Instituting Protest (FILM)

The road-trip story of one man looking at how first and fourteenth amendment rights have effected college campuses over time in the United States, while also looking at the possibility of revoking a diploma from a white nationalist for having different views than ones preferential to a certain college

Automatic Extraction of Narrative Structure from Long Form Text

Automatic understanding of stories is a long-time goal of artificial intelligence and natural language processing research communities. Stories literally explain the human experience. Understanding our stories promotes the understanding of both individuals and groups of people; various cultures, societies, families, organizations, governments, and corporations, to name a few. People use stories to share information. Stories are told –by narrators– in linguistic bundles of words called narratives. My work has given computers awareness of narrative structure. Specifically, where are the boundaries of a narrative in a text. This is the task of determining where a narrative begins and ends, a non-trivial task, because people rarely tell one story at a time. People don’t specifically announce when we are starting or stopping our stories: We interrupt each other. We tell stories within stories. Before my work, computers had no awareness of narrative boundaries, essentially where stories begin and end. My programs can extract narrative boundaries from novels and short stories with an F1 of 0.65. Before this I worked on teaching computers to identify which paragraphs of text have story content, with an F1 of 0.75 (which is state of the art). Additionally, I have taught computers to identify the narrative point of view (POV; how the narrator identifies themselves) and diegesis (how involved in the story’s action is the narrator) with F1 of over 0.90 for both narrative characteristics. For the narrative POV, diegesis, and narrative level extractors I ran annotation studies, with high agreement, that allowed me to teach computational models to identify structural elements of narrative through supervised machine learning. My work has given computers the ability to find where stories begin and end in raw text. This allows for further, automatic analysis, like extraction of plot, intent, event causality, and event coreference. These tasks are impossible when the computer can’t distinguish between which stories are told in what spans of text. There are two key contributions in my work: 1) my identification of features that accurately extract elements of narrative structure and 2) the gold-standard data and reports generated from running annotation studies on identifying narrative structure

In Silico Synchronization of Cellular Populations Through Expression Data Deconvolution

Cellular populations are typically heterogenous collections of cells at different points in their respective cell cycles, each with a cell cycle time that varies from individual to individual. As a result, true single-cell behavior, particularly that which is cell-cycle--dependent, is often obscured in population-level (averaged) measurements. We have developed a simple deconvolution method that can be used to remove the effects of asynchronous variability from population-level time-series data. In this paper, we summarize some recent progress in the development and application of our approach, and provide technical updates that result in increased biological fidelity. We also explore several preliminary validation results and discuss several ongoing applications that highlight the method's usefulness for estimating parameters in differential equation models of single-cell gene regulation.Comment: accepted for the 48th ACM/IEEE Design Automation Conferenc

Toxic structures: Speculation and lead exposure in Detroit\u27s single-family rental market

Foreclosure sales permitted investors to purchase large volumes of low-cost residential properties after the last financial crisis, reshaping patterns of property ownership in low-income housing markets across the US. This study links post-foreclosure property acquisitions by investor-landlords to subsequent lead poisoning cases among children under age six living in Detroit, Michigan. We find that the odds of exhibiting elevated blood lead levels (≥ 5 μg/dL) are higher for children living in investor-owned homes purchased through tax foreclosure sale. These findings highlight the potential for property speculation in post-foreclosure housing markets to exacerbate severe and racialized burdens of excess lead toxicity in low-income communities

Comparing Extant Story Classifiers: Results & New Directions

Having access to a large set of stories is a necessary first step for robust and wide-ranging computational narrative modeling; happily, language data - including stories - are increasingly available in electronic form. Unhappily, the process of automatically separating stories from other forms of written discourse is not straightforward, and has resulted in a data collection bottleneck. Therefore researchers have sought to develop reliable, robust automatic algorithms for identifying story text mixed with other non-story text. In this paper we report on the reimplementation and experimental comparison of the two approaches to this task: Gordon\u27s unigram classifier, and Corman\u27s semantic triplet classifier. We cross-analyze their performance on both Gordon\u27s and Corman\u27s corpora, and discuss similarities, differences, and gaps in the performance of these classifiers, and point the way forward to improving their approaches

