Atopic Dermatitis: The Fate of the Fat

Atopic dermatitis (AD) is a chronic and relapsing inflammatory skin disease in which dry and itchy skin may develop into skin lesions. AD has a strong genetic component, as children from parents with AD have a two-fold increased chance of developing the disease. Genetic risk loci and epigenetic modifications reported in AD mainly locate to genes involved in the immune response and epidermal barrier function. However, AD pathogenesis cannot be fully explained by (epi)genetic factors since environmental triggers such as stress, pollution, microbiota, climate, and allergens also play a crucial role. Alterations of the epidermal barrier in AD, observed at all stages of the disease and which precede the development of overt skin inflammation, manifest as: dry skin; epidermal ultrastructural abnormalities, notably anomalies of the lamellar body cargo system; and abnormal epidermal lipid composition, including shorter fatty acid moieties in several lipid classes, such as ceramides and free fatty acids. Thus, a compelling question is whether AD is primarily a lipid disorder evolving into a chronic inflammatory disease due to genetic susceptibility loci in immunogenic genes. In this review, we focus on lipid abnormalities observed in the epidermis and blood of AD patients and evaluate their primary role in eliciting an inflammatory response.     

Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera

Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are both autoimmune inflammatory and demyelinating diseases of the central nervous system. NMOSD is a highly disabling disease and rapid introduction of the appropriate treatment at the acute phase is crucial to prevent sequelae. Specific criteria were established in 2015 and provide keys to distinguish NMOSD and MS. One of the most reliable criteria for NMOSD diagnosis is detection in patient’s serum of an antibody that attacks the water channel aquaporin-4 (AQP-4). Another target in NMOSD is myelin oligodendrocyte glycoprotein (MOG), delineating a new spectrum of diseases called MOG-associated diseases. Lastly, patients with NMOSD can be negative for both AQP-4 and MOG antibodies. At disease onset, NMOSD symptoms are very similar to MS symptoms from a clinical and radiological perspective. Thus, at first episode, given the urgency of starting the anti-inflammatory treatment, there is an unmet need to differentiate NMOSD subtypes from MS. Here, we used Fourier transform infrared spectroscopy in combination with a machine learning algorithm with the aim of distinguishing the infrared signatures of sera of a first episode of NMOSD from those of a first episode of relapsing-remitting MS, as well as from those of healthy subjects and patients with chronic inflammatory demyelinating polyneuropathy. Our results showed that NMOSD patients were distinguished from MS patients and healthy subjects with a sensitivity of 100% and a specificity of 100%. We also discuss the distinction between the different NMOSD serostatuses. The coupling of infrared spectroscopy of sera to machine learning is a promising cost-effective, rapid and reliable differential diagnosis tool capable of helping to gain valuable time in patients’ treatment.     

The Fight against Cancer by Microgravity: The Multicellular Spheroid as a Metastasis Model

Cancer is a disease exhibiting uncontrollable cell growth and spreading to other parts of the organism. It is a heavy, worldwide burden for mankind with high morbidity and mortality. Therefore, groundbreaking research and innovations are necessary. Research in space under microgravity (µg) conditions is a novel approach with the potential to fight cancer and develop future cancer therapies. Space travel is accompanied by adverse effects on our health, and there is a need to counteract these health problems. On the cellular level, studies have shown that real (r-) and simulated (s-) µg impact survival, apoptosis, proliferation, migration, and adhesion as well as the cytoskeleton, the extracellular matrix, focal adhesion, and growth factors in cancer cells. Moreover, the µg-environment induces in vitro 3D tumor models (multicellular spheroids and organoids) with a high potential for preclinical drug targeting, cancer drug development, and studying the processes of cancer progression and metastasis on a molecular level. This review focuses on the effects of r- and s-µg on different types of cells deriving from thyroid, breast, lung, skin, and prostate cancer, as well as tumors of the gastrointestinal tract. In addition, we summarize the current knowledge of the impact of µg on cancerous stem cells. The information demonstrates that µg has become an important new technology for increasing current knowledge of cancer biology.     

纤维基材料的仿生学研究动向

纤维基技术的应用对仿生学的成功发展呈现出巨大的潜力,因为宇宙成物在生长过程、多毛结构和增强纤维方面具有许多相似性.约七年前,邓肯道夫纺织技术与工艺研究所协同众位生物学家一起开创了仿生学的研发,至今方兴未艾.     

