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We examined temporal variations in overall Emergency Medical Services (EMS) demand, as well as medical and trauma cases separately. We analyzed cases according to time of day and day of week to determine whether population level demand demonstrates temporal patterns that will increase baseline knowledge for EMS planning. We conducted a secondary analysis of data from the Ambulance Victoria data warehouse covering the period 2008-2011. We included all cases of EMS attendance which resulted in 1,203,803 cases for review. Data elements comprised age, gender, date and time of call to the EMS emergency number along with the clinical condition of the patient. We employed Poisson regression to analyze case numbers and trigonometric regression to quantify distribution patterns. EMS demand exhibited a bimodal distribution with the highest peak at 10:00 and a second smaller peak at 19:00. The highest number of cases occurred on Fridays, and the lowest on Tuesdays and Wednesdays. However, the distribution of cases throughout the day differed by day of week. Distribution patterns on Fridays, Saturdays and Sundays differed significantly from the rest of the week (p < 0.001). When categorized into medical or trauma cases, medical cases were more frequent during working hours and involved patients of higher mean age (57 years vs. 49 years for trauma, p < 0.001). Trauma cases peaked on Friday and Saturday nights around midnight. Day of week EMS demand distribution patterns reveal differences that can be masked in aggregate data. Day of week EMS demand distribution patterns showed not only which days have differences in demand but the times of day at which the demand changes. Patterns differed by case type as well. These differences in distribution are important for EMS demand planning. Increased understanding of EMS demand patterns is imperative in a climate of ever-increasing demand and fiscal constraints. Further research is needed into the effect of age and case type on EMS
Cryo-electron microscopy (cryo-EM) has been established as one of the central tools in the structural study of macromolecular complexes. Although intermediate- or low-resolution structural information through negative staining or cryo-EM analysis remains highly valuable, we lack general and efficient ways to achieve unambiguous subunit identification in these applications. Here, we took advantage of the extremely high affinity between a dodecapeptide "PA" tag and the NZ-1 antibody Fab fragment to develop an efficient "yeast inner-subunit PA-NZ-1 labeling" strategy that when combined with cryo-EM could precisely identify subunits in macromolecular complexes. Using this strategy combined with cryo-EM 3D reconstruction, we were able to visualize the characteristic NZ-1 Fab density attached to the PA tag inserted into a surface-exposed loop in the middle of the sequence of CCT6 subunit present in the Saccharomyces cerevisiae group II chaperonin TRiC/CCT. This procedure facilitated the unambiguous localization of CCT6 in the TRiC complex. The PA tag was designed to contain only 12 amino acids and a tight turn configuration; when inserted into a loop, it usually has a high chance of maintaining the epitope structure and low likelihood of perturbing the native structure and function of the target protein compared to other tagging systems. We also found that the association between PA and NZ-1 can sustain the cryo freezing conditions, resulting in very high occupancy of the Fab in the final cryo-EM images. Our study demonstrated the robustness of this strategy combined with cryo-EM in efficient and accurate subunit identification in challenging multi-component complexes. Copyright © 2018 Elsevier Ltd. All rights reserved.
DNA replication in Eukaryotes is a highly dynamic process that involves several dozens of proteins. Some of these proteins form stable complexes that are amenable to high-resolution structure determination by cryo-EM, thanks to the recent advent of the direct electron detector and powerful image analysis algorithm. But many of these proteins associate only transiently and flexibly, precluding traditional biochemical purification. We found that direct mixing of the component proteins followed by 2D and 3D image sorting can capture some very weakly interacting complexes. Even at 2D average level and at low resolution, EM images of these flexible complexes can provide important biological insights. It is often necessary to positively identify the feature-of-interest in a low resolution EM structure. We found that systematically fusing or inserting maltose binding protein (MBP) to selected proteins is highly effective in these situations. In this chapter, we describe the EM studies of several protein complexes involved in the eukaryotic DNA replication over the past decade or so. We suggest that some of the approaches used in these studies may be applicable to structural analysis of other biological systems. © 2016 The Protein Society.
