Mitochondrial DNA (mtDNA) haplogroups and serum levels of anti-oxidant enzymes in patients with osteoarthritis

BACKGROUND: Oxidative stress play a main role in the initiation and progression of the OA disease and leads to the degeneration of mitochondria. To prevent this, the chondrocytes possess a well-coordinated enzymatic antioxidant system. Besides, the mitochondrial DNA (mtDNA) haplogroups are associated with the OA disease. Thus, the main goal of this work is to assess the incidence of the mtDNA haplogroups on serum levels of two of the main antioxidant enzymes, Manganese Superoxide Dismutase (Mn-SOD or SOD2) and catalase, and to test the suitability of these two proteins for potential OA-related biomarkers. METHODS: We analyzed the serum levels of SOD2 and catalase in 73 OA patients and 77 healthy controls carrying the haplogroups J, U and H, by ELISA assay. Knee and hip radiographs were classified according to Kellgren and Lawrence (K/L) scoring from Grade 0 to Grade IV. Appropriate statistical analyses were performed to test the effects of clinical variables, including gender, body mass index (BMI), age, smoking status, diagnosis, haplogroups and radiologic K/L grade on serum levels of these enzymes. RESULTS: Serum levels of SOD2 appeared statistically increased in OA patients when compared with healthy controls (p < 0.001). Even in those OA patients with higher OA severity (K/L grade IV), the serum levels of this antioxidant enzyme appeared more significantly increased than in OA patients with lower K/L grade (p < 0.001). The mtDNA haplogroups showed an influence on serum levels of catalase (p = 0.054), being carriers of the mtDNA haplogroup J those who showed higher serum levels than non-J carriers (p = 0.057). CONCLUSIONS: The increased levels of SOD2 in OA patients indicate an increased oxidative stress OA-related, therefore this antioxidant enzyme could be a suitable candidate biomarker for diagnosis of OA. Mitochondrial haplogroups significantly correlates with serum levels of catalase

Estimating cooling production and monitoring efficiency in chillers using a soft sensor

[EN] Intensive use of heating, ventilation and air conditioning systems in buildings entails monitoring their efficiency. Moreover, cooling systems are key facilities in large buildings and can account up to 44% of the energy consumption. Therefore, monitoring efficiency in chillers is crucial and, for that reason, a sensor to measure the cooling production is required. However, manufacturers rarely install it in the chiller due to its cost. In this paper, we propose a methodology to build a soft sensor that provides an estimation of cooling production and enables monitoring the chiller efficiency. The proposed soft sensor uses independent variables (internal states of the chiller and electric power) and can take advantage of current or past observations of those independent variables. Six methods (from linear approaches to deep learning ones) are proposed to develop the model for the soft sensor, capturing relevant features on the structure of data (involving time, thermodynamic and electric variables and the number of refrigeration circuits). Our approach has been tested on two different chillers (large water-cooled and smaller air-cooled chillers) installed at the Hospital of León. The methods to implement the soft sensor are assessed according to three metrics (MAE, MAPE and R²). In addition to the comparison of methods, the results also include the estimation of cooling production (and the comparison of the true and estimated values) and monitoring the COP indicator for a period of several days and for both chillers.SIMinisterio de Ciencia e InnovaciónEuropean Regional Development Fun

Fully-Convolutional Denoising Auto-Encoders for NILM in Large Non-Residential Buildings

[EN] Great concern regarding energy efficiency has led the research community to develop approaches which enhance the energy awareness by means of insightful representations. An example of intuitive energy representation is the parts-based representation provided by Non-Intrusive Load Monitoring (NILM) techniques which decompose non-measured individual loads from a single total measurement of the installation, resulting in more detailed information about how the energy is spent along the electrical system. Although there are previous works that have achieved important results on NILM, the majority of the NILM systems were only validated in residential buildings, leaving a niche for the study of energy disaggregation in non-residential buildings, which present a specific behavior. In this paper, we suggest a novel fully-convolutional denoising auto-encoder architecture (FCN-dAE) as a convenient NILM system for large non-residential buildings, and it is compared, in terms of particular aspects of large buildings, to previous denoising auto-encoder approaches (dAE) using real electrical consumption from a hospital facility. Furthermore, by means of three use cases, we show that our approach provides extra helpful funcionalities for energy management tasks in large buildings, such as meter replacement, gap filling or novelty detection.SIThis work was supported by the Principado de Asturias Government through the Predoctoral Grant “Severo Ochoa.” Paper no. TSG-00737-202

A Deep Learning Approach for Fusing Sensor Data from Screw Compressors

[EN] Chillers are commonly used for thermal regulation to maintain indoor comfort in medium and large buildings. However, inefficiencies in this process produce significant losses, and optimization tasks are limited because of accessibility to the system. Data analysis techniques transform measurements coming from several sensors into useful information. Recent deep learning approaches have achieved excellent results in many applications. These techniques can be used for computing new data representations that provide comprehensive information from the device. This allows real-time monitoring, where information can be checked with current working operation to detect any type of anomaly in the process. In this work, a model based on a 1D convolutional neural network is proposed for fusing data in order to predict four different control stages of a screw compressor in a chiller. The evaluation of the method was performed using real data from a chiller in a hospital building. Results show a satisfactory performance and acceptable training time in comparison with other recent methods. In addition, the model is capable of predicting control states of other screw compressors different than the one used in the training. Furthermore, two failure cases are simulated, providing an early alarm detection when a continuous wrong classification is performed by the model.SIThis research was funded by the Spanish Ministry of Science and Innovation and the European Regional Development Fund under project DPI2015-69891-C2-1-R/2-R.Ministerio de Economía y Competitivida

