Clinical Trial of Oral Nelfinavir before and during Radiation Therapy for Advanced Rectal Cancer

Purpose Nelfinavir, a PI3-kinase pathway inhibitor, is a radiosensitizer which increases tumor blood flow in preclinical models. We conducted an early-phase study to demonstrate the safety of nelfinavir combined with hypofractionated radiotherapy (RT) and to develop biomarkers of tumor perfusion and radiosensitization for this combinatorial approach. Patients and Methods Ten patients with T3-4 N0-2 M1 rectal cancer received 7 days of oral nelfinavir (1250 mg bd) and a further 7 days of nelfinavir during pelvic RT (25 Gy/5 fractions/7 days). Perfusion CT (p-CT) and DCE-MRI scans were performed pre-treatment, after 7 days of nelfinavir and prior to last fraction of RT. Biopsies taken pre-treatment and 7 days after the last fraction of RT were analysed for tumor cell density (TCD). Results There were 3 drug-related grade 3 adverse events: diarrhea, rash, lymphopenia. On DCE-MRI, there was a mean 42% increase in median Ktrans, and a corresponding median 30% increase in mean blood flow on p-CT during RT in combination with nelfinavir. Median TCD decreased from 24.3% at baseline to 9.2% in biopsies taken 7 days after RT (P=0.01). Overall, 5/9 evaluable patients exhibited good tumor regression on MRI assessed by Tumor Regression Grade (mrTRG). Conclusions This is the first study to evaluate nelfinavir in combination with RT without concurrent chemotherapy. It has shown that nelfinavir-RT is well tolerated and is associated with increased blood flow to rectal tumors. The efficacy of nelfinavir-RT versus RT alone merits clinical evaluation, including measurement of tumor blood flow

Volume 03

Introduction from Dean Dr. Charles Ross Little Shop of Horrors by Longwood Theater Department Who Has the Hottest Hotsauce in Farmville: A Quantitative Comparison of Sauces from Local Restaurants by Cheryl Peck and Charles Hoever Precipitation Effects on the Growth of White Oaks and Virginia Pines on the Mt. Vernon Plantation by Brittany Anderson Design and Synthesis of Novel Ion Binding Molecules for Self-Assembly and Sensing Applications by J. Ervin Sheldon A Statistical Analysis of Algorithms for Playing SameGame by Richard Hayden Intersecting Cylinders at Arbitrary Angles by Yuri Calustro Putting a Foot in the Revolving Door: Strategies for Reducing Teacher Attrition by Candice Fleming and Rebecca Franklin The Effect of Presentation on Spanish Vocabulary Recall by Ashley Yocum How Attractive Are You? Individuals Sensitivity to Number of Sexual Partners by Danielle M. Jagoda and Cristina M. Valdivieso Culturally Relevant Practices for Teaching Code-Switching to African-American Students in Kindergarten Classrooms by Jameka Jones Two Poems – “Dust” and “Check Out Girls” by Amy Ellis Three Poems – “Rosewood Massacre, 1923”, “Jarring” and “Reverence” by Ashley Maser Three Poems – “Dirty Thunderstorm”, “Summer Hide \u27N Seek Car Tag” and “Bliss” by Erikk Shupp Analysis of the Wilton Diptych by Jamie Yurasits “Nod”, “Corriline” “Flying” “Familiar” by Alexander Leonhart Papermaking by Kenny Wolfe and Sally Meadows “Plant” by J. Haley, Amy Jackson, and Morgan Howard “Dare to Dart” by Amy Jackson, Adrienne Heinbaugh and Melissa Dorton Untitled Photographs by Hopson “Lockets” by Morgan Howard Graphic Designs and Untitled Photographs by Ciarra Stalker Selections from a Senior Recital by Joshua Davi

The Intestinal Microbiota and Short-Chain Fatty Acids in Association with Advanced Metrics of Glycemia and Adiposity Among Young Adults with Type 1 Diabetes and Overweight or Obesity

