ASU Scholarship Showcase

Illicit psychostimulant addiction remains a significant problem worldwide, despite decades of research into the neural underpinnings and various treatment approaches. The purpose of this review is to provide a succinct overview of the neurocircuitry involved in drug addiction, as well as the acute and chronic effects of cocaine and amphetamines within this circuitry in humans. Investigational pharmacological treatments for illicit psychostimulant addiction are also reviewed. Our current knowledge base clearly demonstrates that illicit psychostimulants produce lasting adaptive neural and behavioral changes that contribute to the progression and maintenance of addiction. However, attempts at generating pharmacological treatments for psychostimulant addiction have historically focused on intervening at the level of the acute effects of these drugs. The lack of approved pharmacological treatments for psychostimulant addiction highlights the need for new treatment strategies, especially those that prevent or ameliorate the adaptive neural, cognitive, and behavioral changes caused by chronic use of this class of illicit drugs.

Attention deficit/hyperactivity disorder (ADHD) is a risk factor for tobacco use and dependence. This study examines the responsiveness to nicotine of an adolescent model of ADHD, the spontaneously hypertensive rat (SHR). The conditioned place preference (CPP) procedure was used to assess nicotine-induced locomotion and conditioned reward in SHR and the Wistar Kyoto (WKY) control strain over a range of nicotine doses (0.0, 0.1, 0.3 and 0.6 mg/kg). Prior to conditioning, SHRs were more active and less biased toward one side of the CPP chamber than WKY rats. Following conditioning, SHRs developed CPP to the highest dose of nicotine (0.6 mg/kg), whereas WKYs did not develop CPP to any nicotine dose tested. During conditioning, SHRs displayed greater locomotor activity in the nicotine-paired compartment than in the saline-paired compartment across conditioning trials. SHRs that received nicotine (0.1, 0.3, 0.6 mg/kg) in the nicotine-paired compartment showed an increase in locomotor activity between conditioning trials. Nicotine did not significantly affect WKY locomotor activity. These findings suggest that the SHR strain is a suitable model for studying ADHD-related nicotine use and dependence, but highlights potential limitations of the WKY control strain and the CPP procedure for modeling ADHD-related nicotine reward.

Positive allosteric modulators (PAMs) of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors are a diverse class of compounds that increase fast excitatory transmission in the brain. AMPA PAMs have been shown to facilitate long-term potentiation, strengthen communication between various cortical and subcortical regions, and some of these compounds increase the production and release of brain-derived neurotrophic factor (BDNF) in an activity-dependent manner. Through these mechanisms, AMPA PAMs have shown promise as broad spectrum pharmacotherapeutics in preclinical and clinical studies for various neurodegenerative and psychiatric disorders. In recent years, a small collection of preclinical animal studies has also shown that AMPA PAMs may have potential as pharmacotherapeutic adjuncts to extinction-based or cue-exposure therapies for the treatment of drug addiction. The present paper will review this preclinical literature, discuss novel data collected in our laboratory, and recommend future research directions for the possible development of AMPA PAMs as anti-addiction medications.

Background: Increasing our understanding of the factors affecting the severity of the 2009 A/H1N1 influenza pandemic in different regions of the world could lead to improved clinical practice and mitigation strategies for future influenza pandemics. Even though a number of studies have shed light into the risk factors associated with severe outcomes of 2009 A/H1N1 influenza infections in different populations (e.g., [1-5]), analyses of the determinants of mortality risk spanning multiple pandemic waves and geographic regions are scarce. Between-country differences in the mortality burden of the 2009 pandemic could be linked to differences in influenza case management, underlying population health, or intrinsic differences in disease transmission [6]. Additional studies elucidating the determinants of disease severity globally are warranted to guide prevention efforts in future influenza pandemics.

In Mexico, the 2009 A/H1N1 influenza pandemic was characterized by a three-wave pattern occurring in the spring, summer, and fall of 2009 with substantial geographical heterogeneity [7]. A recent study suggests that Mexico experienced high excess mortality burden during the 2009 A/H1N1 influenza pandemic relative to other countries [6]. However, an assessment of potential factors that contributed to the relatively high pandemic death toll in Mexico are lacking. Here, we fill this gap by analyzing a large series of laboratory-confirmed A/H1N1 influenza cases, hospitalizations, and deaths monitored by the Mexican Social Security medical system during April 1 through December 31, 2009 in Mexico. In particular, we quantify the association between disease severity, hospital admission delays, and neuraminidase inhibitor use by demographic characteristics, pandemic wave, and geographic regions of Mexico.

