Mcclearyconley9330

While necroptosis has been shown to contribute to the pathogenesis of post-infarction heart failure (HF), the role of autophagy remains unclear. Likewise, linkage between these two cell death modalities has not been sufficiently investigated. HF was induced by 60-min left coronary occlusion in adult Wistar rats and heart function was assessed 6 weeks later followed by immunoblotting analysis of necroptotic and autophagic proteins in both the left (LV) and right ventricle (RV). HF had no effect on RIP1 and RIP3 expression. PhosphoSer229-RIP3, acting as a pro-necroptotic signal, was increased in LV while deceased in RV of failing hearts. Total MLKL was elevated in RV only. Decrease in pSer555-ULK1, increase in pSer473-Akt and no significant elevation in beclin-1 and LC3-II/I ratio indicated rather a lowered rate of autophagy in LV. No beclin-1 upregulation and decreased LC3 processing also suggested the inhibition of both autophagosome formation and maturation in RV of failing hearts. In contrast, p89 PARP1 fragment, a marker of executed apoptosis, was increased in RV only. This is the first study showing a different signaling in ventricles of the late phase of post-infarction HF, highlighting necroptosis itself rather than its linkage with autophagy in LV, and apoptosis in RV.Building operation data are important for monitoring, analysis, modeling, and control of building energy systems. However, missing data is one of the major data quality issues, making data imputation techniques become increasingly important. There are two key research gaps for missing sensor data imputation in buildings the lack of customized and automated imputation methodology, and the difficulty of the validation of data imputation methods. In this paper, a framework is developed to address these two gaps. First, a validation data generation module is developed based on pattern recognition to create a validation dataset to quantify the performance of data imputation methods. Second, a pool of data imputation methods is tested under the validation dataset to find an optimal single imputation method for each sensor, which is termed as an ensemble method. The method can reflect the specific mechanism and randomness of missing data from each sensor. The effectiveness of the framework is demonstrated by 18 sensors from a real campus building. The overall accuracy of data imputation for those sensors improves by 18.2% on average compared with the best single data imputation method.Ample studies have shown the use of nanofluidics in the ionic diode and osmotic power generation, but similar ionic devices performed with large-sized mesopores are still poorly understood. In this study, we model and realize the mesoscale ionic diode and osmotic power generator, composed of an asymmetric cone-shaped mesopore with its narrow opening filled with a polyelectrolyte (PE) layer with high space charges. We show that, only when the space charge density of a PE layer is sufficiently large (>1×106C/m3), the considered mesopore system is able to create an asymmetric ionic distributions in the pore and then rectify ionic current. As a result, the output osmotic power performance can be improved when the filled PE carries sufficiently high space charges. For example, the considered PE-filled mesopore system can show an amplification of the osmotic power of up to 35.1-fold, compared to the bare solid-state mesopore. The findings provide necessary information for the development of large-sized ionic diode and osmotic power harvesting device.The emergence of antibiotic-resistant bacteria presents a major challenge in terms of increased morbidity, mortality, and healthcare costs [...].In 2017, marginalised groups were disproportionately impacted by extensive flooding in a rural community in Northern New South Wales, Australia, with greater risk of home inundation, displacement and poor mental health. While social capital has been linked with good health and wellbeing, there has been limited investigation into its potential benefits in post-disaster contexts, particularly for marginalised groups. Six months post-flood, a cross-sectional survey was conducted to quantify associations between flood impact, individual social capital and psychological distress (including probable post-traumatic stress disorder). We adopted a community-academic partnership approach and purposive recruitment to increase participation from socio-economically marginalised groups (Aboriginal people and people in financial hardship). These groups reported lower levels of social capital (informal social connectedness, feelings of belonging, trust and optimism) compared to general community participants. Despite this, informal social connectedness and belonging were important factors for all participant groups, associated with reduced risk of psychological distress. In this flood-prone, rural community, there is a pressing need to build social capital collectively through co-designed strategies that simultaneously address the social, cultural and economic needs of marginalised groups. Multiple benefits will ensue for the whole community reduced inequities; strengthened resilience; improved preparedness and lessened risk of long-term distress from disaster events.Regulation of gene transcription is the initial step in the complex process that controls gene expression within bacteria. Transcriptional control involves the joint effort of RNA polymerases and numerous other regulatory factors. Whether global or local, positive or negative, regulators play an essential role in the bacterial cell. For instance, some regulators specifically modify the transcription of virulence genes, thereby being indispensable to pathogenic bacteria. Here, we provide a comprehensive overview of important transcription factors and DNA-binding proteins described for the virulent bacterium Francisella tularensis, the causative agent of tularemia. This is an unexplored research area, and the poorly