Вплив екологічного стану Донецького регіону на його демографічний розвиток

В статті розглянуто важливу проблему впливу забрудненості навколишнього природного середовища на захворюваність та смертність в регіоні. Визначено кореляційну залежність між обсягом викидів забруднюючих речовин та окремими видами захворюваності, а також ступінь їх впливу, побудовано функції, що описують їх.В статье рассмотрена важная проблема влияния загрязненности окружающей естественной среды на заболеваемость и смертность в регионе. Определена корреляционная зависимость между объемом выбросов загрязняющих веществ и отдельными видами заболеваемости, а также степень их влияния, построены функции, которые описывают их.In the article the important problem of influence of muddiness of natural environment is considered on morbidity and death rate in a region. Certainly cross-correlation dependence between the volume of extrass of contaminents and separate types of morbidity, and also degree of their influence, functions which describe them are built. Keywords: environment

Run Time Models in Adaptive Service Infrastructure

Software in the near ubiquitous future will need to cope with vari- ability, as software systems get deployed on an increasingly large diversity of computing platforms and operates in different execution environments. Heterogeneity of the underlying communication and computing infrastruc- ture, mobility inducing changes to the execution environments and therefore changes to the availability of resources and continuously evolving requirements require software systems to be adaptable according to the context changes. Software systems should also be reliable and meet the user's requirements and needs. Moreover, due to its pervasiveness, software systems must be de- pendable. Supporting the validation of these self-adaptive systems to ensure dependability requires a complete rethinking of the software life cycle. The traditional division among static analysis and dynamic analysis is blurred by the need to validate dynamic systems adaptation. Models play a key role in the validation of dependable systems, dynamic adaptation calls for the use of such models at run time. In this paper we describe the approach we have un- dertaken in recent projects to address the challenge of assessing dependability for adaptive software systems

Hepatic P450 Enzyme Activity, Tissue Morphology and Histology of Mink (Mustela vison) Exposed to Polychlorinated Dibenzofurans

Dose- and time-dependent effects of environmentally relevant concentrations of 2,3,7,8-tetrachlorodibenzo-p-dioxin equivalents (TEQ) of 2,3,7,8-tetrachlorodibenzofuran (TCDF), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), or a mixture of these two congeners on hepatic P450 enzyme activity and tissue morphology, including jaw histology, of adult ranch mink were determined under controlled conditions. Adult female ranch mink were fed either TCDF (0.98, 3.8, or 20 ng TEQTCDF/kg bw/day) or PeCDF (0.62, 2.2, or 9.5 ng TEQPeCDF/kg bw/day), or a mixture of TCDF and PeCDF (4.1 ng TEQTCDF/kg bw/day and 2.8 ng TEQPeCDF/kg bw/day, respectively) for 180 days. Doses used in this study were approximately eight times greater than those reported in a parallel field study. Activities of the cytochrome P450 1A enzymes, ethoxyresorufin O-deethylase (EROD) and methoxyresorufin O-deethylase (MROD) were significantly greater in livers of mink exposed to TCDF, PeCDF, and a mixture of the two congeners; however, there were no significant histological or morphological effects observed. It was determined that EROD and MROD activity can be used as sensitive biomarkers of exposure to PeCDF and TCDF in adult female mink; however, under the conditions of this study, the response of EROD/MROD induction occurred at doses that were less than those required to cause histological or morphological changes

Wykorzystanie analizy wrażliwości w przygotowaniu procesu optymalizacji

Speed and efficiency of an optimizing algorithm can be a function of used number of variables. Before optimization of dosing mechanism parameters, sensitivity analysis was performed. Choice of the design variables was the output from this analysis. The article deals with this analysis and interpretation of its results.Szybkość i efektywność algorytmów optymalizacyjnych mogą być funkcjami zastosowanej liczby zmiennych. Przed optymalizacją parametrów mechanizmu dozującego została przeprowadzona analiza wrażliwości, której efektem był dobór proponowanych zmiennych. Artykuł jest poświęcony tej analizie oraz interpretacji jej wyników

A Model for Aryl Hydrocarbon Receptor-Activated Gene Expression Shows Potency and Efficacy Changes and Predicts Squelching Due to Competition for Transcription Co-Activators

