Structural Basis of Tail-Anchored Membrane Protein Biogenesis by the GET Insertase Complex.

Membrane protein biogenesis faces the challenge of chaperoning hydrophobic transmembrane helices for faithful membrane insertion. The guided entry of tail-anchored proteins (GET) pathway targets and inserts tail-anchored (TA) proteins into the endoplasmic reticulum (ER) membrane with an insertase (yeast Get1/Get2 or mammalian WRB/CAML) that captures the TA from a cytoplasmic chaperone (Get3 or TRC40, respectively). Here, we present cryo-electron microscopy reconstructions, native mass spectrometry, and structure-based mutagenesis of human WRB/CAML/TRC40 and yeast Get1/Get2/Get3 complexes. Get3 binding to the membrane insertase supports heterotetramer formation, and phosphatidylinositol binding at the heterotetramer interface stabilizes the insertase for efficient TA insertion in vivo. We identify a Get2/CAML cytoplasmic helix that forms a "gating" interaction with Get3/TRC40 important for TA insertion. Structural homology with YidC and the ER membrane protein complex (EMC) implicates an evolutionarily conserved insertion mechanism for divergent substrates utilizing a hydrophilic groove. Thus, we provide a detailed structural and mechanistic framework to understand TA membrane insertion.

The GET complex mediates insertion of tail-anchored proteins into the ER membrane.

Tail-anchored (TA) proteins, defined by the presence of a single C-terminal transmembrane domain (TMD), play critical roles throughout the secretory pathway and in mitochondria, yet the machinery responsible for their proper membrane insertion remains poorly characterized. Here we show that Get3, the yeast homolog of the TA-interacting factor Asna1/Trc40, specifically recognizes TMDs of TA proteins destined for the secretory pathway. Get3 recognition represents a key decision step, whose loss can lead to misinsertion of TA proteins into mitochondria. Get3-TA protein complexes are recruited for endoplasmic reticulum (ER) membrane insertion by the Get1/Get2 receptor. In vivo, the absence of Get1/Get2 leads to cytosolic aggregation of Get3-TA complexes and broad defects in TA protein biogenesis. In vitro reconstitution demonstrates that the Get proteins directly mediate insertion of newly synthesized TA proteins into ER membranes. Thus, the GET complex represents a critical mechanism for ensuring efficient and accurate targeting of TA proteins.

Maximum Entropy Technique and Regularization Functional for Determining the Pharmacokinetic Parameters in DCE-MRI.

This paper aims to solve the arterial input function (AIF) determination in dynamic contrast-enhanced MRI (DCE-MRI), an important linear ill-posed inverse problem, using the maximum entropy technique (MET) and regularization functionals. In addition, estimating the pharmacokinetic parameters from a DCE-MR image investigations is an urgent need to obtain the precise information about the AIF-the concentration of the contrast agent on the left ventricular blood pool measured over time. For this reason, the main idea is to show how to find a unique solution of linear system of equations generally in the form of [Formula: see text] named an ill-conditioned linear system of equations after discretization of the integral equations, which appear in different tomographic image restoration and reconstruction issues. Here, a new algorithm is described to estimate an appropriate probability distribution function for AIF according to the MET and regularization functionals for the contrast agent concentration when applying Bayesian estimation approach to estimate two different pharmacokinetic parameters. Moreover, by using the proposed approach when analyzing simulated and real datasets of the breast tumors according to pharmacokinetic factors, it indicates that using Bayesian inference-that infer the uncertainties of the computed solutions, and specific knowledge of the noise and errors-combined with the regularization functional of the maximum entropy problem, improved the convergence behavior and led to more consistent morphological and functional statistics and results. Finally, in comparison to the proposed exponential distribution based on MET and Newton's method, or Weibull distribution via the MET and teaching-learning-based optimization (MET/TLBO) in the previous studies, the family of Gamma and Erlang distributions estimated by the new algorithm are more appropriate and robust AIFs.

