Total Body Sodium Depletion and Poor Weight Gain in Children and Young Adults With an Ileostomy

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141860/1/ncp0397.pd

Identification of a Genomic Region Between SLC29A1 and HSP90AB1 Associated With Risk of Bevacizumab-Induced Hypertension: CALGB 80405 (Alliance)

Purpose: Bevacizumab is a VEGF-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of multiple cancers. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy or lead to cardiovascular complications. The factors that contribute to interindividual variability in blood pressure rise during bevacizumab treatment are not well understood.Experimental Design: To identify genomic regions associated with bevacizumab-induced hypertension risk, sequencing of candidate genes and flanking regulatory regions was performed on 61 patients treated with bevacizumab (19 cases developed early-onset grade 3 hypertension and 42 controls had no reported hypertension in the first six cycles of treatment). SNP-based tests for common variant associations and gene-based tests for rare variant associations were performed in 174 candidate genes.Results: Four common variants in independent linkage disequilibrium blocks between SLC29A1 and HSP90AB1 were among the top associations. Validation in larger bevacizumab-treated cohorts supported association between rs9381299 with early grade 3+ hypertension (P = 0.01; OR, 2.4) and systolic blood pressure >180 mm Hg (P = 0.02; OR, 2.1). rs834576 was associated with early grade 3+ hypertension in CALGB 40502 (P = 0.03; OR, 2.9). These SNP regions are enriched for regulatory elements that may potentially increase gene expression. In vitro overexpression of SLC29A1 in human endothelial cells disrupted adenosine signaling and reduced nitric oxide levels that were further lowered upon bevacizumab exposure.Conclusions: The genomic region between SLC29A1 and HSP90AB1 and its role in regulating adenosine signaling are key targets for further investigation into the pathogenesis of bevacizumab-induced hypertension

Using systems science to understand the determinants of inequities in healthy eating

Introduction: Systems thinking has emerged in recent years as a promising approach to understanding and acting on the prevention and amelioration of non-communicable disease. However, the evidence on inequities in non-communicable diseases and their risks factors, particularly diet, has not been examined from a systems perspective. We report on an approach to developing a system oriented policy actor perspective on the multiple causes of inequities in healthy eating. Methods: Collaborative conceptual modelling workshops were held in 2015 with an expert group of representatives from government, non-government health organisations and academia in Australia. The expert group built a systems model using a system dynamics theoretical perspective. The model developed from individual mind maps to pair blended maps, before being finalised as a causal loop diagram. Results: The work of the expert stakeholders generated a comprehensive causal loop diagram of the determinants of inequity in healthy eating (the HE2Diagram). This complex dynamic system has seven sub-systems: (1) food supply and environment; (2) transport; (3) housing and the built environment; (4) employment; (5) social protection; (6) health literacy; and (7) food preferences. Discussion: The HE2causal loop diagram illustrates the complexity of determinants of inequities in healthy eating. This approach, both the process of construction and the final visualisation, can provide the basis for planning the prevention and amelioration of inequities in healthy eating that engages with multiple levels of causes and existing policies and programs

Clinical benefit of a precision medicine based approach for guiding treatment of refractory cancers

Patients and methods: Patients with metastatic solid tumors who had progressed on at least one line of standard of care therapy were referred to the Indiana University Health Precision Genomics Program. Tumor samples were submitted for DNA & RNA next-generation sequencing, fluorescence in situ hybridization, and immunohistochemistry for actionable targets. A multi-disciplinary tumor board reviewed all results. For each patient, the ratio of progression-free survival (PFS) of the genomically guided line of therapy divided by the PFS of their prior line was calculated. Patients whose PFS ratio was ≥ 1.3 were deemed to have a meaningful improvement in PFS. Results: From April 2014-October 2015, 168 patients were evaluated and 101 patients achieved adequate clinical follow-up for analysis. 19 of 44 (43.2%) patients treated with genomically guided therapy attained a PFS ratio ≥ 1.3 vs. 3 of 57 (5.3%) treated with non-genomically guided therapy (p < 0.0001). Similarly, overall PFS ratios (irrespective of cutoff) were higher for patients with genomically guided therapy vs non-genomically guided therapy (p = 0.05). Further, patients treated with genomically guided therapy had a superior median PFS compared to those treated with non-genomically guided therapy (86 days vs. 49 days, p = 0.005, H.R. = 0.55, 95% C.I.:0.37-0.84). Conclusion: Patients with refractory metastatic cancer who receive genomically guided therapy have improved PFS ratios and longer median PFS compared to patients who do not receive genomically guided therapy

