1,006 research outputs found
AN IN SILICO STUDY OF THE DELTA OPIOID RECEPTOR USING SMALL MOLECULES
The DOR is the least studied out of the three opioid receptors (Mu, Kappa, and Delta). The most is known of the Mu Opioid receptor (MOR) and the drugs that target it have led to the global opioid epidemic due to their adverse effects of tolerance and addiction. The DOR is not known for the same adverse effects and therefore, is a promising pharmacological target for the development of new opioid ligands. In this thesis, molecular modeling, simulations and other computational methods are introduced in Chapter 1 where these methods are used to study the activation mechanism of DOR (Chapter 2) and are used to identify novel DOR agonists (Chapter 3). Recently, both the inactive and active conformations of the DOR have been solved. However, the activation mechanism remains to be elusive. In Chapter 2, molecular dynamics (MD) simulations will offer a deeper insight into the dynamics and interactions beginning with the inactive conformation of the receptor when bound to an agonist undergoing a conformational change. Chapter 3 will involve the use of high-throughput screening of new molecules for potential agonist candidates using multiple conformations of the active conformation of the DOR. The top lead compounds subjected further computational analysis on their drug properties to ensure that they do not cause any unwanted side effects. Final lead compounds are available for experimental testing
The Effect of Seasonal Fish Migration on Energy Budgets in Two Coastal Michigan Streams
Migratory fish are known to seasonally enter coastal stream systems but the magnitude of the effects these migrations have on stream energy budgets is not fully understood. The Laurentian Great Lakes have several introduced and native adfluvial fish, where only a few studies have investigated the impacts of their migration on energy budgets in Michigan coastal streams. We quantified the contribution of energy from Chinook salmon (Oncorhynchus tshawytscha) muscle and eggs, steelhead (Oncorhynchus mykiss) eggs, and larval white suckers (Catostomus commersonii) to coastal stream energy budgets. Energy densities and energy delivered to streams were estimated using bomb calorimetry and annual return data from the Little Manistee River Weir and other recent studies. In addition, we compared the energy contribution of these adfluvial fish tissues and aquatic insects to resident stream fish diets in two rivers in western Michigan. Specifically, we examined the energy contribution of Chinook eggs to steelhead parr diets in Bigelow Creek, MI and the contribution of energy by larval white suckers to brown trout (Salmo trutta) and non-migratory rainbow trout (Oncorhynchus mykiss) diets in the Big Manistee River, MI. Our measured energy density values differed markedly from values typically used in the literature, and indicate that some invertebrate groups (Trichoptera) have energy densities that do not significantly differ from salmon eggs which are typically perceived to be energy dense. Our results suggest that steelhead parr in Bigelow Creek consume more energy during the fall when salmon eggs are present. In contrast, large numbers of drifting larval white suckers in the Big Manistee River does not result in an increase in energy intake for trout during spring, but may satisfy base energy needs. Our results suggest that adfluvial fish are an important component of energy transfer between systems and contribute substantial energy to coastal stream energy budgets in Michigan
The Influencer Industry: Constructing And Commodifying Authenticity On Social Media
The most buzzed-about figure in twenty-first century marketing thus far has been the “digital influencer,” industry vernacular for the bloggers, Instagrammers, Pinners, and other social media users who—against the backdrop of widespread economic and professional instability—deliver curated content to audiences on social media and earn income by collaborating with major brands. Driving the rise of this phenomenon have been (1) individuals who want to be recognized as persuasive online (2) advertisers who increasingly direct their budgets to social media, where influencers’ “authentic,” personality-inflected content has proven potent for selling product (3) social media
companies whose tools and rules both advance and encumber these activities and (4) marketing agencies and other marketing-related entities, such as talent agencies and trend forecasters, that build metrics platforms to measure influence, select influencers for advertising campaigns, negotiate deals between influencers and retail brands, and espouse the many benefits of expressing oneself “authentically” online in tandem with corporate sponsors. The precipitous development of an industry around these activities has, since the late 2000s, propelled billions of dollars into the social media economy and helped instigate a chain of events that have and continue to fundamentally change the production of culture. Drawing on 28 in-depth interviews, an analysis of more than 2000 press articles, and participant observation at industry events, this dissertation examines how the above stakeholders construct and negotiate the meaning, value, and practical use of digital influence as they reimagine it as a commodity for the social media age—a commodity whose value shifts in accordance with ever-changing industrial rubrics for cultivating and evaluating authenticity. The dissertation also provides necessary historical-cultural context to the rise of the influencer industry, elucidating its complex roots that predate the digital era. Throughout, I show how in an era where authenticity is increasingly elusive, and trust’s and influence’s meanings as cultural ideals and functions as social
processes are muddied, the influencer industry struggles to pin these concepts down, stabilize and define them, and make money off of these definitions. To this end, the actors involved in the influencer system work together in a variety of ways both intentional and unintentional, with social, industrial, and cultural consequences. These consequences include who can succeed, the shape of technological innovation and regulation, and products themselves. The study offers theoretical and methodological provocations to scholars of influence and authenticity to consider these concepts’ industrially constructed, contextually dependent nature. It also sheds light on practical issues impacted by social- and data-driven consumerism
Health Consequences of Easier Access to Alcohol: New Zealand Evidence