BACKGROUND: Comanagement of glycemia and adiposity is the cornerstone of cardiometabolic risk reduction in type 1 diabetes (T1D), but targets are often not met. The intestinal microbiota and microbiota-derived short-chain fatty acids (SCFAs) influence glycemia and adiposity but have not been sufficiently investigated in longstanding T1D. OBJECTIVES: We evaluated the hypothesis that an increased abundance of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity were associated with improved glycemia but increased adiposity in young adults with longstanding T1D. METHODS: Participants provided stool samples at ≤4 time points (NCT03651622: https://clinicaltrials.gov/ct2/show/NCT03651622). Sequencing of the 16S ribosomal RNA gene measured abundances of SCFA-producing intestinal microbes. GC-MS measured total and specific SCFAs (acetate, butyrate, propionate). DXA (body fat percentage and percentage lean mass) and anthropometrics (BMI) measured adiposity. Continuous glucose monitoring [percentage of time in range (70-180 mg/dL), above range (>180 mg/dL), and below range (54-69 mg/dL)] and glycated hemoglobin (i.e., HbA1c) assessed glycemia. Adjusted and Bonferroni-corrected generalized estimating equations modeled the associations of SCFA-producing gut microbes, fecal SCFAs, and intestinal microbial diversity with glycemia and adiposity. COVID-19 interrupted data collection, so models were repeated restricted to pre-COVID-19 visits. RESULTS: Data were available for ≤45 participants at 101 visits (including 40 participants at 54 visits pre-COVID-19). Abundance of Eubacterium hallii was associated inversely with BMI (all data). Pre-COVID-19, increased fecal propionate was associated with increased percentage of time above range and reduced percentage of time in target and below range; and abundances of 3 SCFA-producing taxa (Ruminococcus gnavus, Eubacterium ventriosum, and Lachnospira) were associated inversely with body fat percentage, of which two microbes were positively associated with percentage lean mass. Abundance of Anaerostipes was associated with reduced percentage of time in range (all data) and with increased body fat percentage and reduced percentage lean mass (pre-COVID-19). CONCLUSIONS: Unexpectedly, fecal propionate was associated with detriment to glycemia, whereas most SCFA-producing intestinal microbes were associated with benefit to adiposity. Future studies should confirm these associations and determine their potential causal linkages in T1D.This study is registered at clinical.trials.gov (NCT03651622; https://clinicaltrials.gov/ct2/show/NCT03651622)

Does the implementation of an electronic prescribing system create unintended medication errors? A study of the sociotechnical context through the analysis of reported medication incidents

<p>Abstract</p> <p>Background</p> <p>Even though electronic prescribing systems are widely advocated as one of the most effective means of improving patient safety, they may also introduce new risks that are not immediately obvious. Through the study of specific incidents related to the processes involved in the administration of medication, we sought to find out if the prescribing system had unintended consequences in creating new errors. The focus of this study was a large acute hospital in the Midlands in the United Kingdom, which implemented a Prescribing, Information and Communication System (PICS).</p> <p>Methods</p> <p>This exploratory study was based on a survey of routinely collected medication incidents over five months. Data were independently reviewed by two of the investigators with a clinical pharmacology and nursing background respectively, and grouped into broad types: sociotechnical incidents (related to human interactions with the system) and non-sociotechnical incidents. Sociotechnical incidents were distinguished from the others because they occurred at the point where the system and the professional intersected and would not have occurred in the absence of the system. The day of the week and time of day that an incident occurred were tested using univariable and multivariable analyses. We acknowledge the limitations of conducting analyses of data extracted from incident reports as it is widely recognised that most medication errors are not reported and may contain inaccurate data. Interpretation of results must therefore be tentative.</p> <p>Results</p> <p>Out of a total of 485 incidents, a modest 15% (n = 73) were distinguished as sociotechnical issues and thus may be unique to hospitals that have such systems in place. These incidents were further analysed and subdivided into categories in order to identify aspects of the context which gave rise to adverse situations and possible risks to patient safety. The analysis of sociotechnical incidents by time of day and day of week indicated a trend for increased proportions of these types of incidents occurring on Sundays.</p> <p>Conclusion</p> <p>Introducing an electronic prescribing system has the potential to give rise to new types of risks to patient safety. Being aware of these types of errors is important to the clinical and technical implementers of such systems in order to, where possible, design out unintended problems, highlight training requirements, and revise clinical practice protocols.</p

The role of networks to overcome large-scale challenges in tomography: The non-clinical tomography users research network

