A Particle-based Multiscale Solver for Compressible Liquid-Vapor Flow

To describe complex flow systems accurately, it is in many cases important to account for the properties of fluid flows on a microscopic scale. In this work, we focus on the description of liquid-vapor flow with a sharp interface between the phases. The local phase dynamics at the interface can be interpreted as a Riemann problem for which we develop a multiscale solver in the spirit of the heterogeneous multiscale method, using a particle-based microscale model to augment the macroscopic two-phase flow system. The application of a microscale model makes it possible to use the intrinsic properties of the fluid at the microscale, instead of formulating (ad-hoc) constitutive relations

Metabolomics and Transcriptomics Reveal the Response Mechanisms of Mikania micrantha to Puccinia spegazzinii Infection

Mikania micrantha is one of the worst invasive species globally and can cause significant negative impacts on agricultural and forestry economics, particularly in Asia and the Pacific region. The rust Puccinia spegazzinii has been used successfully as a biological control agent in several countries to help manage M. micrantha. However, the response mechanisms of M. micrantha to P. spegazzinii infection have never been studied. To investigate the response of M. micrantha to infection by P. spegazzinii, an integrated analysis of metabolomics and transcriptomics was performed. The levels of 74 metabolites, including organic acids, amino acids, and secondary metabolites in M. micrantha infected with P. spegazzinii, were significantly different compared to those in plants that were not infected. After P. spegazzinii infection, the expression of the TCA cycle gene was significantly induced to participate in energy biosynthesis and produce more ATP. The content of most amino acids, such as L-isoleucine, L-tryptophan and L-citrulline, increased. In addition, phytoalexins, such as maackiain, nobiletin, vasicin, arachidonic acid, and JA-Ile, accumulated in M. micrantha. A total of 4978 differentially expressed genes were identified in M. micrantha infected by P. spegazzinii. Many key genes of M. micrantha in the PTI (pattern-triggered immunity) and ETI (effector-triggered immunity) pathways showed significantly higher expression under P. spegazzinii infection. Through these reactions, M. micrantha is able to resist the infection of P. spegazzinii and maintain its growth. These results are helpful for us to understand the changes in metabolites and gene expression in M. micrantha after being infected by P. spegazzinii. Our results can provide a theoretical basis for weakening the defense response of M. micrantha to P. spegazzinii, and for P. spegazzinii as a long-term biological control agent of M. micrantha

Synthesis of Two New Group 13 Benzoato-Chloro Complexes: A Structural Study of Gallium and Indium Chelating Carboxylates

Two new heteroleptic chelated-benzoato gallium (III) and indium (III) complexes have been prepared and structurally characterized. The molecular structures of [GaCl2(4-Mepy)2(O2CPh)]4-Mepy (1) and [InCl(4-Mepy)2(O2CPh)2]4-Mepy (2) have been determined by single-crystal x-ray diffraction. The gallium compound (1) is a distorted octahedron with cis-chloride ligands co-planar with the chelating benzoate and the 4-methylpyridines trans to each other. This is the first example of a Ga(III) structure with a chelating benzoate. The indium compound (2) is a distorted pentagonal bipyramid with two chelating benzoates, one 4-methylpyridine in the plane and a chloride trans to the other 4-methylpyridine. The indium bis-benzoate is an unusual example of a seven-coordinate structure with classical ligands. Both complexes, which due to the chelates, could also be described as pseudo-trigonal bipyramidal, include a three-bladed motif with three roughly parallel aromatic rings that along with a solvent of crystallization and electron-withdrawing chloride ligand(s) stabilize the solid-state structures

The Anti-Sigma Factor MucA of Pseudomonas aeruginosa: Dramatic Differences of a mucA22 vs. a ΔmucA Mutant in Anaerobic Acidified Nitrite Sensitivity of Planktonic and Biofilm Bacteria in vitro and During Chronic Murine Lung Infection

Mucoid mucA22 Pseudomonas aeruginosa (PA) is an opportunistic lung pathogen of cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients that is highly sensitive to acidified nitrite (A-NO2-). In this study, we first screened PA mutant strains for sensitivity or resistance to 20 mM A-NO2- under anaerobic conditions that represent the chronic stages of the aforementioned diseases. Mutants found to be sensitive to A-NO2- included PA0964 (pmpR, PQS biosynthesis), PA4455 (probable ABC transporter permease), katA (major catalase, KatA) and rhlR (quorum sensing regulator). In contrast, mutants lacking PA0450 (a putative phosphate transporter) and PA1505 (moaA2) were A-NO2- resistant. However, we were puzzled when we discovered that mucA22 mutant bacteria, a frequently isolated mucA allele in CF and to a lesser extent COPD, were more sensitive to A-NO2- than a truncated ΔmucA deletion (Δ157–194) mutant in planktonic and biofilm culture, as well as during a chronic murine lung infection. Subsequent transcriptional profiling of anaerobic, A-NO2--treated bacteria revealed restoration of near wild-type transcript levels of protective NO2- and nitric oxide (NO) reductase (nirS and norCB, respectively) in the ΔmucA mutant in contrast to extremely low levels in the A-NO2--sensitive mucA22 mutant. Proteins that were S-nitrosylated by NO derived from A-NO2- reduction in the sensitive mucA22 strain were those involved in anaerobic respiration (NirQ, NirS), pyruvate fermentation (UspK), global gene regulation (Vfr), the TCA cycle (succinate dehydrogenase, SdhB) and several double mutants were even more sensitive to A-NO2-. Bioinformatic-based data point to future studies designed to elucidate potential cellular binding partners for MucA and MucA22. Given that A-NO2- is a potentially viable treatment strategy to combat PA and other infections, this study offers novel developments as to how clinicians might better treat problematic PA infections in COPD and CF airway diseases

