Institution
University of New Mexico
Education•Albuquerque, New Mexico, United States•
About: University of New Mexico is a education organization based out in Albuquerque, New Mexico, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 28870 authors who have published 64767 publications receiving 2578371 citations. The organization is also known as: UNM & Universitatis Novus Mexico.
Topics: Population, Poison control, Laser, Health care, Large Hadron Collider
Papers published on a yearly basis
Papers
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TL;DR: The potential use of BDDCS to estimate the disposition characteristics of novel chemicals (new molecular entities) in the early stages of drug discovery and development and the influence of several measured and in silico parameters in the process of B DDCS category assignment is discussed in detail.
Abstract: Here, we compile the Biopharmaceutics Drug Disposition Classification System (BDDCS) classification for 927 drugs, which include 30 active metabolites. Of the 897 parent drugs, 78.8% (707) are administered orally. Where the lowest measured solubility is found, this value is reported for 72.7% (513) of these orally administered drugs and a dose number is recorded. The measured values are reported for percent excreted unchanged in urine, LogP, and LogD
7.4 when available. For all 927 compounds, the in silico parameters for predicted Log solubility in water, calculated LogP, polar surface area, and the number of hydrogen bond acceptors and hydrogen bond donors for the active moiety are also provided, thereby allowing comparison analyses for both in silico and experimentally measured values. We discuss the potential use of BDDCS to estimate the disposition characteristics of novel chemicals (new molecular entities) in the early stages of drug discovery and development. Transporter effects in the intestine and the liver are not clinically relevant for BDDCS class 1 drugs, but potentially can have a high impact for class 2 (efflux in the gut, and efflux and uptake in the liver) and class 3 (uptake and efflux in both gut and liver) drugs. A combination of high dose and low solubility is likely to cause BDDCS class 4 to be underpopulated in terms of approved drugs (N = 53 compared with over 200 each in classes 1–3). The influence of several measured and in silico parameters in the process of BDDCS category assignment is discussed in detail.
536 citations
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University of Notre Dame1, Michigan State University2, University of New Hampshire3, University of Wyoming4, University of Tennessee5, Oak Ridge National Laboratory6, Marine Biological Laboratory7, Oregon State University8, University of Maryland, College Park9, University of New Mexico10, Kansas State University11, United States Department of Agriculture12, Montana State University13, Virginia Tech14, Central Washington University15, Ball State University16, Wright State University17, University of Georgia18, Indiana University19, University of Canterbury20, United States Geological Survey21, Arizona State University22, Washington State University Vancouver23
TL;DR: It is found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N1O, and it is suggested that increased stream NO3− loading stimulatesDenitrification and concomitant N2o production, but does not increase the N2 O yield.
Abstract: Nitrous oxide (N2O) is a potent greenhouse gas that contributes to climate change and stratospheric ozone destruction. Anthropogenic nitrogen (N) loading to river networks is a potentially important source of N2O via microbial denitrification that converts N to N2O and dinitrogen (N2). The fraction of denitrified N that escapes as N2O rather than N2 (i.e., the N2O yield) is an important determinant of how much N2O is produced by river networks, but little is known about the N2O yield in flowing waters. Here, we present the results of whole-stream 15N-tracer additions conducted in 72 headwater streams draining multiple land-use types across the United States. We found that stream denitrification produces N2O at rates that increase with stream water nitrate (NO3−) concentrations, but that <1% of denitrified N is converted to N2O. Unlike some previous studies, we found no relationship between the N2O yield and stream water NO3−. We suggest that increased stream NO3− loading stimulates denitrification and concomitant N2O production, but does not increase the N2O yield. In our study, most streams were sources of N2O to the atmosphere and the highest emission rates were observed in streams draining urban basins. Using a global river network model, we estimate that microbial N transformations (e.g., denitrification and nitrification) convert at least 0.68 Tg·y−1 of anthropogenic N inputs to N2O in river networks, equivalent to 10% of the global anthropogenic N2O emission rate. This estimate of stream and river N2O emissions is three times greater than estimated by the Intergovernmental Panel on Climate Change.
536 citations
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30 Jan 2008536 citations
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TL;DR: In this paper, the authors present a theory of endogenous protection by explicitly modeling government-industry interactions for which mere “black-box” models previously existed, and whether the Grossman-Helman model stands up to real-world data is investigated.
Abstract: Grossman and Helpman (1994) present a theory of endogenous protection by explicitly modeling government-industry interactions for which mere “black-box” models previously existed. They obtain a Ramsey pricing-type solution to the provision of protection which emphasizes the role of inverse import penetration ratios and import elasticities. On the lobbying side, the model makes predictions about lobbying competition and lobbying spending according to deadweight costs from protection. The model not only makes for richer theory in terms of rigor and elegance, but its predictions are directly testable. Whether the Grossman-Helman model stands up to real-world data is investigated in this paper. Predictions from both the protection side and lobbying side are tested using cross-sectional U.S. nontariff barrier data. We also compare the “second-generation” Grossman-Helpman model with a more traditional specification. Our results call for serious consideration of this model in the political economy literature.
536 citations
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01 Jun 2007
TL;DR: In this article, the authors discuss the importance of emotion communication as evidenced in infants through their emotional signaling to caregivers, their social referencing to significant others, and their growing skills at affective sharing with others.
Abstract: The chapter begins by addressing the theoretical platform endorsed by the authors that consists of an integration of functionalist perspectives with dynamic systems and social contextualism. This integrated perspective entails a flexible approach to emotional behavior: Expressive behavior, action tendencies, and cultural influence on emotion meaning all have their place in understanding emotional development. The chapter goes on to examine early emotional development, highlighting the importance of emotion communication as evidenced in infants through their emotional signaling to caregivers, their social referencing to significant others, and their growing skills at affective sharing with others. The final half of the chapter examines the development of eight specific skills of emotional competence, emphasizing their social effectiveness and individual adaptiveness. We conclude with a discussion of future research directions, including what may be the relational limits of emotion, individual differences in emotional responsiveness to contextual cues, attention processes, and emotion-related goals, some of which may become interiorized with development.
Keywords:
adolescent development;
childhood development;
emotion;
emotional competence;
functionalism;
infanct development;
social context;
social effectiveness
536 citations
Authors
Showing all 29120 results
Name | H-index | Papers | Citations |
---|---|---|---|
Bruce S. McEwen | 215 | 1163 | 200638 |
David Miller | 203 | 2573 | 204840 |
Jing Wang | 184 | 4046 | 202769 |
Paul M. Thompson | 183 | 2271 | 146736 |
David A. Weitz | 178 | 1038 | 114182 |
David R. Williams | 178 | 2034 | 138789 |
John A. Rogers | 177 | 1341 | 127390 |
George F. Koob | 171 | 935 | 112521 |
John D. Minna | 169 | 951 | 106363 |
Carlos Bustamante | 161 | 770 | 106053 |
Lewis L. Lanier | 159 | 554 | 86677 |
Joseph Wang | 158 | 1282 | 98799 |
John E. Morley | 154 | 1377 | 97021 |
Fabian Walter | 146 | 999 | 83016 |
Michael F. Holick | 145 | 767 | 107937 |