- Allele Loss and Reduced Expression of CYCLOPS Genes is a Characteristic Feature of Chromophobe Renal Cell Carcinoma. [Journal Article]
- TOTransl Oncol 2019 Jun 11; 12(9):1131-1137
- Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS (CYCLOPS) genes have been recently identified as the most enriched class of copy-number associated gene dependencies in human…
Copy-number alterations Yielding Cancer Liabilities Owing to Partial losS (CYCLOPS) genes have been recently identified as the most enriched class of copy-number associated gene dependencies in human cancer. These genes are cell essential and render tumor cells highly sensitive to the expression of the remaining copy. Chromophobe renal cell carcinoma (chRCC) is characterized by frequent chromosomal deletions, but the relevance of CYCLOPS genes in this tumor subtype is unclear. We found 39 (31%) of 124 recently published candidate CYCLOPS genes (B. Paolella et al., eLife 2017;6:e23268) located on 7 autosomes that are frequently lost in chRCC. GISTIC and RNA-seq data obtained from the TCGA-KICH database showed that 62% of these CYCLOPS genes had significantly lower expression levels in samples with deletion of the respective gene. As copy number (CN) loss of the CYCLOPS gene SF3B1 (Splicing factor 3B subunit 1) has been recently reported in 71% chRCC, we explored the relevance of SF3B1 CN alteration and SF3B1 expression in a set of chRCC and additional oncocytic renal neoplasms. The frequency of SF3B1 CN loss (65%) was similar to that obtained from the TCGA-KICH database and correlated significantly with both lower SF3B1 mRNA (P < .05) and protein expression (P < .001). Other tumor subtypes with oncocytic cytoplasm had normal SF3B1 CN and displayed strong SF3B1 protein expression. These results suggest that CN loss of CYCLOPS genes is a characteristic feature in chRCC. Since many CYCLOPS genes code for components of proteasomes and transcriptional regulation, their alteration could make chRCC vulnerable to targeted drugs.
- White matter hyperintensity quantification in large-scale clinical acute ischemic stroke cohorts - The MRI-GENIE study. [Journal Article]
- NCNeuroimage Clin 2019 May 29; 23:101884
- White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However,…
White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited.
- Visual cognition in non-amnestic Alzheimer's disease: Relations to tau, amyloid, and cortical atrophy. [Journal Article]
- NCNeuroimage Clin 2019 Jun 04; 23:101889
- Heterogeneity within the Alzheimer's disease (AD) syndromic spectrum is typically classified in a domain-specific manner (e.g., language vs. visual cognitive function). The central aim of this study …
Heterogeneity within the Alzheimer's disease (AD) syndromic spectrum is typically classified in a domain-specific manner (e.g., language vs. visual cognitive function). The central aim of this study was to investigate whether impairment in visual cognitive tasks thought to be subserved by posterior cortical dysfunction in non-amnestic AD presentations is associated with tau, amyloid, or neurodegeneration in those regions using 18F-AV-1451 and 11C-PiB positron emission tomography (PET) and magnetic resonance imaging (MRI). Sixteen amyloid-positive patients who met criteria for either Posterior Cortical Atrophy (PCA; n = 10) or logopenic variant Primary Progressive Aphasia (lvPPA; n = 6) were studied. All participants underwent a structured clinical assessment, neuropsychological battery, structural MRI, amyloid PET, and tau PET. The neuropsychological battery included two visual cognitive tests: VOSP Number Location and Benton Facial Recognition. Surface-based whole-cortical general linear models were used to first explore the similarities and differences between these biomarkers in the two patient groups, and then to assess their regional associations with visual cognitive test performance. The results show that these two variants of AD have both dissociable and overlapping areas of tau and atrophy, but amyloid is distributed with a stereotyped localization in both variants. Performance on both visual cognitive tests were associated with tau and atrophy in the right lateral and medial occipital association cortex, superior parietal cortex, and posterior ventral occipitotemporal cortex. No cortical associations were observed with amyloid PET. We further demonstrate that cortical atrophy has a partially mediating effect on the association between tau pathology and visual cognitive task performance. Our findings show that non-amnestic variants of AD have partially dissociable spatial patterns of tau and atrophy that localize as expected based on symptoms, but similar patterns of amyloid. Further, we demonstrate that impairments of visual cognitive dysfunction are strongly associated with tau in visual cortical regions and mediated in part by atrophy.
- An attempt to conceptually replicate the dissociation between syntax and semantics during sentence comprehension. [Journal Article]
- NNeuroscience 2019 Jun 11
- Is sentence structure processed by the same neural and cognitive resources that are recruited for processing word meanings, or do structure and meaning rely on distinct resources? Linguistic theorizi…
Is sentence structure processed by the same neural and cognitive resources that are recruited for processing word meanings, or do structure and meaning rely on distinct resources? Linguistic theorizing and much behavioral evidence suggest tight integration between lexico-semantic and syntactic representations and processing. However, most current proposals of the neural architecture of language continue to postulate a distinction between the two. One of the earlier and most cited pieces of neuroimaging evidence in favor of this dissociation comes from a paper by Dapretto & Bookheimer (1999). Using a sentence-meaning judgment task, Dapretto & Bookheimer observed two distinct peaks within the left inferior frontal gyrus (LIFG): one more active during a lexico-semantic manipulation, and the other - during a syntactic manipulation. Although the paper is highly cited, no attempt has been made, to our knowledge, to replicate the original finding. We report an fMRI study that attempts to do so. Using a combination of whole-brain, group-level ROI, and participant-specific functional ROI approaches, we fail to replicate the original dissociation. In particular, whereas parts of LIFG respond reliably more strongly during lexico-semantic than syntactic processing, no part of LIFG (including in the region defined around the peak reported by Dapretto & Bookheimer) shows the opposite pattern. We speculate that the original result was a false positive, possibly driven by a small subset of participants or items that biased a fixed-effects analysis with low power.
