Diastolic function measurements and diagnostic consequences: a comparison of pulsed wave- and color-coded tissue Doppler imaging

Tissue Doppler imaging (TDI) plays an important role in assessing diastolic function using echocardiography. However, two different methods [pulsed wave (PW-TDI) and color-coded (CC-TDI)] are currently used. We aimed to compare both measurements. We included 114 patients that were referred to our echocardiography department for evaluation of diastolic left ventricular function. In these patients, we sequentially measured tissue velocities of basal lateral and septal myocardium of the left ventricle in an apical four-chamber view with both PW-TDI and CC-TDI. Our cohort consisted of a heterogeneous group of patients with and without a history of cardiac disease. Mean age of the patients was 52 +/- A 16.7 years, and 62% were males. We found a strong correlation between PW-TDI- and CC-TDI-derived myocardial velocities (r = 0.93; p = 0.001). However, E' (mean of lateral and septal) velocities measured with PW-TDI were consistently higher compared to CC-TDI values [PW-TDI E' 10.3 +/- A 3.9 (SD) cm/s vs. CC-TDI E' 7.7 +/- A 3.1 cm/s; p <0.001]. From these data, we calculated that the relation between E' measured with PW-TDI and CC-TDI can be described as: E' (PW-TDI) = 1.25 + 1.17 x E' (CC-TDI). Consequently, E/E' measured with PW-TDI was consistently lower compared with CC-TDI (9.1 +/- A 3.1 vs. 12.5 +/- A 5.7; p <0.001) From these data, we calculated that the relation between E/E' measured with PW-TDI and CC-TDI can be described as: E/E' (PW-TDI) = 2.13 + 0.56 x E/E' (CC-TDI). Despite a strong correlation, tissue velocities measured with PW-TDI will yield higher values as compared with CC-TDI. This should be taken into account when defining cut-off values for the evaluation of diastolic function

Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide

Evaluation of C-terminal Agrin Fragment as a marker of muscle wasting in patients after acute stroke during early rehabilitation.

BACKGROUND C-terminal Agrin Fragment (CAF) has been proposed as a novel biomarker for sarcopenia originating from the degeneration of the neuromuscular junctions. In patients with stroke muscle wasting is a common observation that predicts functional outcome. We aimed to evaluate agrin sub-fragment CAF22 as a marker of decreased muscle mass and physical performance in the early phase after acute stroke. METHODS Patients with acute ischaemic or haemorrhagic stroke (n = 123, mean age 70 ± 11 y, body mass index BMI 27.0 ± 4.9 kg/m(2)) admitted to inpatient rehabilitation were studied in comparison to 26 healthy controls of similar age and BMI. Functional assessments were performed at begin (23 ± 17 days post stroke) and at the end of the structured rehabilitation programme (49 ± 18 days post stroke) that included physical assessment, maximum hand grip strength, Rivermead motor assessment, and Barthel index. Body composition was assessed by bioelectrical impedance analysis (BIA). Serum levels of CAF22 were measured by ELISA. RESULTS CAF22 levels were elevated in stroke patients at admission (134.3 ± 52.3 pM) and showed incomplete recovery until discharge (118.2 ± 42.7 pM) compared to healthy controls (95.7 ± 31.8 pM, p < 0.001). Simple regression analyses revealed an association between CAF22 levels and parameters of physical performance, hand grip strength, and phase angle, a BIA derived measure of the muscle cellular integrity. Improvement of the handgrip strength of the paretic arm during rehabilitation was independently related to the recovery of CAF22 serum levels only in those patients who showed increased lean mass during the rehabilitation. CONCLUSIONS CAF22 serum profiles showed a dynamic elevation and recovery in the subacute phase after acute stroke. Further studies are needed to explore the potential of CAF22 as a serum marker to monitor the muscle status in patients after stroke

Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability

Deep Neural Network Attribution Methods for Leakage Analysis and Symmetric Key Recovery