Magnetic Gearboxes for Aerospace Applications

Magnetic gearboxes are contactless mechanisms for torque-speed conversion. They present no wear, no friction and no fatigue. They need no lubricant and can be customized for other mechanical properties as stiffness or damping. Additionally, they can protect structures and mechanisms against overloads, limitting the transmitted torque. In this work, spur, planetary and "magdrive" or "harmonic drive" configurations are compared considering their use in aerospace applications. The most recent test data are summarized to provide some useful help for the design engineer

Performance of Magnetic-Superconductor Non-Contact Harmonic Drive for Cryogenic Space Applications

Harmonic drives are profusely used in aerospace mainly because of their compactness and large reduction ratio. However, their use in cryogenic environments is still a challenge. Lubrication and fatigue are non-trivial issues under these conditions. The objective of the Magnetic-Superconductor Cryogenic Non-contact Harmonic Drive (MAGDRIVE) project, funded by the EU Space FP7, is to design, build, and test a new concept of MAGDRIVE. Non-contact interactions among magnets, soft magnetic materials, and superconductors are efficiently used to provide a high reduction ratio gear that smoothly and naturally operates at cryogenic environments. The limiting elements of conventional harmonic drives (teeth, flexspline, and ball bearings) are substituted by contactless mechanical components (magnetic gear and superconducting magnetic bearings). The absence of contact between moving parts prevents wear, lubricants are no longer required, and the operational lifetime is greatly increased. This is the first mechanical reducer in mechanical engineering history without any contact between moving parts. In this paper, the test results of a −1:20 inverse reduction ratio MAGDRIVE prototype are reported. In these tests, successful operation at 40 K and 10−3 Pa was demonstrated for more than 1.5 million input cycles. A maximum torque of 3 N·m and an efficiency of 80% were demonstrated. The maximum tested input speed was 3000 rpm, six times the previous existing record for harmonic drives at cryogenic temperature

Planning and community development: case studies

Planning and Comunity Development: Case Studies, presents the findings of the inter-university Seminar held on 28?29 July 2011 and organized by researchers from the Technical University of Madrid and the University of California, Berkeley, who were fortunate to have the presence of the renowned Professor John Friedmann. Professors, researchers and PhD students from our research groups presented their works as scientific communications that were enriched by the debate among the different researches who attended the Seminar. All of them appear in the picture below in front of the gate of Haviland Hall at UC Berkeley. This book analyses the concept of planning and its evolution so far, leading to the conceptualization of governance as an expression of the planning practice. It also studies the role of social capital and cooperation as tools for the community development. The conceptual analysis is complemented by the development of six case studies that put forward experiences of planning and community development carried out in diverse social and cultural contexts of Latin-America, Europe and North America. This publication comes after more than 20 years of work of the researchers that met at the seminar. Through their work in managing development initiatives, they have learned lessons and have contribute to shape their own body of teaching that develops and analyses the role of planning in public domain to promote community development. This knowledge is synthesized in the model Planning as Working With People, that shows that development is not effective unless is promoted in continuous collaboration with all the actors involved in the process

Applied diagnostics in liver cancer. Efficient combinations of sorafenib with targeted inhibitors blocking AKT/mTOR

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide. There is increasing interest in developing specific markers to serve as predictors of response to sorafenib and to guide targeted therapy. Using a sequencing platform designed to study somatic mutations in a selection of 112 genes (HepatoExome), we aimed to characterize lesions from HCC patients and cell lines, and to use the data to study the biological and mechanistic effects of case-specific targeted therapies used alone or in combination with sorafenib. We characterized 331 HCC cases in silico and 32 paired samples obtained prospectively from primary tumors of HCC patients. Each case was analyzed in a time compatible with the requirements of the clinic (within 15 days). In 53% of the discovery cohort cases, we detected unique mutational signatures, with up to 34% of them carrying mutated genes with the potential to guide therapy. In a panel of HCC cell lines, each characterized by a specific mutational signature, sorafenib elicited heterogeneous mechanistic and biological responses, whereas targeted therapy provoked the robust inhibition of cell proliferation and DNA synthesis along with the blockage of AKT/mTOR signaling. The combination of sorafenib with targeted therapies exhibited synergistic anti-HCC biological activity concomitantly with highly effective inhibition of MAPK and AKT/mTOR signaling. Thus, somatic mutations may lead to identify case-specific mechanisms of disease in HCC lesions arising from multiple etiologies. Moreover, targeted therapies guided by molecular characterization, used alone or in combination with sorafenib, can effectively block important HCC disease mechanisms.FUNDING: Grants from ISCIII, co-financed by the European Union (FEDER) (PI16/00156), Ramón and Cajal research program from MINECO (RYC-2013-14097) and FUNDACIÓN LUCHAMOS POR LA VIDA to JPV. Grants from ISCIII (RD06/0020/0107-RD012/0036/0060) to MAP. Grant from ISCIII (Ref. PIE15/00079) to JC & JPV. NGD is a recipient of a UC-IDIVAL pre-doctoral fellow. I.V. was also supported by the Ramón and Cajal research program

Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

A measurement of the cosmic-ray spectrum for energies exceeding $4{\times}10^{18}$ eV is presented, which is based on the analysis of showers with zenith angles greater than $60^{\circ}$ detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above $5.3{\times}10^{18}$ eV, the "ankle", the flux can be described by a power law $E^{-\gamma}$ with index $\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)}$ followed by a smooth suppression region. For the energy ($E_\text{s}$) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find $E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19}$ eV.Comment: Replaced with published version. Added journal reference and DO