Intraoperative detection of blood vessels with an imaging needle during neurosurgery in humans

Intracranial hemorrhage can be a devastating complication associated with needle biopsies of the brain. Hemorrhage can occur to vessels located adjacent to the biopsy needle as tissue is aspirated into the needle and removed. No intraoperative technology exists to reliably identify blood vessels that are at risk of damage. To address this problem, we developed an “imaging needle” that can visualize nearby blood vessels in real time. The imaging needle contains a miniaturized optical coherence tomography probe that allows differentiation of blood flow and tissue. In 11 patients, we were able to intraoperatively detect blood vessels (diameter, \u3e500 μm) with a sensitivity of 91.2% and a specificity of 97.7%. This is the first reported use of an optical coherence tomography needle probe in human brain in vivo. These results suggest that imaging needles may serve as a valuable tool in a range of neurosurgical needle interventions

Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data

Earth Science satellite missions provide a unique opportunity for scientists to visualize complex and multifaceted observations projected geospatially across maps of the Earth. While visualization tools can help scientists comprehend, analyze, and share data, visualizing Level-2 Earth Sciences data poses its own specific set of challenges. Since the geospatial information in Level-2 data files is stored as independent variables, the plotting process involves matching dimensional information from latitude and longitude with a desired variable. Variables are stored in different ways across various Earth Science data file formats, which complicates the process of extracting data and plotting variables from a given file without requiring extensive user input and prerequisite familiarity with the file type variable structure. In coordination with NASAs Goddard Earth Sciences Data Information Services Center (GES DISC), the team developed a Level-2 Earth Science data visualization tool that aims to address some of the complexities associated with plotting Level-2 data. This tool offers command-line and user interface support for file and variable selection to accommodate varying use cases and degrees of user familiarity with the structure of a given file. The visualization tool is written in Python 3 and utilizes a modular approach to facilitate continued expansion and reuse. In addressing some common complications involved in plotting Level-2 Earth Sciences data, the tool aims to help to link the process of analysis more directly with data acquisition and visualization, bringing analysis closer to data across levels of processing

DETECTION AND DIAGNOSTICS OF A CORONAL SHOCK WAVE DRIVEN BY A PARTIAL-HALO CORONAL MASS EJECTION ON 2000 JUNE 28

A fast partial-halo coronal mass ejection (CME) was observed on 2000 June 28 by instruments on the SOHO spacecraft. The CME leading edge and filamentary cold core were detected over the northwest limb at 2.32 R? by the SOHO UV Coronagraph Spectrometer (UVCS). The broad profile of the O?VI ?1032 line gives evidence of a shock front at the leading edge, supporting the identification of white-light CME sharp leading edges as fast-mode shocks. Line-of-sight speeds are as high as 1500 km s-1, comparable to the projected speed obtained from LASCO. Pumping of the O?VI ?1032 by Ly? (v = 1810 km s-1) and of O?VI ?1037 by O?VI ?1032 (v = 1648 km s-1) were detected, which provide diagnostics of outflow speed and density. The angle of the ejecta with the plane of the sky is obtained, combining the projected speed from LASCO with the line-of sight-speed, and varies between 7? and 46?. In the latter case the projected height of 2.32 R? was at an actual heliocentric distance of 3.6 R?. An associated solar energetic particle (SEP) event was observed at the L1 point following this CME. The abundance and charge-state data are consistent with a gradual shock-accelerated SEP event. A type II radio burst was observed at the same time the shock front was detected by UVCS

DICER-LIKE2 plays a primary role in transitive silencing of transgenes in Arabidopsis.

Dicer-like (DCL) enzymes play a pivotal role in RNA silencing in plants, processing the long double-stranded RNA (dsRNA) that triggers silencing into the primary short interfering RNAs (siRNAs) that mediate it. The siRNA population can be augmented and silencing amplified via transitivity, an RNA-dependent RNA polymerase (RDR)-dependent pathway that uses the target RNA as substrate to generate secondary siRNAs. Here we report that Arabidopsis DCL2-but not DCL4-is required for transitivity in cell-autonomous, post-transcriptional silencing of transgenes. An insertion mutation in DCL2 blocked sense transgene-induced silencing and eliminated accumulation of the associated RDR-dependent siRNAs. In hairpin transgene-induced silencing, the dcl2 mutation likewise eliminated accumulation of secondary siRNAs and blocked transitive silencing, but did not block silencing mediated by primary siRNAs. Strikingly, in all cases, the dcl2 mutation eliminated accumulation of all secondary siRNAs, including those generated by other DCL enzymes. In contrast, mutations in DCL4 promoted a dramatic shift to transitive silencing in the case of the hairpin transgene and enhanced silencing induced by the sense transgene. Suppression of hairpin and sense transgene silencing by the P1/HC-Pro and P38 viral suppressors was associated with elimination of secondary siRNA accumulation, but the suppressors did not block processing of the stem of the hairpin transcript into primary siRNAs. Thus, these viral suppressors resemble the dcl2 mutation in their effects on siRNA biogenesis. We conclude that DCL2 plays an essential, as opposed to redundant, role in transitive silencing of transgenes and may play a more important role in silencing of viruses than currently thought

A Typology of Federal and State Programs Designed to Promote College Enrollment

Over the past four decades, policymakers have developed numerous policies and programs with the goal of increasing college enrollment. A simple Google search of the phrase college access program generates 226,000,000 hits. Entering the same terms into the search engine on the U.S. Department of Education\u27s Web site generates 500 hits. Despite the apparent plentitude of policies and programs, however, college access and choice for recent high school graduates remain stratified by socioeconomic status and race/ethnicity (Thomas & Perna, 2004). Young people from low-income families and whose parents have not attended college, as well as those of African American and Hispanic descent, are less likely than other young people to enroll in college. When they do enroll, these students find themselves concentrated in lower-priced institutions, such as public two-year colleges and less-selective four-year colleges and universities (Baum & Payea, 2004; Ellwood & Kane, 2000; National Center for Education Statistics [NCES], 2003, 2004; Thomas & Perna, 2004)

