Institution
Temple University
Education•Philadelphia, Pennsylvania, United States•
About: Temple University is a education organization based out in Philadelphia, Pennsylvania, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32154 authors who have published 64375 publications receiving 2219828 citations.
Topics: Population, Poison control, Anxiety, Health care, Receptor
Papers published on a yearly basis
Papers
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TL;DR: The mitochondrial protein MICU1 is demonstrated to be a gatekeeper of MCU-mediated Ca(2+)(m) uptake that is essential to prevent [Ca( 2+)](m) overload and associated stress.
552 citations
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University of Vienna1, University of Edinburgh2, Massey University3, Newcastle University4, University of Copenhagen5, University of Glasgow6, Massachusetts Institute of Technology7, Boston College8, Fred Hutchinson Cancer Research Center9, University of Aberdeen10, San Diego State University11, Institut national de la recherche agronomique12, University of Birmingham13, Agricultural Research Organization, Volcani Center14, University of Jena15, University of Lausanne16, University of Warwick17, University of Amsterdam18, Delft University of Technology19, Temple University20, Technical University of Denmark21, Columbia University22
TL;DR: In this paper, the authors argue that the ability to predict and manage the function of these highly complex, dynamically changing communities is limited, and that close coordination of experimental data collection and method development with mathematical model building is needed to achieve significant progress in understanding of microbial dynamics and function.
Abstract: The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth’s soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model–experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved.
552 citations
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Rotem Botvinik-Nezer1, Rotem Botvinik-Nezer2, Felix Holzmeister3, Colin F. Camerer4 +217 more•Institutions (78)
TL;DR: The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.
Abstract: Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses1. The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset2-5. Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.
551 citations
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01 Oct 2009TL;DR: The existence of a J-shaped distribution is demonstrated, sources of bias that cause this distribution are identified, ways to overcome these biases are proposed, and it is shown that overcoming these biases helps product review systems better predict future product sales.
Abstract: Introduction While product review systems that collect and disseminate opinions about products from recent buyers (Table 1) are valuable forms of word-of-mouth communication, evidence suggests that they are overwhelmingly positive. Kadet notes that most products receive almost five stars. Chevalier and Mayzlin also show that book reviews on Amazon and Barnes & Noble are overwhelmingly positive. Is this because all products are simply outstanding? However, a graphical representation of product reviews reveals a J-shaped distribution (Figure 1) with mostly 5-star ratings, some 1-star ratings, and hardly any ratings in between. What explains this J-shaped distribution? If products are indeed outstanding, why do we also see many 1-star ratings? Why aren't there any product ratings in between? Is it because there are no "average" products? Or, is it because there are biases in product review systems? If so, how can we overcome them? The J-shaped distribution also creates some fundamental statistical problems. Conventional wisdom assumes that the average of the product ratings is a sufficient proxy of product quality and product sales. Many studies used the average of product ratings to predict sales. However, these studies showed inconsistent results: some found product reviews to influence product sales, while others did not. The average is statistically meaningful only when it is based on a unimodal distribution, or when it is based on a symmetric bimodal distribution. However, since product review systems have an asymmetric bimodal (J-shaped) distribution, the average is a poor proxy of product quality. This report aims to first demonstrate the existence of a J-shaped distribution, second to identify the sources of bias that cause the J-shaped distribution, third to propose ways to overcome these biases, and finally to show that overcoming these biases helps product review systems better predict future product sales. We tested the distribution of product ratings for three product categories (books, DVDs, videos) with data from Amazon collected between February--July 2005: 78%, 73%, and 72% of the product ratings for books, DVDs, and videos are greater or equal to four stars (Figure 1), confirming our proposition that product reviews are overwhelmingly positive. Figure 1 (left graph) shows a J-shaped distribution of all products. This contradicts the law of "large numbers" that would imply a normal distribution. Figure 1 (middle graph) shows the distribution of three randomly-selected products in each category with over 2,000 reviews. The results show that these reviews still have a J-shaped distribution, implying that the J-shaped distribution is not due to a "small number" problem. Figure 1 (right graph) shows that even products with a median average review (around 3-stars) follow the same pattern.
551 citations
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TL;DR: Single-agent vemurafenib did not show meaningful clinical activity in patients with BRAF V600E mutant CRC, and combination strategies are now under development and may be informed by the presence of intratumor heterogeneity of KRAS and NRAS mutations.
Abstract: Purpose BRAF V600E mutation is seen in 5% to 8% of patients with metastatic colorectal cancer (CRC) and is associated with poor prognosis. Vemurafenib, an oral BRAF V600 inhibitor, has pronounced activity in patients with metastatic melanoma, but its activity in patients with BRAF V600E–positive metastatic CRC was unknown. Patients and Methods In this multi-institutional, open-label study, patients with metastatic CRC with BRAF V600 mutations were recruited to an expansion cohort at the previously determined maximum-tolerated dose of 960 mg orally twice a day. Results Twenty-one patients were enrolled, of whom 20 had received at least one prior metastatic chemotherapy regimen. Grade 3 toxicities included keratoacanthomas, rash, fatigue, and arthralgia. Of the 21 patients treated, one patient had a confirmed partial response (5%; 95% CI, 1% to 24%) and seven other patients had stable disease by RECIST criteria. Median progression-free survival was 2.1 months. Patterns of concurrent mutations, microsatellit...
551 citations
Authors
Showing all 32360 results
Name | H-index | Papers | Citations |
---|---|---|---|
Robert J. Lefkowitz | 214 | 860 | 147995 |
Rakesh K. Jain | 200 | 1467 | 177727 |
Virginia M.-Y. Lee | 194 | 993 | 148820 |
Yury Gogotsi | 171 | 956 | 144520 |
Timothy A. Springer | 167 | 669 | 122421 |
Ralph A. DeFronzo | 160 | 759 | 132993 |
James J. Collins | 151 | 669 | 89476 |
Robert J. Glynn | 146 | 748 | 88387 |
Edward G. Lakatta | 146 | 858 | 88637 |
Steven Williams | 144 | 1375 | 86712 |
Peter Buchholz | 143 | 1181 | 92101 |
David Goldstein | 141 | 1301 | 101955 |
Scott D. Solomon | 137 | 1145 | 103041 |
Donald B. Rubin | 132 | 515 | 262632 |
Jeffery D. Molkentin | 131 | 482 | 61594 |