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.

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.

[Relationship between regional settlement structure and hospital incidence, type of therapy and mortality of non-ruptured abdominal aortic aneurysms]. / Zusammenhang zwischen der regionalen Siedlungsstruktur und der Krankenhausinzidenz, Therapieform und Mortalität von nicht-rupturierten abdominalen Aortenaneurysmen. Sekundärdatenanalyse der deutschen DRG-Statistik von 2005­2014.

INTRODUCTION: In Germany, the regional settlement structure is heterogenous, ranging from densely populated cities with a tight network of vascular health care to large regions in which access to health care is limited in terms of space and time. Therefore, the aim of this secondary data analysis was to investigate the association between the settlement structure of the patient's home district (KT), and the hospital incidence, type of therapy, and mortality of non-ruptured abdominal aortic aneurysms (nrAAA). METHODS: The microdata of the DRG statistics of the Federal Statistical Office for the years 2005-2014 were evaluated. All patients with nrAAA (ICD-10 Code I71.4) who were admitted to a German hospital and treated by open surgery and endovascular repair were included. Classification of treatment was based on the German Operation and Procedure Code. Patients were grouped according to the settlement structure of their home district defined by the Federal Institute for Research on Building, Urban Affairs and Spatial Development (KT1 independent city, KT2 urban district, KT3 rural district, KT4 sparsely populated region). The age-, sex- and risk-adjusted association between the type of settlement structure and in-hospital mortality was analysed using a multivariable multi-level regression model. The Elixhauser co-morbidity score validated for administrative data was used for risk adjustment. RESULTS: Of 95,452 cases included, 88 % were men. Mean age was 72 years. There were 28,970 (30 %) patients in KT1, 37,759 (40 %) in KT2, 14,442 (15 %) in KT3 and 14,281 (15 %) in KT4. The hospital incidence was 12.4 per 100,000 inhabitants in KT1, 11.8 in KT2, 10.8 in KT3 and 11.2 in KT4 (p <0.001, falling trend). The proportion of EVAR treatment was 56 % in KT1, 54 % in KT2, 57 % KT3, and 59 % in KT4 (p <0.001, increasing trend). The raw hospital mortality of patients from KT1 to KT4 was 3.4 %, 3.4 %, 3.2 % and 3.6 %, respectively (p=0.553 for trend). The multivariable regression analysis revealed no statistically significant association between the KT and hospital mortality (KT1=reference, RR KT2=0.97 [95% CI 0.79-1.15], RR KT3=0.98 [0.81-1.14], RR KT4=0.98 [0.86-1.11]). CONCLUSIONS: The study shows that both the hospital incidence and the type of therapy (endovascular vs. open) differed between the settlement structural district types, but there is no urban-rural gap regarding in-hospital mortality of treated nrAAA.

Geographic risk of general and abdominal obesity and related determinants in Iranian children and adolescents: CASPIAN-IV Study.

BACKGROUND: Obesity, as a risk factor for many noncommunicable diseases, is a common public health problem in developed and developing countries. Among Iranian children and adolescents, the prevalence of being overweight has increased by almost 50% in the past two decades. AIMS: To visualize the geographic differences in general and abdominal obesity risks and related determinants among Iranian children and adolescents. METHODS: Participants consisted of 14 880 students, aged 7-19 years, living in urban and rural areas of the Islamic Republic of Iran. Spatial patterns of obesity and its association with related risk factors were identified using Bayesian spatial modeling. RESULTS: The highest spatial risks of general obesity (odds ratio 1.21-1.66 for males and 1.81-2.02 for females) and abdominal obesity (odds ratio 1.20-1.82 for males and 1.25-1.78 for females) were observed in the north, northwest and southwest of the country. Risk of obesity was significantly higher in areas with a higher rate of urban residence, active current smokers and prolonged screen time. CONCLUSION: Identification of high-risk regions for obesity and spatially related risk factors can be used as informative tools for decision-making and planning in health systems at national and subnational levels.

Cohesin depleted cells rebuild functional nuclear compartments after endomitosis.

