1952: Abilene Christian College Bible Lectures - Full Text

Delivered in the Auditorium of Abilene Christian College, February, 1952 ABILENE, TEXAS PRICE, $3.00 firm foundation publishing house Box 77 Austin Cl, Texa

The Phoenix Mars Landing: An Initial Look

This presentation was part of the session : Ongoing and Proposed EDL Technology DevelopmentSixth International Planetary Probe WorkshopNASA's Phoenix Mars Lander will make a landing on Mars on May 25th, 2008. Following on from the overview of the Phoenix entry, descent and landing (EDL) system given at IPPW5, an initial look at the Phoenix landing will be presented, highlighting the salient, high level events that occurred during EDL. Initial EDL flight reconstruction results will be presented, along with a retelling of the flight operations events that occurred on approach to Mars, and during the landing event itself. Note: Given the short time duration between the Phoenix landing and IPPW6, only a presentation will be prepared for the workshop.NAS

DGIdb 2.0: Mining clinically relevant drug-gene interactions

The Drug–Gene Interaction Database (DGIdb, www. dgidb.org) is a web resource that consolidates dis-parate data sources describing drug–gene interac-tions and gene druggability. It provides an intuitive graphical user interface and a documented applica-tion programming interface (API) for querying these data. DGIdb was assembled through an extensive manual curation effort, reflecting the combined in-formation of twenty-seven sources. For DGIdb 2.0, substantial updates have been made to increase content and improve its usefulness as a resource for mining clinically actionable drug targets. Specif-ically, nine new sources of drug–gene interactions have been added, including seven resources specifi-cally focused on interactions linked to clinical trials. These additions have more than doubled the over-all count of drug–gene interactions. The total num-ber of druggable gene claims has also increased by 30%. Importantly, a majority of the unrestricted, publicly-accessible sources used in DGIdb are now automatically updated on a weekly basis, providing the most current information for these sources. Fi-nally, a new web view and API have been developed to allow searching for interactions by drug identifiers to complement existing gene-based search function-ality. With these updates, DGIdb represents a com-prehensive and user friendly tool for mining the druggable genome for precision medicine hypothe-sis generation

Using random forest and decision tree models for a new vehicle prediction approach in computational toxicology

yesDrug vehicles are chemical carriers that provide beneficial aid to the drugs they bear. Taking advantage of their favourable properties can potentially allow the safer use of drugs that are considered highly toxic. A means for vehicle selection without experimental trial would therefore be of benefit in saving time and money for the industry. Although machine learning is increasingly used in predictive toxicology, to our knowledge there is no reported work in using machine learning techniques to model drug-vehicle relationships for vehicle selection to minimise toxicity. In this paper we demonstrate the use of data mining and machine learning techniques to process, extract and build models based on classifiers (decision trees and random forests) that allow us to predict which vehicle would be most suited to reduce a drug’s toxicity. Using data acquired from the National Institute of Health’s (NIH) Developmental Therapeutics Program (DTP) we propose a methodology using an area under a curve (AUC) approach that allows us to distinguish which vehicle provides the best toxicity profile for a drug and build classification models based on this knowledge. Our results show that we can achieve prediction accuracies of 80 % using random forest models whilst the decision tree models produce accuracies in the 70 % region. We consider our methodology widely applicable within the scientific domain and beyond for comprehensively building classification models for the comparison of functional relationships between two variables

1967: Abilene Christian College Bible Lectures - Full Text

LIFTING UP THE CHRIST” Being the Abilene Christian College Annual Bible Lectures 1967 $3.95 Published by ABILENE CHRISTIAN COLLEGE STUDENTS EXCHANGE ACC Station Abilene, Texa

Group cognitive behavioural therapy for women with depression: pilot and feasibility study for a randomised controlled trial using mixed methods

<p>Abstract</p> <p>Background</p> <p>Group Cognitive Behavioural Therapy (CBT) may provide a means of improving mental health among people with depression but few studies have explored its effectiveness. Our aim was to examine the feasibility and acceptability of a randomised controlled trial of a group intervention based on CBT principles for women with depression in primary care.</p> <p>Methods</p> <p>Women aged 30 to 55 years were recruited and randomly assigned to either 12 weeks of the group intervention or usual care (control). The group intervention was based on a manual and used CBT and problem solving principles with weekly topics including raising activity levels, spotting and catching negative thoughts, problem solving and relaxation. Women were recruited from deprived areas of Bristol. The groups were run by facilitators with some experience and background in group work and one weeks training in use of the course manual. Assessments of mental health were made using measures including the PHQ-9. Follow-up was at 3 and 6 months after the intervention. Qualitative methods were used to support the design of the intervention and to help understand issues of acceptability and feasibility. Interviews were conducted with all participants at baseline and at 3 and 6 months although detailed qualitative analysis was based on a purposive sample of 20 participants at the 3 time points.</p> <p>Results</p> <p>Of the 86 participants assessed for eligibility, 52 were allocated to the intervention arm and 21 to the control group. The intervention was delivered according to the manual despite the limited training of the facilitators. The intervention was received favourably by participants and facilitators, with good attendance at sessions for those who engaged with the intervention. Follow up rates at 3 and 6 months for women in both the intervention and control arms were also good. The trial methodology used was appropriate and feasible.</p> <p>Conclusions</p> <p>This study showed that a randomised controlled trial of group CBT for women with depression is feasible and the intervention is acceptable, and may possibly prove to be effective in a larger trial. The cost effectiveness of group CBT for depression should be explored further in a full trial.</p> <p>Trial registration</p> <p><a href="http://www.clinicaltrials.gov/ct2/show/NCT00663078">NCT00663078</a></p

1955: Abilene Christian College Bible Lectures - Full Text

Delivered in the Auditorium of Abilene Christian College, February, 1955 ABILENE, TEXAS PRICE, $3.00 FIRM FOUNDATION PUBLISHING HOUSE Box 77 Austin 61, Texa

Patterns and functional implications of rare germline variants across 12 cancer types

Large-scale cancer sequencing data enable discovery of rare germline cancer susceptibility variants. Here we systematically analyse 4,034 cases from The Cancer Genome Atlas cancer cases representing 12 cancer types. We find that the frequency of rare germline truncations in 114 cancer-susceptibility-associated genes varies widely, from 4% (acute myeloid leukaemia (AML)) to 19% (ovarian cancer), with a notably high frequency of 11% in stomach cancer. Burden testing identifies 13 cancer genes with significant enrichment of rare truncations, some associated with specific cancers (for example, RAD51C, PALB2 and MSH6 in AML, stomach and endometrial cancers, respectively). Significant, tumour-specific loss of heterozygosity occurs in nine genes (ATM, BAP1, BRCA1/2, BRIP1, FANCM, PALB2 and RAD51C/D). Moreover, our homology-directed repair assay of 68 BRCA1 rare missense variants supports the utility of allelic enrichment analysis for characterizing variants of unknown significance. The scale of this analysis and the somatic-germline integration enable the detection of rare variants that may affect individual susceptibility to tumour development, a critical step toward precision medicine

Genome modeling system: A knowledge management platform for genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms