The role of NMR spectroscopy in mapping the conformational landscape of GPCRs.

Over recent years, nuclear magnetic resonance (NMR) spectroscopy has developed into a powerful mechanistic tool for the investigation of G protein-coupled receptors (GPCRs). NMR provides insights which underpin the dynamic nature of these important receptors and reveals experimental evidence for a complex conformational energy landscape that is explored during receptor activation resulting in signalling. NMR studies have highlighted both the dynamic properties of different receptor states as well as the exchange pathways and intermediates formed during activation, extending the static view of GPCRs obtained from other techniques. NMR studies can be undertaken in realistic membrane-like phospholipid environments and an ever-increasing choice of labelling strategies provides comprehensive, receptor-wide information. Combined with other structural methods, NMR is contributing to our understanding of allosteric signal propagation and the interaction of GPCRs with intracellular binding partners (IBP), crucial to explaining cellular signalling.BBSRC BB/K01983 X/

Spatial Distribution of Lead in Sacramento, California, USA

Chronic exposure to lead remains a health concern in many urban areas; Sacramento, California is one example, with state surveillance data showing nearly 3% of screened children reported with blood lead levels over 4.5 μg/dL in 2009. To investigate the environmental exposure, 91 soil samples were collected and analyzed by ICP-AES and ICP-MS for 14 elements. An additional 28 samples were collected from areas of focus and analyzed by hand-held X-ray fluorescence spectrometry for Pb and Zn. Analysis of the metals data revealed non-normal distributions and positive skewness, consistent with anthropogenic input. In addition, high correlation coefficients (≥0.75) of metal concentrations in Cd-Pb, Cd-Zn, Pb-Zn, and Sb-Sn pairs suggest similarities in the input mechanisms. Semivariograms generated from Pb and associated metals reveal these metals to exhibit spatial correlation. A prediction map of lead concentrations in soil was generated by ordinary kriging, showing elevated concentrations in soil located in the central, older area of Sacramento where historic traffic density and industrial activity have been historically concentrated. XRF analysis of Pb and Zn from additional samples verifies elevated concentrations in the central areas of Sacramento as predicted

Active Emergence from Propofol General Anesthesia Is Induced by Methylphenidate

Background: A recent study showed that methylphenidate induces emergence from isoflurane general anesthesia. Isoflurane and propofol are general anesthetics that may have distinct molecular mechanisms of action. The objective of this study was to test the hypothesis that methylphenidate actively induces emergence from propofol general anesthesia. Methods: Using adult rats, the effect of methylphenidate on time to emergence after a single bolus of propofol was determined. The ability of methylphenidate to restore righting during a continuous target-controlled infusion (TCI) of propofol was also tested. In a separate group of rats, a TCI of propofol was established and spectral analysis was performed on electroencephalogram recordings taken before and after methylphenidate administration. Results: Methylphenidate decreased median time to emergence after a single dose of propofol from 735 s (95% CI: 598–897 s, n = 6) to 448 s (95% CI: 371–495 s, n = 6). The difference was statistically significant (P = 0.0051). During continuous propofol anesthesia with a median final target plasma concentration of 4.0 μg/ml (95% CI: 3.2–4.6, n = 6), none of the rats exhibited purposeful movements after injection of normal saline. After methylphenidate, however, all six rats promptly exhibited arousal and had restoration of righting with a median time of 82 s (95% CI: 30–166 s). Spectral analysis of electroencephalogram data demonstrated a shift in peak power from δ (less than 4 Hz) to θ (4–8 Hz) and β (12–30 Hz) after administration of methylphenidate, indicating arousal in 4/4 rats. Conclusions: Methylphenidate decreases time to emergence after a single dose of propofol, and induces emergence during continuous propofol anesthesia in rats. Further study is warranted to test the hypothesis that methylphenidate induces emergence from propofol general anesthesia in humans.National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant K08-GM094394)Massachusetts General Hospital. Dept. of Anesthesia and Critical Car

Regulation of p53 Stability and Apoptosis by a ROR Agonist

Activation of p53 function leading to cell-cycle arrest and/or apoptosis is a promising strategy for development of anticancer therapeutic agents. Here, we describe a novel mechanism for stabilization of p53 protein expression via activation of the orphan nuclear receptor, RORa. We demonstrate that treatment of cancer cells with a newly described synthetic ROR agonist, SR1078, leads to p53 stabilization and induction of apoptosis. These data suggest that synthetic ROR agonists may hold utility in the treatment of cancer

Activation of D1 Dopamine Receptors Induces Emergence from Isoflurane General Anesthesia

Background: A recent study showed that methylphenidate induces emergence from isoflurane anesthesia. Methylphenidate inhibits dopamine and norepinephrine reuptake transporters. The objective of this study was to test the hypothesis that selective dopamine receptor activation induces emergence from isoflurane anesthesia. Methods: In adult rats, we tested the effects of chloro-APB (D1 agonist) and quinpirole (D2 agonist) on time to emergence from isoflurane general anesthesia. We then performed a dose–response study to test for chloro-APB–induced restoration of righting during continuous isoflurane anesthesia. SCH-23390 (D1 antagonist) was used to confirm that the effects induced by chloro-APB are specifically mediated by D1 receptors. In a separate group of animals, spectral analysis was performed on surface electroencephalogram recordings to assess neurophysiologic changes induced by chloro-APB and quinpirole during isoflurane general anesthesia. Results: Chloro-APB decreased median time to emergence from 330 to 50 s. The median difference in time to emergence between the saline control group (n = 6) and the chloro-APB group (n = 6) was 222 s (95% CI: 77–534 s, Mann–Whitney test). This difference was statistically significant (P = 0.0082). During continuous isoflurane anesthesia, chloro-APB dose-dependently restored righting (n = 6) and decreased electroencephalogram δ power (n = 4). These effects were inhibited by pretreatment with SCH-23390. Quinpirole did not restore righting (n = 6) and had no significant effect on the electroencephalogram (n = 4) during continuous isoflurane anesthesia. Conclusions: Activation of D1 receptors by chloro-APB decreases time to emergence from isoflurane anesthesia and produces behavioral and neurophysiologic evidence of arousal during continuous isoflurane anesthesia. These findings suggest that selective activation of a D1 receptor–mediated arousal mechanism is sufficient to induce emergence from isoflurane general anesthesia.National Institutes of Health (U.S.) (Grant DP1-OD003646)National Institutes of Health (U.S.) (Grant K08-GM094394)Massachusetts General Hospital. Dept. of Anesthesia and Critical Car

A state-space model of the burst suppression ratio

Burst suppression is an electroencephalogram pattern observed in states of severely reduced brain activity, such as general anesthesia, hypothermia and anoxic brain injuries. The burst suppression ratio (BSR), defined as the fraction of EEG spent in suppression per epoch, is the standard quantitative measure used to characterize burst suppression. We present a state space model to compute a dynamic estimate of the BSR as the instantaneous probability of suppression. We estimate the model using an approximate EM algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia. Our approach removes the need to artificially average the ratio over long epochs and allows us to make formal statistical comparisons of burst activity at different time points. Our state-space model suggests a more principled way to analyze this key EEG feature that may offer more informative assessments of its associated brain state.Massachusetts General Hospital. Dept. of Anesthesia and Critical CareNational Institutes of Health (U.S.) (Grant DP1 OD003646-01)National Institutes of Health (U.S.) (Grant R01 MH071847)National Institutes of Health (U.S.) (Grant K08 GM094394

A Brain-Machine Interface for Control of Medically-Induced Coma

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.National Institutes of Health (U.S.) (Director's Transformative Award R01 GM104948)National Institutes of Health (U.S.) (Pioneer Award DP1-OD003646)National Institutes of Health (U.S.) (NIH K08-GM094394)Massachusetts General Hospital. Dept. of Anesthesia and Critical Car

Burst suppression probability algorithms: state-space methods for tracking EEG burst suppression

Objective. Burst suppression is an electroencephalogram pattern in which bursts of electrical activity alternate with an isoelectric state. This pattern is commonly seen in states of severely reduced brain activity such as profound general anesthesia, anoxic brain injuries, hypothermia and certain developmental disorders. Devising accurate, reliable ways to quantify burst suppression is an important clinical and research problem. Although thresholding and segmentation algorithms readily identify burst suppression periods, analysis algorithms require long intervals of data to characterize burst suppression at a given time and provide no framework for statistical inference. Approach. We introduce the concept of the burst suppression probability (BSP) to define the brain's instantaneous propensity of being in the suppressed state. To conduct dynamic analyses of burst suppression we propose a state-space model in which the observation process is a binomial model and the state equation is a Gaussian random walk. We estimate the model using an approximate expectation maximization algorithm and illustrate its application in the analysis of rodent burst suppression recordings under general anesthesia and a patient during induction of controlled hypothermia. Main result. The BSP algorithms track burst suppression on a second-to-second time scale, and make possible formal statistical comparisons of burst suppression at different times. Significance. The state-space approach suggests a principled and informative way to analyze burst suppression that can be used to monitor, and eventually to control, the brain states of patients in the operating room and in the intensive care unit.National Institutes of Health (U.S.) (Award DP1-OD003646)National Institutes of Health (U.S.) (Award DP2-OD006454)National Institutes of Health (U.S.) (Award K08-GM094394)Burroughs Wellcome Fund (Award 1010625