described networks of transcription factors merit additional experimental studies to help elucidate the molecular mechanisms of pathogenesis in this bacterium, and how they contribute to disease.While alkali-activated materials (AAMs) have been hailed as a very promising solution to mitigate colossal CO2 emissions from world portland cement production, there is lack of robust models that can demonstrate this claim. This paper pioneers a novel system dynamics model that captures the system complexity of this problem and addresses it in a holistic manner. This paper reports on this object-oriented modeling paradigm to develop a cogent prognostic model for predicting CO2 emissions from cement production. The model accounts for the type of AAM precursor and activator, the service life of concrete structures, carbonation of concrete, AAM market share, and policy implementation period. Using the new model developed in this study, strategies for reducing CO2 emissions from cement production have been identified, and future challenges facing wider AAM implementation have been outlined. The novelty of the model consists in its ability to consider the CO2 emission problem as a system of systems, treating it in a holistic manner, and allowing the user to test diverse policy scenarios, with inherent flexibility and modular architecture. The practical relevance of the model is that it facilitates the decision-making process and policy making regarding the use of AAMs to mitigate CO2 emissions from cement production at low computational cost.The quasi-static penetration properties of hybrid laminates were experimentally investigated. Aramid fabrics, carbon fabrics, and short hemp fibres were applied as the reinforcements of hybrid and non-hybrid composite laminates with polyurethane-polyurea (PUR/PUA) matrix. The laminates were made by hand, in a mould. They were cured at room temperature for 24 h. Hybrid laminates consisted of aramid and carbon layers in two different configurations, i.e., aramid at the innermost layers and outermost layers. Aramid/PUR/PUA and carbon/PUR/PUA composites were fabricated for comparison purposes. Laminates were also prepared via an analogue sequence of laying the reinforcement layers with the addition of 5% by weight of hemp fibres in the PUR/PUA matrix. Quasi-static penetration tests (QSPT) were conducted using a tensile testing machine with a surface-hardened, hemispherical, steel punch (9 mm diameter tip), reflecting the geometry of the Parabellum projectile. A quasi-static puncture test was carried out until the laminate was perforated. The ratio between the support span (Ds) and the punch diameter (Dp) was SPR = Ds/Dp = 5.0. The results showed the influences of laminate hybridisation on the values of absorbed energy, punch shear strength, and damage mechanism in the QSPT test. The addition of hemp fibres to aramid laminates resulted in a positive hybridisation effect. The order of layers of aramid and carbon fabrics in hybrid laminates influenced the results obtained in the QSPT test.Agroecosystem conditions limit the productivity of lowbush blueberry. Our objectives were to investigate the effects on berry yield of agroecosystem and crop management variables, then to develop a recommendation system to adjust nutrient and soil management of lowbush blueberry to given local meteorological conditions. We collected 1504 observations from N-P-K fertilizer trials conducted in Quebec, Canada. The data set, that comprised soil, tissue, and meteorological data, was processed by Bayesian mixed models, machine learning, compositional data analysis, and Markov chains. Our investigative statistical models showed that meteorological indices had the greatest impact on yield. High mean temperature at flower bud opening and after fruit maturation, and total precipitation at flowering stage showed positive effects. Low mean temperature and low total precipitation before bud opening, at flowering, and by fruit maturity, as well as number of freezing days ( less then -5 °C) before flower bud opening, showed negative effects. Soil and tissue tests, and N-P-K fertilization showed smaller effects. Gaussian processes predicted yields from historical weather data, soil test, fertilizer dosage, and tissue test with a root-mean-square-error of 1447 kg ha-1. An in-house Markov chain algorithm optimized yields modelled by Gaussian processes from tissue test, soil test, and fertilizer dosage as conditioned to specified historical meteorological features, potentially increasing yield by a median factor of 1.5. Selleckchem CID44216842 Machine learning, compositional data analysis, and Markov chains allowed customizing nutrient management of lowbush blueberry at local scale.Tafazzin is a phospholipid transacylase that catalyzes the remodeling of cardiolipin, a mitochondrial phospholipid required for oxidative phosphorylation. Mutations of the tafazzin gene cause Barth syndrome, which is characterized by mitochondrial dysfunction and dilated cardiomyopathy, leading to premature death. However, the molecular mechanisms underlying the cause of mitochondrial dysfunction in Barth syndrome remain poorly understood. We again highlight the fact that the tafazzin deficiency is also linked to defective oxidative phosphorylation associated with oxidative stress. All the mitochondrial events are positioned in a context where mitophagy is a key element in mitochondrial quality control. Here, we investigated the role of tafazzin in mitochondrial homeostasis dysregulation and mitophagy alteration. Using a HeLa cell model of tafazzin deficiency, we show that dysregulation of tafazzin in HeLa cells induces alteration of mitophagy. Our findings provide some additional insights into mitochondrial dysfunction associated with Barth syndrome, but also show that mitophagy inhibition is concomitant with apoptosis dysfunction through the inability of abnormal mitochondrial cardiolipin to assume its role in cytoplasmic signal transduction.