4 research outputs found

    Estimating the Age of a Bloodstain Using Mitochondrial rRNA

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    DNA evidence is considered the gold standard of evidence in forensic investigations. DNA is one of the most highly discriminatory pieces of evidence found at crime scenes and can link individuals to scenes. It is not relied on to perform temporal estimates to help establish a timeline for when a crime took place. Previous studies have shown that measurement of the degradation of RNA is a potential tool to establish a temporal estimate of when a blood sample was left at a crime scene. This experiment attempts to improve on previous RNA degradation studies by evaluating the validity of mitochondrial ribosomal RNA and quantitative PCR as method of age determination of a bloodstain. This approach was unsuccessful in estimating the age of a bloodstain due to the lack of consistent degradation as samples aged. The expected starting ratio of mitochondrial ribosomal RNA was also found to be inconsistent. While this approach was unsuccessful, it provides insights that may allow for further refinement of this assay to estimate the age of a bloodstain

    Closed-Loop Systems and In Vitro Neuronal Cultures: Overview and Applications

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    One of the main limitations preventing the realization of a successful dialogue between the brain and a putative enabling device is the intricacy of brain signals. In this perspective, closed-loop in vitro systems can be used to investigate the interactions between a network of neurons and an external system, such as an interacting environment or an artificial device. In this chapter, we provide an overview of closed-loop in vitro systems, which have been developed for investigating potential neuroprosthetic applications. In particular, we first explore how to modify or set a target dynamical behavior in a network of neurons. We then analyze the behavior of in vitro systems connected to artificial devices, such as robots. Finally, we provide an overview of biological neuronal networks interacting with artificial neuronal networks, a configuration currently offering a promising solution for clinical applications
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