9 resultados para animal anatomy

em Duke University


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Preclinical imaging has a critical role in phenotyping, in drug discovery, and in providing a basic understanding of mechanisms of disease. Translating imaging methods from humans to small animals is not an easy task. The purpose of this work is to review high-resolution computed tomography (CT) also known as micro-CT for small-animal imaging. We present the principles, the technologies, the image quality parameters, and the types of applications. We show that micro-CT can be used to provide not only morphological but also functional information such as cardiac function or vascular permeability. Another way in which micro-CT can be used in the study of both function and anatomy is by combining it with other imaging modalities, such as positron emission tomography or single-photon emission tomography. Compared to other modalities, micro-CT imaging is usually regarded as being able to provide higher throughput at lower cost and higher resolution. The limitations are usually associated with the relatively poor contrast mechanisms and the radiation damage, although the use of novel nanoparticle-based contrast agents and careful design of studies can address these limitations.

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Soft-tissue sarcomas (STSs) are rare mesenchymal tumors that arise from muscle, fat and connective tissue. Currently, over 75 subtypes of STS are recognized. The rarity and heterogeneity of patient samples complicate clinical investigations into sarcoma biology. Model organisms might provide traction to our understanding and treatment of the disease. Over the past 10 years, many successful animal models of STS have been developed, primarily genetically engineered mice and zebrafish. These models are useful for studying the relevant oncogenes, signaling pathways and other cell changes involved in generating STSs. Recently, these model systems have become preclinical platforms in which to evaluate new drugs and treatment regimens. Thus, animal models are useful surrogates for understanding STS disease susceptibility and pathogenesis as well as for testing potential therapeutic strategies.

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Diabetes mellitus is becoming increasingly prevalent worldwide. Additionally, there is an increasing number of patients receiving implantable devices such as glucose sensors and orthopedic implants. Thus, it is likely that the number of diabetic patients receiving these devices will also increase. Even though implantable medical devices are considered biocompatible by the Food and Drug Administration, the adverse tissue healing that occurs adjacent to these foreign objects is a leading cause of their failure. This foreign body response leads to fibrosis, encapsulation of the device, and a reduction or cessation of device performance. A second adverse event is microbial infection of implanted devices, which can lead to persistent local and systemic infections and also exacerbates the fibrotic response. Nearly half of all nosocomial infections are associated with the presence of an indwelling medical device. Events associated with both the foreign body response and implant infection can necessitate device removal and may lead to amputation, which is associated with significant morbidity and cost. Diabetes mellitus is generally indicated as a risk factor for the infection of a variety of implants such as prosthetic joints, pacemakers, implantable cardioverter defibrillators, penile implants, and urinary catheters. Implant infection rates in diabetic patients vary depending upon the implant and the microorganism, however, for example, diabetes was found to be a significant variable associated with a nearly 7.2% infection rate for implantable cardioverter defibrillators by the microorganism Candida albicans. While research has elucidated many of the altered mechanisms of diabetic cutaneous wound healing, the internal healing adjacent to indwelling medical devices in a diabetic model has rarely been studied. Understanding this healing process is crucial to facilitating improved device design. The purpose of this article is to summarize the physiologic factors that influence wound healing and infection in diabetic patients, to review research concerning diabetes and biomedical implants and device infection, and to critically analyze which diabetic animal model might be advantageous for assessing internal healing adjacent to implanted devices.

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The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

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High-throughput analysis of animal behavior requires software to analyze videos. Such software typically depends on the experiments' being performed in good lighting conditions, but this ideal is difficult or impossible to achieve for certain classes of experiments. Here, we describe techniques that allow long-duration positional tracking in difficult lighting conditions with strong shadows or recurring "on"/"off" changes in lighting. The latter condition will likely become increasingly common, e.g., for Drosophila due to the advent of red-shifted channel rhodopsins. The techniques enabled tracking with good accuracy in three types of experiments with difficult lighting conditions in our lab. Our technique handling shadows relies on single-animal tracking and on shadows' and flies' being accurately distinguishable by distance to the center of the arena (or a similar geometric rule); the other techniques should be broadly applicable. We implemented the techniques as extensions of the widely-used tracking software Ctrax; however, they are relatively simple, not specific to Drosophila, and could be added to other trackers as well.

