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"systems biology"

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"systems biology"

These pubmed results were generated on 2017/11/03

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

34 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/11/02

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

34 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/11/02

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

32 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/11/01

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

32 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/11/01

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/31

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/31

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Structure-based prediction of protein allostery.

Curr Opin Struct Biol. 2017 Oct 25;50:1-8

Authors: Greener JG, Sternberg MJ

Abstract
Allostery is the functional change at one site on a protein caused by a change at a distant site. In order for the benefits of allostery to be taken advantage of, both for basic understanding of proteins and to develop new classes of drugs, the structure-based prediction of allosteric binding sites, modulators and communication pathways is necessary. Here we review the recently emerging field of allosteric prediction, focusing mainly on computational methods. We also describe the search for cryptic binding pockets and attempts to design allostery into proteins. The development and adoption of such methods is essential or the long-preached potential of allostery will remain elusive.

PMID: 29080471 [PubMed - as supplied by publisher]

Assessment of Variability in the SOMAscan Assay.

Sci Rep. 2017 Oct 27;7(1):14248

Authors: Candia J, Cheung F, Kotliarov Y, Fantoni G, Sellers B, Griesman T, Huang J, Stuccio S, Zingone A, Ryan BM, Tsang JS, Biancotto A

Abstract
SOMAscan is an aptamer-based proteomics assay capable of measuring 1,305 human protein analytes in serum, plasma, and other biological matrices with high sensitivity and specificity. In this work, we present a comprehensive meta-analysis of performance based on multiple serum and plasma runs using the current 1.3 k assay, as well as the previous 1.1 k version. We discuss normalization procedures and examine different strategies to minimize intra- and interplate nuisance effects. We implement a meta-analysis based on calibrator samples to characterize the coefficient of variation and signal-over-background intensity of each protein analyte. By incorporating coefficient of variation estimates into a theoretical model of statistical variability, we also provide a framework to enable rigorous statistical tests of significance in intervention studies and clinical trials, as well as quality control within and across laboratories. Furthermore, we investigate the stability of healthy subject baselines and determine the set of analytes that exhibit biologically stable baselines after technical variability is factored in. This work is accompanied by an interactive web-based tool, an initiative with the potential to become the cornerstone of a regularly updated, high quality repository with data sharing, reproducibility, and reusability as ultimate goals.

PMID: 29079756 [PubMed - in process]

ARSDA: A New Approach for Storing, Transmitting and Analyzing Transcriptomic Data.

G3 (Bethesda). 2017 Oct 27;:

Authors: Xia X

Abstract
Two major stumbling blocks exist in high-throughput sequencing (HTS) data analysis. The first is the sheer file size typically in gigabytes when uncompressed, causing problems in storage, transmission and analysis. However, these files do not need to be so large and can be reduced without loss of information. Each HTS file, either in compressed .SRA or plain text .fastq format, contains numerous identical reads stored as separate entries. For example, among 44603541 forward reads in the SRR4011234.sra file (from a Bacillus subtilis transcriptomic study) deposited at NCBI's SRA database, one read has 497027 identical copies. Instead of storing them as separate entries, one can and should store them as a single entry with the SeqID_NumCopy format (which I dub as FASTA+ format). The second is the proper allocation of reads that map equally well to paralogous genes. I illustrate in detail a new method for such allocation. I have developed ARSDA software that implement these new approaches. A number of HTS files for model species are in the process of being processed and deposited at http://coevol.rdc.uottawa.ca to demonstrate that this approach not only saves a huge amount of storage space and transmission bandwidth, but also dramatically reduces time in downstream data analysis. Instead of matching the 497027 identical reads separately against the Bacillus subtilis genome, one only needs to match it once. ARSDA includes functions to take advantage of HTS data in the new sequence format for downstream data analysis such as gene expression characterization. I contrasted gene expression results between ARSDA and Cufflinks so readers can better appreciate the strength of ARSDA. ARSDA is freely available for Windows, Linux and Macintosh computers at http://dambe.bio.uottawa.ca/ARSDA/ARSDA.aspx.