Clinical significance of elevated B-type natriuretic peptide in patients with acute lung injury with or without right ventricular dilatation: an observational cohort study

BackgroundThe primary objective of this study was to examine levels of B-type natriuretic peptide (BNP) in mechanically ventilated patients with acute lung injury and to test whether the level of BNP would be higher in patients with right ventricular dilatation and would predict mortality.MethodsThis was a prospective, observational cohort study of 42 patients conducted in the intensive care unit of a tertiary care university hospital. BNP was measured and transthoracic echocardiography was performed within 48 hours of the onset of acute lung injury. The left ventricular systolic and diastolic function, right ventricular systolic function, and cardiac output were assessed. BNP was compared in patients with and without right ventricular dilatation, as well as in survivors versus nonsurvivors.ResultsBNP was elevated in mechanically ventilated patients with acute lung injury (median 420 pg/ml; 25-75% interquartile range 156-728 pg/ml). There was no difference between patients with and without right ventricular dilatation (420 pg/ml, 119-858 pg/ml vs. 387 pg/ml, 156-725 pg/ml; p = 0.96). There was no difference in BNP levels between the patients who died and those who survived at 30 days (420 pg/ml, 120-728 pg/ml vs. 385 pg/ml, 159-1070 pg/ml; p = 0.71).ConclusionsIn patients with acute lung injury the level of BNP is increased, but there is no difference in the BNP level between patients with and without right ventricular dilatation. Furthermore, BNP level is not predictive of mortality in this population

Deep Thermal Imaging: Proximate Material Type Recognition in the Wild through Deep Learning of Spatial Surface Temperature Patterns

We introduce Deep Thermal Imaging, a new approach for close-range automatic recognition of materials to enhance the understanding of people and ubiquitous technologies of their proximal environment. Our approach uses a low-cost mobile thermal camera integrated into a smartphone to capture thermal textures. A deep neural network classifies these textures into material types. This approach works effectively without the need for ambient light sources or direct contact with materials. Furthermore, the use of a deep learning network removes the need to handcraft the set of features for different materials. We evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments. Our approach produced recognition accuracies above 98% in 14,860 images of 15 indoor materials and above 89% in 26,584 images of 17 outdoor materials. We conclude by discussing its potentials for real-time use in HCI applications and future directions.Comment: Proceedings of the 2018 CHI Conference on Human Factors in Computing System

Detecting Recent Crop Phenology Dynamics in Corn and Soybean Cropping Systems of Kentucky

Accurate phenological information is essential for monitoring crop development, predicting crop yield, and enhancing resilience to cope with climate change. This study employed a curve-change-based dynamic threshold approach on NDVI (Normalized Differential Vegetation Index) time series to detect the planting and harvesting dates for corn and soybean in Kentucky, a typical climatic transition zone, from 2000 to 2018. We compared satellite-based estimates with ground observations and performed trend analyses of crop phenological stages over the study period to analyze their relationships with climate change and crop yields. Our results showed that corn and soybean planting dates were delayed by 0.01 and 0.07 days/year, respectively. Corn harvesting dates were also delayed at a rate of 0.67 days/year, while advanced soybean harvesting occurred at a rate of 0.05 days/year. The growing season length has increased considerably at a rate of 0.66 days/year for corn and was shortened by 0.12 days/year for soybean. Sensitivity analysis showed that planting dates were more sensitive to the early season temperature, while harvesting dates were significantly correlated with temperature over the entire growing season. In terms of the changing climatic factors, only the increased summer precipitation was statistically related to the delayed corn harvesting dates in Kentucky. Further analysis showed that the increased corn yield was significantly correlated with the delayed harvesting dates (1.37 Bu/acre per day) and extended growing season length (1.67 Bu/acre per day). Our results suggested that seasonal climate change (e.g., summer precipitation) was the main factor influencing crop phenological trends, particularly corn harvesting in Kentucky over the study period. We also highlighted the critical role of changing crop phenology in constraining crop production, which needs further efforts for optimizing crop management practices

On-line monitoring and controlling of cell apoptosis in mammalian cell culture processes using dielectric spectroscopy

We investigate a method to control critical quality attributes and apply Process Analytical Technology (PAT) via online dielectric spectroscopy (DS) feedback. This system has been intensively explored and successfully implemented in GMP manufacturing processes at Biogen. The present bioreactor application however, is basic and only allows the prediction of biomass. To further enhance the cell culture process robustness, we investigated the feasibility of using the full-spectrum dielectric spectroscopy scanning function to detect dielectric property changes in the cells associated with shifts in cell health and/or metabolism. In this proof of concept study, we used several CHO cell processes to demonstrate that DS probes can be used to not only measure the biomass but also reflect the cell’s physiological state changes (e.g. cell apoptosis). The results showed that one or more of the key parameters of delta capacitance (De), critical frequency (fc), and Cole-Cole Alpha (a) from the multi-frequency scanning data could reflect the cell’s early apoptosis induced by chemical treatment, nutrient depletion, or shear stress, which were seen earlier than that obtained from off-line methods (e.g. trypan blue exclusion). In some cases, by responding to the earlier detection, the cell apoptosis was reversed in time and the batch was saved. This enables a potential application, transferrable across programs, of full-spectrum dielectric spectroscopy for earlier detection of physiological changes, allowing for timelier bioreactor process adjustments. In addition, the feasibility of the application of multifrequency scanning in cGMP process for monitoring and control was also explored in this study