Specific Involvement of G Proteins in Regulation of Serum Response Factor-mediated Gene Transcription by Different Receptors

Regulation of serum response factor (SRF)-mediated gene transcription by G protein subunits and G protein-coupled receptors was investigated in transfected NIH3T3 cells and in a cell line that was derived from mice lacking G_(αq) and G_(α11). We found that the constitutively active forms of the α subunits of the G_q and G_(12) class of G proteins, including Gα_q, Gα_(11), Gα_(14), Gα_(16), Gα_(12), and Gα_(13), can activate SRF in NIH3T3 cells. We also found that the type 1 muscarinic receptor (m1R) and α_1-adrenergic receptor (AR)-mediated SRF activation is exclusively dependent on Gα_(q/11), while the receptors for thrombin, lysophosphatidic acid (LPA), thromboxane A2, and endothelin can activate SRF in the absence of Gα_(q/11). Moreover, RGS12 but not RGS2, RGS4, or Axin was able to inhibit Gα_(12) and Gα_(13)-mediated SRF activation. And RGS12, but not other RGS proteins, blocked thrombin- and LPA-mediated SRF activation in the Gα_(q/11)-deficient cells. Therefore, the thrombin, LPA, thromboxane A2, and endothelin receptors may be able to couple to Gα_(12/13). On the contrary, receptors including β_2- and α_2-ARs, m2R, the dopamine receptors type 1 and 2, angiotensin receptors types 1 and 2, and interleukin-8 receptor could not activate SRF in the presence or absence of Gα_(q/11), suggesting that these receptors cannot couple to endogenous G proteins of the G_(12) or G_q classes

eRPCAe^{\text{RPCA}}: Robust Principal Component Analysis for Exponential Family Distributions

Robust Principal Component Analysis (RPCA) is a widely used method for recovering low-rank structure from data matrices corrupted by significant and sparse outliers. These corruptions may arise from occlusions, malicious tampering, or other causes for anomalies, and the joint identification of such corruptions with low-rank background is critical for process monitoring and diagnosis. However, existing RPCA methods and their extensions largely do not account for the underlying probabilistic distribution for the data matrices, which in many applications are known and can be highly non-Gaussian. We thus propose a new method called Robust Principal Component Analysis for Exponential Family distributions ($e^{\text{RPCA}}$), which can perform the desired decomposition into low-rank and sparse matrices when such a distribution falls within the exponential family. We present a novel alternating direction method of multiplier optimization algorithm for efficient $e^{\text{RPCA}}$ decomposition. The effectiveness of $e^{\text{RPCA}}$ is then demonstrated in two applications: the first for steel sheet defect detection, and the second for crime activity monitoring in the Atlanta metropolitan area

Subsecond total-body imaging using ultrasensitive positron emission tomography.

A 194-cm-long total-body positron emission tomography/computed tomography (PET/CT) scanner (uEXPLORER), has been constructed to offer a transformative platform for human radiotracer imaging in clinical research and healthcare. Its total-body coverage and exceptional sensitivity provide opportunities for innovative studies of physiology, biochemistry, and pharmacology. The objective of this study is to develop a method to perform ultrahigh (100 ms) temporal resolution dynamic PET imaging by combining advanced dynamic image reconstruction paradigms with the uEXPLORER scanner. We aim to capture the fast dynamics of initial radiotracer distribution, as well as cardiac motion, in the human body. The results show that we can visualize radiotracer transport in the body on timescales of 100 ms and obtain motion-frozen images with superior image quality compared to conventional methods. The proposed method has applications in studying fast tracer dynamics, such as blood flow and the dynamic response to neural modulation, as well as performing real-time motion tracking (e.g., cardiac and respiratory motion, and gross body motion) without any external monitoring device (e.g., electrocardiogram, breathing belt, or optical trackers)

An Efficient Adaptive Search Algorithm for Scheduling Real-Time Traffic

Proc. Fourth IEEE International Conference on Network Protocols (ICNP), pp. 14-22, Columbus, OH, October 1996.The article of record as published may be found at http://dx.doi.org/10.1109/ICNP.1996.564885For many service disciplines that provide delay guarantees, the scheduler of a channel repeatedly searches for the smallest element in a set of priority values (or deadlines). It is required that each search finishes within a time bound. Furthermore, the search algorithm should be highly efficient. To meet these requirements, we have developed a search algorithm based upon a new data structure, called adaptive heap; it behaves like a heap most of the time, but adaptively changes its strategy when necessary to satisfy the time bound. We show that the algorithm has optimal worst case time complexity and good average performance. To further improve efficiency, the basic algorithm is extended to include the use of group scheduling. We present empirical results on the performance of adaptive heap search with and without group scheduling. We conclude that adaptive heap search performs as intended, and that group scheduling provides a substantial reduction in the scheduler’s work when channel utilization is high

Effects of ozone addition on the kinetics and efficiencies of methane conversion at fuel-rich conditions

Compression–expansion processes have the potential of converting mechanical work to chemical energy at fuel-rich conditions, allowing for the storage of fluctuating renewable energies. In this work, the conversion of methane and natural gas (NG) is investigated for this purpose. A focus is on using ozone as a reaction promoter for the otherwise slow reaction. The kinetics of fuel-rich methane/NG oxidation with ozone addition is investigated experimentally and numerically. To this end, ignition delay times (IDTs) for CH$_4$/O$_2$/O$_3$/Ar and NG/O$_2$/O$_3$/Ar mixtures are measured in a rapid compression machine (RCM). It is shown that a reaction mechanism obtained by simply combining a previously developed mechanism for methane conversion (PolyMech2.0) with an ozone sub-mechanism does not accurately predict IDTs. Sensitivity analyses identify reactions in the methane submechanism that become more important for ignition delay time when ozone is added in comparison to mixtures without O$_3$. The rate coefficients of these reactions are modified within their uncertainty ranges to better match the experimentally obtained IDTs. The resulting kinetic model, named PolyMech 3.0, predicts the IDTs obtained in RCM-experiments well. Analysis reveals a two-fold promoting effect of ozone addition on methane/air ignition: Ozone causes a temperature rise by the reactions associated with its decomposition. Ozone also forms reactive products such as hydrogen and oxygen radicals, which can then promote reactions of the hydrocarbons. Quantitative analysis shows that the latter effect is more pronounced. Using PolyMech 3.0, parametric simulation studies for methane conversion in four-stroke engine cycles are carried out to explore the effects of ozone addition on chemical energy storage and efficiencies of engine-based polygeneration processes. Results show that with ozone addition, methane conversion can take place at high engine speeds, while without ozone, there is nearly zero conversion of fuel rich methane mixtures because of the low reactivity. Therefore, ozone addition allows for reasonable efficiencies across a wider range of operating conditions