Adhesive and degradative properties of human placental cytotrophoblast cells in vitro.

Human fetal development depends on the embryo rapidly gaining access to the maternal circulation. The trophoblast cells that form the fetal portion of the human placenta have solved this problem by transiently exhibiting certain tumor-like properties. Thus, during early pregnancy fetal cytotrophoblast cells invade the uterus and its arterial network. This process peaks during the twelfth week of pregnancy and declines rapidly thereafter, suggesting that the highly specialized, invasive behavior of the cytotrophoblast cells is closely regulated. Since little is known about the actual mechanisms involved, we developed an isolation procedure for cytotrophoblasts from placentas of different gestational ages to study their adhesive and invasive properties in vitro. Cytotrophoblasts isolated from first, second, and third trimester human placentas were plated on the basement membrane-like extracellular matrix produced by the PF HR9 teratocarcinoma cell line. Cells from all trimesters expressed the calcium-dependent cell adhesion molecule cell-CAM 120/80 (E-cadherin) which, in the placenta, is specific for cytotrophoblasts. However, only the first trimester cytotrophoblast cells degraded the matrices on which they were cultured, leaving large gaps in the basement membrane substrates and releasing low molecular mass 3H-labeled matrix components into the medium. No similar degradative activity was observed when second or third trimester cytotrophoblast cells, first trimester human placental fibroblasts, or the human choriocarcinoma cell lines BeWo and JAR were cultured on radiolabeled matrices. To begin to understand the biochemical basis of this degradative behavior, the substrate gel technique was used to analyze the cell-associated and secreted proteinase activities expressed by early, mid, and late gestation cytotrophoblasts. Several gelatin-degrading proteinases were uniquely expressed by early gestation, invasive cytotrophoblasts, and all these activities could be abolished by inhibitors of metalloproteinases. By early second trimester, the time when cytotrophoblast invasion rapidly diminishes in vivo, the proteinase pattern of the cytotrophoblasts was identical to that of term, noninvasive cells. These results are the first evidence suggesting that specialized, temporally regulated metalloproteinases are involved in trophoblast invasion of the uterus. Since the cytotrophoblasts from first trimester and later gestation placentas maintain for several days the temporally regulated degradative behavior displayed in vivo, the short-term cytotrophoblast outgrowth culture system described here should be useful in studying some of the early events in human place

The electron thermal structure in the dayside Martian ionosphere implied by the MGS radio occultation data

We propose a revised Chapman model for the ionosphere of Mars by allowing for vertical variation of electron temperature. An approximate energy balance between solar EUV heating and CO2 collisional cooling is applied in the dayside Martian ionosphere, analogous to the method recently proposed by Withers et al. (2014). The essence of the model is to separate the contributions of the neutral and electron thermal structures to the apparent width of the main ionospheric layer. Application of the model to the electron density profiles from the Mars Global Surveyor (MGS) radio occultation measurements reveals a clear trend of elevated electron temperature with increasing solar zenith angle (SZA). It also reveals that the characteristic length scale for the change of electron temperature with altitude decreases with increasing SZA. These observations may imply enhanced topside heat influx near the terminator, presumably an outcome of the solar wind interactions with the Martian upper atmosphere. Our analysis also reveals a tentative asymmetry in electron temperature between the northern and southern hemispheres, consistent with the scenario of elevated electron temperature within minimagnetospheres

Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off

Bundling of graph edges (node-to-node connections) is a common technique to enhance visibility of overall trends in the edge structure of a large graph layout, and a large variety of bundling algorithms have been proposed. However, with strong bundling, it becomes hard to identify origins and destinations of individual edges. We propose a solution: we optimize edge coloring to differentiate bundled edges. We quantify strength of bundling in a flexible pairwise fashion between edges, and among bundled edges, we quantify how dissimilar their colors should be by dissimilarity of their origins and destinations. We solve the resulting nonlinear optimization, which is also interpretable as a novel dimensionality reduction task. In large graphs the necessary compromise is whether to differentiate colors sharply between locally occurring strongly bundled edges ("local bundles"), or also between the weakly bundled edges occurring globally over the graph ("global bundles"); we allow a user-set global-local tradeoff. We call the technique "peacock bundles". Experiments show the coloring clearly enhances comprehensibility of graph layouts with edge bundling.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

The clinical and therapeutic uses of MDM2 and PSMA and their potential interaction in aggressive cancers

Prostate-specific membrane antigen (PSMA) overexpression is observed in the neovasculature of solid tumors, but not in the vasculature of normal tissues. Increased PSMA expression is positively associated with tumor stage and grade, although its function in cancer remains unclear. Mouse double minute 2 (MDM2) is a negative regulator of the p53 tumor suppressor and is reported to regulate VEGF expression and angiogenesis. Both proteins have been considered as biomarkers and therapeutic targets for advanced solid tumors. Our work and a recent microarray-based gene profiling study suggest there could be signaling interplay between MDM2 and PSMA. We herein review the mechanisms underlining the outgrowth of tumors associated with PSMA and MDM2, their potential interaction and how this may be applied to anticancer therapeutics