Cohesin plays an essential role in chromatin loop extrusion, but its impact on a compartmentalized nuclear architecture, linked to nuclear functions, is less well understood. Using live-cell and super-resolved 3D microscopy, here we find that cohesin depletion in a human colon cancer derived cell line results in endomitosis and a single multilobulated nucleus with chromosome territories pervaded by interchromatin channels. Chromosome territories contain chromatin domain clusters with a zonal organization of repressed chromatin domains in the interior and transcriptionally competent domains located at the periphery. These clusters form microscopically defined, active and inactive compartments, which likely correspond to A/B compartments, which are detected with ensemble Hi-C. Splicing speckles are observed nearby within the lining channel system. We further observe that the multilobulated nuclei, despite continuous absence of cohesin, pass through S-phase with typical spatio-temporal patterns of replication domains. Evidence for structural changes of these domains compared to controls suggests that cohesin is required for their full integrity.

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.

Co-localization analysis in fluorescence microscopy via maximum entropy copula.

Co-localization analysis is a popular method for quantitative analysis in fluorescence microscopy imaging. The localization of marked proteins in the cell nucleus allows a deep insight into biological processes in the nucleus. Several metrics have been developed for measuring the co-localization of two markers, however, they depend on subjective thresholding of background and the assumption of linearity. We propose a robust method to estimate the bivariate distribution function of two color channels. From this, we can quantify their co- or anti-colocalization. The proposed method is a combination of the Maximum Entropy Method (MEM) and a Gaussian Copula, which we call the Maximum Entropy Copula (MEC). This new method can measure the spatial and nonlinear correlation of signals to determine the marker colocalization in fluorescence microscopy images. The proposed method is compared with MEM for bivariate probability distributions. The new colocalization metric is validated on simulated and real data. The results show that MEC can determine co- and anti-colocalization even in high background settings. MEC can, therefore, be used as a robust tool for colocalization analysis.

The Effects of Minimum Caseload Requirements on Management and Outcome in Abdominal Aortic Aneurysm Repair.

BACKGROUND: The German quality assurance guideline on abdominal aortic aneurysm (AAA) was implemented by the Joint Federal Committee (Gemeinsamer Bundesausschuss, G-BA) in 2008. The aims of this study were to verify the association between hospital case volume and outcome and to assess the hypothetical effect of minimum caseload requirements. METHODS: The German diagnosis-related groups statistics for the years 2012 to 2016 were scrutinized for AAA (ICD-10 GM I71.3/4) with procedure codes for endo - vascular or open surgical treatment. The primary endpoint was in-hospital mortality. Logistic regression models were used for risk adjustment, and odds ratios (OR) were calculated as a function of the annual hospital-level case volume of AAA. In a hypo - thetical approach, the linear distances for various minimum caseloads (MC) were evaluated to assess accessibility. RESULTS: The mortality of intact AAA (iAAA) was 2.7% (men [M] 2.4%, women [W] 4.2%); ruptured AAA (rAAA), 36.9% (M 36.9%, F 37.5%). An inverse relationship between annual hospital case volume of AAA and mortality was confirmed (iAAA/rAAA: from 3.9%/51% [<10 cases/year] through 3.3%/37% [30-39 cases/year] to 1.9%/28% [≥ 75 cases/year]). For a reference category of 30 AAA procedures/year, the following significant OR were found: 10 AAA cases/year, OR 1.21 (95% confidence interval [1.20; 1.21]); 20 cases, OR 1.09 [1.09; 1.09]; 50 cases, OR 0.89 [0.89; 0.89]; 75 cases, OR 0.82 [0.82; 0.82]. In a hypothetical centralization scenario with assumed MC of 30/year, 86% of the population would have to travel less than 100 km to the nearest hospital; with an MC of 40, this would apply to only 50% (without redistribution effects). CONCLUSION: In the observed period, a significant correlation was confirmed between high annual case volume and low in-hospital mortality. A minimum caseload requirement of 30 AAA operations/year seems reasonable in view of the accessibility of hospitals. Cite this.

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.

Spatio-temporal pattern of two common cancers among Iranian women: An adaptive smoothing model.

