Selection of strawberry cultivars with tolerance to Tetranychus urticae (Acari: Tetranychidae) and high yield under different managements.

Tetranychus urticae Koch (Acari: Tetranychidae) is considered the main pest of strawberry. Several factors can favor its development, among them the genotype susceptibility and cropping system. The aims of this study were to evaluate the agronomic performance of strawberry cultivars under different managements and to identify strawberry cultivars that meet tolerance to T. urticae and high fruit yield. Thirteen cultivars of strawberry ('Albion', 'Aleluia', 'Aromas', 'Camarosa', 'Camino Real', 'Campinas', 'Diamante', 'Dover', 'Festival', 'Seascape', 'Toyonoka', 'Tudla', and 'Ventana') under three managements (open field, low tunnel, and high tunnel) were evaluated. The T. urticae attack to different cultivars was influenced by managements, being low tunnel the one that provided higher infestations in the most evaluated cultivars. 'Camarosa' was the cultivar with the lower incidence of pest and 'Dover' had the higher infestation. The genotype most suitable for growing under different managements is the 'Festival' genotype, since it meets tolerance to T. urticae, high fruit yield, and phenotypic stability

Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume

The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer’s Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer’s disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Dibenzofuran-induced mitochondrial dysfunction: Interaction with ANT carrier

Exposure to environmental pollutants such as dibenzofurans and furans is linked to the pathophysiology of several diseases. Dibenzofuran (DBF) is listed as a pollutant of concern due to its persistence in the environment, bioaccumulation and toxicity to humans, being associated with the development of lung diseases and cancers, due to its extremely toxic properties such as carcinogenic and teratogenic. Mitochondria play a key role in cellular homeostasis and keeping a proper energy supply for eukaryotic cells is essential in the fulfillment of the tissues energy-demand. Therefore, interference with mitochondrial function leads to cell death and organ failure. In this work, the effects of DBF on isolated rat liver mitochondria were analyzed. DBF exposure caused a markedly increase in the lag phase that follows depolarization induced by ADP, indicating an effect in the phosphorylative system. This was associated with a dose-dependent decrease in ATPase activity. Moreover, DBF also increased the threshold to the induction of the mitochondrial permeability transition (MPT) by calcium. Pretreatment of mitochondria with DBF also increased the concentration of carboxyatractyloside (CAT) necessary to abolish ADP phosphorylation and to induce the MPT, suggesting that DBF may interfere with mitochondria through an effect on the adenine nucleotide translocase (ANT). By co-immunoprecipitating ANT and Cyclophilin D (CypD) following MPT induction, we observed that in the presence of DBF, the ratio CypD/ANT was decreased. This demonstrates that DBF interferes with the ANT and so prevents CypD binding to the ANT, causing decreased phosphorylative capacity and inhibiting the MPT, which is also reflected by an increase in calcium retention capacity. Clarifying the role of pollutants in some mechanisms of toxicity, such as unbalance of bioenergetics status and mitochondrial function, may help to explain the progressive and chronic evolution of diseases derived from exposure to environmental pollutants.This work was supported by Fundação para a Ciência e a Tecnologia, Portugal (grant SFRH/BD/38372/2007 to FVD, grant SFRH/BD/ 44674/2008 to APG, grant SFRH/BD/38467/2007 to JST and grant SFRH/BD/44796/2008 to ATV)

The SAMI galaxy survey: Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model

We present a novel Bayesian method, referred to as BLOBBY3D, to infer gas kinematics that mitigates the effects of beam smearing for observations using integral field spectroscopy. The method is robust for regularly rotating galaxies despite substructure in the gas distribution. Modelling the gas substructure within the disc is achieved by using a hierarchical Gaussian mixture model. To account for beam smearing effects, we construct a modelled cube that is then convolved per wavelength slice by the seeing, before calculating the likelihood function. We show that our method can model complex gas substructure including clumps and spiral arms. We also show that kinematic asymmetries can be observed after beam smearing for regularly rotating galaxies with asymmetries only introduced in the spatial distribution of the gas. We present findings for our method applied to a sample of 20 star-forming galaxies from the SAMI Galaxy Survey. We estimate the global H α gas velocity dispersion for our sample to be in the range σ¯v ∼[7, 30] km s−1. The relative difference between our approach and estimates using the single Gaussian component fits per spaxel is σ¯v/σ¯v = −0.29 ± 0.18 for the H α flux-weighted mean velocity dispersion