Managing projects with distributed and embedded knowledge through interactions

In project-based industries studies show difficulties in extracting, distributing and applying embedded and practice knowledge across structural and organisational boundaries. We focus on interorganisational projects consisting of distributed and embedded knowledge. Interaction becomes important in order to cooperate and share interorganisational and distributed knowledge. The aim of the research is to explore how sharing and generating practice based and distributed knowledge occurs through interaction in interorganisational projects and how this is managed. The study focuses on the design phase and relates traditional design practices to concurrent design practices. In the study we observed six cases of design meetings in the construction and oil and gas industry and performed 31 interviews. The paper contributes with the following: (1) understanding and visualisation of interaction patterns, (2) insight in use of various forms of interaction, and (3) ways of managing distributed and embedded knowledge through interaction.     

Purification and structural characterisation of lipid transfer protein from red wine and grapes

Lipid transfer proteins (LTP) play a major role in plant defence and are of particular interest due to their known ability to cause allergic reactions. These proteins are expressed in grapes and also remain detectable after vinification, especially in red wine. However, it remains unknown whether the protein undergoes any changes during the vinification process. Here, we present a purification method for LTPs from Dornfelder grapes and wine. By liquid-chromatography–mass spectroscopy (LC–MS/MS) we identified LTPs from two different species (Vitis vinifera and Vitis aestivalis). Additionally, the purified LTPs were characterised using spectrometric methods, confirming their high purity and structural stability during vinification. We conclude that LTPs are resistant to the alcohol content (13.5 vol%), acidic milieu of wine and other ingredients present during the vinification process, indicating that the allergenic potential of grape LTP is not diminished by the vinification process.     

Characterization of glow‐discharge–treated cellulose acetate membrane surfaces for single‐layer enzyme electrode studies

Cellulose acetate membranes (CA) were modified by means of plasma polymerization of ethylene diamine (EDA) and n‐butylamine (n‐BA). The motivation for this work was the application of a modified membrane for the single‐layer enzyme electrode. A tubular reactor with the external radiofrequency (13.56 MHz) excitation was used. Surface modification was performed at 5, 10, and 15 W power (at 27 Pa working pressure) for 5, 10, 15 min. Modified surfaces were characterized in detail by FTIR–ATR, XPS (ESCA), contact angle, and enzyme immobilization activity. The best treatment results were obtained for EDA with 5 W and 30 min and 15 W and 10 min. These results are discussed using surface analysis data. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 81: 1341–1352, 2001     

Use of the Cone Calorimeter and ConeTools software for development of innovative intumescing graphite systems

The Cone Calorimeter test method has been one of the most used small‐scale fire test method for years now and is at present widely spread over the world. In contrast to many other fire test methods, the Cone Calorimeter provides a range of data with sound scientific basis, which allows a wide range of applications. It can be used for modelling and also for enhanced product development. This paper describes the use of the Cone Calorimeter for the development of new innovative materials in combination with a mathematical model. As example, the cost effective development of an innovative intumescing graphite system for protecting particle board is explained. The performance goal of the project is to obtain the threshold values for a B class in the Single Burning Item (SBI) test method used for the newly developed Euroclass system. The focus of this paper is on the development tools and not on the chemical development of the protective system. During the research it was necessary to develop a new sample holder for the Cone Calorimeter. The results from the project show that the industry can save development time and resources by using the Cone Calorimeter in combination with a simple mathematical model. Copyright © 2010 John Wiley & Sons, Ltd.     

Factorial interlaboratory tests for microbiological measurement methods

This paper presents a validation approach for microbiological methods based on a combination of interlaboratory tests and factorial experiments. It requires not more than 4 participants but is achieving comparable statistical confidence as in method validation studies with 8–12 participants, if properly designed. The approach is illustrated by a comprehensive validation of the Arxula adeninivorans yeast estrogen screen (A-YES) assay for the detection of estrogenic activity in mineral water.     

Agent-based simulation for science,technology, and innovation policy

Scientometrics - Policymaking implies planning, and planning requires prediction—or at least some knowledge about the future. This contribution starts from the challenges of complexity,...