature based on oligonucleotide positional frequencies, taking into account the nature of promoters. A radial basis function neural network for identifying transcription start sites (RBF-TSS) is proposed and employed as a classification algorithm. Using non-overlapping chunks (windows) of size 50 and 500 on the human genome, the proposed method achieves an area under the Receiver Operator Characteristic curve (auROC) of 94.75% and 95.08% respectively, providing increased performance over existing TSS prediction methods

Complexity of Bidirectional Transcription and Alternative Splicing at Human RCAN3 Locus

Human RCAN3 (regulator of calcineurin 3) belongs to the human RCAN gene family