Our ability to visualize and quantify the internal structures of objects via computed tomography (CT) has fundamentally transformed science. As tomographic tools have become more broadly accessible, researchers across diverse disciplines have embraced the ability to investigate the 3D structure-function relationships of an enormous array of items. Whether studying organismal biology, animal models for human health, iterative manufacturing techniques, experimental medical devices, engineering structures, geological and planetary samples, prehistoric artifacts, or fossilized organisms, computed tomography has led to extensive methodological and basic sciences advances and is now a core element in science, technology, engineering, and mathematics (STEM) research and outreach toolkits. Tomorrow's scientific progress is built upon today's innovations. In our data-rich world, this requires access not only to publications but also to supporting data. Reliance on proprietary technologies, combined with the varied objectives of diverse research groups, has resulted in a fragmented tomography-imaging landscape, one that is functional at the individual lab level yet lacks the standardization needed to support efficient and equitable exchange and reuse of data. Developing standards and pipelines for the creation of new and future data, which can also be applied to existing datasets is a challenge that becomes increasingly difficult as the amount and diversity of legacy data grows. Global networks of CT users have proved an effective approach to addressing this kind of multifaceted challenge across a range of fields. Here we describe ongoing efforts to address barriers to recently proposed FAIR (Findability, Accessibility, Interoperability, Reuse) and open science principles by assembling interested parties from research and education communities, industry, publishers, and data repositories to approach these issues jointly in a focused, efficient, and practical way. By outlining the benefits of networks, generally, and drawing on examples from efforts by the Non-Clinical Tomography Users Research Network (NoCTURN), specifically, we illustrate how standardization of data and metadata for reuse can foster interdisciplinary collaborations and create new opportunities for future-looking, large-scale data initiatives

ENM2020 : A FREE ONLINE COURSE AND SET OF RESOURCES ON MODELING SPECIES NICHES AND DISTRIBUTIONS

The field of distributional ecology has seen considerable recent attention, particularly surrounding the theory, protocols, and tools for Ecological Niche Modeling (ENM) or Species Distribution Modeling (SDM). Such analyses have grown steadily over the past two decades-including a maturation of relevant theory and key concepts-but methodological consensus has yet to be reached. In response, and following an online course taught in Spanish in 2018, we designed a comprehensive English-language course covering much of the underlying theory and methods currently applied in this broad field. Here, we summarize that course, ENM2020, and provide links by which resources produced for it can be accessed into the future. ENM2020 lasted 43 weeks, with presentations from 52 instructors, who engaged with >2500 participants globally through >14,000 hours of viewing and >90,000 views of instructional video and question-and-answer sessions. Each major topic was introduced by an "Overview" talk, followed by more detailed lectures on subtopics. The hierarchical and modular format of the course permits updates, corrections, or alternative viewpoints, and generally facilitates revision and reuse, including the use of only the Overview lectures for introductory courses. All course materials are free and openly accessible (CC-BY license) to ensure these resources remain available to all interested in distributional ecology.Peer reviewe

X-linked primary ciliary dyskinesia due to mutations in the cytoplasmic axonemal dynein assembly factor PIH1D3

By moving essential body fluids and molecules, motile cilia and flagella govern respiratory mucociliary clearance, laterality determination and the transport of gametes and cerebrospinal fluid. Primary ciliary dyskinesia (PCD) is an autosomal recessive disorder frequently caused by non-assembly of dynein arm motors into cilia and flagella axonemes. Before their import into cilia and flagella, multi-subunit axonemal dynein arms are thought to be stabilized and pre-assembled in the cytoplasm through a DNAAF2–DNAAF4–HSP90 complex akin to the HSP90 co-chaperone R2TP complex. Here, we demonstrate that large genomic deletions as well as point mutations involving PIH1D3 are responsible for an X-linked form of PCD causing disruption of early axonemal dynein assembly. We propose that PIH1D3, a protein that emerges as a new player of the cytoplasmic pre-assembly pathway, is part of a complementary conserved R2TP-like HSP90 co-chaperone complex, the loss of which affects assembly of a subset of inner arm dyneins

An organelle-specific protein landscape identifies novel diseases and molecular mechanisms

Contains fulltext : 158967.pdf (publisher's version ) (Open Access)Cellular organelles provide opportunities to relate biological mechanisms to disease. Here we use affinity proteomics, genetics and cell biology to interrogate cilia: poorly understood organelles, where defects cause genetic diseases. Two hundred and seventeen tagged human ciliary proteins create a final landscape of 1,319 proteins, 4,905 interactions and 52 complexes. Reverse tagging, repetition of purifications and statistical analyses, produce a high-resolution network that reveals organelle-specific interactions and complexes not apparent in larger studies, and links vesicle transport, the cytoskeleton, signalling and ubiquitination to ciliary signalling and proteostasis. We observe sub-complexes in exocyst and intraflagellar transport complexes, which we validate biochemically, and by probing structurally predicted, disruptive, genetic variants from ciliary disease patients. The landscape suggests other genetic diseases could be ciliary including 3M syndrome. We show that 3M genes are involved in ciliogenesis, and that patient fibroblasts lack cilia. Overall, this organelle-specific targeting strategy shows considerable promise for Systems Medicine

Automated workflow-based exploitation of pathway databases provides new insights into genetic associations of metabolite profiles

Background: Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results: Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions: We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression