Robust Outlier-Adaptive Filtering for Vision-Aided Inertial Navigation.

With the advent of unmanned aerial vehicles (UAVs), a major area of interest in the research field of UAVs has been vision-aided inertial navigation systems (V-INS). In the front-end of V-INS, image processing extracts information about the surrounding environment and determines features or points of interest. With the extracted vision data and inertial measurement unit (IMU) dead reckoning, the most widely used algorithm for estimating vehicle and feature states in the back-end of V-INS is an extended Kalman filter (EKF). An important assumption of the EKF is Gaussian white noise. In fact, measurement outliers that arise in various realistic conditions are often non-Gaussian. A lack of compensation for unknown noise parameters often leads to a serious impact on the reliability and robustness of these navigation systems. To compensate for uncertainties of the outliers, we require modified versions of the estimator or the incorporation of other techniques into the filter. The main purpose of this paper is to develop accurate and robust V-INS for UAVs, in particular, those for situations pertaining to such unknown outliers. Feature correspondence in image processing front-end rejects vision outliers, and then a statistic test in filtering back-end detects the remaining outliers of the vision data. For frequent outliers occurrence, variational approximation for Bayesian inference derives a way to compute the optimal noise precision matrices of the measurement outliers. The overall process of outlier removal and adaptation is referred to here as "outlier-adaptive filtering". Even though almost all approaches of V-INS remove outliers by some method, few researchers have treated outlier adaptation in V-INS in much detail. Here, results from flight datasets validate the improved accuracy of V-INS employing the proposed outlier-adaptive filtering framework.

Latency Compensated Visual-Inertial Odometry for Agile Autonomous Flight.

In visual-inertial odometry (VIO), inertial measurement unit (IMU) dead reckoning acts as the dynamic model for flight vehicles while camera vision extracts information about the surrounding environment and determines features or points of interest. With these sensors, the most widely used algorithm for estimating vehicle and feature states for VIO is an extended Kalman filter (EKF). The design of the standard EKF does not inherently allow for time offsets between the timestamps of the IMU and vision data. In fact, sensor-related delays that arise in various realistic conditions are at least partially unknown parameters. A lack of compensation for unknown parameters often leads to a serious impact on the accuracy of VIO systems and systems like them. To compensate for the uncertainties of the unknown time delays, this study incorporates parameter estimation into feature initialization and state estimation. Moreover, computing cross-covariance and estimating delays in online temporal calibration correct residual, Jacobian, and covariance. Results from flight dataset testing validate the improved accuracy of VIO employing latency compensated filtering frameworks. The insights and methods proposed here are ultimately useful in any estimation problem (e.g., multi-sensor fusion scenarios) where compensation for partially unknown time delays can enhance performance.

RGS13 acts as a nuclear repressor of CREB.

Cyclic AMP-induced phosphorylation of the transcription factor CREB elicits expression of genes mediating diverse biological functions. In lymphoid organs, the neurotransmitter norepinephrine stimulates beta(2)-adrenergic receptors on B lymphocytes to promote CREB-dependent expression of genes like the B cell Oct 2 coactivator (OCA-B). Although CREB phosphorylation recruits cofactors such as CBP/p300 to stimulate transcription, bona fide endogenous inhibitors of CREB-coactivator or CREB-DNA interactions have not emerged. Here, we identified RGS13, a member of the Regulator of G protein Signaling (RGS) protein family, as a nuclear factor that suppresses CREB-mediated gene expression. cAMP or Ca(2+) signaling promoted RGS13 accumulation in the nucleus, where it formed a complex with phosphorylated CREB and CBP/p300. RGS13 reduced the apparent affinity of pCREB for both the CRE and CBP. B lymphocytes from Rgs13(-/-) mice had more beta(2)-agonist-induced OCA-B expression. Thus, RGS13 inhibits CREB-dependent transcription of target genes through disruption of complexes formed at the promoter.

Preclinical Characterization of XL092, a Novel Receptor Tyrosine Kinase Inhibitor of MET, VEGFR2, AXL, and MER.