Generative modeling of the enteric nervous system employing point pattern analysis and graph construction

We describe a generative network model of the architecture of the enteric nervous system (ENS) in the colon employing data from images of human and mouse tissue samples obtained through confocal microscopy. Our models combine spatial point pattern analysis with graph generation to characterize the spatial and topological properties of the ganglia (clusters of neurons and glial cells), the inter-ganglionic connections, and the neuronal organization within the ganglia. We employ a hybrid hardcore-Strauss process for spatial patterns and a planar random graph generation for constructing the spatially embedded network. We show that our generative model may be helpful in both basic and translational studies, and it is sufficiently expressive to model the ENS architecture of individuals who vary in age and health status. Increased understanding of the ENS connectome will enable the use of neuromodulation strategies in treatment and clarify anatomic diagnostic criteria for people with bowel motility disorders.Comment: 17 pages, 5 figure

Fate of the lower extremity in patients with VA-ECMO via femoral cannulation

Background: Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a salvage therapy in patients with severe cardiopulmonary failure. Femoral cannulation is associated with limb complications including ischemia, limb loss, arterial infections and wound infections. This study aims to evaluate these complications and management related to successful outcomes. Methods: A retrospective review was conducted in 17 patients requiring VA- ECMO support via femoral cannulation from 1/ 2010 till 4/2012. After cannulation, all patients had near infared spectroscopy (NIRS) monitoring after cannula placement and most had placement of distal arterial perfusion catheters (DPC). At decannulation, all patients had femoral cutdown with closure of arteriotomies by primary repair or patch angioplasty with bovine pericardium. Primary study endpoints included ischemia, limb loss, arterial infection; secondary endpoints were wound infection and post-discharge symptoms. Results: Seventeen patients were supported with VA-ECMO during the study period with arterial cannula size of 16-20 French. All patients had NIRS monitoring after cannula placement and 13/17 patients had DPC placement, with no subsequent ischemia. Two of 4 patients without DPC developed ischemia; one was decannulated and the other resolved spontaneously. At decannulation, open arterial repair was performed as described. In this study population, simple wound infection occurred in 3/17with Vacuum Assisted Closure (VAC) devices were placed at the timed if appropriate. There were no arterial infections and no instances of limb ischemia requiring amputation. There were no complaints of rest pain during outpatient follow-up. Conclusions: Limb complications related to femoral cannulation for VA-ECMO can lead to prolonged morbidity and limb loss. NIRS and placement of DPC, primary repair of arteriotomy or patch angioplasty, along with aggressive wound care, can dramatically decrease rates of limb ischemia, limb loss and infection

A-to-I RNA editing in the earliest-diverging Eumetazoan phyla

© The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Molecular Biology and Evolution 34 (2017): 1890-1901, doi:10.1093/molbev/msx125.The highly conserved ADAR enzymes, found in all multicellular metazoans, catalyze the editing of mRNA transcripts by the deamination of adenosines to inosines. This type of editing has two general outcomes: site specific editing, which frequently leads to recoding, and clustered editing, which is usually found in transcribed genomic repeats. Here, for the first time, we looked for both editing of isolated sites and clustered, non-specific sites in a basal metazoan, the coral Acropora millepora during spawning event, in order to reveal its editing pattern. We found that the coral editome resembles the mammalian one: it contains more than 500,000 sites, virtually all of which are clustered in non-coding regions that are enriched for predicted dsRNA structures. RNA editing levels were increased during spawning and increased further still in newly released gametes. This may suggest that editing plays a role in introducing variability in coral gametes.This work was supported by the Australian Research Council (to PK), the European Research Council (grant 311257), the I-CORE Program of the Planning and Budgeting Committee in Israel (grants 41/11 and 1796/12), and the Israel Science Foundation (1380/14)