Methods: We analyzed a large series of laboratory-confirmed pandemic A/H1N1 influenza cases from a prospective surveillance system maintained by the Mexican Social Security system, April-December 2009. We considered a spectrum of disease severity encompassing outpatient visits, hospitalizations, and deaths, and recorded demographic and geographic information on individual patients. We assessed the impact of neuraminidase inhibitor treatment and hospital admission delay (≤ > 2 days after disease onset) on the risk of death by multivariate logistic regression.

Results: Approximately 50% of all A/H1N1-positive patients received antiviral medication during the Spring and Summer 2009 pandemic waves in Mexico while only 9% of A/H1N1 cases received antiviral medications during the fall wave (P < 0.0001). After adjustment for age, gender, and geography, antiviral treatment significantly reduced the risk of death (OR = 0.52 (95% CI: 0.30, 0.90)) while longer hospital admission delays increased the risk of death by 2.8-fold (95% CI: 2.25, 3.41).

Conclusions: Our findings underscore the potential impact of decreasing admission delays and increasing antiviral use to mitigate the mortality burden of future influenza pandemics.

Network reconstruction is a fundamental problem for understanding many complex systems with unknown interaction structures. In many complex systems, there are indirect interactions between two individuals without immediate connection but with common neighbors. Despite recent advances in network reconstruction, we continue to lack an approach for reconstructing complex networks with indirect interactions. Here we introduce a two-step strategy to resolve the reconstruction problem, where in the first step, we recover both direct and indirect interactions by employing the Lasso to solve a sparse signal reconstruction problem, and in the second step, we use matrix transformation and optimization to distinguish between direct and indirect interactions. The network structure corresponding to direct interactions can be fully uncovered. We exploit the public goods game occurring on complex networks as a paradigm for characterizing indirect interactions and test our reconstruction approach. We find that high reconstruction accuracy can be achieved for both homogeneous and heterogeneous networks, and a number of empirical networks in spite of insufficient data measurement contaminated by noise. Although a general framework for reconstructing complex networks with arbitrary types of indirect interactions is yet lacking, our approach opens new routes to separate direct and indirect interactions in a representative complex system.

Recently, the phenomenon of quantum-classical correspondence breakdown was uncovered in optomechanics, where in the classical regime the system exhibits chaos but in the corresponding quantum regime the motion is regular - there appears to be no signature of classical chaos whatsoever in the corresponding quantum system, generating a paradox. We find that transient chaos, besides being a physically meaningful phenomenon by itself, provides a resolution. Using the method of quantum state diffusion to simulate the system dynamics subject to continuous homodyne detection, we uncover transient chaos associated with quantum trajectories. The transient behavior is consistent with chaos in the classical limit, while the long term evolution of the quantum system is regular. Transient chaos thus serves as a bridge for the quantum-classical transition (QCT). Strikingly, as the system transitions from the quantum to the classical regime, the average chaotic transient lifetime increases dramatically (faster than the Ehrenfest time characterizing the QCT for isolated quantum systems). We develop a physical theory to explain the scaling law.

Background: Use of synthetic cathinones, which are designer stimulants found in “bath salts,” has increased dramatically in recent years. Following governmental bans of methylenedioxypyrovalerone, mephedrone, and methylone, a second generation of synthetic cathinones with unknown abuse liability has emerged as replacements.

Methods: Using a discrete trials current intensity threshold intracranial self-stimulation procedure, the present study assessed the effects of 2 common second-generation synthetic cathinones, α‐pyrrolidinopentiophenone (0.1–5mg/kg) and 4-methyl-N-ethcathinone (1–100mg/kg) on brain reward function. Methamphetamine (0.1–3mg/kg) was also tested for comparison purposes.