The multi-receptor tyrosine kinase inhibitor XL092 has been developed to inhibit the activity of oncogenic targets, including MET, VEGFR2, and the TAM family of kinases TYRO3, AXL and MER. Presented here is a preclinical evaluation of XL092. XL092 causes a significant decrease in tumor MET and AXL phosphorylation (P < 0.01) in murine Hs 746T xenograft models relative to vehicle, and a 96% inhibition of VEGFR2 phosphorylation in murine lungs. Dose-dependent tumor growth inhibition with XL092 was observed in various murine xenograft models, with dose-dependent tumor regression seen in the NCI-H441 model. Tumor growth inhibition was enhanced with the combination of XL092 with anti-PD-1, anti-programmed death ligand-1 (PD-L1), or anti-CTLA-4 compared with any of these agents alone in the MC38 murine syngeneic model and with anti-PD-1 in the CT26 colorectal cancer survival model. In vivo, XL092 promoted a decrease in the tumor microvasculature and significant increases of peripheral CD4+ T cells and B cells and decreases in myeloid cells versus vehicle. Significant increases in CD8+ T cells were also observed with XL092 plus anti-PD-1 or anti-PD-L1 versus vehicle. In addition, XL092 promoted M2 to M1 repolarization of macrophages in vitro and inhibited primary human macrophage efferocytosis in a dose-dependent manner. In summary, XL092 was shown to have significant antitumor and immunomodulatory activity in animal models both alone and in combination with immune checkpoint inhibitors, supporting its evaluation in clinical trials.

RGS16 inhibits signalling through the G alpha 13-Rho axis.

G alpha 13 stimulates the guanine nucleotide exchange factors (GEFs) for Rho, such as p115Rho-GEF. Activated Rho induces numerous cellular responses, including actin polymerization, serum response element (SRE)-dependent gene transcription and transformation. p115Rho-GEF contains a Regulator of G protein Signalling domain (RGS box) that confers GTPase activating protein (GAP) activity towards G alpha 12 and G alpha 13 (ref. 3). In contrast, classical RGS proteins (such as RGS16 and RGS4) exhibit RGS domain-dependent GAP activity on G alpha i and G alpha q, but not G alpha 12 or G alpha 13 (ref 4). Here, we show that RGS16 inhibits G alpha 13-mediated, RhoA-dependent reversal of stellation and SRE activation. The RGS16 amino terminus binds G alpha 13 directly, resulting in translocation of G alpha 13 to detergent-resistant membranes (DRMs) and reduced p115Rho-GEF binding. RGS4 does not bind G alpha 13 or attenuate G alpha 13-dependent responses, and neither RGS16 nor RGS4 affects G alpha 12-mediated signalling. These results elucidate a new mechanism whereby a classical RGS protein regulates G alpha 13-mediated signal transduction independently of the RGS box.

Phenotyping Flowering in Canola (Brassica napus L.) and Estimating Seed Yield Using an Unmanned Aerial Vehicle-Based Imagery.

Phenotyping crop performance is critical for line selection and variety development in plant breeding. Canola (Brassica napus L.) flowers, the bright yellow flowers, indeterminately increase over a protracted period. Flower production of canola plays an important role in yield determination. Yellowness of canola petals may be a critical reflectance signal and a good predictor of pod number and, therefore, seed yield. However, quantifying flowering based on traditional visual scales is subjective, time-consuming, and labor-consuming. Recent developments in phenotyping technologies using Unmanned Aerial Vehicles (UAVs) make it possible to effectively capture crop information and to predict crop yield via imagery. Our objectives were to investigate the application of vegetation indices in estimating canola flower numbers and to develop a descriptive model of canola seed yield. Fifty-six diverse Brassica genotypes, including 53 B. napus lines, two Brassica carinata lines, and a Brassica juncea variety, were grown near Saskatoon, SK, Canada from 2016 to 2018 and near Melfort and Scott, SK, Canada in 2017. Aerial imagery with geometric and radiometric corrections was collected through the flowering stage using a UAV mounted with a multispectral camera. We found that the normalized difference yellowness index (NDYI) was a useful vegetation index for representing canola yellowness, which is related to canola flowering intensity during the full flowering stage. However, the flowering pixel number estimated by the thresholding method improved the ability of NDYI to detect yellow flowers with coefficient of determination (R 2) ranging from 0.54 to 0.95. Moreover, compared with using a single image date, the NDYI-based flowering pixel numbers integrated over time covers more growth information and can be a good predictor of pod number and thus, canola yield with R 2 up to 0.42. These results indicate that NDYI-based flowering pixel numbers can perform well in estimating flowering intensity. Integrated flowering intensity extracted from imagery over time can be a potential phenotype associated with canola seed yield.

Functional antagonism of IL-1alpha induced gene expression profiles define the cAMP/PKA pathway as a unique regulator of IL-1alpha signaling networks.

Interleukin-1 (IL-1alpha) induced inflammatory and pro-fibrotic responses in human lung fibroblasts are mediated by activation of MAPK and NFkappaB pathways. The purpose of the present study was to broadly profile the activity of a variety of compounds which function as inhibitors of these key signaling pathways that may affect IL-1alpha mediated gene changes. A reference set of genes was derived from microarray analysis of IL-1alpha stimulated cells. The genes were chosen to provide a range of expression profiles which serve to represent the actions of the underlying signaling network. We show that G(s)-coupled receptor agonists have a unique pattern of activity as represented by their impact on IL-1alpha dependent gene changes. These effects were not mimicked by direct inhibitors of p38, JNK, MEK or IKK but were mimicked by forskolin and cAMP analogs. These findings indicate that cAMP/PKA serves as a point of convergence for regulation of IL-1alpha responses by multiple G(s)-coupled receptors and regulates IL-1alpha responses by a distinct mechanism that does not solely involve direct inhibition of p38, JNK, MEK or IKK. The data also point to a potentially useful paradigm wherein monitoring of a small subset of genes is sufficient to identify pathway activity of novel compounds.

A combination of ultrahigh throughput PathHunter and cytokine secretion assays to identify glucocorticoid receptor agonists.

The use of ultrahigh throughput screens (uHTS) is a well-accepted mechanism to identify agonists and antagonists of target receptors. We used the Path Hunter [Path Hunter technology is a registered trademark of DiscoveRx Corporation.] technology from DiscoveRx to screen the entire Merck compound library for glucocorticoid receptor (GR) agonists in a 2.2-microl total reaction volume assayed in a 3456-well plate format. This single addition, homogenous assay which utilizes the principle of enzyme fragment complementation (EFC) to detect nuclear translocation of GR, an initial step of receptor activation, was used to successfully screen a large library of small molecules as indicated by an average signal to background ratio of approximately 4-fold and an average Z-factor value of 0.45. Hits from the HTS campaign were studied in a cytokine secretion assay in primary human monocytes to gain functional information regarding these compounds in a phenotypic and physiologically relevant setting. Our data indicate that using the PathHunter assay, we successfully identified compounds that showed agonism for the GR receptor in primary human monocytes and due to their performance in a physiologically relevant model they likely will have a better chance to evoke clinical efficacy.

High-Throughput UAV Image-Based Method Is More Precise Than Manual Rating of Herbicide Tolerance.

The traditional visual rating system is labor-intensive, time-consuming, and prone to human error. Unmanned aerial vehicle (UAV) imagery-based vegetation indices (VI) have potential applications in high-throughput plant phenotyping. The study objective is to determine if UAV imagery provides accurate and consistent estimations of crop injury from herbicide application and its potential as an alternative to visual ratings. The study was conducted at the Kernen Crop Research Farm, University of Saskatchewan in 2016 and 2017. Fababean (Vicia faba L.) crop tolerance to nine herbicide tank mixtures was evaluated with 2 rates distributed in a randomized complete block design (RCBD) with 4 blocks. The trial was imaged using a multispectral camera with a ground sample distance (GSD) of 1.2 cm, one week after the treatment application. Visual ratings of growth reduction and physiological chlorosis were recorded simultaneously with imaging. The optimized soil-adjusted vegetation index (OSAVI) was calculated from the thresholded orthomosaics. The UAV-based vegetation index (OSAVI) produced more precise results compared to visual ratings for both years. The coefficient of variation (CV) of OSAVI was ~1% when compared to 18-43% for the visual ratings. Furthermore, Tukey's honestly significance difference (HSD) test yielded a more precise mean separation for the UAV-based vegetation index than visual ratings. The significant correlations between OSAVI and the visual ratings from the study suggest that undesirable variability associated with visual assessments can be minimized with the UAV-based approach. UAV-based imagery methods had greater precision than the visual-based ratings for crop herbicide damage. These methods have the potential to replace visual ratings and aid in screening crops for herbicide tolerance.

Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens.

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research.

A 1,536-well [(35)S]GTPgammaS scintillation proximity binding assay for ultra-high-throughput screening of an orphan galphai-coupled GPCR.

Members of the superfamily of seven transmembrane receptors, known as G protein-coupled receptors (GPCRs), are important targets for many therapeutic areas in drug discovery. A homogeneous guanosine 5'-O-(3-[(35)S]thio)triphosphate ([(35)S]GTPgammaS) scintillation proximity assay (SPA) binding assay targeting a Galphai-coupled GPCR recombinantly expressed in membranes of Chinese hamster ovary (CHO) cells was developed and miniaturized into 1,536-well plate format. The primary ultra-high-throughput screen of the entire compound collection was accomplished on the Kalypsys (San Diego, CA) robotic platform at a concentration of 8 muM using the 1,536-well [(35)S]GTPgammaS SPA binding functional assay. The signal-to-noise ratio of the primary screen was approximately 2.1-fold, and the plate coefficient of variation for the compound field was approximately 11%. The hit rate from the primary screen for receptor agonists at >35% activity was approximately 0.3%. Primary hits were cherry-picked, confirmed in triplicate, counterscreened against untransfected CHO cell membranes, and further analyzed in a cyclic AMP functional assay, resulting in 34 leads for optimization.

Ultra-high-throughput screening for antagonists of a Gi-coupled receptor in a 2.2-microl 3,456-well plate format cyclicAMP assay.

3',5'-Cyclic adenosine monophosphate (cAMP) is a common intracellular second messenger that enables cells to respond to external stimuli. Measurement of intracellular cAMP concentrations is thus widely used for studying guanosine triphosphate binding protein-coupled receptors (GPCRs), which make up a large class of pharmaceutical drug targets. Although several assay technologies exist to measure cAMP, most are not suitable for ultra-high-throughput screening (uHTS), as is often required for screening large (greater than 1 million) chemical libraries for the identification of suitable leads for drug development. Here we report that the enzyme fragment complementation assay, a homogeneous gain of signal assay based on complementation of two fragments of a beta-galactosidase enzyme, is compatible with uHTS requirements of a 2.2-microl total assay volume in 3,456-well plate format. We describe the miniaturization of this assay into 3,456-well plate format exhibiting comparable sensitivity and plate statistics to those of a 384-well assay and the application of this assay in uHTS for the identification of antagonists of a Gi-coupled receptor.

Iterative Focused Screening with Biological Fingerprints Identifies Selective Asc-1 Inhibitors Distinct from Traditional High Throughput Screening.

N-methyl-d-aspartate receptors (NMDARs) mediate glutamatergic signaling that is critical to cognitive processes in the central nervous system, and NMDAR hypofunction is thought to contribute to cognitive impairment observed in both schizophrenia and Alzheimer's disease. One approach to enhance the function of NMDAR is to increase the concentration of an NMDAR coagonist, such as glycine or d-serine, in the synaptic cleft. Inhibition of alanine-serine-cysteine transporter-1 (Asc-1), the primary transporter of d-serine, is attractive because the transporter is localized to neurons in brain regions critical to cognitive function, including the hippocampus and cortical layers III and IV, and is colocalized with d-serine and NMDARs. To identify novel Asc-1 inhibitors, two different screening approaches were performed with whole-cell amino acid uptake in heterologous cells stably expressing human Asc-1: (1) a high-throughput screen (HTS) of 3 M compounds measuring 35S l-cysteine uptake into cells attached to scintillation proximity assay beads in a 1536 well format and (2) an iterative focused screen (IFS) of a 45 000 compound diversity set using a 3H d-serine uptake assay with a liquid scintillation plate reader in a 384 well format. Critically important for both screening approaches was the implementation of counter screens to remove nonspecific inhibitors of radioactive amino acid uptake. Furthermore, a 15 000 compound expansion step incorporating both on- and off-target data into chemical and biological fingerprint-based models for selection of additional hits enabled the identification of novel Asc-1-selective chemical matter from the IFS that was not identified in the full-collection HTS.

High-Throughput Screen of GluK1 Receptor Identifies Selective Inhibitors with a Variety of Kinetic Profiles Using Fluorescence and Electrophysiology Assays.

GluK1, a kainate subtype of ionotropic glutamate receptors, exhibits an expression pattern in the CNS consistent with involvement in pain processing and migraine. Antagonists of GluK1 have been shown to reduce pain signaling in the spinal cord and trigeminal nerve, and are predicted to provide pain and migraine relief. We developed an ultra-high-throughput small-molecule screen to identify antagonists of GluK1. Using the calcium indicator dye fluo-4, a multimillion-member small-molecule library was screened in 1536-well plate format on the FLIPR (Fluorescent Imaging Plate Reader) Tetra against cells expressing a calcium-permeable GluK1. Following confirmation in the primary assay and subsequent counter-screen against the endogenous Par-1 receptor, 6100 compounds were selected for dose titration to assess potency and selectivity. Final triage of 1000 compounds demonstrating dose-dependent inhibition with IC50 values of less than 12 µM was performed in an automated whole-cell patch clamp electrophysiology assay. Although a weak correlation between electrophysiologically active and calcium-imaging active compounds was observed, the identification of electrophysiologically active compounds with a range of kinetic profiles revealed a broad spectrum of mechanisms of action.

Screening of HIV-1 Protease Using a Combination of an Ultra-High-Throughput Fluorescent-Based Assay and RapidFire Mass Spectrometry.

HIV-1 protease (PR) represents one of the primary targets for developing antiviral agents for the treatment of HIV-infected patients. To identify novel PR inhibitors, a label-free, high-throughput mass spectrometry (HTMS) assay was developed using the RapidFire platform and applied as an orthogonal assay to confirm hits identified in a fluorescence resonance energy transfer (FRET)-based primary screen of > 1 million compounds. For substrate selection, a panel of peptide substrates derived from natural processing sites for PR was evaluated on the RapidFire platform. As a result, KVSLNFPIL, a new substrate measured to have a ~ 20- and 60-fold improvement in k cat/K m over the frequently used sequences SQNYPIVQ and SQNYPIV, respectively, was identified for the HTMS screen. About 17% of hits from the FRET-based primary screen were confirmed in the HTMS confirmatory assay including all 304 known PR inhibitors in the set, demonstrating that the HTMS assay is effective at triaging false-positives while capturing true hits. Hence, with a sampling rate of ~7 s per well, the RapidFire HTMS assay enables the high-throughput evaluation of peptide substrates and functions as an efficient tool for hits triage in the discovery of novel PR inhibitors.

Use of high-throughput mass spectrometry to reduce false positives in protease uHTS screens.

As a label-free technology, mass spectrometry (MS) enables assays to be generated that monitor the conversion of substrates with native sequences to products without the requirement for substrate modifications or indirect detection methods. Although traditional liquid chromatography (LC)-MS methods are relatively slow for a high-throughput screening (HTS) paradigm, with cycle times typically ≥ 60 s per sample, the Agilent RapidFire High-Throughput Mass Spectrometry (HTMS) System, with a cycle time of 5-7 s per sample, enables rapid analysis of compound numbers compatible with HTS. By monitoring changes in mass directly, HTMS assays can be used as a triaging tool by eliminating large numbers of false positives resulting from fluorescent compound interference or from compounds interacting with hydrophobic fluorescent dyes appended to substrates. Herein, HTMS assays were developed for multiple protease programs, including cysteine, serine, and aspartyl proteases, and applied as a confirmatory assay. The confirmation rate for each protease assay averaged <30%, independent of the primary assay technology used (i.e., luminescent, fluorescent, and time-resolved fluorescent technologies). Importantly, >99% of compounds designed to inhibit the enzymes were confirmed by the corresponding HTMS assay. Hence, HTMS is an effective tool for removing detection-based false positives from ultrahigh-throughput screening, resulting in hit lists enriched in true actives for downstream dose response titrations and hit-to-lead efforts.

