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We present a multifaceted approach to effectively probe complex local protein environments utilizing the vibrational reporter unnatural amino acid (UAA) 4-cyano-l-phenylalanine (pCNPhe) in the model system superfolder green fluorescent protein (sfGFP). This approach combines temperature-dependent infrared (IR) spectroscopy, X-ray crystallography, and molecular dynamics (MD) simulations to provide a molecular interpretation of the local environment of the nitrile group in the protein. Specifically, a two-step enantioselective synthesis was developed that provided an 87% overall yield of pCNPhe in high purity without the need for chromatography. It was then genetically incorporated individually at three unique sites (74, 133, and 149) in sfGFP to probe these local protein environments. The incorporation of the UAA site-specifically in sfGFP utilized an engineered, orthogonal tRNA synthetase in E. coli using the Amber codon suppression protocol, and the resulting UAA-containing sfGFP constructs were then explored with this approach. This methodology was effectively utilized to further probe the local environments of two surface sites (sites 133 and 149) that we previously explored with room temperature IR spectroscopy and X-ray crystallography and a new interior site (site 74) featuring a complex local environment around the nitrile group of pCNPhe. Site 133 was found to be solvent-exposed, while site 149 was partially buried. Site 74 was found to consist of three distinct local environments around the nitrile group including nonspecific van der Waals interactions, hydrogen-bonding to a structural water, and hydrogen-bonding to a histidine side chain.

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Protein-protein interactions (PPIs) have been extensively utilized in synthetic biology to construct artificial gene networks. However, synthetic regulation of gene expression by PPIs in E. coli has largely relied upon repressors, and existing PPI-controlled transcriptional activators have generally been employed with heterodimeric interactions. Here we report a highly modular, PPI-dependent transcriptional activator, cCadC, that was designed to be compatible with homomeric interactions. We describe the process of engineering cCadC from a transmembrane protein into a soluble cytosolic regulator. We then show that gene transcription by cCadC can be controlled by homomeric PPIs and furthermore discriminates between dimeric and higher-order interactions. Finally, we demonstrate that cCadC activity can be placed under small molecule regulation using chemically induced dimerization or ligand dependent stabilization. This work should greatly expand the scope of PPIs that can be employed in artificial gene circuits in E. coli and complements the existing repertoire of tools for transcriptional regulation in synthetic biology.

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Directed evolution has been remarkably successful in identifying enzyme variants with new or improved properties, such as altered substrate scope or novel reactivity. Genetically encodable biosensors (GEBs), which convert the concentration of a small molecule ligand into an easily detectable output signal, have seen increasing application to enzyme directed evolution in the last decade. GEBs enable the use of high-throughput methods to assess enzyme activity of very large libraries, which can accelerate the search for variants with desirable activity. Here, we review different classes of GEBs and their properties in the context of enzyme evolution, how GEBs have been integrated into directed evolution workflows, and recent examples of enzyme evolution efforts utilizing GEBs. Finally, we discuss the advantages, challenges, and opportunities for using GEBs in the directed evolution of enzymes.

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The use of automatic electrical stimulation in response to early seizure detection has been introduced as a new treatment for intractable epilepsy. For the effective application of this method as a successful treatment, improving the accuracy of the early seizure detection is crucial. In this paper, we proposed the application of a frequency-based algorithm derived from principal component analysis (PCA), and demonstrated improved efficacy for early seizure detection in a pilocarpine-induced epilepsy rat model. A total of 100 ictal electroencephalographs (EEG) during spontaneous recurrent seizures from 11 epileptic rats were finally included for the analysis. PCA was applied to the covariance matrix of a conventional EEG frequency band signal. Two PCA results were compared: one from the initial segment of seizures (5 sec of seizure onset) and the other from the whole segment of seizures. In order to compare the accuracy, we obtained the specific threshold satisfying the target performance from the training set, and compared the False Positive (FP), False Negative (FN), and Latency (Lat) of the PCA based feature derived from the initial segment of seizures to the other six features in the testing set. The PCA based feature derived from the initial segment of seizures performed significantly better than other features with a 1.40% FP, zero FN, and 0.14 s Lat. These results demonstrated that the proposed frequency-based feature from PCA that captures the characteristics of the initial phase of seizure was effective for early detection of seizures. Experiments with rat ictal EEGs showed an improved early seizure detection rate with PCA applied to the covariance of the initial 5 s segment of visual seizure onset instead of using the whole seizure segment or other conventional frequency bands.