Elucidating opportunities and pitfalls in the treatment of experimental traumatic brain injury to optimize and facilitate clinical translation

The aim of this review is to discuss the research presented in a symposium entitled "Current Progress in characterizing therapeutic strategies and challenges in experimental CNS injury" which was presented at the 2016 International Behavioral Neuroscience Society annual meeting. Herein we discuss diffuse and focal traumatic brain injury (TBI) and ensuing chronic behavioral deficits as well as potential rehabilitative approaches. We also discuss the effects of stress on executive function after TBI as well as the response of the endocrine system and regulatory feedback mechanisms. The role of the endocannabinoids after CNS injury is also discussed. Finally, we conclude with a discussion of antipsychotic and antiepileptic drugs, which are provided to control TBI-induced agitation and seizures, respectively. The review consists predominantly of published data.National Institutes of Health [HD069620, HD069620-S1, NS060005, NS084967, NS094950, NS099683]; University of Pittsburgh Physicians/UPMC Academic Foundation; Arizona Biomedical Research Commission through Arizona Department of Health Services [ADHS14-00003606]; Valley Research Partnership Awards [P2201607, P1201607]; Phoenix Children's Hospital Mission Support Funds18 month embargo; published online: 30 May 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Cloning and Characterization of a Norbelladine 4′-<i>O-</i>Methyltransferase Involved in the Biosynthesis of the Alzheimer’s Drug Galanthamine in <i>Narcissus</i> sp. <i>aff. pseudonarcissus</i>

<div><p>Galanthamine is an Amaryllidaceae alkaloid used to treat the symptoms of Alzheimer’s disease. This compound is primarily isolated from daffodil <i>(Narcissus</i> spp.<i>)</i>, snowdrop (<i>Galanthus</i> spp.), and summer snowflake (<i>Leucojum aestivum)</i>. Despite its importance as a medicine, no genes involved in the biosynthetic pathway of galanthamine have been identified. This absence of genetic information on biosynthetic pathways is a limiting factor in the development of synthetic biology platforms for many important botanical medicines. The paucity of information is largely due to the limitations of traditional methods for finding biochemical pathway enzymes and genes in non-model organisms. A new bioinformatic approach using several recent technological improvements was applied to search for genes in the proposed galanthamine biosynthetic pathway, first targeting methyltransferases due to strong signature amino acid sequences in the proteins. Using Illumina sequencing, a <i>de novo</i> transcriptome assembly was constructed for daffodil. BLAST was used to identify sequences that contain signatures for plant <i>O</i>-methyltransferases in this transcriptome. The program HAYSTACK was then used to identify methyltransferases that fit a model for galanthamine biosynthesis in leaf, bulb and inflorescence tissues. One candidate gene for the methylation of norbelladine to 4′-<i>O</i>-methylnorbelladine in the proposed galanthamine biosynthetic pathway was identified. This methyltransferase cDNA was expressed in <i>E. coli</i> and the protein purified by affinity chromatography. The resulting protein was found to be a norbelladine 4′-<i>O</i>-methyltransferase (<i>Np</i>N4OMT) of the proposed galanthamine biosynthetic pathway.</p></div

Phylogenetic analysis of <i>Np</i>N4OMT1.

<p>A maximum-likelihood phylogenetic tree of characterized methyltransferases listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223.s009" target="_blank">Table S2 </a><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Takeshita1" target="_blank">[22]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Widiez1" target="_blank">[27]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Schrder1" target="_blank">[46]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Gang1" target="_blank">[49]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Kopycki1" target="_blank">[53]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Day1" target="_blank">[63]</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0103223#pone.0103223-Kato1" target="_blank">[70]</a>. Alignment constructed using MUSCLE.</p