GES DISC Data Recipes in Jupyter Notebooks

The Earth Science Data and Information System (ESDIS) Project manages twelve Distributed Active Archive Centers (DAACs) which are geographically dispersed across the United States. The DAACs are responsible for ingesting, processing, archiving, and distributing Earth science data produced from various sources (satellites, aircraft, field measurements, etc.). In response to projections of an exponential increase in data production, there has been a recent effort to prototype various DAAC activities in the cloud computing environment. This, in turn, led to the creation of an initiative, called the Cloud Analysis Toolkit to Enable Earth Science (CATEES), to develop a Python software package in order to transition Earth science data processing to the cloud. This project, in particular, supports CATEES and has two primary goals. One, to transition data recipes created by the Goddard Earth Science Data and Information Service Center (GES DISC) into an interactive and educational environment using JupyterNotebooks. Two, to acclimate Earth scientists to cloud computing. To accomplish these goals, we create JupyterNotebooks to compartmentalize the different steps of data analysis and help users obtain and parse data from the command line. We also develop a Docker container, comprised of Jupyter Notebooks, Python dependencies, and command line tools, and configure it into an easy-to-deploy package. The end result is an end-to-end product that simulates the use case of end users working in the cloud computing environment

Heterogeneity in Readouts of Canonical Wnt Pathway Activity within Intestinal Crypts

BACKGROUND: Canonical Wnt pathway signaling is necessary for maintaining the proliferative capacity of mammalian intestinal crypt base columnar stem cells (CBCs). Furthermore, dysregulation of the Wnt pathway is a major contributor to disease, including oncogenic transformation of the intestinal epithelium. Given the critical importance of this pathway, numerous tools have been used as proxy measures for Wnt pathway activity, yet the relationship between Wnt target gene expression and reporter allele activity within individual cells at the crypt base remains unclear. RESULTS: Here, we describe a novel Axin2-CreERT2-tdTomato allele that efficiently marks both WntHigh CBCs and radioresistant reserve intestinal stem cells. We analyze the molecular and functional identity of Axin2-CreERT2-tdTomato-marked cells using single cell gene expression profiling and tissue regeneration assays and find that Axin2 reporter activity does not necessarily correlate with expression of Wnt target genes and, furthermore, that Wnt target genes themselves vary in their expression patterns at the crypt base. CONCLUSIONS: Wnt target genes and reporter alleles can vary greatly in their cell-type specificity, demonstrating that these proxies cannot be used interchangeably. Furthermore, Axin2-CreERT2-tdTomato is a robust marker of both active and reserve intestinal stem cells and is thus useful for understanding the intestinal stem cell compartment

Posttraumatic Stress Disorder Biomarker — p11

Post-traumatic stress disorder (PTSD) is a chronic and disabling anxiety disorder associated with a traumatic event [1]. It is linked to increased risk of suicide and deficits in social functioning [2, 3]. Despite extensive study in psychiatry, the underlying mechanisms of PTSD are still poorly understood [4, 5]. Currently, the diagnosis for PTSD is based on clinical observation and symptom checklist [4, 6-8] and no laboratory blood-based tests. Although biomarker discovery for PTSD is not easy [8], a reliable biomarker would significantly impact the diagnosis and therapeutic monitoring of PTSD. Developing interventions to identify and treat PTSD requires objective approaches to determining the presence of PTSD [8]. Substantial data indicate several potential biomarkers for PTSD. Of these candidate markers, p11 (S100A10) has been studied in PTSD animal models [7] and in human subjects with PTSD [6]. We found that p11 is over-expressed in both animal models and post-mortem brains of subjects with PTSD [7]. Incorporating testing of p11, a novel biomarker for PTSD, into clinical practice, along with more subjective measures, such as participants’ medical history, mental status, duration of symptoms, and symptom checklist or self-report, would provide additional power to predict impending PTSD. In this chapter, we discuss the biomarker concept and the potential clinical utility of PTSD biomarkers. We further discuss the potential of p11 as a PTSD biomarker and as a tool that may enhance PTSD diagnosis and intervention in health care practice

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format

Functional Activation and Effective Connectivity Differences in Adolescent Marijuana Users Performing a Simulated Gambling Task

Background. Adolescent marijuana use is associated with structural and functional differences in forebrain regions while performing memory and attention tasks. In the present study, we investigated neural processing in adolescent marijuana users experiencing rewards and losses. Fourteen adolescents with frequent marijuana use (\u3e5 uses per week) and 14 nonuser controls performed a computer task where they were required to guess the outcome of a simulated coin flip while undergoing magnetic resonance imaging. Results. Across all participants, ?Wins? and ?Losses? were associated with activations including cingulate, middle frontal, superior frontal, and inferior frontal gyri and declive activations. Relative to controls, users had greater activity in the middle and inferior frontal gyri, caudate, and claustrum during ?Wins? and greater activity in the anterior and posterior cingulate, middle frontal gyrus, insula, claustrum, and declive during ?Losses.? Effective connectivity analyses revealed similar overall network interactions among these regions for users and controls during both ?Wins? and ?Losses.? However, users and controls had significantly different causal interactions for 10 out of 28 individual paths during the ?Losses? condition. Conclusions. Collectively, these results indicate adolescent marijuana users have enhanced neural responses to simulated monetary rewards and losses and relatively subtle differences in effective connectivity