No-Boundary Thinking in Bioinformatics Research

Currently there are definitions from many agencies and research societies defining bioinformatics as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT)

Prospectus, April 29, 1974

STUDENTS SEEK GOVERNMENT POSTS; 14 Candidates Run For Major Stu-Go Positions; College Construction Nearing Completion; I.O.C. Sponsors Spring Carnival; Cruisin\u27 \u2774; President\u27s Report; Raines To Speak On Education; Parkland\u27s New School Fight Song; P/C Sponsors Festival Of Foreign Films; A Film For The Times; Doobie\u27s Latest Disappointing; A Column By and For Women; Going Back To Work; Hypertension Screening Tests May 6; Candidates\u27 Platforms; Let\u27s Go To The Bars; Fire Destroys Campus Building; Monday\u27s Coach; IM Department Still Scheduling Sports Events; Give The Girls A Break; Parkland College Baseball (Tentative 1974 Scehdule); Bowling Bulletin Board; Cobra Statistics Reveal Good Odds; Classified Ads; Prepare For Graduation; Graduation Calendar Events; Cobra Tracksters Run To Second At Harper Meet; Crosswords; Parkland Events; Krannert Art Schedule; P/C Jazz Band To Perform In J/C Competition; Committee Announced Special Day; SCI Plans Symposium; Attention E. I. U. Transfer Students; Mime Group Performs Visual Composition; Blood Bank I.D. Cards; Summer Field Course In American Southwesthttps://spark.parkland.edu/prospectus_1974/1014/thumbnail.jp

Self‐pollination in island and mainland populations of the introduced hummingbird‐pollinated plant, Nicotiana glauca (Solanaceae)

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142032/1/ajb20672.pd

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

Using cases to support divergent roles in distributed collaboration

leake,sbogaert,avalerio,moder¦ Case-based reasoning has been applied successfully to many diagnostic tasks, and much attention has been directed towards maximizing performance of the case-based diagnostic process. In distributed collaboration contexts, however, high-performance CBR alone may not be sufficient: individual abilities and organizational roles introduce unique constraints on how support should be applied. To maximize the usefulness of a case-based support system, system design must reflect divergent user capabilities and roles. This paper presents a case study of a CBR-based system to support collaborative distributed troubleshooting by ad hoc teams of sailors and shipboard experts. It shows how case sharing between participants can be used to increase confidence and aid situation assessment, “jump-starting ” the aid process. It also shows how information from cases can be used to streamline communication between collaborators, and how the communication process needed to handle novel situations can be exploited as a natural vehicle for dialogue-driven generation of new cases to fill gaps in the existing case-base

BinPacker: Packing-Based De Novo Transcriptome Assembly from RNA-seq Data.

High-throughput RNA-seq technology has provided an unprecedented opportunity to reveal the very complex structures of transcriptomes. However, it is an important and highly challenging task to assemble vast amounts of short RNA-seq reads into transcriptomes with alternative splicing isoforms. In this study, we present a novel de novo assembler, BinPacker, by modeling the transcriptome assembly problem as tracking a set of trajectories of items with their sizes representing coverage of their corresponding isoforms by solving a series of bin-packing problems. This approach, which subtly integrates coverage information into the procedure, has two exclusive features: 1) only splicing junctions are involved in the assembling procedure; 2) massive pell-mell reads are assembled seemingly by moving a comb along junction edges on a splicing graph. Being tested on both real and simulated RNA-seq datasets, it outperforms almost all the existing de novo assemblers on all the tested datasets, and even outperforms those ab initio assemblers on the real dog dataset. In addition, it runs substantially faster and requires less memory space than most of the assemblers. BinPacker is published under GNU GENERAL PUBLIC LICENSE and the source is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_1.0.tar.gz/download. Quick installation version is available from: http://sourceforge.net/projects/transcriptomeassembly/files/BinPacker_binary.tar.gz/download

Development of Noviomimetics as C‑Terminal Hsp90 Inhibitors

KU-32 and KU-596 are novobiocin-derived, C-terminal heat shock protein 90 (Hsp90) modulators that induce Hsp70 levels and manifest neuroprotective activity. However, the synthetically complex noviose sugar requires 10 steps to prepare, which makes translational development difficult. In this study, we developed a series of “noviomimetic” analogues of KU-596, which contain noviose surrogates that can be easily prepared, while maintaining the ability to induce Hsp70 levels. Both sugar and sugar analogues were designed, synthesized, and evaluated in a luciferase reporter assay, which identified compound <b>37</b>, a benzyl containing noviomimetic, as the most potent inducer of Hsp70

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.publishe