Modified Maximum Entropy Method and Estimating the AIF via DCE-MRI Data Analysis.

Background: For the kinetic models used in contrast-based medical imaging, the assignment of the arterial input function named AIF is essential for the estimation of the physiological parameters of the tissue via solving an optimization problem. Objective: In the current study, we estimate the AIF relayed on the modified maximum entropy method. The effectiveness of several numerical methods to determine kinetic parameters and the AIF is evaluated-in situations where enough information about the AIF is not available. The purpose of this study is to identify an appropriate method for estimating this function. Materials and Methods: The modified algorithm is a mixture of the maximum entropy approach with an optimization method, named the teaching-learning method. In here, we applied this algorithm in a Bayesian framework to estimate the kinetic parameters when specifying the unique form of the AIF by the maximum entropy method. We assessed the proficiency of the proposed method for assigning the kinetic parameters in the dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), when determining AIF with some other parameter-estimation methods and a standard fixed AIF method. A previously analyzed dataset consisting of contrast agent concentrations in tissue and plasma was used. Results and Conclusions: We compared the accuracy of the results for the estimated parameters obtained from the MMEM with those of the empirical method, maximum likelihood method, moment matching ("method of moments"), the least-square method, the modified maximum likelihood approach, and our previous work. Since the current algorithm does not have the problem of starting point in the parameter estimation phase, it could find the best and nearest model to the empirical model of data, and therefore, the results indicated the Weibull distribution as an appropriate and robust AIF and also illustrated the power and effectiveness of the proposed method to estimate the kinetic parameters.

Regional variation in endovascular treatment rate and in-hospital mortality of abdominal aortic aneurysms in Germany.

Background: Abdominal aortic aneurysms (AAA) can be treated by either open surgery (OAR) or endovascular aortic repair (EVAR). The aim of this study was to analyze regional variations in application of (EVAR) and in-hospital mortality after intact AAA (iAAA) repair. Methods: Using data provided by the German Federal Statistical Office, a nationwide analysis for 2012 to 2014 was conducted. Patients with a diagnosis of iAAA (I71.4) and corresponding procedure codes for OAR (5-384.5/7) or EVAR (5-38a.1) were included. Odds ratios (ORs) for use of EVAR (proportion of EVAR among total EVAR + OAR cases) and mortality were calculated for all regions in Germany. ORs for EVAR use were adjusted for age, sex, and risk (Elixhauser score). ORs for mortality were additionally adjusted for type of procedure (OAR/EVAR). Results: Finally, 31,757 procedures for iAAA were included. Median age of all patients was 73 years (interquartile range 67-78 years) and 87.1 % were male. The mean proportion of EVAR procedures was 72.6 %; however, the application of EVAR for repair of iAAA varied widely depending on region. The lowest unadjusted regional rate of EVAR use was 48.8 %, while the highest was 92.5 %. After adjustment, the lowest regional OR for EVAR use (compared to the nationwide mean) was 0.23 (95 % confidence interval [0.15-0.36]), the highest 5.93 [1.79-19.65]. Overall in-hospital mortality was 2.9 % (OAR 6.2 %; EVAR 1.7 %). The adjusted regional OR for mortality ranged from 0.31 [0.07-1.42] to 4.98 [2.08-11.93]. Conclusions: This study reveals variations in use of EVAR and in-hospital mortality for iAAA treatment in Germany. This may imply that selection of treatment might not only be influenced by patient characteristics, but also by regional location. These results need to be taken into account when discussing centralization of AAA treatment in Germany.

The impact of model assumptions in scalar-on-image regression.