PURPOSE: Considering the increase in incidence of breast and cervix uteri cancers in Iran, this study investigates spatio-temporal patterns of the incidence of these two cancers by estimating the step changes between pairs of adjacent regions and between the Iranian women from 2004 to 2009. METHODS: Using an adaptive smoothing model, spatio-temporal mapping of the breast and cervix uteri cancers and their changes were studied. Identification of step changes between the neighboring spatial units was carried out by modeling adjacency matrix elements as random variables. RESULTS: There was a high relative risk of breast cancer around the central northern half of Iran, and a high relative risk of cervix uteri cancer was seen in the northeastern part of Iran. Northwest and southeast of Iran had a relatively low risk of breast and cervix uteri cancer. In general, step changes were largely similar between the two diseases with an agreement coefficient of 56%. This was observed in the Chaharmahal & Bakhtiari, and Kohgiluye & Boyerahmad provinces on the central band of Iran, as well as some eastern and northern regions on the map that were distinct from their adjacent provinces from the aspect of relative risk of both cancers. CONCLUSION: Identifying areas with high/low incidence risk can help health authorities to make better decisions to prevent and control breast and cervix uteri cancers and allocate resources more efficiently. In addition, determining and identifying the step changes in unexplained components of the disease risk can lead to a deeper understanding of the spatial structure of unmeasured confounding factors.

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.

Joint Spatio-Temporal Shared Component Model with an Application in Iran Cancer Data

Background: Among the proposals for joint disease mapping, the shared component model has become more popular. Another advance to strengthen inference of disease data is the extension of purely spatial models to include time aspect. We aim to combine the idea of multivariate shared components with spatio-temporal modelling in a joint disease mapping model and apply it for incidence rates of seven prevalent cancers in Iran which together account for approximately 50% of all cancers. Methods: In the proposed model, each component is shared by different subsets of diseases, spatial and temporal trends are considered for each component, and the relative weight of these trends for each component for each relevant disease can be estimated. Results: For esophagus and stomach cancers the Northern provinces was the area of high risk. For colorectal cancer Gilan, Semnan, Fars, Isfahan, Yazd and East-Azerbaijan were the highest risk provinces. For bladder and lung cancer, the northwest were the highest risk area. For prostate and breast cancers, Isfahan, Yazd, Fars, Tehran, Semnan, Mazandaran and Khorasane-Razavi were the highest risk part. The smoking component, shared by esophagus, stomach, bladder and lung, had more effect in Gilan, Mazandaran, Chaharmahal and Bakhtiari, Kohgilouyeh and Boyerahmad, Ardebil and Tehran provinces, in turn. For overweight and obesity component, shared by esophagus, colorectal, prostate and breast cancers the largest effect was found for Tehran, Khorasane-Razavi, Semnan, Yazd, Isfahan, Fars, Mazandaran and Gilan, in turn. For low physical activity component, shared by colorectal and breast cancers North-Khorasan, Ardebil, Golestan, Ilam, Khorasane-Razavi and South-Khorasan had the largest effects, in turn. The smoking component is significantly more important for stomach than for esophagus, bladder and lung. The overweight and obesity had significantly more effect for colorectal than of esophagus cancer. Conclusions: The presented model is a valuable model to model geographical and temporal variation among diseases and has some interesting potential features and benefits over other joint models.

Bivariate spatiotemporal disease mapping of cancer of the breast and cervix uteri among Iranian women.

Cervical cancer in women is one of the most common cancers and breast cancer has grown dramatically in recent years. The purpose of this study was to map the incidence of breast and cervix uteri cancer among Iranian women over a 6-year period (2004-2009) searching for trend changes and risk factors. Cancer incidence data were extracted from the annual reports of the National Cancer Registry in Iran. Hierarchical Bayesian models, including random spatial and temporal effects was utilized together with bivariate, spatio-temporal shared component modelling. The provinces Tehran, Isfahan, Mazandaran and Gilan were found to have the highest relative risk (RR) of breast cancer, while the highest RR of cervix uteri cancer was observed in Tehran, Golestan, Khuzestan and Khorasan Razavi. Shared risk factors (smoking component) between the two cancers were seen to have the highest influence in Tehran, Khorasan Razavi, Yazd, Isfahan, Golestan, Khuzestan, Fars and Mazandaran, while the least were observed in Kohgiluyeh Boyerahmad. Apparent differences and distinctions between high-risk and low-risk provinces reveal a pattern of obvious dispersion for these cancers in Iran that should be considered when allocating healthcare resources and services in different areas.

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.

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.

Initial high-resolution microscopic mapping of active and inactive regulatory sequences proves non-random 3D arrangements in chromatin domain clusters.