<div><p>A stochastic model of nuclear receptor-mediated transcription was developed based on activation of the aryl hydrocarbon receptor (AHR) by 2,3,7,8-tetrachlorodibenzodioxin (TCDD) and subsequent binding the activated AHR to xenobiotic response elements (XREs) on DNA. The model was based on effects observed in cells lines commonly used as <i>in vitro</i> experimental systems. Following ligand binding, the AHR moves into the cell nucleus and forms a heterodimer with the aryl hydrocarbon nuclear translocator (ARNT). In the model, a requirement for binding to DNA is that a generic coregulatory protein is subsequently bound to the AHR-ARNT dimer. Varying the amount of coregulator available within the nucleus altered both the potency and efficacy of TCDD for inducing for transcription of CYP1A1 mRNA, a commonly used marker for activation of the AHR. Lowering the amount of available cofactor slightly increased the EC50 for the transcriptional response without changing the efficacy or maximal response. Further reduction in the amount of cofactor reduced the efficacy and produced non-monotonic dose-response curves (NMDRCs) at higher ligand concentrations. The shapes of these NMDRCs were reminiscent of the phenomenon of squelching. Resource limitations for transcriptional machinery are becoming apparent in eukaryotic cells. Within single cells, nuclear receptor-mediated gene expression appears to be a stochastic process; however, intercellular communication and other aspects of tissue coordination may represent a compensatory process to maintain an organism’s ability to respond on a phenotypic level to various stimuli within an inconstant environment.</p></div

Estimates of cancer potency of 2,3,7,8-tetrachlorodibenzo(p)dioxin using linear and nonlinear dose-response modeling and toxicokinetics

Linear and nonlinear toxicity criteria were derived for 2,3,7,8-tetrachlorodibenzo(p)dioxin (TCDD) using the recent National Toxicology Program rat cancer bioassay. Dose-response relationships were assessed for combined liver tumors based on lifetime average liver concentrations (LALCs) estimated with a toxicokinetic model. Rat LALC estimates at the 1% point of departure (POD) were obtained with benchmark dose (BMD) modeling to yield the BMD in terms of LALC. The same toxicokinetic model was used to backextrapolate the human-equivalent external dose (HED). A linear cancer slope factor (CSF) with a value of 1 × 10 per pg/kg/day was calculated as the ratio between the benchmark response rate and the HED at the lower confidence limit of the benchmark dose (BMDL). A nonlinear reference dose (RfD) with a value of 100 pg/kg/day was developed from the BMD value by applying uncertainty factors to rat internal and human external doses. The RfD was 100 times higher than the 10 risk-specific dose (RSD) based on the linear CSF. For comparison, BMD and BMDL values were developed for key events in the tumor promotion mode of action (MOA) of TCDD. This MOA involves dysregulation of the normal function of the aryl hydrocarbon receptor and its associated biological processes and results in pathologies that drive tumor promotion and progression. The BMD values for key events were consistent with the timing of the key events within the MOA and provided support for the choices of the 1% tumor rate as a POD and dichotomous Hill model for representing receptor-mediated carcinogenicity. Because a threshold toxicity criterion most accurately reflects the MOA, the RfD for TCDD with a value of 100 pg/kg/day is considered appropriate for regulatory purposes, consistent with a 2006 NRC panel's recommendation to develop a threshold-based cancer potency factor for TCDD and with the methodology in U.S. Environmental Protection Agency's Cancer Guidelines

Modeled transcriptional dose-response plots at varying amounts of cofactor and non-AHR-ARNT cofactor binding sites.

<p>(<b>A</b>) Reduction in the amount of cofactor (CoF) at a constant concentration/amount of competing non-AHR binding proteins (1535 molecules). The modeled response and Hill equation fits are shown for cofactor amounts of 2000, 1500 and 1200 molecules. At 1000 molecules of cofactor and less, squelching was apparent, shown by a reduction in the responses at higher TCDD concentrations and the biphasic appearance of the DR curves. (<b>B</b>) Increasing the amount of competing non-AHR binding proteins (Other) also produced a squelching-like response at high ligand concentrations with squelching occurring at 7500 or more molecules of non-AHR cofactor binding proteins. The amount of cofactor was kept constant at 1500 molecules. The Hill equation fits are shown for competing non-AHR binding site (Other) amounts of 2500 or less.</p

Contour plots of the modeled transcriptional responses showing the relationship between number of cofactor molecules and the number of competing non-AHR (Other) binding proteins.

<p>The x-axes show the applied concentration of TCDD. The y-axes show the amount of other binding proteins available in the cell. The fold change in CYP1A1 mRNA is represented by the colors on the plots and the color bar to the right. The number at the upper left of each plot shows the number of molecules of cofactor.</p