UWB Propagation through Walls

The propagation of ultra wide band (UWB) signals through walls is analyzed. For this propagation studies, it is necessary to consider not only propagation at a single frequency but in the whole band. The UWB radar output signal is formed by both transmitter and antenna. The effects of antenna receiving and transmitting responses for various antenna types (such as small and aperture antennas) are studied in the frequency as well as time domain. Moreover, UWB radar output signals can be substantially affected due to electromagnetic wave propagation through walls and multipath effects

Роль фактора некроза опухоли-альфа в прогнозировании тяжести и исхода сепсиса у пациентов неотложного отделения с системным воспалением

Aim of the study was to determine whether the TNF-a levels, proximal inflammatory mediator, in septic patients presenting to the emergency department (ED) and admitted to the intensive care unit (ICU) are associated with progression to severe sepsis, septic shock or death. Material and methods. A retrospective observational study was performed on a sample of one hundred adult subjects presenting to the ED with systemic inflammatory response syndrome of 2 etiologies: presumed (and later confirmed in the ICU and/or operating room) severe acute pancreatitis or generalized peritonitis. Blood TNF-a samples measurements were taken shortly after ED admission. TNF-a was measured by commercial ELISA test in plasma. Results. Mean values of TNF-a on admission (day zero, in ED) were 191,5-fold lower in group with septic shock compared to severe sepsis group and were 63-fold higher in survivors (p<0.01). The area under the curve (AUC) for the TNF-a plots for severity of clinical status was 0.813 and for outcome 0.834. Patients with TNF-a levels lower than 7.95 pg/mL had a 3.2-fold higher probability of septic shock development than those with higher values, at the cutoff level sensitivity was 83,9% and specificity 72,5%. Patients with TNF-a levels higher than 10.5 pg/mL had a 4.8-fold higher probability to survive than those with lower values, at the cutoff level sensitivity was 83,0% and specificity 77,4%. Conclusion: Decreasing in TNF-a concentration leads to the septic shock development and fatal outcome. TNF-a is very good predictor of sepsis severity and outcome. Key words: sepsis, tumor necrosis factor-alpha, emergency medical services, survival rate, severity of illness index.Цель исследования — определить, связаны ли уровни ФНО-a, ключевого медиатора воспаления, у пациентов с сепсисом, поступающих в отделение неотложной помощи и переводящихся в отделение реанимации, с прогрессированием его до тяжелого сепсиса, септического шока и смерти. Материал и методы. Ретроспективное обсервационное исследование было выполнено на выборке в 100 взрослых человек, поступивших в неотложное отделение с признаками системного воспаления двух возможных этиологий: тяжелый острый панкреатит (предполагаемый, а затем подтвержденный в отделении реанимации и/или операционной) или общий перитонит. Производили измерения ФНО-a в крови сразу после поступления. ФНО-a измеряли коммерчески доступным ELISA-методом в плазме крови. Результаты. Средние уровни ФНО-a при поступлении (день 0, в неотложном отделении) были в 191,5 раз ниже в группе с септическим шоком по сравнению с группой тяжелого сепсиса и в 63 раза выше у выживших (

Impairment of a model peptide by oxidative stress: Thermodynamic stabilities of asparagine diamide C(alpha)-radical foldamers

Electron structure calculations on N-acetyl asparagine N-methylamide were performed to identify the global minimum from which radicals were formed after H-abstraction by the OH radical. It was found that the radical generated by breaking the C–H bond of the alpha-carbon was thermodynamically the most stable one in the gas- and aqueous phases. The extended ((beta)L and (beta)D) backbone conformations are the most stable, but syn–syn or inverse gamma-turn ((gamma)L) and gamma-turn ((gamma)D) have substantial stability too. The highest energy conformers are the degenerate eL and eD foldamers. Clearly, the most stable beta foldamer is the most likely intermediate for racemization

Statistical learning leads to persistent memory: evidence for one-year consolidation

Statistical learning is a robust mechanism of the brain that enables the extraction of environmental patterns, which is crucial in perceptual and cognitive domains. However, the dynamical change of processes underlying long-term statistical memory formation has not been tested in an appropriately controlled design. Here we show that a memory trace acquired by statistical learning is resistant to inference as well as to forgetting after one year. Participants performed a statistical learning task and were retested one year later without further practice. The acquired statistical knowledge was resistant to interference, since after one year, participants showed similar memory performance on the previously practiced statistical structure after being tested with a new statistical structure. These results could be key to understand the stability of long-term statistical knowledge

Mutational analysis of the latency-associated nuclear antigen DNA-binding domain of Kaposi's sarcoma-associated herpesvirus reveals structural conservation among gammaherpesvirus origin-binding proteins

The latency-associated nuclear antigen (LANA) of Kaposi's sarcoma-associated herpesvirus functions as an origin-binding protein (OBP) and transcriptional regulator. LANA binds the terminal repeats via the C-terminal DNA-binding domain (DBD) to support latent DNA replication. To date, the structure of LANA has not been solved. Sequence alignments among OBPs of gammaherpesviruses have revealed that the C terminus of LANA is structurally related to EBNA1, the OBP of Epstein–Barr virus. Based on secondary structure predictions for LANADBD and published structures of EBNA1DBD, this study used bioinformatics tools to model a putative structure for LANADBD bound to DNA. To validate the predicted model, 38 mutants targeting the most conserved motifs, namely three α-helices and a conserved proline loop, were constructed and functionally tested. In agreement with data for EBNA1, residues in helices 1 and 2 mainly contributed to sequence-specific DNA binding and replication activity, whilst mutations in helix 3 affected replication activity and multimer formation. Additionally, several mutants were isolated with discordant phenotypes, which may aid further studies into LANA function. In summary, these data suggest that the secondary and tertiary structures of LANA and EBNA1 DBDs are conserved and are critical for (i) sequence-specific DNA binding, (ii) multimer formation, (iii) LANA-dependent transcriptional repression, and (iv) DNA replication