BACKGROUND: The association of active transcription regulatory elements (TREs) with DNAse I hypersensitivity (DHS[+]) and an 'open' local chromatin configuration has long been known. However, the 3D topography of TREs within the nuclear landscape of individual cells in relation to their active or inactive status has remained elusive. Here, we explored the 3D nuclear topography of active and inactive TREs in the context of a recently proposed model for a functionally defined nuclear architecture, where an active and an inactive nuclear compartment (ANC-INC) form two spatially co-aligned and functionally interacting networks. RESULTS: Using 3D structured illumination microscopy, we performed 3D FISH with differently labeled DNA probe sets targeting either sites with DHS[+], apparently active TREs, or DHS[-] sites harboring inactive TREs. Using an in-house image analysis tool, DNA targets were quantitatively mapped on chromatin compaction shaped 3D nuclear landscapes. Our analyses present evidence for a radial 3D organization of chromatin domain clusters (CDCs) with layers of increasing chromatin compaction from the periphery to the CDC core. Segments harboring active TREs are significantly enriched at the decondensed periphery of CDCs with loops penetrating into interchromatin compartment channels, constituting the ANC. In contrast, segments lacking active TREs (DHS[-]) are enriched toward the compacted interior of CDCs (INC). CONCLUSIONS: Our results add further evidence in support of the ANC-INC network model. The different 3D topographies of DHS[+] and DHS[-] sites suggest positional changes of TREs between the ANC and INC depending on their functional state, which might provide additional protection against an inappropriate activation. Our finding of a structural organization of CDCs based on radially arranged layers of different chromatin compaction levels indicates a complex higher-order chromatin organization beyond a dichotomic classification of chromatin into an 'open,' active and 'closed,' inactive state.

Incidence, Treatment and Mortality in Patients with Abdominal Aortic Aneurysms.

BACKGROUND: Aim of this study was to analyze hospital incidence, type of treatment, and hospital mortality rates of patients with abdominal aortic aneurysm (AAA) in Germany from 2005 to 2014. METHODS: Microdata of the diagnosis-related group (DRG) statistics compiled by the German Federal Statistical Office for the years 2005-2014 were analyzed. Patients who were hospitalized for a ruptured AAA (rAAA, ICD-10 code I71.3, treated either surgically or conservatively) or received surgical treatment for an unruptured AAA (nrAAA, ICD-10-Code I71.4, treated either with open surgery or an endovascular procedure) were included in the analysis. The "European Standard Population 2013" was used for direct standardization of the hospital incidences. In-hospital mortality was calculated with standardization for age and risk. RESULTS: The standardized overall hospital incidence of AAA was 27.9 and 3.3 cases per 100 000 people for men and women, respectively; over the period of the study, the incidence of rAAA fell by 30% in both sexes and that of nrAAA rose by 16% in men and 42% in women. The percentage of patients receiving endovascular treatment rose from 29% to 75% in patients with nrAAA and from 8% to 36% in patients with rAAA. The age- and risk-standardized in-hospital mortality of nrAAA was 3.3% in men and 5.3% in women. The in-hospital mortality of surgically treated rAAA was 39% in men and 48% in women. CONCLUSION: The hospital incidence of AAA rose from 2005 to 2014, while that of rAAA fell. Endovascular treatment became more common for nrAAA as well as rAAA, and in-hospital mortality fell for both.

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.

Maximum Entropy Approach in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

BACKGROUND: In the estimation of physiological kinetic parameters from Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) data, the determination of the arterial input function (AIF) plays a key role. OBJECTIVES: This paper proposes a Bayesian method to estimate the physiological parameters of DCE-MRI along with the AIF in situations, where no measurement of the AIF is available. METHODS: In the proposed algorithm, the maximum entropy method (MEM) is combined with the maximum a posterior approach (MAP). To this end, MEM is used to specify a prior probability distribution of the unknown AIF. The ability of this method to estimate the AIF is validated using the Kullback-Leibler divergence. Subsequently, the kinetic parameters can be estimated with MAP. The proposed algorithm is evaluated with a data set from a breast cancer MRI study. RESULTS: The application shows that the AIF can reliably be determined from the DCE-MRI data using MEM. Kinetic parameters can be estimated subsequently. CONCLUSIONS: The maximum entropy method is a powerful tool to reconstructing images from many types of data. This method is useful for generating the probability distribution based on given information. The proposed method gives an alternative way to assess the input function from the existing data. The proposed method allows a good fit of the data and therefore a better estimation of the kinetic parameters. In the end, this allows for a more reliable use of DCE-MRI.