Complex statistical models such as scalar-on-image regression often require strong assumptions to overcome the issue of nonidentifiability. While in theory, it is well understood that model assumptions can strongly influence the results, this seems to be underappreciated, or played down, in practice. This article gives a systematic overview of the main approaches for scalar-on-image regression with a special focus on their assumptions. We categorize the assumptions and develop measures to quantify the degree to which they are met. The impact of model assumptions and the practical usage of the proposed measures are illustrated in a simulation study and in an application to neuroimaging data. The results show that different assumptions indeed lead to quite different estimates with similar predictive ability, raising the question of their interpretability. We give recommendations for making modeling and interpretation decisions in practice based on the new measures and simulations using hypothetic coefficient images and the observed data.

Editor's Choice - High Annual Hospital Volume is Associated with Decreased in Hospital Mortality and Complication Rates Following Treatment of Abdominal Aortic Aneurysms: Secondary Data Analysis of the Nationwide German DRG Statistics from 2005 to 2013.

OBJECTIVES: The aim of this study was to analyse the association between annual hospital procedural volume and post-operative outcomes following repair of abdominal aortic aneurysms (AAA) in Germany. METHODS: Data were extracted from nationwide Diagnosis Related Group (DRG) statistics provided by the German Federal Statistical Office. Cases with a diagnosis of AAA (ICD-10 GM I71.3, I71.4) and procedure codes for endovascular aortic repair (EVAR; OPS 5-38a.1*) or open aortic repair (OAR; OPS 5-38.45, 5-38.47) treated between 2005 and 2013 were included. Hospitals were empirically grouped to quartiles depending on the overall annual volume of AAA procedures. A multilevel multivariable regression model was applied to adjust for sex, medical risk, type of procedure, and type of admission. Primary outcome was in hospital mortality. Secondary outcomes were complications, use of blood products, and length of stay (LOS). The association between AAA volume and in hospital mortality was also estimated as a function of continuous volume. RESULTS: A total of 96,426 cases, of which 11,795 (12.6%) presented as ruptured (r)AAA, were treated in >700 hospitals (annual median: 501). The crude in hospital mortality was 3.3% after intact (i)AAA repair (OAR 5.3%; EVAR 1.7%). Volume was inversely associated with mortality after OAR and EVAR. Complication rates, LOS, and use of blood products were lower in high volume hospitals. After rAAA repair, crude mortality was 40.4% (OAR 43.2%; EVAR 27.4%). An inverse association between mortality and volume was shown for rAAA repair; the same accounts for the use of blood products. When considering volume as a continuous variate, an annual caseload of 75-100 elective cases was associated with the lowest mortality risk. CONCLUSIONS: In hospital mortality and complication rates following AAA repair are inversely associated with annual hospital volume. The use of blood products and the LOS are lower in high volume hospitals. A minimum annual case threshold for AAA procedures might improve post-operative results.

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data.

OBJECTIVE: This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. METHODS: German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. RESULTS: A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. CONCLUSIONS: There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties.

Quantitative analyses of the 3D nuclear landscape recorded with super-resolved fluorescence microscopy.

Recent advancements of super-resolved fluorescence microscopy have revolutionized microscopic studies of cells, including the exceedingly complex structural organization of cell nuclei in space and time. In this paper we describe and discuss tools for (semi-) automated, quantitative 3D analyses of the spatial nuclear organization. These tools allow the quantitative assessment of highly resolved different chromatin compaction levels in individual cell nuclei, which reflect functionally different regions or sub-compartments of the 3D nuclear landscape, and measurements of absolute distances between sites of different chromatin compaction. In addition, these tools allow 3D mapping of specific DNA/RNA sequences and nuclear proteins relative to the 3D chromatin compaction maps and comparisons of multiple cell nuclei. The tools are available in the free and open source R packages nucim and bioimagetools. We discuss the use of masks for the segmentation of nuclei and the use of DNA stains, such as DAPI, as a proxy for local differences in chromatin compaction. We further discuss the limitations of 3D maps of the nuclear landscape as well as problems of the biological interpretation of such data.

Bayesian mixed-effects model for the analysis of a series of FRAP images.