In cryo-electron microscopy (cryo-EM), a microscope generates a top view of a sample of randomly oriented copies of a molecule. The problem of single particle reconstruction (SPR) from cryo-EM is to use the resulting set of noisy two-dimensional projection images taken at unknown directions to reconstruct the three-dimensional (3D) structure of the molecule. In some situations, the molecule under examination exhibits structural variability, which poses a fundamental challenge in SPR. The heterogeneity problem is the task of mapping the space of conformational states of a molecule. It has been previously suggested that the leading eigenvectors of the covariance matrix of the 3D molecules can be used to solve the heterogeneity problem. Estimating the covariance matrix is challenging, since only projections of the molecules are observed, but not the molecules themselves. In this paper, we formulate a general problem of covariance estimation from noisy projections of samples. This problem has intimate connections with matrix completion problems and high-dimensional principal component analysis. We propose an estimator and prove its consistency. When there are finitely many heterogeneity classes, the spectrum of the estimated covariance matrix reveals the number of classes. The estimator can be found as the solution to a certain linear system. In the cryo-EM case, the linear operator to be inverted, which we term the projection covariance transform, is an important object in covariance estimation for tomographic problems involving structural variation. Inverting it involves applying a filter akin to the ramp filter in tomography. We design a basis in which this linear operator is sparse and thus can be tractably inverted despite its large size. We demonstrate via numerical experiments on synthetic datasets the robustness of our algorithm to high levels of noise. PMID:25699132
Investigating organelles such as the Golgi complex depends increasingly on high-throughput quantitative morphological analyses from multiple experimental or genetic conditions. Light microscopy (LM) has been an effective tool for screening but fails to reveal fine details of Golgi structures such as vesicles, tubules and cisternae. Electron microscopy (EM) has sufficient resolution but traditional transmission EM (TEM) methods are slow and inefficient. Newer volume scanning EM (volume-SEM) methods now have the potential to speed up 3D analysis by automated sectioning and imaging. However, they produce large arrays of sections and/or images, which require labour-intensive 3D reconstruction for quantitation on limited cell numbers. Here, we show that the information storage, digital waste and workload involved in using volume-SEM can be reduced substantially using sampling-based stereology. Using the Golgi as an example, we describe how Golgi populations can be sensed quantitatively using single random slices and how accurate quantitative structural data on Golgi organelles of individual cells can be obtained using only 5-10 sections/images taken from a volume-SEM series (thereby sensing population parameters and cell-cell variability). The approach will be useful in techniques such as correlative LM and EM (CLEM) where small samples of cells are treated and where there may be variable responses. For Golgi study, we outline a series of stereological estimators that are suited to these analyses and suggest workflows, which have the potential to enhance the speed and relevance of data acquisition in volume-SEM.
The information content of cryo EM data sets exceeds that of the electron scattering potential (cryo EM) density initially derived for structure determination. Previously we demonstrated the power of data variance analysis for characterizing regions of cryo EM density that displayed functionally important variance anomalies associated with maturation cleavage events in Nudaurelia Omega Capensis Virus and the presence or absence of a maturation protease in bacteriophage HK97 procapsids. Here we extend the analysis in two ways. First, instead of imposing icosahedral symmetry on every particle in the data set during the variance analysis, we only assume that the data set as a whole has icosahedral symmetry. This change removes artifacts of high variance along icosahedral symmetry axes, but retains all of the features previously reported in the HK97 data set. Second we present a covariance analysis that reveals correlations in structural dynamics (variance) between the interior of the HK97 procapsid with the protease and regions of the exterior (not seen in the absence of the protease). The latter analysis corresponds well with hydrogen deuterium exchange studies previously published that reveal the same correlation. Copyright © 2018 Elsevier Inc. All rights reserved.
Ice-repellent coatings can have significant impact on global energy savings and improving safety in many infrastructures, transportation, and cooling systems. Recent efforts for developing ice-phobic surfaces have been mostly devoted to utilizing lotus-leaf-inspired superhydrophobic surfaces, yet these surfaces fail in high-humidity conditions due to water condensation and frost formation and even lead to increased ice adhesion due to a large surface area. We report a radically different type of ice-repellent material based on slippery, liquid-infused porous surfaces (SLIPS), where a stable, ultrasmooth, low-hysteresis lubricant overlayer is maintained by infusing a water-immiscible liquid into a nanostructured surface chemically functionalized to have a high affinity to the infiltrated liquid and lock it in place. We develop a direct fabrication method of SLIPS on industrially relevant metals, particularly aluminum, one of the most widely used lightweight structural materials. We demonstrate that SLIPS-coated Al surfaces not only suppress ice/frost accretion by effectively removing condensed moisture but also exhibit at least an order of magnitude lower ice adhesion than state-of-the-art materials. On the basis of a theoretical analysis followed by extensive icing/deicing experiments, we discuss special advantages of SLIPS as ice-repellent surfaces: highly reduced sliding droplet sizes resulting from the extremely low contact angle hysteresis. We show that our surfaces remain essentially frost-free in which any conventional materials accumulate ice. These results indicate that SLIPS is a promising candidate for developing robust anti-icing materials for broad applications, such as refrigeration, aviation, roofs, wires, outdoor signs, railings, and wind turbines. 2b1af7f3a8