ABSTRACT
It has been shown that excessive white light exposure during retinal microsurgery can induce retinal damage. To address this problem, one can illuminate the retina with a device that alternates between white, and less damaging limited-spectrum light. The surgeon is then presented with a fully colored video by recoloring the limited-spectrum light frames, using information from the white-light frames. To obtain accurately colored images, while reducing phototoxicity, we have developed a novel algorithm that monitors the quality of the recolored images and determines when white light may be substituted by limited-spectrum light. We show qualitatively and quantitatively that our system can provide reliable images using a significantly smaller light dose as compared to other state-of-the-art coloring schemes.
Subject(s)
Colorimetry/methods , Lighting/methods , Microsurgery/methods , Retina/anatomy & histology , Retina/surgery , Retinoscopy/methods , Surgery, Computer-Assisted/methods , Feedback , Humans , Image Interpretation, Computer-Assisted/methods , Ophthalmologic Surgical Procedures/methods , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
When accounting for structural fluctuations or measurement errors, a single rigid structure may not be sufficient to represent a protein. One approach to solve this problem is to represent the possible conformations as a discrete set of observed conformations, an ensemble. In this work, we follow a different richer approach, and introduce a framework for estimating probability density functions in very high dimensions, and then apply it to represent ensembles of folded proteins. This proposed approach combines techniques such as kernel density estimation, maximum likelihood, cross-validation, and bootstrapping. We present the underlying theoretical and computational framework and apply it to artificial data and protein ensembles obtained from molecular dynamics simulations. We compare the results with those obtained experimentally, illustrating the potential and advantages of this representation.
Subject(s)
Computer Simulation , Models, Molecular , Proteins/chemistry , Algorithms , Amino Acid Motifs , Likelihood Functions , Microfilament Proteins/chemistry , Peptides/chemistry , Probability , Protein ConformationABSTRACT
Electroreceptive fish detect nearby objects by processing the information contained in the pattern of electric currents through their skin. In weakly electric fish, these currents arise from a self-generated field (the electric organ discharge), depending on the electrical properties of the surrounding medium. The electric image can be defined as the pattern of transepidermal voltage distributed over the receptive surface. To understand electrolocation it is necessary to know how electric image of objects are generated. In pulse mormyrids, the electric organ is localized at the tail, far from the receptors and fires a short biphasic pulse. Consequently, if all the elements in the environment are resistive, the stimulus at every point on the skin has the same waveform. Then, any measure of the amplitude (for example, the peak to peak amplitude) could be the unique parameter of the stimulus at any point of the skin. We have developed a model to calculate the image, corroborating that images are spread over the whole sensory surface and have an opposite center-surround, "Mexican-hat" shape. As a consequence, the images of different objects superimpose. We show theoretically and by simulation that the image of a pair of objects is not the simple addition of the individual images of these objects.