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BACKGROUND: Photographs of skin wounds have the most important information during the secondary intention healing (SIH). However, there is no standard method for handling those images and analyzing them efficiently and conveniently. OBJECTIVE: To investigate the sequential changes of SIH depending on the body sites using a color patch method. METHODS: We performed retrospective reviews of 30 patients (11 facial and 19 non-facial areas) who underwent SIH for the restoration of skin defects and captured sequential photographs with a color patch which is specially designed for automatically calculating defect and scar sizes. RESULTS: Using a novel image analysis method with a color patch, skin defects were calculated more accurately (range of error rate: -3.39% ~ + 3.05%). All patients had smaller scar size than the original defect size after SIH treatment (rates of decrease: 18.8% ~ 86.1%), and facial area showed significantly higher decrease rate compared with the non-facial area such as scalp and extremities (67.05 ± 12.48 vs. 53.29 ± 18.11, P < 0.05). From the result of estimating the date corresponding to the half of the final decrement, all of the facial area showed improvements within two weeks (8.45 ± 3.91), and non-facial area needed 14.33 ± 9.78 days. CONCLUSION: From the results of sequential changes of skin defects, SIH can be recommended as an alternative treatment method for restoration with more careful dressing for initial two weeks.

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In this paper, a correction method of defocus and geometric distortion for projected images on nonideal projection surfaces is proposed. To offer distortion-free images on curved projection surfaces, a camera captures the projected image to estimate the distortion. To compensate for defocus, which is due to the change in distance from the projector to the projection surface, the space varying point-spread function of the projector is modeled using a thin lens model. The performance of the proposed algorithm is verified from experiments when the projection surface is curved; the defocus is compensated for using the space varying point-spread function while correcting for the geometric distortion. Employing a point-spread function model, which depends on the distance from the projector to the projection surface, is quite simple and accurate; therefore, a focused image could be obtained using space varying deconvolution. The aim of our proposed method is for application to mobile projectors.

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Fluorescence lifetime imaging microscopy (FLIM) is a microscopic imaging technique to present an image of fluorophore lifetimes. It circumvents the problems of typical imaging methods such as intensity attenuation from depth since a lifetime is independent of the excitation intensity or fluorophore concentration. The lifetime is estimated from the time sequence of photon counts observed with signal-dependent noise, which has a Poisson distribution. Conventional methods usually estimate single or biexponential decay parameters. However, a lifetime component has a distribution or width, because the lifetime depends on macromolecular conformation or inhomogeneity. We present a novel algorithm based on a sparse representation which can estimate the distribution of lifetime. We verify the enhanced performance through simulations and experiments.

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In certain image acquisitions processes, like in fluorescence microscopy or astronomy, only a limited number of photons can be collected due to various physical constraints. The resulting images suffer from signal dependent noise, which can be modeled as a Poisson distribution, and a low signal-to-noise ratio. However, the majority of research on noise reduction algorithms focuses on signal independent Gaussian noise. In this paper, we model noise as a combination of Poisson and Gaussian probability distributions to construct a more accurate model and adopt the contourlet transform which provides a sparse representation of the directional components in images. We also apply hidden Markov models with a framework that neatly describes the spatial and interscale dependencies which are the properties of transformation coefficients of natural images. In this paper, an effective denoising algorithm for Poisson-Gaussian noise is proposed using the contourlet transform, hidden Markov models and noise estimation in the transform domain. We supplement the algorithm by cycle spinning and Wiener filtering for further improvements. We finally show experimental results with simulations and fluorescence microscopy images which demonstrate the improved performance of the proposed approach.

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Non-planar screens are increasingly used in mobile projectors and virtual reality environments. When the screen is modeled as a second order polynomial, a quadric transfer method can be employed to compensate for image distortion. This method uses the quadric matrix that models 3D surface information of a quadric screen. However, if the shape of the screen changes or the screen is moved, the 3D shape of the screen must be measured again to update the quadric matrix. We propose a new method of compensating for image distortion resulting from variation of the quadric screen. The proposed method is simpler and faster than remeasuring the 3D screen matrix.

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A subject-specific local in vivo passive shimming method, focusing on the prefrontal and temporal regions, is proposed. The aim of the investigation is to show that subject variability exists in optimal passive shimming and that the proposed method can be effectively used to overcome these differences. A shimming structure capable of adjusting the position of the passive shims to within a millimeter resolution is built. The optimal shim positions for each individual subject are computed from obtained field map using a convex optimization algorithm. Passive shim experiments at predetermined fixed shim positions vs. individually adjusted shim positions were performed and compared. The results show that intersubject variability exists in the optimal shim positions and that the location-sensitive method proposed can be useful for improving main field homogeneity in vivo.

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The majority of color histogram equalization methods do not yield uniform histogram in gray scale. After converting a color histogram equalized image into gray scale, the contrast of the converted image is worse than that of an 1-D gray scale histogram equalized image. We propose a novel 3-D color histogram equalization method that produces uniform distribution in gray scale histogram by defining a new cumulative probability density function in 3-D color space. Test results with natural and synthetic images are presented to compare and analyze various color histogram equalization algorithms based upon 3-D color histograms. We also present theoretical analysis for nonideal performance of existing methods.