Atrial Arrhythmia in Ageing Spontaneously Hypertensive Rats: Unraveling the Substrate in Hypertension and Ageing

Background

Both ageing and hypertension are known risk factors for atrial fibrillation (AF) although the pathophysiological contribution or interaction of the individual factors remains poorly understood. Here we aim to delineate the arrhythmogenic atrial substrate in mature spontaneously hypertensive rats (SHR).

Methods

SHR were studied at 12 and 15 months of age (n = 8 per group) together with equal numbers of age-matched normotensive Wistar-Kyoto control rats (WKY). Electrophysiologic study was performed on superfused isolated right and left atrial preparations using a custom built high-density multiple-electrode array to determine effective refractory periods (ERP), atrial conduction and atrial arrhythmia inducibility. Tissue specimens were harvested for structural analysis.

Results

Compared to WKY controls, the SHR demonstrated: Higher systolic blood pressure (p<0.0001), bi-atrial enlargement (p<0.05), bi-ventricular hypertrophy (p<0.05), lower atrial ERP (p = 0.008), increased atrial conduction heterogeneity (p = 0.001) and increased atrial interstitial fibrosis (p = 0.006) & CD68-positive macrophages infiltration (p<0.0001). These changes resulted in higher atrial arrhythmia inducibility (p = 0.01) and longer induced AF episodes (p = 0.02) in 15-month old SHR. Ageing contributed to incremental bi-atrial hypertrophy (p<0.01) and atrial conduction heterogeneity (p<0.01) without affecting atrial ERP, fibrosis and arrhythmia inducibility. The limited effect of ageing on the atrial substrate may be secondary to the reduction in CD68-positive macrophages.

Conclusions

Significant atrial electrical and structural remodeling is evident in the ageing spontaneously hypertensive rat atria. Concomitant hypertension appears to play a greater pathophysiological role than ageing despite their compounding effect on the atrial substrate. Inflammation is pathophysiologically linked to the pro-fibrotic changes in the hypertensive atria.     

Decoding the mechanisms of gait generation in salamanders by combining neurobiology, modeling and robotics

Vertebrate animals exhibit impressive locomotor skills. These locomotor skills are due to the complex interactions between the environment, the musculo-skeletal system and the central nervous system, in particular the spinal locomotor circuits. We are interested in decoding these interactions in the salamander, a key animal from an evolutionary point of view. It exhibits both swimming and stepping gaits and is faced with the problem of producing efficient propulsive forces using the same musculo-skeletal system in two environments with significant physical differences in density, viscosity and gravitational load. Yet its nervous system remains comparatively simple. Our approach is based on a combination of neurophysiological experiments, numerical modeling at different levels of abstraction, and robotic validation using an amphibious salamander-like robot. This article reviews the current state of our knowledge on salamander locomotion control, and presents how our approach has allowed us to obtain a first conceptual model of the salamander spinal locomotor networks. The model suggests that the salamander locomotor circuit can be seen as a lamprey-like circuit controlling axial movements of the trunk and tail, extended by specialized oscillatory centers controlling limb movements. The interplay between the two types of circuits determines the mode of locomotion under the influence of sensory feedback and descending drive, with stepping gaits at low drive, and swimming at high drive.     

Effete,a Drosophila Chromatin-Associated Ubiquitin-Conjugating Enzyme That Affects Telomeric and Heterochromatic Position Effect Variegation

Drosophila telomeres are elongated by the transposition of telomere-specific retrotransposons rather than telomerase activity. Proximal to the terminal transposon array, Drosophila chromosomes contain several kilobases of a complex satellite DNA termed telomere-associated sequences (TASs). Reporter genes inserted into or next to the TAS are silenced through a mechanism called telomere position effect (TPE). TPE is reminiscent of the position effect variegation (PEV) induced by Drosophila constitutive heterochromatin. However, most genes that modulate PEV have no effect on TPE, and systematic searches for TPE modifiers have so far identified only a few dominant suppressors. Surprisingly, only a few of the genes required to prevent telomere fusion have been tested for their effect on TPE. Here, we show that with the exception of the effete (eff; also called UbcD1) mutant alleles, none of the tested mutations at the other telomere fusion genes affects TPE. We also found that mutations in eff, which encodes a class I ubiquitin-conjugating enzyme, act as suppressors of PEV. Thus, eff is one of the rare genes that can modulate both TPE and PEV. Immunolocalization experiments showed that Eff is a major constituent of polytene chromosomes. Eff is enriched at several euchromatic bands and interbands, the TAS regions, and the chromocenter. Our results suggest that Eff associates with different types of chromatin affecting their abilities to regulate gene expression.     

Molecular phylogeny of Harpactorinae and Bactrodinae uncovers complex evolution of sticky trap predation in assassin bugs (Heteroptera: Reduviidae)

Sticky trap predation, the use of adhesive substances to trap and capture prey, is an intriguing yet poorly studied predatory strategy. Unique among known sticky trap predators, assassin bugs (Reduviidae) have evolved both exogenous and endogenous sticky trap predatory mechanisms: some trap their prey with sticky plant resins, some scavenge insects entrapped by sticky plant trichomes and others self‐produce sticky secretions. The evolution of these different strategies in assassin bugs is poorly understood due to the lack of comprehensive phylogenies. We reconstruct a phylogeny of Reduviidae (141 taxa; > 5000 bp) focusing on the Harpactorinae and Bactrodinae that engage in sticky trap predation. Ancestral state reconstruction, and temporal and geographical divergence analyses show that sticky trap predation techniques in assassin bugs evolved at least seven times independently since the late Cretaceous: use of sticky plant trichomes evolved as many as four times, resin‐use twice independently and once as a transition from trichome use, and ‘self‐stickiness’ once. Exogenous and endogenous sticky traps first appeared in the Neotropics, with the two exogenous mechanisms (resin and trichome use) subsequently evolving independently in the Old World. This study illustrates, for the first time, the complex evolutionary pattern of sticky trap predation within assassin bugs.     

Use of cell cultures in vitro to assess the uptake of long dsRNA in plant cells

In Vitro Cellular & Developmental Biology - Plant - While RNAi approaches based on transgenic plants overexpressing double-stranded RNAs (dsRNAs) have yielded a number of genetically modified...     

The Barnes Maze Task Reveals Specific Impairment of Spatial Learning Strategy in the Intrahippocampal Kainic Acid Model for Temporal Lobe Epilepsy

Neurochemical Research - Temporal lobe epilepsy (TLE) is an acquired form of focal epilepsy, in which patients not only suffer from unprovoked, devastating seizures, but also from severe...     

Rational antibiotic design: in silico structural comparison of the functional cavities of penicillin-binding proteins and ß-lactamases

The class of ß-lactam antibiotics has proven highly efficient in targeting bacterial penicillin-binding proteins (PBP) leading to the blocking of the bacterial cell wall synthesis. However, the benefit of these drugs is limited because of bacterial resistance mechanisms; the most widespread resistance involves ß-lactamase enzymes (ßLACT) that inactivate ß-lactam-based molecules. We focused on PBPs and ßLACTs from enterobacteria, and performed a detailed in silico study of PBPs whose inactivation is lethal for the bacteria and of ßLACTs that have a PBP-type catalytic mechanism. The comparison of the sequences and structures of PBPs and ßLACTs shows an almost perfect conservation of the catalytic site, and a high spatial resemblance of the whole functional cavity despite a very low overall sequence identity. Some notable differences in the functional cavity were observed in the vicinity of the catalytic site: four tyrosines are well conserved in the PBPs, whereas the residues occurring at equivalent positions in the ßLACT families present other physicochemical properties. These tyrosines are thus good candidates to be targeted in designing new antibiotic molecules with increased affinity and specificity for PBPs, with the goal of overcoming drug resistance. Our analysis also identified residues that have similar characteristics in most ßLACT families and different properties in PBPs; these are interesting targets for new ligands that specifically inhibit ßLACT proteins. The in silico approach presented here can be extended to other protein systems in view of guiding and improving rational drug design.     

In vitro machine learning-based CAR T immunological synapse quality measurements correlate with patient clinical outcomes

The human immune system consists of a highly intelligent network of billions of independent, self-organized cells that interact with each other. Machine learning (ML) is an artificial intelligence (AI) tool that automatically processes huge amounts of image data. Immunotherapies have revolutionized the treatment of blood cancer. Specifically, one such therapy involves engineering immune cells to express chimeric antigen receptors (CAR), which combine tumor antigen specificity with immune cell activation in a single receptor. To improve their efficacy and expand their applicability to solid tumors, scientists optimize different CARs with different modifications. However, predicting and ranking the efficacy of different "off-the-shelf" immune products (e.g., CAR or Bispecific T-cell Engager [BiTE]) and selection of clinical responders are challenging in clinical practice. Meanwhile, identifying the optimal CAR construct for a researcher to further develop a potential clinical application is limited by the current, time-consuming, costly, and labor-intensive conventional tools used to evaluate efficacy. Particularly, more than 30 years of immunological synapse (IS) research data demonstrate that T cell efficacy is not only controlled by the specificity and avidity of the tumor antigen and T cell interaction, but also it depends on a collective process, involving multiple adhesion and regulatory molecules, as well as tumor microenvironment, spatially and temporally organized at the IS formed by cytotoxic T lymphocytes (CTL) and natural killer (NK) cells. The optimal function of cytotoxic lymphocytes (including CTL and NK) depends on IS quality. Recognizing the inadequacy of conventional tools and the importance of IS in immune cell functions, we investigate a new strategy for assessing CAR-T efficacy by quantifying CAR IS quality using the glass-support planar lipid bilayer system combined with ML-based data analysis. Previous studies in our group show that CAR-T IS quality correlates with antitumor activities in vitro and in vivo. However, current manually quantified IS quality data analysis is time-consuming and labor-intensive with low accuracy, reproducibility, and repeatability. In this study, we develop a novel ML-based method to quantify thousands of CAR cell IS images with enhanced accuracy and speed. Specifically, we used artificial neural networks (ANN) to incorporate object detection into segmentation. The proposed ANN model extracts the most useful information to differentiate different IS datasets. The network output is flexible and produces bounding boxes, instance segmentation, contour outlines (borders), intensities of the borders, and segmentations without borders. Based on requirements, one or a combination of this information is used in statistical analysis. The ML-based automated algorithm quantified CAR-T IS data correlates with the clinical responder and non-responder treated with Kappa-CAR-T cells directly from patients. The results suggest that CAR cell IS quality can be used as a potential composite biomarker and correlates with antitumor activities in patients, which is sufficiently discriminative to further test the CAR IS quality as a clinical biomarker to predict response to CAR immunotherapy in cancer. For translational research, the method developed here can also provide guidelines for designing and optimizing numerous CAR constructs for potential clinical development.Trial Registration: ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00881920","term_id":"NCT00881920"}}NCT00881920.