Results: Results revealed both α‐pyrrolidinopentiophenone and 4-methyl-N-ethcathinone produced significant intracranial self-stimulation threshold reductions similar to that of methamphetamine. α‐Pyrrolidinopentiophenone (1mg/kg) produced a significant maximal reduction in intracranial self-stimulation thresholds (~19%) most similar to maximal reductions produced by methamphetamine (1mg/kg, ~20%). Maximal reductions in intracranial self-stimulation thresholds produced by 4-methyl-N-ethcathinone were observed at 30mg/kg (~15%) and were comparable with those observed with methamphetamine and α‐pyrrolidinopentiophenone tested at the 0.3-mg/kg dose (~14%). Additional analysis of the ED50 values from log-transformed data revealed the rank order potency of these drugs as methamphetamine ≈ α‐pyrrolidinopentiophenone>4-methyl-N-ethcathinone.

Conclusions: These data suggest that the newer second-generation synthetic cathinones activate the brain reward circuitry and thus may possess a similar degree of abuse potential as prototypical illicit psychostimulants such as methamphetamine as well as the first generation synthetic cathinone methylenedioxypyrovalerone, as previously reported.

A remarkable phenomenon in spatiotemporal dynamical systems is chimera state, where the structurally and dynamically identical oscillators in a coupled networked system spontaneously break into two groups, one exhibiting coherent motion and another incoherent. This phenomenon was typically studied in the setting of non-local coupling configurations. We ask what can happen to chimera states under systematic changes to the network structure when links are removed from the network in an orderly fashion but the local coupling topology remains invariant with respect to an index shift. We find the emergence of multicluster chimera states. Remarkably, as a parameter characterizing the amount of link removal is increased, chimera states of distinct numbers of clusters emerge and persist in different parameter regions. We develop a phenomenological theory, based on enhanced or reduced interactions among oscillators in different spatial groups, to explain why chimera states of certain numbers of clusters occur in certain parameter regions. The theoretical prediction agrees well with numerics.

In spite of the recent interest and advances in linear controllability of complex networks, controlling nonlinear network dynamics remains an outstanding problem. Here we develop an experimentally feasible control framework for nonlinear dynamical networks that exhibit multistability. The control objective is to apply parameter perturbation to drive the system from one attractor to another, assuming that the former is undesired and the latter is desired. To make our framework practically meaningful, we consider restricted parameter perturbation by imposing two constraints: it must be experimentally realizable and applied only temporarily. We introduce the concept of attractor network, which allows us to formulate a quantifiable controllability framework for nonlinear dynamical networks: a network is more controllable if the attractor network is more strongly connected. We test our control framework using examples from various models of experimental gene regulatory networks and demonstrate the beneficial role of noise in facilitating control.

Background: Highly refined surveillance data on the 2009 A/H1N1 influenza pandemic are crucial to quantify the spatial and temporal characteristics of the pandemic. There is little information about the spatial-temporal dynamics of pandemic influenza in South America. Here we provide a quantitative description of the age-specific morbidity pandemic patterns across administrative areas of Peru.

Methods: We used daily cases of influenza-like-illness, tests for A/H1N1 influenza virus infections, and laboratory-confirmed A/H1N1 influenza cases reported to the epidemiological surveillance system of Peru's Ministry of Health from May 1 to December 31, 2009. We analyzed the geographic spread of the pandemic waves and their association with the winter school vacation period, demographic factors, and absolute humidity. We also estimated the reproduction number and quantified the association between the winter school vacation period and the age distribution of cases.

Results: The national pandemic curve revealed a bimodal winter pandemic wave, with the first peak limited to school age children in the Lima metropolitan area, and the second peak more geographically widespread. The reproduction number was estimated at 1.6–2.2 for the Lima metropolitan area and 1.3–1.5 in the rest of Peru. We found a significant association between the timing of the school vacation period and changes in the age distribution of cases, while earlier pandemic onset was correlated with large population size. By contrast there was no association between pandemic dynamics and absolute humidity.

Conclusions: Our results indicate substantial spatial variation in pandemic patterns across Peru, with two pandemic waves of varying timing and impact by age and region. Moreover, the Peru data suggest a hierarchical transmission pattern of pandemic influenza A/H1N1 driven by large population centers. The higher reproduction number of the first pandemic wave could be explained by high contact rates among school-age children, the age group most affected during this early wave.