The binding behavior of molecules in nuclei of living cells can be studied through the analysis of images from fluorescence recovery after photobleaching experiments. However, there is still a lack of methodology for the statistical evaluation of FRAP data, especially for the joint analysis of multiple dynamic images. We propose a hierarchical Bayesian nonlinear model with mixed-effect priors based on local compartment models in order to obtain joint parameter estimates for all nuclei as well as to account for the heterogeneity of the nuclei population. We apply our method to a series of FRAP experiments of DNA methyltransferase 1 tagged to green fluorescent protein expressed in a somatic mouse cell line and compare the results to the application of three different fixed-effects models to the same series of FRAP experiments. With the proposed model, we get estimates of the off-rates of the interactions of the molecules under study together with credible intervals, and additionally gain information about the variability between nuclei. The proposed model is superior to and more robust than the tested fixed-effects models. Therefore, it can be used for the joint analysis of data from FRAP experiments on various similar nuclei.

Stage-dependent remodeling of the nuclear envelope and lamina during rabbit early embryonic development.

Utilizing 3D structured illumination microscopy, we investigated the quality and quantity of nuclear invaginations and the distribution of nuclear pores during rabbit early embryonic development and identified the exact time point of nucleoporin 153 (NUP153) association with chromatin during mitosis. Contrary to bovine early embryonic nuclei, featuring almost exclusively nuclear invaginations containing a small volume of cytoplasm, nuclei in rabbit early embryonic stages show additionally numerous invaginations containing a large volume of cytoplasm. Small-volume invaginations frequently emanated from large-volume nuclear invaginations but not vice versa, indicating a different underlying mechanism. Large- and small-volume nuclear envelope invaginations required the presence of chromatin, as they were restricted to chromatin-positive areas. The chromatin-free contact areas between nucleolar precursor bodies (NPBs) and large-volume invaginations were free of nuclear pores. Small-volume invaginations were not in contact with NPBs. The number of invaginations and isolated intranuclear vesicles per nucleus peaked at the 4-cell stage. At this stage, the nuclear surface showed highly concentrated clusters of nuclear pores surrounded by areas free of nuclear pores. Isolated intranuclear lamina vesicles were usually NUP153 negative. Cytoplasmic, randomly distributed NUP153-positive clusters were highly abundant at the zygote stage and decreased in number until they were almost absent at the 8-cell stage and later. These large NUP153 clusters may represent a maternally provided NUP153 deposit, but they were not visible as clusters during mitosis. Major genome activation at the 8- to 16-cell stage may mark the switch from a necessity for a deposit to on-demand production. NUP153 association with chromatin is initiated during metaphase before the initiation of the regeneration of the lamina. To our knowledge, the present study demonstrates for the first time major remodeling of the nuclear envelope and its underlying lamina during rabbit preimplantation development.

Dissection of cell cycle-dependent dynamics of Dnmt1 by FRAP and diffusion-coupled modeling.

DNA methyltransferase 1 (Dnmt1) reestablishes methylation of hemimethylated CpG sites generated during DNA replication in mammalian cells. Two subdomains, the proliferating cell nuclear antigen (PCNA)-binding domain (PBD) and the targeting sequence (TS) domain, target Dnmt1 to the replication sites in S phase. We aimed to dissect the details of the cell cycle-dependent coordinated activity of both domains. To that end, we combined super-resolution 3D-structured illumination microscopy and fluorescence recovery after photobleaching (FRAP) experiments of GFP-Dnmt1 wild type and mutant constructs in somatic mouse cells. To interpret the differences in FRAP kinetics, we refined existing data analysis and modeling approaches to (i) account for the heterogeneous and variable distribution of Dnmt1-binding sites in different cell cycle stages; (ii) allow diffusion-coupled dynamics; (iii) accommodate multiple binding classes. We find that transient PBD-dependent interaction directly at replication sites is the predominant specific interaction in early S phase (residence time Tres ≤ 10 s). In late S phase, this binding class is taken over by a substantially stronger (Tres ∼22 s) TS domain-dependent interaction at PCNA-enriched replication sites and at nearby pericentromeric heterochromatin subregions. We propose a two-loading-platform-model of additional PCNA-independent loading at postreplicative, heterochromatic Dnmt1 target sites to ensure faithful maintenance of densely methylated genomic regions.