Chronobiology of high blood pressure

BIOCOS, the project aimed at studying BIOlogical systems in their COSmos, has obtained a great deal of expertise in the fields of blood pressure (BP) and heart rate (HR) monitoring and of marker rhythmometry for the purposes of screening, diagnosis, treatment, and prognosis. Prolonging the monitoring reduces the uncertainty in the estimation of circadian parameters; the current recommendation of BIOCOS requires monitoring for at least 7 days. The BIOCOS approach consists of a parametric and a non-parametric analysis of the data, in which the results from the individual subject are being compared with gender- and age-specified reference values in health. Chronobiological designs can offer important new information regarding the optimization of treatment by timing its administration as a function of circadian and other rhythms. New technological developments are needed to close the loop between the monitoring of blood pressure and the administration of antihypertensive drugs

Activation of TRPC6 channels is essential for lung ischaemia–reperfusion induced oedema in mice

Lung ischaemia–reperfusion-induced oedema (LIRE) is a life-threatening condition that causes pulmonary oedema induced by endothelial dysfunction. Here we show that lungs from mice lacking nicotinamide adenine dinucleotide phosphate (NADPH) oxidase (Nox2y/−) or the classical transient receptor potential channel 6 (TRPC6−/−) are protected from LIR-induced oedema (LIRE). Generation of chimeric mice by bone marrow cell transplantation and endothelial-specific Nox2 deletion showed that endothelial Nox2, but not leukocytic Nox2 or TRPC6, are responsible for LIRE. Lung endothelial cells from Nox2- or TRPC6-deficient mice showed attenuated ischaemia-induced Ca2+ influx, cellular shape changes and impaired barrier function. Production of reactive oxygen species was completely abolished in Nox2y/− cells. A novel mechanistic model comprising endothelial Nox2-derived production of superoxide, activation of phospholipase C-γ, inhibition of diacylglycerol (DAG) kinase, DAG-mediated activation of TRPC6 and ensuing LIRE is supported by pharmacological and molecular evidence. This mechanism highlights novel pharmacological targets for the treatment of LIRE

TMFoldRec: a statistical potential-based transmembrane protein fold recognition tool.

BACKGROUND: Transmembrane proteins (TMPs) are the key components of signal transduction, cell-cell adhesion and energy and material transport into and out from the cells. For the deep understanding of these processes, structure determination of transmembrane proteins is indispensable. However, due to technical difficulties, only a few transmembrane protein structures have been determined experimentally. Large-scale genomic sequencing provides increasing amounts of sequence information on the proteins and whole proteomes of living organisms resulting in the challenge of bioinformatics; how the structural information should be gained from a sequence. RESULTS: Here, we present a novel method, TMFoldRec, for fold prediction of membrane segments in transmembrane proteins. TMFoldRec based on statistical potentials was tested on a benchmark set containing 124 TMP chains from the PDBTM database. Using a 10-fold jackknife method, the native folds were correctly identified in 77 % of the cases. This accuracy overcomes the state-of-the-art methods. In addition, a key feature of TMFoldRec algorithm is the ability to estimate the reliability of the prediction and to decide with an accuracy of 70 %, whether the obtained, lowest energy structure is the native one. CONCLUSION: These results imply that the membrane embedded parts of TMPs dictate the TM structures rather than the soluble parts. Moreover, predictions with reliability scores make in this way our algorithm applicable for proteome-wide analyses. AVAILABILITY: The program is available upon request for academic use

Prediction of protein structural classes for low-homology sequences based on predicted secondary structure

<p>Abstract</p> <p>Background</p> <p>Prediction of protein structural classes (<it>α</it>, <it>β</it>, <it>α </it>+ <it>β </it>and <it>α</it>/<it>β</it>) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulation and interactions. Many methods have been developed for high-homology protein sequences, and the prediction accuracies can achieve up to 90%. However, for low-homology sequences whose average pairwise sequence identity lies between 20% and 40%, they perform relatively poorly, yielding the prediction accuracy often below 60%.</p> <p>Results</p> <p>We propose a new method to predict protein structural classes on the basis of features extracted from the predicted secondary structures of proteins rather than directly from their amino acid sequences. It first uses PSIPRED to predict the secondary structure for each protein sequence. Then, the <it>chaos game representation </it>is employed to represent the predicted secondary structure as two time series, from which we generate a comprehensive set of 24 features using <it>recurrence quantification analysis</it>, <it>K-string based information entropy </it>and <it>segment-based analysis</it>. The resulting feature vectors are finally fed into a simple yet powerful Fisher's discriminant algorithm for the prediction of protein structural classes. We tested the proposed method on three benchmark datasets in low homology and achieved the overall prediction accuracies of 82.9%, 83.1% and 81.3%, respectively. Comparisons with ten existing methods showed that our method consistently performs better for all the tested datasets and the overall accuracy improvements range from 2.3% to 27.5%. A web server that implements the proposed method is freely available at <url>http://www1.spms.ntu.edu.sg/~chenxin/RKS_PPSC/</url>.</p> <p>Conclusion</p> <p>The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the predicted secondary structure sequences, which is capable of characterizing the sequence order information, local interactions of the secondary structural elements, and spacial arrangements of <it>α </it>helices and <it>β </it>strands. Thus, it is a valuable method to predict protein structural classes particularly for low-homology amino acid sequences.</p