3 resultados para Caro, Annibal, 1507-1566.

em Duke University


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BACKGROUND AND PURPOSE: Previous studies have demonstrated that treatment strategy plays a critical role in ensuring maximum stone fragmentation during shockwave lithotripsy (SWL). We aimed to develop an optimal treatment strategy in SWL to produce maximum stone fragmentation. MATERIALS AND METHODS: Four treatment strategies were evaluated using an in-vitro experimental setup that mimics stone fragmentation in the renal pelvis. Spherical stone phantoms were exposed to 2100 shocks using the Siemens Modularis (electromagnetic) lithotripter. The treatment strategies included increasing output voltage with 100 shocks at 12.3 kV, 400 shocks at 14.8 kV, and 1600 shocks at 15.8 kV, and decreasing output voltage with 1600 shocks at 15.8 kV, 400 shocks at 14.8 kV, and 100 shocks at 12.3 kV. Both increasing and decreasing voltages models were run at a pulse repetition frequency (PRF) of 1 and 2 Hz. Fragmentation efficiency was determined using a sequential sieving method to isolate fragments less than 2 mm. A fiberoptic probe hydrophone was used to characterize the pressure waveforms at different output voltage and frequency settings. In addition, a high-speed camera was used to assess cavitation activity in the lithotripter field that was produced by different treatment strategies. RESULTS: The increasing output voltage strategy at 1 Hz PRF produced the best stone fragmentation efficiency. This result was significantly better than the decreasing voltage strategy at 1 Hz PFR (85.8% vs 80.8%, P=0.017) and over the same strategy at 2 Hz PRF (85.8% vs 79.59%, P=0.0078). CONCLUSIONS: A pretreatment dose of 100 low-voltage output shockwaves (SWs) at 60 SWs/min before increasing to a higher voltage output produces the best overall stone fragmentation in vitro. These findings could lead to increased fragmentation efficiency in vivo and higher success rates clinically.

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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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The dynamics of a population undergoing selection is a central topic in evolutionary biology. This question is particularly intriguing in the case where selective forces act in opposing directions at two population scales. For example, a fast-replicating virus strain outcompetes slower-replicating strains at the within-host scale. However, if the fast-replicating strain causes host morbidity and is less frequently transmitted, it can be outcompeted by slower-replicating strains at the between-host scale. Here we consider a stochastic ball-and-urn process which models this type of phenomenon. We prove the weak convergence of this process under two natural scalings. The first scaling leads to a deterministic nonlinear integro-partial differential equation on the interval $[0,1]$ with dependence on a single parameter, $\lambda$. We show that the fixed points of this differential equation are Beta distributions and that their stability depends on $\lambda$ and the behavior of the initial data around $1$. The second scaling leads to a measure-valued Fleming-Viot process, an infinite dimensional stochastic process that is frequently associated with a population genetics.