Spatially regularized estimation for the analysis of dynamic contrast-enhanced magnetic resonance imaging data.

Competing compartment models of different complexities have been used for the quantitative analysis of dynamic contrast-enhanced magnetic resonance imaging data. We present a spatial elastic net approach that allows to estimate the number of compartments for each voxel such that the model complexity is not fixed a priori. A multi-compartment approach is considered, which is translated into a restricted least square model selection problem. This is done by using a set of basis functions for a given set of candidate rate constants. The form of the basis functions is derived from a kinetic model and thus describes the contribution of a specific compartment. Using a spatial elastic net estimator, we chose a sparse set of basis functions per voxel, and hence, rate constants of compartments. The spatial penalty takes into account the voxel structure of an image and performs better than a penalty treating voxels independently. The proposed estimation method is evaluated for simulated images and applied to an in vivo dataset.

Sensitivity to prior specification in Bayesian genome-based prediction models.

Different statistical models have been proposed for maximizing prediction accuracy in genome-based prediction of breeding values in plant and animal breeding. However, little is known about the sensitivity of these models with respect to prior and hyperparameter specification, because comparisons of prediction performance are mainly based on a single set of hyperparameters. In this study, we focused on Bayesian prediction methods using a standard linear regression model with marker covariates coding additive effects at a large number of marker loci. By comparing different hyperparameter settings, we investigated the sensitivity of four methods frequently used in genome-based prediction (Bayesian Ridge, Bayesian Lasso, BayesA and BayesB) to specification of the prior distribution of marker effects. We used datasets simulated according to a typical maize breeding program differing in the number of markers and the number of simulated quantitative trait loci affecting the trait. Furthermore, we used an experimental maize dataset, comprising 698 doubled haploid lines, each genotyped with 56110 single nucleotide polymorphism markers and phenotyped as testcrosses for the two quantitative traits grain dry matter yield and grain dry matter content. The predictive ability of the different models was assessed by five-fold cross-validation. The extent of Bayesian learning was quantified by calculation of the Hellinger distance between the prior and posterior densities of marker effects. Our results indicate that similar predictive abilities can be achieved with all methods, but with BayesA and BayesB hyperparameter settings had a stronger effect on prediction performance than with the other two methods. Prediction performance of BayesA and BayesB suffered substantially from a non-optimal choice of hyperparameters.

The potential of 3D-FISH and super-resolution structured illumination microscopy for studies of 3D nuclear architecture: 3D structured illumination microscopy of defined chromosomal structures visualized by 3D (immuno)-FISH opens new perspectives for studies of nuclear architecture.

Three-dimensional structured illumination microscopy (3D-SIM) has opened up new possibilities to study nuclear architecture at the ultrastructural level down to the ~100 nm range. We present first results and assess the potential using 3D-SIM in combination with 3D fluorescence in situ hybridization (3D-FISH) for the topographical analysis of defined nuclear targets. Our study also deals with the concern that artifacts produced by FISH may counteract the gain in resolution. We address the topography of DAPI-stained DNA in nuclei before and after 3D-FISH, nuclear pores and the lamina, chromosome territories, chromatin domains, and individual gene loci. We also look at the replication patterns of chromocenters and the topographical relationship of Xist-RNA within the inactive X-territory. These examples demonstrate that an appropriately adapted 3D-FISH/3D-SIM approach preserves key characteristics of the nuclear ultrastructure and that the gain in information obtained by 3D-SIM yields new insights into the functional nuclear organization.

Natural history and morphology of the hoverfly Pseudomicrodon biluminiferus and its parasitic relationship with ants nesting in bromeliads.

