Osteopoikilosis is a benign, autosomal dominant sclerosing dysplasia of bone characterized by the presence of numerous bone islands in the skeleton. Presentation
The radiographic appearance of osteopoikilosis on an X-ray is characterized by a pattern of numerous white densities of similar size spread throughout all the bones. This is a systemic condition. It must be differentiated from blastic metastasis, which can also present radiographically as white densities interspersed throughout bone. Blastic metastasis tends to present with larger and more irregular densities in less of a uniform pattern. Another differentiating factor is age, with blastic metastasis mostly affecting older people, and osteopoikilosis being found in people 20 years of age and younger. The distribution is variable, though it does not tend to affect the ribs, spine, or skull. Cause
Epidemiology
Men and women are affected in equal number, reflecting the fact that osteopoikilosis attacks indiscriminately. Additionally, the disease is often associated with melorheostosis, despite the apparent lack of correlation between melorheostosis and genetic heritability. It has been tied to LEMD3. Buschke–Ollendorff syndrome is a similar condition, which is also associated with LEMD3. See also
List of radiographic findings associated with cutaneous conditions

References


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If the mechanisms a pathogens uses to initially enter a new species are well characterized and understood a certain level of risk control and prevention can be obtained. In contact, a poor understanding of pathogens, and their associated diseases, makes it harder for preventive measures to be takenAlternative hosts can also potentially have a critical role in the evolution and diffusion of a pathogen. When a pathogen crosses species it often acquires new characteristics that allow it to breach host barriers. Different pathogen variants can have very different effects on host species. Thus it can be beneficial to CST analysis to compare the same pathogens occurring in different host species. Phylogenetic analysis can be used to track a pathogens history through different species populations. Even if a pathogen is new and highly divergent, phylogenetic comparison can be very insightful. A useful strategy for investigating the history of epidemics caused by pathogen transmission combines molecular clock analysis, to estimate the timescale of the epidemic, and coalescent theory, to infer the demographic history of the pathogen. When constructing phylogenies, computer databases and tools are often used. Programs, such as BLAST, are used to annotate pathogen sequences, while databases like GenBank provide information about functions based on the pathogens genomic structure. Trees are constructed using computational methods such as MPR or Bayesian Inference, and models are created depending on the needs of the study. Single rate dated tip (SRDT) models, for example, allows for estimates of timescale under a phylogenetic tree.