Trends in office internal gains and the impact on space heating and cooling demands

Internal gains from occupants, equipment and lighting contribute a significant proportion of the heat gains in an office space. Looking at trends in Generation-Y, it appears there are two diverging paths for future ICT demand: one where energy demand is carefully regulated and the other where productivity enhancers such as multiple monitors and media walls causes an explosion of energy demand within the space. These internal gains scenarios were simulated on a variety of different building archetypes to test their influence on the space heating and cooling demand. It was demonstrated that in offices with a high quality facade, internal gains are the dominant factor. As a case study, it was shown that natural ventilation is only possible when the ICT demand is carefully regulated

Which Soft Tissue Sarcoma Patients with Lung Metastases Should not Undergo Pulmonary Resection?

Using the second best method of meta-analysis it is significantly shown that patients with an interval of less than 7 months between diagnosis of soft tissue sarcoma and lung surgery for metastases do not benefit

Growth description for vessel wall adaptation: a thick-walled mixture model of abdominal aortic aneurysm evolution

(1) Background: Vascular tissue seems to adapt towards stable homeostatic mechanical conditions, however, failure of reaching homeostasis may result in pathologies. Current vascular tissue adaptation models use many ad hoc assumptions, the implications of which are far from being fully understood; (2) Methods: The present study investigates the plausibility of different growth kinematics in modeling Abdominal Aortic Aneurysm (AAA) evolution in time. A structurally motivated constitutive description for the vessel wall is coupled to multi-constituent tissue growth descriptions; Constituent deposition preserved either the constituent’s density or its volume, and Isotropic Volume Growth (IVG), in-Plane Volume Growth (PVG), in-Thickness Volume Growth (TVG) and No Volume Growth (NVG) describe the kinematics of the growing vessel wall. The sensitivity of key modeling parameters is explored, and predictions are assessed for their plausibility; (3) Results: AAA development based on TVG and NVG kinematics provided not only quantitatively, but also qualitatively different results compared to IVG and PVG kinematics. Specifically, for IVG and PVG kinematics, increasing collagen mass production accelerated AAA expansion which seems counterintuitive. In addition, TVG and NVG kinematics showed less sensitivity to the initial constituent volume fractions, than predictions based on IVG and PVG; (4) Conclusions: The choice of tissue growth kinematics is of crucial importance when modeling AAA growth. Much more interdisciplinary experimental work is required to develop and validate vascular tissue adaption models, before such models can be of any practical use

Retroviruses integrate into a shared, non-palindromic DNA motif.

Many DNA-binding factors, such as transcription factors, form oligomeric complexes with structural symmetry that bind to palindromic DNA sequences1. Palindromic consensus nucleotide sequences are also found at the genomic integration sites of retroviruses2-6 and other transposable elements7-9, and it has been suggested that this palindromic consensus arises as a consequence of the structural symmetry in the integrase complex2,3. However, we show here that the palindromic consensus sequence is not present in individual integration sites of human T-cell lymphotropic virus type 1 (HTLV-1) and human immunodeficiency virus type 1 (HIV-1), but arises in the population average as a consequence of the existence of a non-palindromic nucleotide motif that occurs in approximately equal proportions on the plus strand and the minus strand of the host genome. We develop a generally applicable algorithm to sort the individual integration site sequences into plus-strand and minus-strand subpopulations, and use this to identify the integration site nucleotide motifs of five retroviruses of different genera: HTLV-1, HIV-1, murine leukaemia virus (MLV), avian sarcoma leucosis virus (ASLV) and prototype foamy virus (PFV). The results reveal a non-palindromic motif that is shared between these retroviruses

Free serum haemoglobin is associated with brain atrophy in secondary progressive multiple sclerosis.

Background A major cause of disability in secondary progressive multiple sclerosis (SPMS) is progressive brain atrophy, whose pathogenesis is not fully understood. The objective of this study was to identify protein biomarkers of brain atrophy in SPMS. Methods We used surface-enhanced laser desorption-ionization time-of-flight mass spectrometry to carry out an unbiased search for serum proteins whose concentration correlated with the rate of brain atrophy, measured by serial MRI scans over a 2-year period in a well-characterized cohort of 140 patients with SPMS. Protein species were identified by liquid chromatography-electrospray ionization tandem mass spectrometry. Results There was a significant (p<0.004) correlation between the rate of brain atrophy and a rise in the concentration of proteins at 15.1 kDa and 15.9 kDa in the serum. Tandem mass spectrometry identified these proteins as alpha-haemoglobin and beta-haemoglobin, respectively.  The abnormal concentration of free serum haemoglobin was confirmed by ELISA (p<0.001). The serum lactate dehydrogenase activity was also highly significantly raised (p<10-12) in patients with secondary progressive multiple sclerosis. Conclusions An underlying low-grade chronic intravascular haemolysis is a potential source of the iron whose deposition along blood vessels in multiple sclerosis plaques contributes to the neurodegeneration and consequent brain atrophy seen in progressive disease. Chelators of free serum iron will be ineffective in preventing this neurodegeneration, because the iron (Fe2+) is chelated by haemoglobin

Balancing the robustness and predictive performance of biomarkers.

Recent studies have highlighted the importance of assessing the robustness of putative biomarkers identified from experimental data. This has given rise to the concept of stable biomarkers, which are ones that are consistently identified regardless of small perturbations to the data. Since stability is not by itself a useful objective, we present a number of strategies that combine assessments of stability and predictive performance in order to identify biomarkers that are both robust and diagnostically useful. Moreover, by wrapping these strategies around logistic regression classifiers regularized by the elastic net penalty, we are able to assess the effects of correlations between biomarkers upon their perceived stability. We use a synthetic example to illustrate the properties of our proposed strategies. In this example, we find that: (i) assessments of stability can help to reduce the number of false-positive biomarkers, although potentially at the cost of missing some true positives; (ii) combining assessments of stability with assessments of predictive performance can improve the true positive rate; and (iii) correlations between biomarkers can have adverse effects on their stability and hence must be carefully taken into account when undertaking biomarker discovery. We then apply our strategies in a proteomics context to identify a number of robust candidate biomarkers for the human disease HTLV1-associated myelopathy/tropical spastic paraparesis (HAM/TSP)