The syrphid subfamily Microdontinae is characterized by myrmecophily of their immature stages, i.e., they develop in ant nests. Data on natural history of microdontines are scarce, especially in the Neotropics. Based on fieldwork in southern Brazil, this study provided new data on development and ecology of the hoverfly Pseudomicrodon biluminiferus (Hull) (Diptera: Syrphidae) as well as the first morphological descriptions of male genitalia, larvae, and pupa. Immature specimens were specifically found in colonies of the ant species Crematogaster limata Smith (Hymenoptera: Formicidae) found in rosettes of the bromeliad species Aechmea lindenii (E. Morren) Baker (Poales: Bromeliaceae) and A. nudicaulis (L.) Grisebach. Third instar larvae were observed preying on ant larvae, revealing the parasitic nature of P. biluminiferus. In this and several other aspects, the natural history of P. biluminiferus is similar to that of Holarctic microdontine species. Exceptions include: (i) indications that adults of P. biluminiferus outlast the winter months (in contrast to 3(rd)instar larvae in Holarctic species) and (ii) P. biluminiferus' relationship with bromeliads. The importance of bromeliads for this host-parasite system is evaluated in this paper. The single occurrence of another, unidentified microdontine species' pupae in a nest of the ant species Camponotus melanoticus Emery (Hymenoptera: Formicidae) is reported.

Automatic post-picking using MAPPOS improves particle image detection from cryo-EM micrographs.

Cryo-electron microscopy (cryo-EM) studies using single particle reconstruction are extensively used to reveal structural information on macromolecular complexes. Aiming at the highest achievable resolution, state of the art electron microscopes automatically acquire thousands of high-quality micrographs. Particles are detected on and boxed out from each micrograph using fully- or semi-automated approaches. However, the obtained particles still require laborious manual post-picking classification, which is one major bottleneck for single particle analysis of large datasets. We introduce MAPPOS, a supervised post-picking strategy for the classification of boxed particle images, as additional strategy adding to the already efficient automated particle picking routines. MAPPOS employs machine learning techniques to train a robust classifier from a small number of characteristic image features. In order to accurately quantify the performance of MAPPOS we used simulated particle and non-particle images. In addition, we verified our method by applying it to an experimental cryo-EM dataset and comparing the results to the manual classification of the same dataset. Comparisons between MAPPOS and manual post-picking classification by several human experts demonstrated that merely a few hundred sample images are sufficient for MAPPOS to classify an entire dataset with a human-like performance. MAPPOS was shown to greatly accelerate the throughput of large datasets by reducing the manual workload by orders of magnitude while maintaining a reliable identification of non-particle images.

Flexibly deployed Pax genes in eye development at the early evolution of animals demonstrated by studies on a hydrozoan jellyfish.

Pax transcription factors are involved in a variety of developmental processes in bilaterians, including eye development, a role typically assigned to Pax-6. Although no true Pax-6 gene has been found in nonbilateral animals, some jellyfish have eyes with complex structures. In the cubozoan jellyfish Tripedalia, Pax-B, an ortholog of vertebrate Pax-2/5/8, had been proposed as a regulator of eye development. Here we have isolated three Pax genes (Pax-A, Pax-B, and Pax-E) from Cladonema radiatum, a hydrozoan jellyfish with elaborate eyes. Cladonema Pax-A is strongly expressed in the retina, whereas Pax-B and Pax-E are highly expressed in the manubrium, the feeding and reproductive organ. Misexpression of Cladonema Pax-A induces ectopic eyes in Drosophila imaginal discs, whereas Pax-B and Pax-E do not. Furthermore, Cladonema Pax-A paired domain protein directly binds to the 5' upstream region of eye-specific Cladonema opsin genes, whereas Pax-B does not. Our data suggest that Pax-A, but not Pax-B or Pax-E, is involved in eye development and/or maintenance in Cladonema. Phylogenetic analysis indicates that Pax-6, Pax-B, and Pax-A belong to different Pax subfamilies, which diverged at the latest before the Cnidaria-Bilateria separation. We argue that our data, showing the involvement of Pax genes in hydrozoan eye development as in bilaterians, supports the monophyletic evolutionary origin of all animal eyes. We then propose that during the early evolution of animals, distinct classes of Pax genes, which may have played redundant roles at that time, were flexibly deployed for eye development in different animal lineages.