Deep Neural Networks (DNNs) have recently received significant attention in the side-channel community due to their state-of-the-art performance in security testing of embedded systems. However, research on the subject mostly focused on techniques to improve the attack efficiency in terms of the number of traces required to extract secret parameters. What has not been investigated in detail is a constructive approach of DNNs as a tool to evaluate and improve the effectiveness of countermeasures against side-channel attacks. In this work, we try to close this gap by applying attribution methods that aim for interpreting DNN decisions, in order to identify leaking operations in cryptographic implementations. In particular, we investigate three different approaches that have been proposed for feature visualization in image classification tasks and compare them regarding their suitability to reveal Points of Interests (POIs) in side-channel traces. We show by experiments with three separate data sets that Layer-wise Relevance Propagation (LRP) proposed by Bach et al. provides the best result in most cases. Finally, we demonstrate that attribution can also serve as a powerful side-channel distinguisher in DNN-based attack setups

Genome Sequence Analyses of Pseudomonas savastanoi pv. glycinea and Subtractive Hybridization-Based Comparative Genomics with Nine Pseudomonads

Bacterial blight, caused by Pseudomonas savastanoi pv. glycinea (Psg), is a common disease of soybean. In an effort to compare a current field isolate with one isolated in the early 1960s, the genomes of two Psg strains, race 4 and B076, were sequenced using 454 pyrosequencing. The genomes of both Psg strains share more than 4,900 highly conserved genes, indicating very low genetic diversity between Psg genomes. Though conserved, genome rearrangements and recombination events occur commonly within the two Psg genomes. When compared to each other, 437 and 163 specific genes were identified in B076 and race 4, respectively. Most specific genes are plasmid-borne, indicating that acquisition and maintenance of plasmids may represent a major mechanism to change the genetic composition of the genome and even acquire new virulence factors. Type three secretion gene clusters of Psg strains are near identical with that of P. savastanoi pv. phaseolicola (Pph) strain 1448A and they shared 20 common effector genes. Furthermore, the coronatine biosynthetic cluster is present on a large plasmid in strain B076, but not in race 4. In silico subtractive hybridization-based comparative genomic analyses with nine sequenced phytopathogenic pseudomonads identified dozens of specific islands (SIs), and revealed that the genomes of Psg strains are more similar to those belonging to the same genomospecies such as Pph 1448A than to other phytopathogenic pseudomonads. The number of highly conserved genes (core genome) among them decreased dramatically when more genomes were included in the subtraction, suggesting the diversification of pseudomonads, and further indicating the genome heterogeneity among pseudomonads. However, the number of specific genes did not change significantly, suggesting these genes are indeed specific in Psg genomes. These results reinforce the idea of a species complex of P. syringae and support the reclassification of P. syringae into different species

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets

Impact of renal impairment on atrial fibrillation: ESC-EHRA EORP-AF Long-Term General Registry

Background: Atrial fibrillation (AF) and renal impairment share a bidirectional relationship with important pathophysiological interactions. We evaluated the impact of renal impairment in a contemporary cohort of patients with AF. Methods: We utilised the ESC-EHRA EORP-AF Long-Term General Registry. Outcomes were analysed according to renal function by CKD-EPI equation. The primary endpoint was a composite of thromboembolism, major bleeding, acute coronary syndrome and all-cause death. Secondary endpoints were each of these separately including ischaemic stroke, haemorrhagic event, intracranial haemorrhage, cardiovascular death and hospital admission. Results: A total of 9306 patients were included. The distribution of patients with no, mild, moderate and severe renal impairment at baseline were 16.9%, 49.3%, 30% and 3.8%, respectively. AF patients with impaired renal function were older, more likely to be females, had worse cardiac imaging parameters and multiple comorbidities. Among patients with an indication for anticoagulation, prescription of these agents was reduced in those with severe renal impairment, p&nbsp;&lt;.001. Over 24&nbsp;months, impaired renal function was associated with significantly greater incidence of the primary composite outcome and all secondary outcomes. Multivariable Cox regression analysis demonstrated an inverse relationship between eGFR and the primary outcome (HR 1.07 [95% CI, 1.01–1.14] per 10&nbsp;ml/min/1.73&nbsp;m2 decrease), that was most notable in patients with eGFR &lt;30&nbsp;ml/min/1.73&nbsp;m2 (HR 2.21 [95% CI, 1.23–3.99] compared to eGFR ≥90&nbsp;ml/min/1.73&nbsp;m2). Conclusion: A significant proportion of patients with AF suffer from concomitant renal impairment which impacts their overall management. Furthermore, renal impairment is an independent predictor of major adverse events including thromboembolism, major bleeding, acute coronary syndrome and all-cause death in patients with AF