We evaluate the health effects of a reduction in New Zealand\u27s minimum legal purchase age for alcohol. Difference-in-differences (DD) estimates show a substantial increase in alcohol-related hospitalizations among those newly eligible to purchase liquor, around 24.6% (s.e.=5.5%) for males and 22% (s.e.=8.1%) for females. There is less evidence of an effect among ineligible younger cohorts. There is little evidence of alcohol either complementing or substituting for drugs. We do not find evidence that earlier access to alcohol is associated with learning from experience. We also present regression discontinuity estimates, but emphasize DD estimates since in a simulation of a rational addiction model DD estimates are closer than regression discontinuity estimates to the policy\u27s true effect
Misallocation and manufacturing TFP in Colombia
Following Hsieh and Klenow (2009) this paper studies productivity dispersion in Colombian industrial establishments using the Colombian Annual Manufacturing Survey (AMS) from 1982 to 1998. We consider how much a hypothetical removal of firm-level distortions would increase manufacturing productivity in Colombia and compare it with the United States. We find that such a reallocation would increase manufacturing Total Factor Productivity (TFP) in Colombia around 15% more than in the United States in our baseline calibration. We find that distortions have been increasing over time. Productivity gains are larger if we use Colombia’s higher estimated elasticity of output with respect to capital. Furthermore we show that TFP is positively correlated with exporting status, age, size, and location in the Oriental region and the capital of the country
The phosphoinositide 3-kinase-dependent activation of Btk is required for optimal eicosanoid production and generation of reactive oxygen species in antigen-stimulated mast cells
Activated mast cells are a major source of the eicosanoids PGD(2) and leukotriene C(4) (LTC(4)), which contribute to allergic responses. These eicosanoids are produced following the ERK1/2-dependent activation of cytosolic phospholipase A(2), thus liberating arachidonic acid, which is subsequently metabolized by the actions of 5-lipoxygenase and cyclooxygenase to form LTC(4) and PGD(2), respectively. These pathways also generate reactive oxygen species (ROS), which have been proposed to contribute to FcepsilonRI-mediated signaling in mast cells. In this study, we demonstrate that, in addition to ERK1/2-dependent pathways, ERK1/2-independent pathways also regulate FcepsilonRI-mediated eicosanoid and ROS production in mast cells. A role for the Tec kinase Btk in the ERK1/2-independent regulatory pathway was revealed by the significantly attenuated FcepsilonRI-dependent PGD(2), LTC(4), and ROS production in bone marrow-derived mast cells of Btk(-/-) mice. The FcepsilonRI-dependent activation of Btk and eicosanoid and ROS generation in bone marrow-derived mast cells and human mast cells were similarly blocked by the PI3K inhibitors, Wortmannin and LY294002, indicating that Btk-regulated eicosanoid and ROS production occurs downstream of PI3K. In contrast to ERK1/2, the PI3K/Btk pathway does not regulate cytosolic phospholipase A(2) phosphorylation but rather appears to regulate the generation of ROS, LTC(4), and PGD(2) by contributing to the necessary Ca(2+) signal for the production of these molecules. These data demonstrate that strategies to decrease mast cell production of ROS and eicosanoids would have to target both ERK1/2- and PI3K/Btk-dependent pathways
The efficacy of systematic, explicit literacy instruction in kindergarten and first grade
This investigation examined the extent to which teacher implemented systematic, explicit instruction affected the literacy achievement of kindergarten and first grade students. Two cohorts of students in a southwestern United States school district were utilized for this study. Cohort 1 (n=94) received classroom literacy instruction from the state adopted basal reading series. Cohort 2 (n=96) received literacy instruction from the basal series and an additional reading program designed to systematically and explicitly teach phonological awareness, letter name identification, and the alphabetic principle. Each cohort was followed from the middle of kindergarten through the end of first grade. Kindergarten measures included the Texas Primary Reading Inventory (TPRI) tests of phonological awareness, letter naming, letter sound knowledge, and listening comprehension, and were administered at the middle and end of kindergarten. At the beginning of first grade, TPRI phonological awareness, word reading, reading comprehension, and fluency were measured. Middle of year first grade variables were TPRI reading comprehension and fluency. End of the year first grade measures were TPRI word reading, fluency, reading comprehension, and Iowa Test of Basic Skills (ITBS) word analysis, reading comprehension, listening comprehension, vocabulary, and spelling. A MANCOVA was conducted at each interval using English language learner status as the covariate. Hierarchical regression analysis was conducted to determine which variables best predicted end of first grade reading comprehension, word reading, and fluency. Results from the MANCOVA indicated that Cohort 2 outperformed Cohort 1 on kindergarten TPRI measures of phonological awareness, letter naming, and letter sound correspondences. Cohort 2 also performed better than Cohort 1 on first grade TPRI reading comprehension, fluency, and end of year word reading, however, there were no statistically significant differences on the ITBS measures. Conclusions and recommendations for further research and for practice are also discussed
Generalized Forward-Backward Splitting with Penalization for Monotone Inclusion Problems
We introduce a generalized forward-backward splitting method with penalty
term for solving monotone inclusion problems involving the sum of a finite
number of maximally monotone operators and the normal cone to the nonempty set
of zeros of another maximal monotone operator. We show weak ergodic convergence
of the generated sequence of iterates to a solution of the considered monotone
inclusion problem, provided the condition corresponded to the Fitzpatrick
function of the operator describing the set of the normal cone is fulfilled.
Under strong monotonicity of an operator, we show strong convergence of the
iterates. Furthermore, we utilize the proposed method for minimizing a
large-scale hierarchical minimization problem concerning the sum of
differentiable and nondifferentiable convex functions subject to the set of
minima of another differentiable convex function. We illustrate the
functionality of the method through numerical experiments addressing
constrained elastic net and generalized Heron location problems
- …