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Institution

Boston Children's Hospital

HealthcareBoston, Massachusetts, United States
About: Boston Children's Hospital is a healthcare organization based out in Boston, Massachusetts, United States. It is known for research contribution in the topics: Population & Medicine. The organization has 165409 authors who have published 215589 publications receiving 6885627 citations.


Papers
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Journal ArticleDOI
TL;DR: Three subgroups comprise the TRP channel family; the best understood of these mediates responses to painful stimuli, and other proposed functions include repletion of intracellular calcium stores, receptor-mediated excitation and modulation of the cell cycle.
Abstract: Mammalian homologues of the Drosophila transient receptor potential (TRP) channel gene encode a family of at least 20 ion channel proteins. They are widely distributed in mammalian tissues, but their specific physiological functions are largely unknown. A common theme that links the TRP channels is their activation or modulation by phosphatidylinositol signal transduction pathways. The channel subunits have six transmembrane domains that most probably assemble into tetramers to form non-selective cationic channels, which allow for the influx of calcium ions into cells. Three subgroups comprise the TRP channel family; the best understood of these mediates responses to painful stimuli. Other proposed functions include repletion of intracellular calcium stores, receptor-mediated excitation and modulation of the cell cycle.

1,130 citations

Journal ArticleDOI
TL;DR: The importance of a plant-based diet is evident from the current dietary recommendations that emphasize an increase in the proportion and amount of fruit and vegetables that should be consumed, and interpretation of the role of individual components of the diet is difficult from epidemiologic and dietary studies.

1,129 citations

Journal ArticleDOI
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

1,129 citations

Posted ContentDOI
Konrad J. Karczewski1, Konrad J. Karczewski2, Laurent C. Francioli2, Laurent C. Francioli1, Grace Tiao2, Grace Tiao1, Beryl B. Cummings2, Beryl B. Cummings1, Jessica Alföldi1, Jessica Alföldi2, Qingbo Wang2, Qingbo Wang1, Ryan L. Collins1, Ryan L. Collins2, Kristen M. Laricchia2, Kristen M. Laricchia1, Andrea Ganna2, Andrea Ganna3, Andrea Ganna1, Daniel P. Birnbaum2, Laura D. Gauthier2, Harrison Brand2, Harrison Brand1, Matthew Solomonson1, Matthew Solomonson2, Nicholas A. Watts2, Nicholas A. Watts1, Daniel R. Rhodes4, Moriel Singer-Berk2, Eleanor G. Seaby2, Eleanor G. Seaby1, Jack A. Kosmicki2, Jack A. Kosmicki1, Raymond K. Walters1, Raymond K. Walters2, Katherine Tashman1, Katherine Tashman2, Yossi Farjoun2, Eric Banks2, Timothy Poterba1, Timothy Poterba2, Arcturus Wang2, Arcturus Wang1, Cotton Seed1, Cotton Seed2, Nicola Whiffin5, Nicola Whiffin2, Jessica X. Chong6, Kaitlin E. Samocha7, Emma Pierce-Hoffman2, Zachary Zappala8, Zachary Zappala2, Anne H. O’Donnell-Luria9, Anne H. O’Donnell-Luria1, Anne H. O’Donnell-Luria2, Eric Vallabh Minikel2, Ben Weisburd2, Monkol Lek10, Monkol Lek2, James S. Ware2, James S. Ware5, Christopher Vittal2, Christopher Vittal1, Irina M. Armean1, Irina M. Armean2, Irina M. Armean11, Louis Bergelson2, Kristian Cibulskis2, Kristen M. Connolly2, Miguel Covarrubias2, Stacey Donnelly2, Steven Ferriera2, Stacey Gabriel2, Jeff Gentry2, Namrata Gupta2, Thibault Jeandet2, Diane Kaplan2, Christopher Llanwarne2, Ruchi Munshi2, Sam Novod2, Nikelle Petrillo2, David Roazen2, Valentin Ruano-Rubio2, Andrea Saltzman2, Molly Schleicher2, Jose Soto2, Kathleen Tibbetts2, Charlotte Tolonen2, Gordon Wade2, Michael E. Talkowski1, Michael E. Talkowski2, Benjamin M. Neale1, Benjamin M. Neale2, Mark J. Daly2, Daniel G. MacArthur1, Daniel G. MacArthur2 
30 Jan 2019-bioRxiv
TL;DR: Using an improved human mutation rate model, human protein-coding genes are classified along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.
Abstract: Summary Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism’s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes. Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved model of human mutation, we classify human protein-coding genes along a spectrum representing intolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

1,128 citations

Journal ArticleDOI
TL;DR: IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.
Abstract: It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. IDSA considers adherence to these guidelines to be voluntary, with the ultimate determination regarding their application to be made by the physician in the light of each patient's individual circumstances.

1,124 citations


Authors

Showing all 165661 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
Frederick E. Shelton3271485295883
Robert Langer2812324326306
Graham A. Colditz2611542256034
Frank B. Hu2501675253464
George M. Whitesides2401739269833
Eugene Braunwald2301711264576
Ralph B. D'Agostino2261287229636
Mark J. Daly204763304452
Eric B. Rimm196988147119
Virginia M.-Y. Lee194993148820
Bernard Rosner1901162147661
Stuart H. Orkin186715112182
Mark Hallett1861170123741
Ralph Weissleder1841160142508
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202380
2022447
202119,544
202016,558
201913,868
201812,020