MODELOWANIE MATEMATYCZNE I SYSTEM STEROWANIA BUDYNKIEM NIEMAL ZEROENERGETYCZNYM

The article examines three different kinds of mathematical model of nearly zero energy building. The first model enables to optimize the structure and the definition of key parameters of energy efficient building. The second model is necessary for passive house designing with renewable energy sources. The third model should be used for monitoring and control of energy supply system of nearly zero energy building through year every hour of winter and summer.W artykule rozważono trzy różne typy matematycznego modelu budynku o niemal zerowym zużyciu energii. Pierwszy model pozwala zoptymalizować strukturę i definicję kluczowych parametrów budynku energooszczędnego. Drugi model jest niezbędny do zaprojektowania domu pasywnego wykorzystującego odnawialne źródła energii. Trzeci model powinien być stosowany do godzinowego monitorowania i monitorowania systemu energetycznego budynku o niskim zużyciu energii przez cały rok

Gene expression signatures of peripheral CD4+ T cells clearly discriminate between patients with acute and chronic hepatitis B infection

CD4+ T and regulatory T cells (Tregs) seem to play a key role in persistence of hepatitis B virus (HBV) infection. However, the molecular events by which Tregs exert their modulatory activity are largely unknown. The transcriptional profiles of CD4+ T cells of healthy controls (HCs) and patients affected by acute hepatitis B (AVH-B) or chronic hepatitis B (CHB) infection were established using a custom expression array consisting of 350 genes relevant for CD4+ T cell and Treg function. These studies were complemented by real-time reverse-transcription polymerase chain reaction. Peripheral blood mononuclear cells (PBMCs) were also analyzed for the presence of Tregs, which were more abundant in the acute stage of the disease (7%) than in HCs and CHB infection (HCs versus AVH-B, P = 0.003; AVH-B versus CHB, P = 0.04). One hundred eighteen genes (34%) intrinsically differentiate HBV-infected patients from HCs. Using gene ontology, we identified T cell receptor signaling and clusterization, mitogen-activated protein kinase kinase signaling, cell adhesion, cytokines and inflammatory responses, cell cycle/cell proliferation, and apoptosis as the most prominent affected modules. A higher expression of CCR1, CCR3, CCR4, CCR5, and CCR8 was seen in AVH-B than in CHB-infected patients and HCs. Annotation of the interconnected functional network of genes provided a unique representation of global immune activation during acute infection. Almost all genes were down-regulated in patients with CHB infection. Conclusion: The fingerprints enable clear discrimination between patients suffering from AVH-B or CHB infection. The observed profiles suggest accumulation of effector T cells with a potential role in necro-inflammation during the acute stage. Subsequent down-regulated effector functions support the hypothesis of suppressed CD4+ effector T cells favoring viral persistence in the chronic infection stage

Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data

Determining the routes of introduction provides not only information about the history of an invasion process, but also information about the origin and construction of the genetic composition of the invading population. It remains difficult, however, to infer introduction routes from molecular data because of a lack of appropriate methods. We evaluate here the use of an approximate Bayesian computation (ABC) method for estimating the probabilities of introduction routes of invasive populations based on microsatellite data. We considered the crucial case of a single source population from which two invasive populations originated either serially from a single introduction event or from two independent introduction events. Using simulated datasets, we found that the method gave correct inferences and was robust to many erroneous beliefs. The method was also more efficient than traditional methods based on raw values of statistics such as assignment likelihood or pairwise F(ST). We illustrate some of the features of our ABC method, using real microsatellite datasets obtained for invasive populations of the western corn rootworm, Diabrotica virgifera virgifera. Most computations were performed with the DIYABC program (http://www1.montpellier.inra.fr/CBGP/diyabc/)