Reducing cardiovascular risk (CVR) is the main focus of diabetes mellitus (DM) management nowadays. Complex pathogenic mechanisms that are the subject of this review lead to early and severe atherosclerosis in DM patients. Although it is not a cardiovascular disease equivalent at the moment of diagnosis, DM subjects are affected by numerous cardiovascular complications, such as acute coronary syndrome, stroke, or peripheral artery disease, as the disease duration increases. Therefore, early therapeutic intervention is mandatory and recent guidelines focus on intensive CVR factor management: hyperglycaemia, hypertension, and dyslipidaemia. Most important, the appearance of oral or injectable antidiabetic medication such as SGLT-2 inhibitors or GLP-1 agonists has proven that an antidiabetic drug not only reduces glycaemia, but also reduces CVR by complex mechanisms. A profound understanding of intimate mechanisms that generate atherosclerosis in DM and ways to inhibit or delay them are of the utmost importance in a society where cardiovascular morbidity and mortality are predominant.

No abstract

Escherichia wli ribosomes display a remarkable heterogeneity when submitted to polyacrylamide-gel electrophoresis (4O/, acrylamide). Both the 70-S ribosomes and 5 0 3 ribosomal subunits are resolved into a t least four and the 30-S ribosomal subunits into three particle subclasses.After reversal of the current, all particles refocus into one single band a t the origin. Ribosomes recovered from the gel after electrophoresis have retained some 40--100°/, of their capacity to synthesize peptide bonds. Their sedimentation behaviour has remained unaltered. Upon reelectrophoresis, no new peaks are detectable although the relative proportions of the various subclasses are frequently changed. The ratio in the occurrence of these subclasses is readily affected by a variety of factors, however, some of which are not directly related to the electrophoretic technique itself.The three classes of ribosomes and subunits (70-8, 5 0 3 and 30-S) display approximately equal electrophoretic mobilities when the sieving action is reduced to a minimum. This conclusion follows from experiments in which the ribosomes are submitted to electrophoresis in a sucrose gradient or in 0.4O/, agarose gels. I n contrast, electrophoresis in polyacrylamide gels with a gradient in pore size reveals the same ribosomal diversity as noted in gels with a fixed acrylamide concentration of 4O/,. I n these pore-gradient gels (3 -So/, acrylamide), the migration rate of each ribosomal subclass decreases continuously when the time of electrophoresis is prolonged. After about 30 h, further penetration seems to be blocked.All three classes consist of particles with low electrophoretic mobility (designated I particles) and those which move faster (designated I1 particles). The I particles are partially converted to I1 particles by incubation a t 37 "C and/or pelleting prior to elcctrophoresis. The I1 particles are converted to I particles upon raising the ribosome concentration. The electrophoretic profiles displayed by the various 50-S subclasses arc not strongly affected by variations in Mg2+ concentration in the range 0.5-10.0 mM. The electropherograms of 30-8 subunits become more diffuse when the Mg2+ concentration is raised. The possible occurrence of ribosomal dimers and/or conformation changes is discussed.Polyacrylamide-gel electrophoresis has proved to be a power-ful tool for fractionating various kinds of biologically important macromolecules like proteins [1,2], RNAs [3--51 and DNAs [el. Hjerten et al. [7] were the first to describe an electrophoretic separation of Escherichia coli ribosomal subunits in polyacrylamide gels. Later on, Dahlberg et al. [S] used composite gels of agarose and polyacrylamide to characterize bacterial polyribosornes, ribosomes and ribosomal subunits. Agarose can be omitted when only 70-S ribosomes and subunits are to be separated and we have used 40/, polyacrylamide gels to analyse ribosomal mixtures of E . coli after their interaction with the initiation factor IF-3 [9]. Dahlberg et al. [S] already noticed an unanti...

Despite the promising results obtained by deep learning methods in the field of medical image segmentation, lack of sufficient data always hinders performance to a certain degree. In this work, we explore the feasibility of applying deep learning methods on a pilot dataset. We present a simple and practical approach to perform segmentation in a 2D, slice-by-slice manner, based on region of interest (ROI) localization, applying an optimized training regime to improve segmentation performance from regions of interest. We start from two popular segmentation networks, the preferred model for medical segmentation, U-Net, and a general-purpose model, DeepLabV3+. Furthermore, we show that ensembling of these two fundamentally different architectures brings constant benefits by testing our approach on two different datasets, the publicly available ACDC challenge, and the imATFIB dataset from our in-house conducted clinical study. Results on the imATFIB dataset show that the proposed approach performs well with the provided training volumes, achieving an average Dice Similarity Coefficient of the whole heart of 89.89% on the validation set. Moreover, our algorithm achieved a mean Dice value of 91.87% on the ACDC validation, being comparable to the second best-performing approach on the challenge. Our approach provides an opportunity to serve as a building block of a computer-aided diagnostic system in a clinical setting.

No abstract

No abstract

No abstract

Aims: We aimed to compare cardiac volumes measured with echocardiography (echo) and cardiac magnetic resonance imaging (MRI) in a mixed cohort of healthy controls (controls) and patients with atrial fibrillation (AF). Materials and methods: In total, 123 subjects were included in our study; 99 full datasets were analyzed. All the participants underwent clinical evaluation, EKG, echo, and cardiac MRI acquisition. Participants with full clinical data were grouped into 63 AF patients and 36 controls for calculation of left atrial volume (LA Vol) and 51 AF patients and 30 controls for calculation of left ventricular end-diastolic volume (LV EDV), end-systolic volume (ESV), and LV ejection fraction (LV EF). Results: No significant differences in LA Vol were observed (p > 0.05) when measured by either echo or MRI. However, echo provided significantly lower values for left ventricular volume (p < 0.0001). The echo LA Vol of all the subjects correlated well with that measured by MRI (Spearmen correlation coefficient r = 0.83, p < 0.0001). When comparing the two methods, significant positive correlations of EDV (all subjects: r = 0.55; Controls: r = 0.71; and AF patients: r = 0.51) and ESV (all subjects: r = 0.62; Controls: r = 0.47; and AF patients: r = 0.66) were found, with a negative bias for values determined using echo. For a subgroup of participants with ventricular volumes smaller than 49.50 mL, this bias was missing, thus in this case echocardiography could be used as an alternative for MRI. Conclusion: Good correlation and reduced bias were observed for LA Vol and EF determined by echo as compared to cardiac MRI in a mixed cohort of patients with AF and healthy volunteers. For the determination of volume values below 49.50 mL, an excellent correlation was observed between values obtained using echo and MRI, with comparatively reduced bias for the volumes determined by echo. Therefore, in certain cases, echocardiography could be used as a less expensive, less time-consuming, and contraindication free alternative to MRI for cardiac volume determination.