Technical University of Denmark

About: Technical University of Denmark is a education organization based out in Kongens Lyngby, Hovedstaden, Denmark. It is known for research contribution in the topics: Population & Catalysis. The organization has 24126 authors who have published 66394 publications receiving 2443649 citations. The organization is also known as: Danmarks Tekniske Universitet & DTU.

Why chronic wounds will not heal: a novel hypothesis.

Abstract: The present paper presents a hypothesis aimed at explaining why venous leg ulcers, pressure ulcers, and diabetic foot ulcers develop into a chronic state. We propose that the lack of proper wound healing is at least in part caused by inefficient eradication of infecting, opportunistic pathogens, a situation reminiscent of chronic Pseudomonas aeruginosa infections found in patients suffering from cystic fibrosis (CF). We have analyzed sections from chronic wounds by fluorescence in situ hybridization and found distinct microcolonies--the basal structures of bacterial biofilms. Several researchers have previously reported that another important hallmark of biofilm formation is development of increased tolerance to various antimicrobial measures and treatments. Furthermore, the immune response to infecting bacteria in the cystic fibrosis lung is dominated by polymorphonuclear neutrophils (PMNs), and we have recently shown that in vitro biofilms of P. aeruginosa produce a shielding mechanism that offers protection from the phagocytic activity of PMNs. We hypothesize that the presence of P. aeruginosa in biofilms, and the lack of concomitant elimination by attended PMNs, are the main causes of inefficient eradication by antibiotic treatment and antimicrobial activity of the innate immune system, respectively.

Mid-infrared supercontinuum covering the 1.4–13.3 μm molecular fingerprint region using ultra-high NA chalcogenide step-index fibre

Abstract: Mid-infrared supercontinuum generation with a record-breaking spectral coverage of 1.4–13.3 µm is demonstrated by launching intense ultra-short pulses into short pieces of ultra-high numerical aperture step-index chalcogenide glass optical fibre consisting of a GaAsSe cladding and an As2Se3 core.

Protein oxidation in muscle foods: A review

Abstract: Protein oxidation in living tissues is known to play an essential role in the pathogenesis of relevant degenerative diseases, whereas the occurrence and impact of protein oxidation (Pox) in food systems have been ignored for decades. Currently, the increasing interest among food scientists in this topic has led to highlight the influence that Pox may have on meat quality and human nutrition. Recent studies have contributed to solid scientific knowledge regarding basic oxidation mechanisms, and in advanced methodologies to accurately assess Pox in food systems. Some of these studies have provided insight into the reactions involved in the oxidative modifications undergone by muscle proteins. Moreover, a variety of products derived from oxidized muscle proteins, including cross-links and carbonyls, have been identified. The impact of oxidation on protein functionality and on specific meat quality traits has also been addressed. Some other recent studies have shed light on the complex interaction mechanisms between myofibrillar proteins and certain redox-active compounds such as tocopherols and phenolic compounds. This paper is devoted to review the most relevant findings on the occurrence and consequences of Pox in muscle foods. The efficiency of different anti-oxidant strategies against the oxidation of muscle proteins is also reported.

Analysis and prediction of leucine-rich nuclear export signals

Abstract: We present a thorough analysis of nuclear export signals and a prediction server, which we have made publicly available. The machine learning prediction method is a significant improvement over the generally used consensus patterns. Nuclear export signals (NESs) are extremely important regulators of the subcellular location of proteins. This regulation has an impact on transcription and other nuclear processes, which are fundamental to the viability of the cell. NESs are studied in relation to cancer, the cell cycle, cell differentiation and other important aspects of molecular biology. Our conclusion from this analysis is that the most important properties of NESs are accessibility and flexibility allowing relevant proteins to interact with the signal. Furthermore, we show that not only the known hydrophobic residues are important in defining a nuclear export signals. We employ both neural networks and hidden Markov models in the prediction algorithm and verify the method on the most recently discovered NESs. The NES predictor (NetNES) is made available for general use at http://www.cbs.dtu.dk/.