- Global Health-related Training Opportunities: A National Survey of Pulmonary and Critical Care Medicine Fellowship Programs. [Journal Article]
- AAAnn Am Thorac Soc 2019 Jun 14
- CONCLUSIONS: PCCM program leaders are interested in offering global health-related training opportunities, but important barriers include lack of mentorship, dedicated fellowship time, and established global partnerships. Future research is needed to better understand global health-related interests and training needs of incoming fellows, and to design creative solutions for providing global health-related training across academic institutions with variable global health-related training capacities.
- Proactive Population Health Strategy to Offer Tobacco Dependence Treatment to Smokers in a Primary Care Practice Network. [Journal Article]
- JGJ Gen Intern Med 2019 Jun 13
- CONCLUSIONS: Smokers responding to a population-based, proactive outreach strategy had better provision of tobacco cessation treatment when referred to either a health system-based or community-based program compared with usual care. The health system-based strategy outperformed the quitline-based one in several measures. Future work should aim to improve population reach and test the effect on smoking cessation rates.
- Communicating Uncertainty: a Narrative Review and Framework for Future Research. [Review]
- JGJ Gen Intern Med 2019 Jun 13
- Discussing the uncertainty associated with a clinical decision is thought to be a critical element of shared decision-making. Yet, empirical evidence suggests that clinicians rarely communicate clini…
Discussing the uncertainty associated with a clinical decision is thought to be a critical element of shared decision-making. Yet, empirical evidence suggests that clinicians rarely communicate clinical uncertainty to patients, and indeed the culture within healthcare environments is often to equate uncertainty with ignorance or failure. Understanding the rationale for discussion of uncertainty along with the current evidence about approaches to communicating and managing uncertainty can advance shared decision-making as well as highlight gaps in evidence. With an increasing focus on personalized healthcare, and advances in genomics and new disease biomarkers, a more sophisticated understanding of how to communicate the limitations and errors that come from applying population-based, epidemiologic findings to predict individuals' futures is going to be essential. This article provides a narrative review of studies relating to the communication of uncertainty, highlighting current strategies together with challenges and barriers, and outlining a framework for future research.
- Publisher Correction: Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. [Published Erratum]
- SRSci Rep 2019 Jun 14; 9(1):8721
- A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
- A machine learning approach to predicting psychosis using semantic density and latent content analysis. [Journal Article]
- NSNPJ Schizophr 2019 Jun 13; 5(1):9
- Subtle features in people's everyday language may harbor the signs of future mental illness. Machine learning offers an approach for the rapid and accurate extraction of these signs. Here we investig…
Subtle features in people's everyday language may harbor the signs of future mental illness. Machine learning offers an approach for the rapid and accurate extraction of these signs. Here we investigate two potential linguistic indicators of psychosis in 40 participants of the North American Prodrome Longitudinal Study. We demonstrate how the linguistic marker of semantic density can be obtained using the mathematical method of vector unpacking, a technique that decomposes the meaning of a sentence into its core ideas. We also demonstrate how the latent semantic content of an individual's speech can be extracted by contrasting it with the contents of conversations generated on social media, here 30,000 contributors to Reddit. The results revealed that conversion to psychosis is signaled by low semantic density and talk about voices and sounds. When combined, these two variables were able to predict the conversion with 93% accuracy in the training and 90% accuracy in the holdout datasets. The results point to a larger project in which automated analyses of language are used to forecast a broad range of mental disorders well in advance of their emergence.
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- Simulating multiple faceted variability in single cell RNA sequencing. [Journal Article]
- NCNat Commun 2019 Jun 13; 10(1):2611
- The abundance of new computational methods for processing and interpreting transcriptomes at a single cell level raises the need for in silico platforms for evaluation and validation. Here, we presen…
The abundance of new computational methods for processing and interpreting transcriptomes at a single cell level raises the need for in silico platforms for evaluation and validation. Here, we present SymSim, a simulator that explicitly models the processes that give rise to data observed in single cell RNA-Seq experiments. The components of the SymSim pipeline pertain to the three primary sources of variation in single cell RNA-Seq data: noise intrinsic to the process of transcription, extrinsic variation indicative of different cell states (both discrete and continuous), and technical variation due to low sensitivity and measurement noise and bias. We demonstrate how SymSim can be used for benchmarking methods for clustering, differential expression and trajectory inference, and for examining the effects of various parameters on their performance. We also show how SymSim can be used to evaluate the number of cells required to detect a rare population under various scenarios.