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G protein-coupled Receptor Kinase 6 (GRK6) belongs to a family of kinases that phosphorylate GPCRs. GRK6 levels were found to be altered in Parkinson's Disease (PD) and D(2) dopamine receptors are supersensitive in mice lacking GRK6 (GRK6-KO mice). To understand how GRK6 modulates the behavioral manifestations of dopamine deficiency and responses to L-DOPA, we used three approaches to model PD in GRK6-KO mice: 1) the cataleptic response to haloperidol; 2) introducing GRK6 mutation to an acute model of absolute dopamine deficiency, DDD mice; 3) hemiparkinsonian 6-OHDA model. Furthermore, dopamine-related striatal signaling was analyzed by assessing the phosphorylation of AKT/GSK3β and ERK1/2. GRK6 deficiency reduced cataleptic behavior, potentiated the acute effect of L-DOPA in DDD mice, reduced rotational behavior in hemi-parkinsonian mice, and reduced abnormal involuntary movements induced by chronic L-DOPA. These data indicate that approaches to regulate GRK6 activity could be useful in modulating both therapeutic and side-effects of L-DOPA.

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Computed tomography (CT) is one of the most valuable modalities for in vivo imaging because it is fast, high-resolution, cost-effective, and non-invasive. Moreover, CT is heavily used not only in the clinic (for both diagnostics and treatment planning) but also in preclinical research as micro-CT. Although CT is inherently effective for lung and bone imaging, soft tissue imaging requires the use of contrast agents. For small animal micro-CT, nanoparticle contrast agents are used in order to avoid rapid renal clearance. A variety of nanoparticles have been used for micro-CT imaging, but the majority of research has focused on the use of iodine-containing nanoparticles and gold nanoparticles. Both nanoparticle types can act as highly effective blood pool contrast agents or can be targeted using a wide variety of targeting mechanisms. CT imaging can be further enhanced by adding spectral capabilities to separate multiple co-injected nanoparticles in vivo. Spectral CT, using both energy-integrating and energy-resolving detectors, has been used with multiple contrast agents to enable functional and molecular imaging. This review focuses on new developments for in vivo small animal micro-CT using novel nanoparticle probes applied in preclinical research.

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MOTIVATION: Although many network inference algorithms have been presented in the bioinformatics literature, no suitable approach has been formulated for evaluating their effectiveness at recovering models of complex biological systems from limited data. To overcome this limitation, we propose an approach to evaluate network inference algorithms according to their ability to recover a complex functional network from biologically reasonable simulated data. RESULTS: We designed a simulator to generate data representing a complex biological system at multiple levels of organization: behaviour, neural anatomy, brain electrophysiology, and gene expression of songbirds. About 90% of the simulated variables are unregulated by other variables in the system and are included simply as distracters. We sampled the simulated data at intervals as one would sample from a biological system in practice, and then used the sampled data to evaluate the effectiveness of an algorithm we developed for functional network inference. We found that our algorithm is highly effective at recovering the functional network structure of the simulated system-including the irrelevance of unregulated variables-from sampled data alone. To assess the reproducibility of these results, we tested our inference algorithm on 50 separately simulated sets of data and it consistently recovered almost perfectly the complex functional network structure underlying the simulated data. To our knowledge, this is the first approach for evaluating the effectiveness of functional network inference algorithms at recovering models from limited data. Our simulation approach also enables researchers a priori to design experiments and data-collection protocols that are amenable to functional network inference.

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BACKGROUND: In recent years large bibliographic databases have made much of the published literature of biology available for searches. However, the capabilities of the search engines integrated into these databases for text-based bibliographic searches are limited. To enable searches that deliver the results expected by comparative anatomists, an underlying logical structure known as an ontology is required. DEVELOPMENT AND TESTING OF THE ONTOLOGY: Here we present the Mammalian Feeding Muscle Ontology (MFMO), a multi-species ontology focused on anatomical structures that participate in feeding and other oral/pharyngeal behaviors. A unique feature of the MFMO is that a simple, computable, definition of each muscle, which includes its attachments and innervation, is true across mammals. This construction mirrors the logical foundation of comparative anatomy and permits searches using language familiar to biologists. Further, it provides a template for muscles that will be useful in extending any anatomy ontology. The MFMO is developed to support the Feeding Experiments End-User Database Project (FEED, https://feedexp.org/), a publicly-available, online repository for physiological data collected from in vivo studies of feeding (e.g., mastication, biting, swallowing) in mammals. Currently the MFMO is integrated into FEED and also into two literature-specific implementations of Textpresso, a text-mining system that facilitates powerful searches of a corpus of scientific publications. We evaluate the MFMO by asking questions that test the ability of the ontology to return appropriate answers (competency questions). We compare the results of queries of the MFMO to results from similar searches in PubMed and Google Scholar. RESULTS AND SIGNIFICANCE: Our tests demonstrate that the MFMO is competent to answer queries formed in the common language of comparative anatomy, but PubMed and Google Scholar are not. Overall, our results show that by incorporating anatomical ontologies into searches, an expanded and anatomically comprehensive set of results can be obtained. The broader scientific and publishing communities should consider taking up the challenge of semantically enabled search capabilities.