Altered Oxygen Utilisation in Rat Left Ventricle and Soleus after 14 Days, but Not 2 Days, of Environmental Hypoxia.

The effects of environmental hypoxia on cardiac and skeletal muscle metabolism are dependent on the duration and severity of hypoxic exposure, though factors which dictate the nature of the metabolic response to hypoxia are poorly understood. We therefore set out to investigate the time-dependence of metabolic acclimatisation to hypoxia in rat cardiac and skeletal muscle. Rats were housed under normoxic conditions, or exposed to short-term (2 d) or sustained (14 d) hypoxia (10% O2), after which samples were obtained from the left ventricle of the heart and the soleus for assessment of metabolic regulation and mitochondrial function. Mass-corrected maximal oxidative phosphorylation was 20% lower in the left ventricle following sustained but not short-term hypoxia, though no change was observed in the soleus. After sustained hypoxia, the ratio of octanoyl carnitine- to pyruvate- supported respiration was 11% and 12% lower in the left ventricle and soleus, respectively, whilst hexokinase activity increased by 33% and 2.1-fold in these tissues. mRNA levels of PPARα targets fell after sustained hypoxia in both tissues, but those of PPARα remained unchanged. Despite decreased Ucp3 expression after short-term hypoxia, UCP3 protein levels and mitochondrial coupling remained unchanged. Protein carbonylation was 40% higher after short-term but not sustained hypoxic exposure in the left ventricle, but was unchanged in the soleus at both timepoints. Our findings therefore demonstrate that 14 days, but not 2 days, of hypoxia induces a loss of oxidative capacity in the left ventricle but not the soleus, and a substrate switch away from fatty acid oxidation in both tissues.JAH received a PhD Studentship from the Biotechnology and Biological Sciences Research Council (Grant number: BB/F016581/1, www.bbsrc.ac.uk (http://www.bbsrc.ac.uk/). SLB received no specific funding for this work. HY received a Departmental Summer Studentship Bursary from Imperial College, London (www.imperial.ac.uk (http://www.imperial.ac.uk/)). AJM received an academic fellowship from the Research Councils UK (www.rcuk.ac.uk (http://www.rcuk.ac.uk/)). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.This is the final version of the article. It first appeared from PLOS via http://dx.doi.org/10.1371/journal.pone.013856

Data Assimilation Predictive GAN (DA-PredGAN): applied to determine the spread of COVID-19

We propose the novel use of a generative adversarial network (GAN) (i) to make predictions in time (PredGAN) and (ii) to assimilate measurements (DA-PredGAN). In the latter case, we take advantage of the natural adjoint-like properties of generative models and the ability to simulate forwards and backwards in time. GANs have received much attention recently, after achieving excellent results for their generation of realistic-looking images. We wish to explore how this property translates to new applications in computational modelling and to exploit the adjoint-like properties for efficient data assimilation. To predict the spread of COVID-19 in an idealised town, we apply these methods to a compartmental model in epidemiology that is able to model space and time variations. To do this, the GAN is set within a reduced-order model (ROM), which uses a low-dimensional space for the spatial distribution of the simulation states. Then the GAN learns the evolution of the low-dimensional states over time. The results show that the proposed methods can accurately predict the evolution of the high-fidelity numerical simulation, and can efficiently assimilate observed data and determine the corresponding model parameters

Multidrug-resistant and methicillin-resistant Staphylococcus aureus (MRSA) in hog slaughter and processing plant workers and their community in North Carolina (USA)

Background: Use of antimicrobials in industrial food-animal production is associated with the presence of antimicrobial resistant Staphylococcus aureus among animals and humans. Hog slaughter/processing plants process large numbers of animals from industrial animal operations, and are environments conducive to the exchange of bacteria between animals and workers. Objectives: To compare the prevalence of methicillin-resistant S. aureus (MRSA) and multidrug resistant S. aureus(MDRSA) carriage between processing plant workers, their household members, and community residents. Methods: We conducted a cross-sectional study of hog slaughter/processing plant workers, their household members, and community residents in North Carolina. Participants responded to a questionnaire and provided a nasal swab. Swabs were tested for S. aureus, and isolates tested for antimicrobial susceptibility and subjected to multilocus sequence typing. Results: The prevalence of S. aureus was 21.6%, 30.2%, and 22.5% among 162 workers, 63 household members, and 111 community residents, respectively. The overall prevalence of MRSA and MDRSA tested by disk diffusion was 4.8% and 6.9%, respectively. The adjusted prevalence of MDRSA among workers was 1.96 times (95% CI: 0.71, 5.45) the prevalence in community residents. The adjusted average number of antimicrobial classes to which S. aureus isolates from workers were resistant was 2.54 times (95% CI: 1.16, 5.56) the number among isolates from community residents. One MRSA isolate and two MDRSA isolates from workers were identified as sequence type 398, a type associated with exposure to livestock. Conclusions: Although the prevalence of S. aureus and MRSA was similar in hog slaughter/processing plant workers and their household and community members, S. aureus isolates from workers were resistant to a greater number of antimicrobial classes. These findings may be related to the non-therapeutic use of antimicrobials in food-animal production

