Institution
Nathan Kline Institute for Psychiatric Research
Nonprofit•Orangeburg, New York, United States•
About: Nathan Kline Institute for Psychiatric Research is a nonprofit organization based out in Orangeburg, New York, United States. It is known for research contribution in the topics: Schizophrenia & Poison control. The organization has 1225 authors who have published 3061 publications receiving 228747 citations. The organization is also known as: Nathan S. Kline Institute for Psychiatric Research.
Papers published on a yearly basis
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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.
5,187 citations
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Rutgers University1, New York University2, University of Oxford3, Harvard University4, Bangor University5, University of Copenhagen6, National Institutes of Health7, Oregon Health & Science University8, Yale University9, Nathan Kline Institute for Psychiatric Research10, Medical College of Wisconsin11, University of Oulu12, Radboud University Nijmegen13, National Yang-Ming University14, Cleveland Clinic15, Duke University16, Max Planck Society17, Emory University18, University of Queensland19, University of Michigan20, Kennedy Krieger Institute21, Washington University in St. Louis22, Technische Universität München23, Leiden University24, University of Texas at Dallas25, Charité26, University of Pittsburgh27, Southeast University28, Otto-von-Guericke University Magdeburg29, Massachusetts Institute of Technology30, University of Western Ontario31, Medical University of Vienna32, Beijing Normal University33
TL;DR: The 1000 Functional Connectomes Project (Fcon_1000) as discussed by the authors is a large-scale collection of functional connectome data from 1,414 volunteers collected independently at 35 international centers.
Abstract: Although it is being successfully implemented for exploration of the genome, discovery science has eluded the functional neuroimaging community. The core challenge remains the development of common paradigms for interrogating the myriad functional systems in the brain without the constraints of a priori hypotheses. Resting-state functional MRI (R-fMRI) constitutes a candidate approach capable of addressing this challenge. Imaging the brain during rest reveals large-amplitude spontaneous low-frequency (<0.1 Hz) fluctuations in the fMRI signal that are temporally correlated across functionally related areas. Referred to as functional connectivity, these correlations yield detailed maps of complex neural systems, collectively constituting an individual's "functional connectome." Reproducibility across datasets and individuals suggests the functional connectome has a common architecture, yet each individual's functional connectome exhibits unique features, with stable, meaningful interindividual differences in connectivity patterns and strengths. Comprehensive mapping of the functional connectome, and its subsequent exploitation to discern genetic influences and brain-behavior relationships, will require multicenter collaborative datasets. Here we initiate this endeavor by gathering R-fMRI data from 1,414 volunteers collected independently at 35 international centers. We demonstrate a universal architecture of positive and negative functional connections, as well as consistent loci of inter-individual variability. Age and sex emerged as significant determinants. These results demonstrate that independent R-fMRI datasets can be aggregated and shared. High-throughput R-fMRI can provide quantitative phenotypes for molecular genetic studies and biomarkers of developmental and pathological processes in the brain. To initiate discovery science of brain function, the 1000 Functional Connectomes Project dataset is freely accessible at www.nitrc.org/projects/fcon_1000/.
2,787 citations
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Columbia University1, University of Oxford2, New York University3, Nathan Kline Institute for Psychiatric Research4, University College London5, University of Pennsylvania6, University of California, Los Angeles7, University of Iowa8, McGill University9, French Institute of Health and Medical Research10, French Institute for Research in Computer Science and Automation11, John Radcliffe Hospital12, Imperial College London13, Mauna Kea Technologies14
TL;DR: This study is the largest evaluation of nonlinear deformation algorithms applied to brain image registration ever conducted and suggests that the findings are generalizable to new subject populations that are labeled or evaluated using different labeling protocols.
2,214 citations
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New York University1, Nathan Kline Institute for Psychiatric Research2, MIND Institute3, Katholieke Universiteit Leuven4, University of Utah5, Yale University6, University of California, Los Angeles7, Massachusetts Institute of Technology8, Trinity College, Dublin9, Ben-Gurion University of the Negev10, Carnegie Mellon University11, Ludwig Maximilian University of Munich12, Oregon Health & Science University13, Indiana University14, California Institute of Technology15, San Diego State University16, Netherlands Institute for Neuroscience17, University of Groningen18, University of Wisconsin-Madison19, Cornell University20, University of Pittsburgh21, Stanford University22, University of Michigan23, Kennedy Krieger Institute24, Johns Hopkins University25
TL;DR: W Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity.
Abstract: Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.
1,939 citations
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TL;DR: The genome-wide characteristics of rare (<1% frequency) copy number variation in ASD are analysed using dense genotyping arrays to reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
Abstract: The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
1,919 citations
Authors
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Name | H-index | Papers | Citations |
---|---|---|---|
Marjo-Riitta Järvelin | 156 | 923 | 100939 |
Jeffrey A. Lieberman | 145 | 706 | 85306 |
Paul M. Matthews | 140 | 617 | 88802 |
Joseph E. LeDoux | 139 | 478 | 91500 |
Daniel C. Javitt | 112 | 406 | 39413 |
Peter R. Schofield | 109 | 693 | 50892 |
Ralph A. Nixon | 102 | 317 | 45855 |
Michael P. Milham | 99 | 317 | 42144 |
Donald F. Klein | 96 | 514 | 32835 |
F. Xavier Castellanos | 96 | 236 | 42904 |
Jeffrey Kaye | 91 | 425 | 38849 |
Steven H. Ferris | 89 | 317 | 38506 |
Donald C. Goff | 88 | 319 | 25782 |
Karen Duff | 87 | 180 | 31810 |
John J. Foxe | 87 | 334 | 26171 |