Pappasflindt8171

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Repeat proteins are abundant in eukaryotic proteomes. They are involved in many eukaryotic specific functions, including signalling. For many of these proteins, the structure is not known, as they are difficult to crystallise. Today, using direct coupling analysis and deep learning it is often possible to predict a protein's structure. However, the unique sequence features present in repeat proteins have been a challenge to use direct coupling analysis for predicting contacts. Here, we show that deep learning-based methods (trRosetta, DeepMetaPsicov (DMP) and PconsC4) overcomes this problem and can predict intra- and inter-unit contacts in repeat proteins. In a benchmark dataset of 815 repeat proteins, about 90% can be correctly modelled. Further, among 48 PFAM families lacking a protein structure, we produce models of forty-one families with estimated high accuracy.Naja atra is a major venomous snake found in Taiwan. The bite of this snake causes extensive wound necrosis or necrotizing soft tissue infection. Conventional microbial culture-based techniques may fail to identify potential human pathogens and render antibiotics ineffective in the management of wound infection. Therefore, we evaluated 16S Sanger sequencing and next-generation sequencing (NGS) to identify bacterial species in the oropharynx of N. atra. selleck products Using conventional microbial culture methods and the VITEK 2 system, we isolated nine species from snakebite wounds. On the basis of the 16S Sanger sequencing of bacterial clones from agar plates, we identified 18 bacterial species in the oropharynx of N. atra, including Morganella morganii, Proteus vulgaris, and Proteus mirabilis, which were also present in the infected bite wound. Using NGS of 16S metagenomics, we uncovered more than 286 bacterial species in the oropharynx of N. atra. In addition, the bacterial species identified using 16S Sanger sequencing accounted for only 2% of those identified through NGS of 16S metagenomics. The bacterial microbiota of the oropharynx of N. atra were modeled better using NGS of 16S metagenomics compared to microbial culture-based techniques. Stenotrophomonas maltophilia, Acinetobacter baumannii, and Proteus penneri were also identified in the NGS of 16S metagenomics. Understanding the bacterial microbiota that are native to the oropharynx of N. atra, in addition to the bite wound, may have additional therapeutic implications regarding empiric antibiotic selection for managing N. atra bites.Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score-the IntelliSep Index (ISI)-that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence (n = 307), we defined specific metrics-the aspect ratio and visco-elastic inertial response-that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence (n = 94) and healthy donors (n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis.We demonstrate that the native configuration of a self-mixing interferometer attains a minimum detectable displacement of 0.72 nm or λ/1870 at the laser wavelength of 1310 nm, obtained by the bare laser diode package including a monitor photodiode, observed in the electrical domain by means of an oscilloscope and without any electronic processing of the signal.We report here the first-ever, to the best of our knowledge, observation of an inconsistency in the fringe disappearance that occurs in self-mixing interferometers. The disappearance of fringes has been observed in vibration and absolute distance sensing schemes under moderate/strong feedback regimes, and it has a major impact on the design of self-mixing sensors. The number of missing fringes that mostly depends on the feedback strength is also linked to the establishment of the initial stable solution, and, as a consequence, the first modulation period will result in more fringes than expected in the case of an already permanent modulation. We demonstrate that this phenomenon is entirely predicted by the well-admitted dynamic rate equation model of the laser under optical feedback followed by the perfect agreement with experimental results.Fluorescence imaging techniques such as fluorescein angiography and fundus autofluorescence are often used to diagnose retinal pathologies; however, there are currently no standardized test methods for evaluating device performance. Here we present microstructured fluorescent phantoms fabricated using a submicron-scale three-dimensional printing technology, direct laser writing (DLW). We employ an in situ DLW technique to print 10 µm diameter microfluidic channels that support perfusions of fluorescent dyes. We then demonstrate how broadband photoresist fluorescence can be exploited to generate resolution targets and biomimetic models of retinal vasculature using standard DLW processes. The results indicate that these approaches show significant promise for generating better performance evaluation tools for fluorescence microscopy and imaging devices.