Rare-Earth Orthophosphates From Atomistic Simulations

Lanthanide phosphates (LnPO4) are considered as a potential nuclear waste form for immobilization of Pu and minor actinides (Np, Am, and Cm). In that respect, in the recent years we have applied advanced atomistic simulation methods to investigate various properties of these materials on the atomic scale. In particular, we computed several structural, thermochemical, thermodynamic and radiation damage related parameters. From a theoretical point of view, these materials turn out to be excellent systems for testing quantum mechanics-based computational methods for strongly correlated electronic systems. On the other hand, by conducting joint atomistic modeling and experimental research, we have been able to obtain enhanced understanding of the properties of lanthanide phosphates. Here we discuss joint initiatives directed at understanding the thermodynamically driven long-term performance of these materials, including long-term stability of solid solutions with actinides and studies of structural incorporation of f elements into these materials. In particular, we discuss the maximum load of Pu into the lanthanide-phosphate monazites. We also address the importance of our results for applications of lanthanide-phosphates beyond nuclear waste applications, in particular the monazite-xenotime systems in geothermometry. For this we have derived a state-of-the-art model of monazite-xenotime solubilities. Last but not least, we discuss the advantage of usage of atomistic simulations and the modern computational facilities for understanding of behavior of nuclear waste-related materials

Single-particle cryo-EM analysis of the shell architecture and internal organization of an intact α-carboxysome

Carboxysomes are proteinaceous bacterial microcompartments that sequester the key enzymes for carbon fixation in cyanobacteria and some proteobacteria. They consist of a virus-like icosahedral shell, encapsulating several enzymes, including ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO), responsible for the first step of the Calvin-Benson-Bassham cycle. Despite their significance in carbon fixation and great bioengineering potentials, the structural understanding of native carboxysomes is currently limited to low-resolution studies. Here, we report the characterization of a native α-carboxysome from a marine cyanobacterium by single-particle cryoelectron microscopy (cryo-EM). We have determined the structure of its RuBisCO enzyme, and obtained low-resolution maps of its icosahedral shell, and of its concentric interior organization. Using integrative modeling approaches, we have proposed a complete atomic model of an intact carboxysome, providing insight into its organization and assembly. This is critical for a better understanding of the carbon fixation mechanism and toward repurposing carboxysomes in synthetic biology for biotechnological applications

Multidrug-Resistant and Methicillin-Resistant Staphylococcus aureus (MRSA) in Hog Slaughter and Processing Plant Workers and Their Community in North Carolina (USA)

Background: Use of antimicrobials in industrial food-animal production is associated with the presence of antimicrobial-resistant Staphylococcus aureus (S. aureus) among animals and humans. Hog slaughter/processing plants process large numbers of animals from industrial animal operations and are environments conducive to the exchange of bacteria between animals and workers

Longitudinal Plasma Metabolomics Profile in Pregnancy—A Study in an Ethnically Diverse U.S. Pregnancy Cohort

Amino acids, fatty acids, and acylcarnitine metabolites play a pivotal role in maternal and fetal health, but profiles of these metabolites over pregnancy are not completely established. We described longitudinal trajectories of targeted amino acids, fatty acids, and acylcarnitines in pregnancy. We quantified 102 metabolites and combinations (37 fatty acids, 37 amino acids, and 28 acylcarnitines) in plasma samples from pregnant women in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons cohort (n = 214 women at 10-14 and 15-26 weeks, 107 at 26-31 weeks, and 103 at 33-39 weeks). We used linear mixed models to estimate metabolite trajectories and examined variation by body mass index (BMI), race/ethnicity, and fetal sex. After excluding largely undetected metabolites, we analyzed 77 metabolites and combinations. Levels of 13 of 15 acylcarnitines, 7 of 25 amino acids, and 18 of 37 fatty acids significantly declined over gestation, while 8 of 25 amino acids and 10 of 37 fatty acids significantly increased. Several trajectories appeared to differ by BMI, race/ethnicity, and fetal sex although no tests for interactions remained significant after multiple testing correction. Future studies merit longitudinal measurements to capture metabolite changes in pregnancy, and larger samples to examine modifying effects of maternal and fetal characteristics

CARDIAN: a novel computational approach for real-time end-diastolic frame detection in intravascular ultrasound using bidirectional attention networks

IntroductionChanges in coronary artery luminal dimensions during the cardiac cycle can impact the accurate quantification of volumetric analyses in intravascular ultrasound (IVUS) image studies. Accurate ED-frame detection is pivotal for guiding interventional decisions, optimizing therapeutic interventions, and ensuring standardized volumetric analysis in research studies. Images acquired at different phases of the cardiac cycle may also lead to inaccurate quantification of atheroma volume due to the longitudinal motion of the catheter in relation to the vessel. As IVUS images are acquired throughout the cardiac cycle, end-diastolic frames are typically identified retrospectively by human analysts to minimize motion artefacts and enable more accurate and reproducible volumetric analysis.MethodsIn this paper, a novel neural network-based approach for accurate end-diastolic frame detection in IVUS sequences is proposed, trained using electrocardiogram (ECG) signals acquired synchronously during IVUS acquisition. The framework integrates dedicated motion encoders and a bidirectional attention recurrent network (BARNet) with a temporal difference encoder to extract frame-by-frame motion features corresponding to the phases of the cardiac cycle. In addition, a spatiotemporal rotation encoder is included to capture the IVUS catheter's rotational movement with respect to the coronary artery.ResultsWith a prediction tolerance range of 66.7 ms, the proposed approach was able to find 71.9%, 67.8%, and 69.9% of end-diastolic frames in the left anterior descending, left circumflex and right coronary arteries, respectively, when tested against ECG estimations. When the result was compared with two expert analysts’ estimation, the approach achieved a superior performance.DiscussionThese findings indicate that the developed methodology is accurate and fully reproducible and therefore it should be preferred over experts for end-diastolic frame detection in IVUS sequences