Effect of strengthened standards on Chinese ironmaking and steelmaking emissions

China has produced roughly half of the world’s steel in recent years, but the country’s iron and steel industry is a major source of air pollutants, especially particulate matter, SO2 and NOx emissions. To reduce such emissions, China imposed new emission standards in 2015 and promoted ultralow emission standards in 2019. Here we use measurements from China’s continuous emissions monitoring systems (covering 69–91% of national iron and steel production) to develop hourly, facility-level emissions estimates for China’s iron and steel industry. In turn, we use this data to evaluate the emission reductions related to China’s increasingly stringent policies. We find steady declines in emission concentrations at iron- and steelmaking plants since the 2015 standards were implemented. From 2014 to 2018, particulate matter and SO2 emissions fell by 47% and 42%, respectively, and NOx increased by 3%, even as the production increased by 14%. Moreover, we estimate that if all facilities achieve the ultralow emission standards, particulate matter, SO2 and NOx emissions will drop by a further 50%, 37% and 58%, respectively. Our results thus reveal the substantial benefits of the Chinese government’s interventions to curb emissions from iron and steel production and emphasize the promise of ongoing ultralow emission renovations

Assessing fossil fuel CO₂ emissions in California using atmospheric observations and models

Analysis systems incorporating atmospheric observations could provide a powerful tool for validating fossil fuel CO2 (ffCO2) emissions reported for individual regions, provided that fossil fuel sources can be separated from other CO2 sources or sinks and atmospheric transport can be accurately accounted for. We quantified ffCO2 by measuring radiocarbon (14C) in CO2, an accurate fossil-carbon tracer, at nine observation sites in California for three months in 2014–15. There is strong agreement between the measurements and ffCO2 simulated using a high-resolution atmospheric model and a spatiotemporally-resolved fossil fuel flux estimate. Inverse estimates of total in-state ffCO2 emissions are consistent with the California Air Resources Board's reported ffCO2 emissions, providing tentative validation of California's reported ffCO2 emissions in 2014–15. Continuing this prototype analysis system could provide critical independent evaluation of reported ffCO2 emissions and emissions reductions in California, and the system could be expanded to other, more data-poor regions

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

The mass area of jets

We introduce a new characteristic of jets called mass area. It is defined so as to measure the susceptibility of the jet's mass to contamination from soft background. The mass area is a close relative of the recently introduced catchment area of jets. We define it also in two variants: passive and active. As a preparatory step, we generalise the results for passive and active areas of two-particle jets to the case where the two constituent particles have arbitrary transverse momenta. As a main part of our study, we use the mass area to analyse a range of modern jet algorithms acting on simple one and two-particle systems. We find a whole variety of behaviours of passive and active mass areas depending on the algorithm, relative hardness of particles or their separation. We also study mass areas of jets from Monte Carlo simulations as well as give an example of how the concept of mass area can be used to correct jets for contamination from pileup. Our results show that the information provided by the mass area can be very useful in a range of jet-based analyses.Comment: 36 pages, 12 figures; v2: improved quality of two plots, added entry in acknowledgments, nicer form of formulae in appendix A; v3: added section with MC study and pileup correction, version accepted by JHE

Expression of HA of HPAI H5N1 Virus at US2 Gene Insertion Site of Turkey Herpesvirus Induced Better Protection than That at US10 Gene Insertion Site

Herpesvirus of turkey (HVT) is being widely used as a vector for development of recombinant vaccines and US2 and US10 genes are often chosen as insertion sites for targeted gene expression. However, the different effects of the two genes for generation of recombinant HVT vaccines were unknown. In order to compare the effects of inserted genes in the two sites on the efficacy of the recombinant vaccines, host-protective haemagglutinin (HA) gene of the highly pathogenic avian influenza virus (HPAIV) H5N1 was inserted into either US2 or US10 gene locus of the HVT. The resulting US2 (rHVT-US2-HA) or US10 (rHVT-US10-HA) recombinant HVT viruses were used to infect chicken embryo fibroblasts. Plaques and the growth kinetics of rHVT-US2-HA-infected chicken embryo fibroblasts were similar to those of parental HVT whereas rHVT-US10-HA infected chicken embryo fibroblasts had different growth kinetics and plaque formation. The viremia levels in rHVT-US10-HA virus-infected chickens were significantly lower than those of rHVT-US2-HA group on 28 days post infection. The vaccine efficacy of the two recombinant viruses against H5N1 HPAIV and virulent Marek's disease virus was also evaluated in 1-day-old vaccinated chickens. rHVT-US2-HA-vaccinated chickens were better protected with reduced mortality than rHVT-US10-HA-vaccinated animals following HPAIV challenge. Furthermore, the overall hemaglutination inhibition antibody titers of rHVT-US2-HA-vaccinated chickens were higher than those of rHVT-US10-HA-vaccinated chickens. Protection levels against Marek's disease virus challenge following vaccination with either rHVT-US2-HA or rHVT-US10-HA, however, were similar to those of the parental HVT virus. These results, for the first time, indicate that US2 gene provides a favorable foreign gene insertion site for generation of recombinant HVT vaccines

Quantum phases with differing computational power

The observation that concepts from quantum information has generated many alternative indicators of quantum phase transitions hints that quantum phase transitions possess operational significance with respect to the processing of quantum information. Yet, studies on whether such transitions lead to quantum phases that differ in their capacity to process information remain limited. Here We show that there exist quantum phase transitions that cause a distinct qualitative change in our ability to simulate certain quantum systems under perturbation of an external field by local operations and classical communication. In particular, we show that in certain quantum phases of the XY model, adiabatic perturbations of the external magnetic field can be simulated by local spin operations, whereas the resulting effect within other phases results in coherent non-local interactions. We discuss the potential implications to adiabatic quantum computation, where a computational advantage exists only when adiabatic perturbation results in coherent multi-body interactions.Comment: 7 pages, 4 figures, with published title "Quantum phases with differing computational power