Oral Anticoagulation in Patients with Chronic Kidney Disease and Non-Valvular Atrial Fibrillation: The FAERC Study.

Atrial fibrillation (AF) is the most common arrhythmia in patients with chronic kidney disease (CKD), and its presence is associated with a higher risk of stroke and mortality. MATERIAL AND METHODS: The FAERC study performed a retrospective multicentre analysis of historical cohorts in which data were collected from arrhythmia diagnosis onwards. RESULTS: We analysed a Spanish cohort of 4749 patients with CKD (mean eGFR 33.9 mL/min) followed up in the nephrology clinic, observing a 12.2% prevalence of non-valvular AF. In total, 98.6% of these patients were receiving anticoagulant treatment, mainly with coumarins (79.7%). Using direct-acting oral anticoagulants (DOACs) was associated with fewer cerebrovascular events than using acenocoumarol, but in contrast with other studies, we could not corroborate the association of risk of bleeding, coronary events, or death with a type of anticoagulant prescribed. CONCLUSIONS: Atrial fibrillation is highly prevalent in renal patients. Direct-acting anticoagulants seem to be associated with fewer ischemic-embolic complications, with no differences in bleeding, coronary events, or mortality rates.

Host-Pathogen Interactions in Leaf Petioles of Common Ash and Manchurian Ash Infected with Hymenoscyphus fraxineus.

Some common ash trees (Fraxinus excelsior) show tolerance towards shoot dieback caused by the invasive ascomycete Hymenoscyphus fraxineus. Leaf petioles are considered to serve as a pathogen colonization route to the shoots. We compared four common ash clones with variation in disease tolerance, and included the native host, Manchurian ash (Fraxinus mandshurica), as a reference. Tissue colonization, following rachis inoculation by H. fraxineus, was monitored by histochemical observations and a quantitative polymerase chain reaction (qPCR) assay specific to H. fraxineus. Axial spread of the pathogen towards the petiole base occurred primarily within the phloem and parenchyma, tissues rich in starch in healthy petioles. In inoculated petioles, a high content of phenolics surrounded the hyphae, presumably a host defense response. There was a relationship between field performance and susceptibility to leaf infection in three of the four studied common ash clones, i.e., good field performance was associated with a low petiole colonization level and vice versa. Low susceptibility to leaf infection may counteract leaf-to-shoot spread of the pathogen in common ash, but the limited number of clones studied warrants caution and a larger study. The Manchurian ash clone had the highest petiole colonization level, which may suggest that this native host has evolved additional mechanisms to avoid shoot infection.

Defensive strategies of Norway spruce and Kurile larch heartwood elucidated on the micron-level.

To decarbonize the building sector, the use of durable wood materials must be increased. Inspiration for environmentally benign wood protection systems is sought in durable tree species depositing phenolic extractives in their heartwood. Based on the hypothesis that the micro-distribution of extractives influences durability, we compared the natural impregnation patterns of non-durable, but readily available Norway spruce to more durable Kurile larch by mapping the distribution of heartwood extractives with Confocal Raman Imaging and multivariate data decomposition. Phenolics of both species were associated with hydrophobic oleoresin, likely facilitating diffusion through the tissue. They accumulated preferentially in lignin-rich sub-compartments of the cell wall. Yet, the distribution of extractives was found not to be the same. The middle lamellae contained flavonoids in larch and aromatic waxes in spruce, which was also found in rays and epithelial cells. Spruce-lignans were tentatively identified in all cell types, while larch-flavonoids were not present in resin channels, hinting at a different origin of synthesis. Larch-oleoresin without flavonoids was only found in lumina, indicating that the presence of phenolics in the mixture influences the final destination. Together our findings suggest, that spruce heartwood-defense focuses on water regulation, while the more efficient larch strategy is based on antioxidants.

Understanding the Formation of Heartwood in Larch Using Synchrotron Infrared Imaging Combined With Multivariate Analysis and Atomic Force Microscope Infrared Spectroscopy.

Formation of extractive-rich heartwood is a process in live trees that make them and the wood obtained from them more resistant to fungal degradation. Despite the importance of this natural mechanism, little is known about the deposition pathways and cellular level distribution of extractives. Here we follow heartwood formation in Larix gmelinii var. Japonica by use of synchrotron infrared images analyzed by the unmixing method Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS). A subset of the specimens was also analyzed using atomic force microscopy infrared spectroscopy. The main spectral changes observed in the transition zone when going from sapwood to heartwood was a decrease in the intensity of a peak at approximately 1660 cm-1 and an increase in a peak at approximately 1640 cm-1. There are several possible interpretations of this observation. One possibility that is supported by the MCR-ALS unmixing is that heartwood formation in larch is a type II or Juglans-type of heartwood formation, where phenolic precursors to extractives accumulate in the sapwood rays. They are then oxidized and/or condensed in the transition zone and spread to the neighboring cells in the heartwood.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis. In this work, a special variant of the unmixing algorithm Multivariate Curve Resolution Alternating Least Squares (MCR-ALS) for incomplete multisets is proposed to provide a solution for this kind of problem. This algorithm allows analyzing simultaneously images collected with different spectroscopic platforms without losing spatial resolution and ensuring spatial coherence among the images treated. The incomplete multiset structure concatenates images of the two platforms at the lowest spatial resolution with the image acquired with the highest spatial resolution. As a result, the constituents of the sample analyzed are defined by a single set of distribution maps, common to all platforms used and with the highest spatial resolution, and their related extended spectral signatures, covering the signals provided by each of the fused techniques. We demonstrate the potential of the new variant of MCR-ALS for multitechnique analysis on three case studies: (i) a model example of MIR and Raman images of pharmaceutical mixture, (ii) FT-IR and Raman images of palatine tonsil tissue, and (iii) mass spectrometry and Raman images of bean tissue.

Application of a sparseness constraint in multivariate curve resolution - Alternating least squares.

The use of sparseness in chemometrics is a concept that has increased in popularity. The advantage is, above all, a better interpretability of the results obtained. In this work, sparseness is implemented as a constraint in multivariate curve resolution - alternating least squares (MCR-ALS), which aims at reproducing raw (mixed) data by a bilinear model of chemically meaningful profiles. In many cases, the mixed raw data analyzed are not sparse by nature, but their decomposition profiles can be, as it is the case in some instrumental responses, such as mass spectra, or in concentration profiles linked to scattered distribution maps of powdered samples in hyperspectral images. To induce sparseness in the constrained profiles, one-dimensional and/or two-dimensional numerical arrays can be fitted using a basis of Gaussian functions with a penalty on the coefficients. In this work, a least squares regression framework with L0-norm penalty is applied. This L0-norm penalty constrains the number of non-null coefficients in the fit of the array constrained without having an a priori on the number and their positions. It has been shown that the sparseness constraint induces the suppression of values linked to uninformative channels and noise in MS spectra and improves the location of scattered compounds in distribution maps, resulting in a better interpretability of the constrained profiles. An additional benefit of the sparseness constraint is a lower ambiguity in the bilinear model, since the major presence of null coefficients in the constrained profiles also helps to limit the solutions for the profiles in the counterpart matrix of the MCR bilinear model.