Education•Fargo, North Dakota, United States•
About: North Dakota State University is a education organization based out in Fargo, North Dakota, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 9715 authors who have published 19717 publications receiving 493160 citations. The organization is also known as: North Dakota State University of Agriculture and Applied Sciences & NDSU.
Papers published on a yearly basis
TL;DR: In this paper, the authors present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macro-autophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes.
Abstract: In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (in most higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagy-related protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.
•01 May 1997
TL;DR: Survival analysis:techniques for censored and truncated data, Survival analysis: techniques for censored data analysis, survival analysis, and survival analysis techniques for truncated and uncoded data analysis.
Abstract: Survival analysis:techniques for censored and truncated data , Survival analysis:techniques for censored and truncated data , کتابخانه مرکزی دانشگاه علوم پزشکی ایران
TL;DR: The definition, characteristics, and classification of big data along with some discussions on cloud computing are introduced, and research challenges are investigated, with focus on scalability, availability, data integrity, data transformation, data quality, data heterogeneity, privacy, legal and regulatory issues, and governance.
TL;DR: There is no “gold standard” measure of emotional responding, and experiential, physiological, and behavioural measures are all relevant to understanding emotion and cannot be assumed to be interchangeable.
Abstract: A consensual, componential model of emotions conceptualises them as experiential, physiological, and behavioural responses to personally meaningful stimuli. The present review examines this model in terms of whether different types of emotion-evocative stimuli are associated with discrete and invariant patterns of responding in each response system, how such responses are structured, and if such responses converge across different response systems. Across response systems, the bulk of the available evidence favours the idea that measures of emotional responding reflect dimensions rather than discrete states. In addition, experiential, physiological, and behavioural response systems are associated with unique sources of variance, which in turn limits the magnitude of convergence across measures. Accordingly, the authors suggest that there is no “gold standard” measure of emotional responding. Rather, experiential, physiological, and behavioural measures are all relevant to understanding emotion and cannot ...
TL;DR: The consistent relationships between risk perceptions and behavior, larger than suggested by prior meta-analyses, suggest that risk perceptions are rightly placed as core concepts in theories of health behavior.
Abstract: Background: Risk perceptions are central to many health behavior theories. However, the relationship between risk perceptions and behavior, muddied by instances of inappropriate assessment and analysis, often looks weak. Method: A meta-analysis of eligible studies assessing the bivariate association between adult vaccination and perceived likelihood, susceptibility, or severity was conducted. Results: Thirty-four studies met inclusion criteria (N 15,988). Risk likelihood (pooled r .26), susceptibility (pooled r .24), and severity (pooled r .16) significantly predicted vaccination behavior. The risk perception behavior relationship was larger for studies that were prospective, had higher quality risk measures, or had unskewed risk or behavior measures. Conclusions: The consistent relationships between risk perceptions and behavior, larger than suggested by prior meta-analyses, suggest that risk perceptions are rightly placed as core concepts in theories of health behavior.
Showing all 9781 results
|Russell E. Glasgow
|S. Vincent Rajkumar
|Thomas E. Joiner
|James E. Mitchell
|John E. Schulenberg
|Christopher J. Cramer
|Ross D. Crosby
|Mark E. Sorrells
|Mark S. Gordon
|Osvaldo E. Sala
|Gary A. Churchill
|David W. Schindler
|William K. Lauenroth
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