Error de inclinación paleomagnética en materiales aluviales del Oligoceno superior del sector Suroriental de la Cuenca del Ebro (Región Surpirenaica, NE de España)

Alluvial red-beds of two Oligocene succesions in the Southeastem Ebro Basin (Southem Pyrenean foreland, NE Spain) show inclination shallowing, taking into account the reference Oligocene palaeolatitude expected for this region. This fact is interpreted to reflect an inclination error due to either these factors: hydrodynamic control of magnetic particles in the depositional environment, differential compaction of sediment during burial and tectonic deformation. The studied lithofacies are split into five groups: gray sandstones, red sandstones, red siltstones, red mudstones and limestones. A strong positive correlation between the relative amount of phyllosilicates and the magnitude of the inclination error has been established. Lithofacies with low percentage of phyllosilicates (limestones and gray sandstones) display a statistically not significant error of 5" with respect to the magnetic palaeofield inclination, whereas the sediments with a higher phyllosilicate content (siltstones and mudstones) show significant errors of up to 25". This observation has not a major consequence for the interpretation of the magnetic polarity but is crucial for palaeogeographic and palinspastic reconstmctions based on palaeolatitudinal data. The obtained results in this study highlight that the interpretation of paleolatitude based on paleomagnetic data is sometimes not straightfonvard and it requires a detailed evaluation of the rock magnetic parameters (AMS in particular) to reveal the presence of such inclination deflection

Ensemble of feature extraction methods to improve the structural damage classification in a wind turbine foundation

The condition monitoring of offshore wind power plants is an important topic that remains open. This monitoring aims to lower the maintenance cost of these plants. One of the main components of the wind power plant is the wind turbine foundation. This study describes a data-driven structural damage classification methodology applied in a wind turbine foundation. A vibration response was captured in the structure using an accelerometer network. After arranging the obtained data, a feature vector of 58 008 features was obtained. An ensemble approach of feature extraction methods was applied to obtain a new set of features. Principal Component Analysis (PCA) and Laplacian eigenmaps were used as dimensionality reduction methods, each one separately. The union of these new features is used to create a reduced feature matrix. The reduced feature matrix is used as input to train an Extreme Gradient Boosting (XGBoost) machine learning-based classification model. Four different damage scenarios were applied in the structure. Therefore, considering the healthy structure, there were 5 classes in total that were correctly classified. Five-fold cross validation is used to obtain a final classification accuracy. As a result, 100% of classification accuracy was obtained after applying the developed damage classification methodology in a wind-turbine offshore jacket-type foundation benchmark structure

Proteomic Analysis of Polypeptides Captured from Blood during Extracorporeal Albumin Dialysis in Patients with Cholestasis and Resistant Pruritus

Albumin dialysis using the molecular adsorbent recirculating system (MARS) is a new therapeutic approach for liver diseases. To gain insight into the mechanisms involved in albumin dialysis, we analyzed the peptides and proteins absorbed into the MARS strong anion exchange (SAX) cartridges as a result of the treatment of patients with cholestasis and resistant pruritus. Proteins extracted from the SAX MARS cartridges after patient treatment were digested with two enzymes. The resulting peptides were analyzed by multidimensional liquid chromatography coupled to tandem mass spectrometry. We identified over 1,500 peptide sequences corresponding to 144 proteins. In addition to the proteins that are present in control albumin-derived samples, this collection includes 60 proteins that were specific to samples obtained after patient treatment. Five of these proteins (neutrophil defensin 1 [HNP-1], secreted Ly-6/uPAR-related protein 1 [SLURP1], serum amyloid A, fibrinogen alpha chain and pancreatic prohormone) were confirmed to be removed by the dialysis procedure using targeted selected-reaction monitoring MS/MS. Furthermore, capture of HNP-1 and SLURP1 was also validated by Western blot. Interestingly, further analyses of SLURP1 in serum indicated that this protein was 3-fold higher in cholestatic patients than in controls. Proteins captured by MARS share certain structural and biological characteristics, and some of them have important biological functions. Therefore, their removal could be related either to therapeutic or possible adverse effects associated with albumin dialysis

Identification of a novel polyfluorinated compound as a lead to inhibit human enzymes aldose reductase and AKR1B10 : structure determination of both ternary complexes and implications for drug design

Aldo-keto reductases (AKRs) are mostly monomeric enzymes which fold into a highly conserved ([alpha]/[beta])8 barrel, while their substrate specificity and inhibitor selectivity are determined by interaction with residues located in three highly variable external loops. The closely related human enzymes aldose reductase (AR or AKR1B1) and AKR1B10 are of biomedical interest because of their involvement in secondary diabetic complications (AR) and in cancer, e.g. hepatocellular carcinoma and smoking-related lung cancer (AKR1B10). After characterization of the IC50 values of both AKRs with a series of polyhalogenated compounds, 2,2',3,3',5,5',6,6'-octafluoro-4,4'-biphenyldiol (JF0064) was identified as a lead inhibitor of both enzymes with a new scaffold (a 1,1'-biphenyl-4,4'-diol). An ultrahigh-resolution X-ray structure of the AR-­NADP+-JF0064 complex has been determined at 0.85 Å resolution, allowing it to be observed that JF0064 interacts with the catalytic residue Tyr48 through a negatively charged hydroxyl group (i.e. the acidic phenol). The non-competitive inhibition pattern observed for JF0064 with both enzymes suggests that this acidic hydroxyl group is also present in the case of AKR1B10. Moreover, the combination of surface lysine methylation and the introduction of K125R and V301L mutations enabled the determination of the X-ray crystallo­graphic structure of the corresponding AKR1B10-NADP+-JF0064 complex. Comparison of the two structures has unveiled some important hints for subsequent structure-based drug-design efforts