Assessment of Chemical Facility Ethylene Oxide Emissions Using Mobile and Multipoint Monitoring.

Ethylene oxide (EtO) is a hazardous air pollutant that can be emitted from a variety of difficult to measure industrial sources, such as fugitive leaks, wastewater handling, and episodic releases. Emerging next generation emission measurement (NGEM) approaches capable of time-resolved, low parts per billion by volume (ppbv) method detection limits (MDLs) can help facilities understand and reduce EtO and other air pollutant emissions from these sources yielding a range of environmental and public health benefits. In October 2021, a first of its kind 4-day observational study was conducted at an EtO chemical facility in the midwestern United States. The study had dual objectives to both improve understanding of EtO emission sources within the facility and advance NGEM methods. Using cavity ring-down spectroscopy (CRDS) instruments, a combination of mobile surveys and stationary multipoint process unit monitoring assessed EtO concentrations in and near facility operations, while testing and comparing measurement methods. The study concluded that four main areas of EtO source emissions existed within the facility, each possessing unique emission characteristics. Episodic EtO emissions from supply railcar switchovers and batch reactor washouts, lasting seconds to minutes in duration, produced EtO concentrations exceeding 500 ppbv inside the process unit in some cases. In one instance, EtO at ~30 ppbv was briefly observed hundreds of meters from the process unit. Lower level but more sustained EtO concentrations were observed near an EtO transfer pump and wastewater tank outfall and drain system. Overall, 4.6% of mobile survey data were above the 1.2 ppbv mobile test MDL while the nine stationary sampling locations ranged from 17.7% to 82.8% of data above the 1.0 ppbv multipoint test MDL. This paper describes the EtO emissions observed in and near the four defined source areas within the facility and provides details of the NGEM method development advances accomplished as part of the study.

An automated tool for detection of FLAIR-hyperintense white-matter lesions in Multiple Sclerosis.

In Multiple Sclerosis (MS), detection of T2-hyperintense white matter (WM) lesions on magnetic resonance imaging (MRI) has become a crucial criterion for diagnosis and predicting prognosis in early disease. Automated lesion detection is not only desirable with regard to time and cost effectiveness but also constitutes a prerequisite to minimize user bias. Here, we developed and evaluated an algorithm for automated lesion detection requiring a three-dimensional (3D) gradient echo (GRE) T1-weighted and a FLAIR image at 3 Tesla (T). Our tool determines the three tissue classes of gray matter (GM) and WM as well as cerebrospinal fluid (CSF) from the T1-weighted image, and, then, the FLAIR intensity distribution of each tissue class in order to detect outliers, which are interpreted as lesion beliefs. Next, a conservative lesion belief is expanded toward a liberal lesion belief. To this end, neighboring voxels are analyzed and assigned to lesions under certain conditions. This is done iteratively until no further voxels are assigned to lesions. Herein, the likelihood of belonging to WM or GM is weighed against the likelihood of belonging to lesions. We evaluated our algorithm in 53 MS patients with different lesion volumes, in 10 patients with posterior fossa lesions, and 18 control subjects that were all scanned at the same 3T scanner (Achieva, Philips, Netherlands). We found good agreement with lesions determined by manual tracing (R2 values of over 0.93 independent of FLAIR slice thickness up to 6mm). These results require validation with data from other protocols based on a conventional FLAIR sequence and a 3D GRE T1-weighted sequence. Yet, we believe that our tool allows fast and reliable segmentation of FLAIR-hyperintense lesions, which might simplify the quantification of lesions in basic research and even clinical trials.