Lipoxygenase genes and their targeted disruption.

Analysis of the human and mouse genome sequences has enabled a detailed analysis of the structure and organization of the lipoxygenase genes in the respective species. Humans appear to possess six functional genes and at least three pseudogenes while mice have seven functional genes. The arrangement of the genes is quite similar between the species with most of the human lipoxygenase genes appearing on the short arm of chromosome 17 and in mice on the syntenic portion of chromosome 11. The 5-lipoxygenase gene is unique in several respects including its distinct separate chromosomal localization and its size (4-7 x larger than other lipoxygenase genes). Three of the seven murine lipoxygenase genes have been disrupted by gene targeting. While the knockout mice appear outwardly normal, a number of important findings have been discovered using these mice and these will be covered in this review.

Reproducing kernel hilbert space approach for the online update of radial bases in neuro-adaptive control.

Classical work in model reference adaptive control for uncertain nonlinear dynamical systems with a radial basis function (RBF) neural network adaptive element does not guarantee that the network weights stay bounded in a compact neighborhood of the ideal weights when the system signals are not persistently exciting (PE). Recent work has shown, however, that an adaptive controller using specifically recorded data concurrently with instantaneous data guarantees boundedness without PE signals. However, the work assumes fixed RBF network centers, which requires domain knowledge of the uncertainty. Motivated by reproducing kernel Hilbert space theory, we propose an online algorithm for updating the RBF centers to remove the assumption. In addition to proving boundedness of the resulting neuro-adaptive controller, a connection is made between PE signals and kernel methods. Simulation results show improved performance.

Functional characterization of the G protein regulator RGS13.

The signaling cascades evoked by G protein-coupled receptors are a predominant mechanism of cellular communication. The regulators of G protein signaling (RGS) comprise a family of proteins that attenuate G protein-mediated signal transduction. Here we report the characterization of RGS13, the smallest member of the RGS family, which has been cloned from human lung. RGS13 has been found most abundantly in human tonsil, followed by thymus, lung, lymph node, and spleen. RGS13 is a GTPase-activating protein for Galpha(i) and Galpha(o) but not Galpha(s). RGS13 binds Galpha(q) in the presence of aluminum magnesium fluoride, suggesting that it bears GTPase-activating protein activity toward Galpha(q). RGS13 blocks MAPK activity induced by Galpha(i)- or Galpha(q)-coupled receptors. RGS13 also attenuates GTPase-deficient Galpha(q) (Galpha(q)QL) mediated cAMP response element activation but not transcription evoked by constitutively active Galpha(12) or Galpha(13). Surprisingly, RGS13 inhibits cAMP generation elicited by stimulation of the beta(2)-adrenergic receptor. These data suggest that RGS13 may regulate Galpha(i)-, Galpha(q)-, and Galpha(s)-coupled signaling cascades.

Heterotrimeric G protein signaling: role in asthma and allergic inflammation.

Asthma and rhinitis are pathophysiologic conditions associated with a prototypical allergic response to inhaled allergens consisting of both neuromechanical and inflammatory components. Heptahelical receptors that bind guanosine triphosphate-binding proteins (G proteins), referred to as G protein-coupled receptors (GPCRs), have been intimately linked with asthma and allergic inflammation for many years. G protein signaling mediates responses throughout the immune, nervous, and muscular systems that might contribute to the pathogenesis of allergic processes and asthma. For example, GPCR agonists or antagonists are used as therapies for asthma either by promoting airway smooth muscle relaxation (beta2 adrenergic receptor agonists) or by inhibiting inflammation in the nasal mucosa and airways (cysteinyl leukotriene receptor antagonists). The focus of this review is to explore how downstream signaling cascades elicited by GPCR activation contribute to the allergic phenotype and the mechanism by which pharmaceuticals alter signaling to generate a therapeutic effect. We also discuss physiologic modulators of G protein signaling, such as regulator of G protein signaling proteins and G protein receptor kinases, inasmuch as they represent potential new therapeutic targets in the treatment of atopy and other inflammatory conditions.