Dark Matter in the Dwarf Galaxy NGC 247

Dwarf galaxies are dominated by dark matter even in the innermost regions and, therefore, provide excellent probes for the investigation of dark halos. To that purpose, we analyse ROSAT PSPC-data of the dwarf galaxy NGC 247. We focus in particular on the diffuse X-ray emission in the $1/4$keV band. Assuming an isothermal density profile, we find that the mass of the hot emitting gas is about $10^8 {\rm M_{\odot}}$, corresponding to $\lesssim 0.5$ of the total dynamical mass of the galaxy. The total mass of NGC 247, as derived from the X-ray data agrees quite well with the value obtained from the measured rotation curve (Burlak). The X-ray profile in the $3/4$keV and $1.5$keV band shows an excess at a radial distance of about $15$ arcmin from the center. Such a ``hump'' in the radial X-ray profile can be explained by the presence of a cluster of young low mass stars or brown dwarfs. Therefore, NGC 247 offers the possibility to observe the formation of a halo of MACHOs.Comment: 6 pages, accepted for publication in A &

An Efficient Workflow for Modelling High-Dimensional Spatial Extremes

A successful model for high-dimensional spatial extremes should, in principle, be able to describe both weakening extremal dependence at increasing levels and changes in the type of extremal dependence class as a function of the distance between locations. Furthermore, the model should allow for computationally tractable inference using inference methods that efficiently extract information from data and that are robust to model misspecification. In this paper, we demonstrate how to fulfil all these requirements by developing a comprehensive methodological workflow for efficient Bayesian modelling of high-dimensional spatial extremes using the spatial conditional extremes model while performing fast inference with R-INLA. We then propose a post hoc adjustment method that results in more robust inference by properly accounting for possible model misspecification. The developed methodology is applied for modelling extreme hourly precipitation from high-resolution radar data in Norway. Inference is computationally efficient, and the resulting model fit successfully captures the main trends in the extremal dependence structure of the data. Robustifying the model fit by adjusting for possible misspecification further improves model performance

Fast spatial simulation of extreme high-resolution radar precipitation data using INLA

We develop a methodology for modelling and simulating high-dimensional spatial precipitation extremes, using a combination of the spatial conditional extremes model, latent Gaussian models and integrated nested Laplace approximations (INLA). The spatial conditional extremes model requires data with Laplace marginal distributions, but precipitation distributions contain point masses at zero that complicate necessary standardisation procedures. We propose to model conditional extremes of nonzero precipitation only, while separately modelling precipitation occurrences. The two models are then combined to create a complete model for extreme precipitation. Nonzero precipitation marginals are modelled using a combination of latent Gaussian models with gamma and generalised Pareto likelihoods. Four different models for precipitation occurrence are investigated. New empirical diagnostics and parametric models are developed for describing components of the spatial conditional extremes model. We apply our framework to simulate spatial precipitation extremes over a water catchment in Central Norway, using high-density radar data. Inference on a 6000-dimensional data set is performed within hours, and the simulated data capture the main trends of the observed data well

Incidence of Arrhythmias and Myocardial Ischaemia During Haemodialysis and Haemofiltration

Thirty-two patients (10 male, 22 female; age 37-82 years) undergoing maintenance haemodialysis or haemofiltration were studied by means of Holter device capable of simultaneously analysing rhythm and ST changes in three leads. Twenty-five patients were on haemodialysis, seven on haemofiltration, mean duration of haemodialysis/haemofiltration being 3.4±3 years. Incidence of ventricular tachycardia was low, being detected only in 1 of 32 patients. Ventricular premature beats in excess of 10/h during a period of 2 h were found in 8 of 32 patients and 100 supraventricular premature beats for 2 h or more in 4 of 32 patients. Both ventricular premature beats and supraventricular premature beats were most frequently recorded during the last hour of haemodialysis/haemofiltration. ECG signs of ischaemia were detected in eight patients, four of whom were asymptomatic. Ischaemia also occurred predominantly during the last hour of haemodialysis/haemofiltration. Two symptomatic patients displayed neither arrhythmias nor ST-changes while being monitored. The study shows that silent ischaemia and arrhythmias in patients under going chronic haemodialysis/haemofiltration may not be infrequent. Recognition of these events could be of importance in the management of these patient

Управління трудовим потенціалом при створенні інноваційної продукції

Super-resolution microscopy (SRM) bypasses the diffraction limit, a physical barrier that restricts the optical resolution to roughly 250 nm and was previously thought to be impenetrable. SRM techniques allow the visualization of subcellular organization with unprecedented detail, but also confront biologists with the challenge of selecting the best-suited approach for their particular research question. Here, we provide guidance on how to use SRM techniques advantageously for investigating cellular structures and dynamics to promote new discoveries

Bayesian Networks for Max-linear Models

We study Bayesian networks based on max-linear structural equations as introduced in Gissibl and Kl\"uppelberg [16] and provide a summary of their independence properties. In particular we emphasize that distributions for such networks are generally not faithful to the independence model determined by their associated directed acyclic graph. In addition, we consider some of the basic issues of estimation and discuss generalized maximum likelihood estimation of the coefficients, using the concept of a generalized likelihood ratio for non-dominated families as introduced by Kiefer and Wolfowitz [21]. Finally we argue that the structure of a minimal network asymptotically can be identified completely from observational data.Comment: 18 page

TSC22 in mammary gland development and breast cancer

Mammary gland involution is characterised by a high degree of apoptosis. By identifying genes that are upregulated at this developmental stage, we aimed to discover key factors that are involved in the induction of mammary epithelial cell death and therefore present potential tumour suppressors for breast cancer. Among 96 genes recently identified as specifically upregulated early during involution were the transforming growth factor beta (TGFβ)-stimulated clone 22 homologue (TSC-22/TGFβ1-induced transcript 4) and TGFβ3 [1]. TGFβ3 has recently been shown to be necessary for induction of apoptosis during mammary gland involution, while TSC-22 overexpression can lead to cell death. We have therefore tested whether TSC-22 mRNA expression can be induced by TGFβ3 and whether it is involved in or necessary for TGFβ-induced apoptosis. We further show that TSC-22 can enhance TGFβ3-induced Smad response and epithelial cell death. In addition, overexpression of TSC-22 alone can induce a Smad response and apoptosis in mammary epithelial cell cultures, which is independent of p53. Further, we have performed tests to study the necessity for Smad proteins during TSC-22-induced apoptosis, and to establish the intracellular localisation of TSC-22. A pilot study on a small cohort of archival breast cancer cases, representing all stages of malignant progression, shows that TSC-22 protein was reduced or undetectable in 60% of breast carcinomas when compared with adjacent normal breast tissue, suggesting that TSC-22 could indeed be a potential novel tumour suppressor gene. We shall present data showing that methylation of the TSC-22 promoter is not involved in the reduction of TSC-22 protein in breast cancer

Ecological resilience in lakes and the conjunction fallacy

There is a pressing need to apply stability and resilience theory to environmental management to restore degraded ecosystems effectively and to mitigate the effects of impending environmental change. Lakes represent excellent model case studies in this respect and have been used widely to demonstrate theories of ecological stability and resilience that are needed to underpin preventative management approaches. However, we argue that this approach is not yet fully developed because the pursuit of empirical evidence to underpin such theoretically grounded management continues in the absence of an objective probability framework. This has blurred the lines between intuitive logic (based on the elementary principles of probability) and extensional logic (based on assumption and belief) in this field