Risk Theory with Affine Dividend Payment Strategies

We consider a classical compound Poisson risk model with affine dividend payments. We illustrate how both by analytical and probabilistic techniques closed-form expressions for the expected discounted dividends until ruin and the Laplace transform of the time to ruin can be derived for exponentially distributed claim amounts. Moreover, numerical examples are given which compare the performance of the proposed strategy to classical barrier strategies and illustrate that such affine strategies can be a noteworthy compromise between profitability and safety in collective risk theory

LXRα improves myocardial glucose tolerance and reduces cardiac hypertrophy in a mouse model of obesity-induced type 2 diabetes

Aims/hypothesis Diabetic cardiomyopathy is a myocardial disease triggered by impaired insulin signalling, increased fatty acid uptake and diminished glucose utilisation. Liver X receptors (LXRs) are key transcriptional regulators of metabolic homeostasis. However, their effect in the diabetic heart is largely unknown. Methods We cloned murine Lxr alpha (also known as Nr1h3) behind the a-myosin heavy chain (alpha Mhc; also known as Myh6) promoter to create transgenic (Lxr alpha-Tg) mice and transgene-negative littermates (wild-type [WT]). A mouse model of type 2 diabetes was induced by a high-fat diet (HFD, 60% energy from fat) over 16 weeks and compared with a low-fat diet (10% energy from fat). A mouse model of type 1 diabetes was induced via streptozotocin injection over 12 weeks. Results HFD manifested comparable increases in body weight, plasma triacylglycerol and insulin resistance per OGTT in Lxr alpha-Tg and WT mice. HFD significantly increased left ventricular weight by 21% in WT hearts, but only by 5% in Lxr alpha-Tg. To elucidate metabolic effects in the heart, microPET (positron emission tomography) imaging revealed that cardiac glucose uptake was increased by 1.4-fold in WT mice on an HFD, but further augmented by 1.7-fold in Lxr alpha-Tg hearts, in part through 5' adenosine monophosphate-activated protein kinase (AMPK) phosphorylation and restoration of glucose transporter 4 (GLUT4). By contrast, streptozotocin-induced ablation of insulin signalling diminished cardiac glucose uptake levels and caused cardiac dysfunction, indicating that insulin may be important in Lxr alpha-mediated glucose uptake. Chromatin immunoprecipitation assays identified natriuretic peptides, atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP), as potential direct targets of cardiac Lxr alpha overexpression. Conclusions/interpretation Cardiac-specific Lxr alpha overexpression ameliorates the progression of HFD-induced left ventricular hypertrophy in association with increased glucose reliance and natriuretic peptide signalling during the early phase of diabetic cardiomyopathy. These findings implicate a potential protective role for LXR in targeting metabolic disturbances underlying diabetes

Cold Physiology: Postprandial Blood Flow Dynamics and Metabolism in the Antarctic Fish Pagothenia borchgrevinki

Previous studies on metabolic responses to feeding (i.e. the specific dynamic action, SDA) in Antarctic fishes living at temperatures below zero have reported long-lasting increases and small peak responses. We therefore hypothesized that the postprandial hyperemia also would be limited in the Antarctic fish Pagothenia borchgrevinki. The proportion of cardiac output directed to the splanchnic circulation in unfed fish was 18%, which is similar to temperate fish species. Contrary to our prediction, however, gastrointestinal blood flow had increased by 88% at twenty four hours after feeding due to a significant increase in cardiac output and a significant decrease in gastrointestinal vascular resistance. While gastric evacuation time appeared to be longer than in comparable temperate species, digestion had clearly commenced twenty four hours after feeding as judged by a reduction in mass of the administered feed. Even so, oxygen consumption did not increase suggesting an unusually slowly developing SDA. Adrenaline and angiotensin II was injected into unfed fish to investigate neuro-humoral control mechanisms of gastrointestinal blood flow. Both agonists increased gastrointestinal vascular resistance and arterial blood pressure, while systemic vascular resistance was largely unaffected. The hypertension was mainly due to increased cardiac output revealing that the heart and the gastrointestinal vasculature, but not the somatic vasculature, are important targets for these agonists. It is suggested that the apparently reduced SDA in P. borchgrevinki is due to a depressant effect of the low temperature on protein assimilation processes occurring outside of the gastrointestinal tract, while the gastrointestinal blood flow responses to feeding and vasoactive substances resemble those previously observed in temperate species

Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model

Several firing patterns experimentally observed in neural populations have been successfully correlated to animal behavior. Population bursting, hereby regarded as a period of high firing rate followed by a period of quiescence, is typically observed in groups of neurons during behavior. Biophysical membrane-potential models of single cell bursting involve at least three equations. Extending such models to study the collective behavior of neural populations involves thousands of equations and can be very expensive computationally. For this reason, low dimensional population models that capture biophysical aspects of networks are needed. \noindent The present paper uses a firing-rate model to study mechanisms that trigger and stop transitions between tonic and phasic population firing. These mechanisms are captured through a two-dimensional system, which can potentially be extended to include interactions between different areas of the nervous system with a small number of equations. The typical behavior of midbrain dopaminergic neurons in the rodent is used as an example to illustrate and interpret our results. \noindent The model presented here can be used as a building block to study interactions between networks of neurons. This theoretical approach may help contextualize and understand the factors involved in regulating burst firing in populations and how it may modulate distinct aspects of behavior.Comment: 25 pages (including references and appendices); 12 figures uploaded as separate file

Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation, volcanic activity or aridity. Their analytical detection depends on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge and often restrict sampling strategies. To help overcome these limitations, we present a framework based on Flow Imaging Microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify 7 commonly found classes: mineral dust, felsic and basaltic volcanic ash (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber) and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system’s potentials and limitations with respect to the detection of mineral dust, pollen grains and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non destructive, fully reproducible and does not require any sample preparation step. The presented framework can bolster research in the field, by cutting down processing time, supporting human-operated microscopy and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented

Efficacy of EGFR Inhibition Is Modulated by Model, Sex, Genetic Background and Diet: Implications for Preclinical Cancer Prevention and Therapy Trials

Molecule-targeted therapies are being widely developed and deployed, but they are frequently less effective in clinical trials than predicted based upon preclinical studies. Frequently, only a single model or genetic background is utilized using diets that are not relevant to that consumed by most cancer patients, which may contribute to the lack of predictability of many preclinical therapeutic studies. Inhibition of epidermal growth factor receptor (EGFR) in colorectal cancer was used to investigate potential causes for low predictive values of many preclinical studies. The efficacy of the small molecule EGFR inhibitor AG1478 was evaluated using two mouse models, ApcMin/+ and azoxymethane (AOM), both sexes on three genetic backgrounds, C57BL/6J (B6) and A/J (A) inbred strains and AB6F1 hybrids, and two diets, standard chow (STD) or Western-style diet (WD). AG1478 has significant anti-tumor activity in the B6-ApcMin/+ model with STD but only moderately on the WD and in the AOM model on an A background with a WD but not STD. On the F1 hybrid background AG1478 is effective in the ApcMin/+ model with either STD or WD, but has only moderate efficacy in the AOM model with either diet. Sex differences were also observed. Unexpectedly, the level of liver EGFR phosphorylation inhibition by AG1478 was not positively correlated with inhibition of tumor growth in the AOM model. Model-dependent interactions between genetic background and diet can dramatically impact preclinical results, and indicate that low predictive values of preclinical studies can be attributed to study designs that do not account for the heterogeneous patient population or the diets they consume. Better-designed preclinical studies should lead to more accurate predictions of therapeutic response in the clinic

Discovery of a nanodiamond-rich layer in the Greenland ice sheet

We report the discovery in the Greenland ice sheet of a discrete layer of free nanodiamonds (NDs) in very high abundances, implying most likely either an unprecedented influx of extraterrestrial (ET) material or a cosmic impact event that occurred after the last glacial episode. From that layer, we extracted n-diamonds and hexagonal diamonds (lonsdaleite), an accepted ET impact indicator, at abundances of up to about 5!106 times background levels in adjacent younger and older ice. The NDs in the concentrated layer are rounded, suggesting they most likely formed during a cosmic impact through some process similar to carbon-vapor deposition or high-explosive detonation. This morphology has not been reported previously in cosmic material, but has been observed in terrestrial impact material. This is the first highly enriched, discrete layer of NDs observed in glacial ice anywhere, and its presence indicates that ice caps are important archives of ET events of varying magnitudes. Using a preliminary ice chronology based on oxygen isotopes and dust stratigraphy, the ND-rich layer appears to be coeval with ND abundance peaks reported at numerous North American sites in a sedimentary layer, the Younger Dryas boundary layer (YDB), dating to 12.9 0.1 ka. However, more investigation is needed to confirm this association

Air temperature variations and gradients along the coast and fjords of western Spitsbergen

Daily temperature measurements from six meteorological stations along the coast and fjords of western Spitsbergen have been digitized and quality controlled in a Norwegian, Russian and Polish collaboration. Complete daily data series have been reconstructed back to 1948 for all of the stations. One of the station’s monthly temperature series has previously been extended back to 1898 and is included in this study. The long-term series show large temperature variability on western Spitsbergen with colder periods in the 1910s and 1960s and warmer periods in the 1930s, 1950s and in the 21st century. The most recent years are the warmest ones in the instrumental records. There is a positive and statistically significant trend in the annual times series for all of the stations; however, the strongest warming is seen in winter and spring. For the period 1979-2015, the linear trends range from 1.0 to 1.38°C/decade for the annual series and from 2.0 to 2.38°C/decade in winter. Threshold statistics demonstrate a decrease in the number of cold days per year and an increase in the number of warm days. A decreasing inter-annual variability is observed. In winter, spring and autumn, the stations in the northernmost areas of west Spitsbergen and in the innermost parts of Isfjorden are the coldest ones. In summer, however, the southernmost station is the coldest one

Detection of ice core particles via deep neural networks

Insoluble particles in ice cores record signatures of past climate parameters like vegetation dynamics, volcanic activity, and aridity. For some of them, the analytical detection relies on intensive bench microscopy investigation and requires dedicated sample preparation steps. Both are laborious, require in-depth knowledge, and often restrict sampling strategies. To help overcome these limitations, we present a framework based on flow imaging microscopy coupled to a deep neural network for autonomous image classification of ice core particles. We train the network to classify seven commonly found classes, namely mineral dust, felsic and mafic (basaltic) volcanic ash grains (tephra), three species of pollen (Corylus avellana, Quercus robur, Quercus suber), and contamination particles that may be introduced onto the ice core surface during core handling operations. The trained network achieves 96.8 % classification accuracy at test time. We present the system's potential and its limitations with respect to the detection of mineral dust, pollen grains, and tephra shards, using both controlled materials and real ice core samples. The methodology requires little sample material, is non-destructive, fully reproducible, and does not require any sample preparation procedures. The presented framework can bolster research in the field by cutting down processing time, supporting human-operated microscopy, and further unlocking the paleoclimate potential of ice core records by providing the opportunity to identify an array of ice core particles. Suggestions for an improved system to be deployed within a continuous flow analysis workflow are also presented