Seminal plasma AnnexinA2 protein is a relevant biomarker for stallions which require removal of seminal plasma for sperm survival upon refrigeration†

Some stallions yield ejaculates that do not tolerate conservation by refrigeration prior to artificial insemination (AI), showing improvement after removal of most of the seminal plasma (SP) by centrifugation. In this study, the SP-proteome of 10 different stallions was defined through high-performance liquid chromatography with tandem mass spectrometry and bioinformatic analysis in relation to the ability of the ejaculates to maintain semen quality when cooled and stored at 5°C. Stallions were classified into three groups, depending on this ability: those maintaining good quality after direct extension in a commercial extender (good), stallions requiring removal of seminal plasma (RSP) to maintain seminal quality (good-RSP), and stallions, unable to maintain good semen quality even after RSP (poor). Pathway enrichment analysis of the proteins identified in whole equine SP using human orthologs was performed using g: profiler showing enriched Reactome and the Kyoto Encyclopedia of Genes and Genomes pathways related to hexose metabolism, vesicle mediated transport, post translational modification of proteins and immune response. Specific proteins overrepresented in stallions tolerating conservation by refrigeration included a peroxiredoxin-6 like protein, and transcobalamin-2, a primary vitamin B12-binding, and transport protein. Also, the protein involved in protein glycosylation, ST3 beta-galactoside alpha-2,3-sialyltransferase 1 was present in good stallions. These proteins were nearly absent in poor stallions. Particularly, annexinA2 appeared as to be the most powerful discriminant variable for identification of stallions needing RSP prior to refrigeration, with a P = 0.002 and a q value = 0.005. Overall this is the first detailed study of the equine SP-proteome, showing the potential value of specific proteins as discriminant bio-markers for clinical classification of stallions for AI.

Consumption of fibre rich foods

Foods such as fruit, vegetables, and cereals, and particularly whole grain, are rich in dietary fibre and have been proved to have multiple beneficial effects for the human health. The present research was designed to assess some eating practices related to fibre-rich foods in different countries, namely Argentina, Croatia, Hungary, Latvia, Portugal, and Romania. A cross-sectional descriptive study was undertaken on a sample of 4905 adult participants, obeying all ethical guidelines for this type of research. Regarding the data treatment, basic statistics was complemented with the tree classification analysis. Generally, the results show a low consumption of salads and vegetables, i.e., up to 11 servings/week (for 78.2% of participants), with Croatia in the lead (86.6%). Regarding fruit, a great majority of data also indicated low consumption (92.3%), most especially for Latvia (98.3%). The level of consumption of whole cereals was also low (72.6%), particularly for Latvia (90.0%). The tree classification analysis showed that while the first discriminant variable for the consumption of salads and vegetables was country, followed by education, for the consumption of fruit, it was country and then sex, and finally, for the consumption of whole cereals, it was sex and followed by country. The results allowed the conclusion that the consumption of foods rich in dietary fibre was very low for these countries, highlighting the necessity to implement strategies that incentivise the consumption of such foods, which are very important for a healthy diet.

Reading and Deafness: Eye Tracking in Deaf Readers with Different Linguistic Background

The aim of this study was to investigate, using an eye-tracking tool, the processes behind the exploration of written texts performed by deaf people with different language skills and different educational backgrounds. Our sample comprised 36 deaf participants (12 of whom use Italian sign language most of the time, 12 who use Italian only, and 12 who can use both languages) and 12 hearing participants who could not understand any sign language. This research shows how in respect of oculomotor movements the discriminant variable is linked to the different educational backgrounds and the reading habits of participants.

Separating dijet resonances using the color discriminant variable

Color-singlet and color-octet vector bosons predicted in theories beyond the Standard Model have the potential to be discovered as dijet resonances at the LHC. A color-singlet resonance that has leptophobic couplings needs further investigation to be distinguished from a color-octet one. In previous work, we introduced a method for discriminating between the two kinds of resonances when their couplings are flavor-universal, using measurements of the dijet resonance mass, total decay width and production cross-section. Here, we describe two extensions of that work. First, we broaden the method to the case where the vector resonances have flavor non-universal couplings, by incorporating measurements of the heavy-flavor decays of the resonance. Second, we apply the method to separating vector bosons from color-octet scalars and excited quarks.

Application of multivariate statistical methods in the assessment of mountain organic soil transformation in the central Sudetes

Summary In studies of organic soil degradation and transformation, alongside the conventional methods used in soil science, an increase in the importance of advanced statistical methods can be observed. In this study some multivariate statistical methods were applied in an investigation of organic soil transformation in the central Sudetes. Andrews curves, linear and kernel discriminant variable analysis and cluster analysis were used. The similarities among peatland soils and their layers were determined. It can be stated that the application of statistical methods in soil science research related to organic soil transformation is a valuable tool. The use of various statistical methods (such as Andrews curves, linear and kernel discriminant variables and cluster analysis) can with high probability confirm earlier laboratory or field observations. This is particularly justified in the case of organic soils derived from varied geobotanical peat materials, different types of peatlands and water supply types, which impact the primary properties of the soil.

Allocation of oaks to Kraft classes based on linear and nonlinear kernel discriminant variables

SummaryA method of discriminant variable determination was used to visualize the division of oak trees into Kraft classes. Usual discriminant variables and several types of kernel discriminant variables were studied. For this purpose the traits of oak (Quercus L.) trees, measured on standing trees, were used. These traits included height of tree, breast height diameter and crown projection area. The use of the Gaussian kernel and modified Gaussian kernel enabled the clearest division into Kraft classes. In particular, the latter method proved to be the most effective.