Examining impulsivity as an endophenotype using a behavioral approach: a DRD2 TaqI A and DRD4 48-bp VNTR association study

BACKGROUND: Research on the genetic basis for impulsivity has revealed an array of ambiguous findings. This may be a result of limitations to self-report assessments of impulsivity. Behavioral measures that assess more narrowly defined aspects of impulsivity may clarify genetic influences. This study examined the relationship between possession of the DRD2 TaqI A and DRD4 48 bp VNTR genetic polymorphisms and performance on a behavioral measure of impulsivity, the delay discounting task (DDT), and three traditional self-report measures. METHODS: 195 individuals (42% male) were recruited from a university campus and were assessed in small group sessions using personal computers. Genotyping was conducted using previously established protocols. For the DRD2 TaqI A locus, individuals were designated as possessing at least one copy of the A1 allele (A1+) or not (A1-), and for the DRD4 48-bp VNTR locus, individuals were designated as having at least one long allele (7 repeats or longer, L+) or not (L-). Principal analyses used multiple univariate factorial 2 (A1+/A1-) × 2 (L+/L-) analyses of variance. RESULTS: A significant main effect of A1+ status on DDT performance was evident (p = .006) as well as a significant interaction effect (p = .006) between both genes. No other significant effects were evident on the self-report measures, with the exception of a trend toward an interaction effect on the Sensation Seeking Scale. Exploratory analyses suggested that the significant effects were not a function of population stratification or gender. DISCUSSION: These data suggest that the DRD2 TaqI A and DRD4 VNTR polymorphisms influence impulsivity as measured with a delay discounting task. Specifically, these findings suggest that an interaction between the functional effects of the two unlinked genotypes results in significant difference in the balance of mesolimbic dopaminergic activation relative to frontal-parietal activation. However, these findings are also the first in this area and must be replicated. CONCLUSION: These findings suggest a meaningful interaction between the DRD2 TaqI A and DRD4 VNTR polymorphisms in the expression of impulsivity and provide initial support for the utility of using behavioral measures for clarifying genetic influences on impulsivity

Trade-off between transcriptome plasticity and genome evolution in cephalopods

Author Posting. © The Author(s), 2017. This is the author's version of the work. It is posted here by permission of Cell Press for personal use, not for redistribution. The definitive version was published in Cell 169 (2017): 191-202, doi:10.1016/j.cell.2017.03.025.RNA editing, a post-transcriptional process, allows the diversification of proteomes beyond the genomic blueprint; however it is infrequently used among animals. Recent reports suggesting increased levels of RNA editing in squids thus raise the question of their nature and effects in these organisms. We here show that RNA editing is particularly common in behaviorally sophisticated coleoid cephalopods, with tens of thousands of evolutionarily conserved sites. Editing is enriched in the nervous system affecting molecules pertinent for excitability and neuronal morphology. The genomic sequence flanking editing sites is highly conserved, suggesting that the process confers a selective advantage. Due to the large number of sites, the surrounding conservation greatly reduces the number of mutations and genomic polymorphisms in protein coding regions. This trade-off between genome evolution and transcriptome plasticity highlights the importance of RNA recoding as a strategy for diversifying proteins, particularly those associated with neural function.NLB was supported by a post-doctoral scholarship from the Center for Nanoscience and Nanotechnology, Tel-Aviv University. The research of RU is supported by the Israel Science Foundation (772/13). The research of EYL was supported by the European Research Council (311257) and the Israel Science Foundation (1380/14). The research of JJCR was supported by the National Institutes of Health [1R0111223855, 1R01NS64259], the National Science Foundation (HRD- 1137725), and the Frank R. Lillie and Laura and Arthur Colwin Research Fellowships from the Marine Biological Laboratory in Woods Hole. The work of JJCR and EE was supported by grant No 094/2013 from the United States-Israel Binational Science Foundation (BSF).2018-04-0