PMID: 29079682 [PubMed - as supplied by publisher]

Effect of an intensified multifactorial intervention on cardiovascular outcomes and mortality in type 2 diabetes (J-DOIT3): an open-label, randomised controlled trial.

Lancet Diabetes Endocrinol. 2017 Oct 24;:

Authors: Ueki K, Sasako T, Okazaki Y, Kato M, Okahata S, Katsuyama H, Haraguchi M, Morita A, Ohashi K, Hara K, Morise A, Izumi K, Ishizuka N, Ohashi Y, Noda M, Kadowaki T, J-DOIT3 Study Group

Abstract
BACKGROUND: Limited evidence suggests that multifactorial interventions for control of glucose, blood pressure, and lipids reduce macrovascular complications and mortality in patients with type 2 diabetes. However, safe and effective treatment targets for these risk factors have not been determined for such interventions.
METHODS: In this multicentre, open-label, randomised, parallel-group trial, undertaken at 81 clinical sites in Japan, we randomly assigned (1:1) patients with type 2 diabetes aged 45-69 years with hypertension, dyslipidaemia, or both, and an HbA1c of 6·9% (52·0 mmol/mol) or higher, to receive conventional therapy for glucose, blood pressure, and lipid control (targets: HbA1c <6·9% [52·0 mmol/mol], blood pressure <130/80 mm Hg, LDL cholesterol <120 mg/dL [or 100 mg/dL in patients with a history of coronary artery disease]) or intensive therapy (HbA1c <6·2% [44·3 mmol/mol], blood pressure <120/75 mm Hg, LDL cholesterol <80 mg/dL [or 70 mg/dL in patients with a history of coronary artery disease]). Randomisation was done using a computer-generated, dynamic balancing method, stratified by sex, age, HbA1c, and history of cardiovascular disease. Neither patients nor investigators were masked to group assignment. The primary outcome was occurrence of any of a composite of myocardial infarction, stroke, revascularisation (coronary artery bypass surgery, percutaneous transluminal coronary angioplasty, carotid endarterectomy, percutaneous transluminal cerebral angioplasty, and carotid artery stenting), and all-cause mortality. The primary analysis was done in the intention-to-treat population. This study is registered with ClinicalTrials.gov, number NCT00300976.
FINDINGS: Between June 16, 2006, and March 31, 2009, 2542 eligible patients were randomly assigned to intensive therapy or conventional therapy (1271 in each group) and followed up for a median of 8·5 years (IQR 7·3-9·0). Two patients in the intensive therapy group were found to be ineligible after randomisation and were excluded from the analyses. During the intervention period, mean HbA1c, systolic blood pressure, diastolic blood pressure, and LDL cholesterol concentrations were significantly lower in the intensive therapy group than in the conventional therapy group (6·8% [51·0 mmol/mol] vs 7·2% [55·2 mmol/mol]; 123 mm Hg vs 129 mm Hg; 71 mm Hg vs 74 mm Hg; and 85 mg/dL vs 104 mg/dL, respectively; all p<0·0001). The primary outcome occurred in 109 patients in the intensive therapy group and in 133 patients in the conventional therapy group (hazard ratio [HR] 0·81, 95% CI 0·63-1·04; p=0·094). In a post-hoc breakdown of the composite outcome, frequencies of all-cause mortality (HR 1·01, 95% CI 0·68-1·51; p=0·95) and coronary events (myocardial infarction, coronary artery bypass surgery, and percutaneous transluminal coronary angioplasty; HR 0·86, 0·58-1·27; p=0·44) did not differ between groups, but cerebrovascular events (stroke, carotid endarterectomy, percutaneous transluminal cerebral angioplasty, and carotid artery stenting) were significantly less frequent in the intensive therapy group (HR 0·42, 0·24-0·74; p=0·002). Apart from non-severe hypoglycaemia (521 [41%] patients in the intensive therapy group vs 283 [22%] in the conventional therapy group, p<0·0001) and oedema (193 [15%] vs 129 [10%], p=0·0001), the frequencies of major adverse events did not differ between groups.
INTERPRETATION: Our results do not fully support the efficacy of further intensified multifactorial intervention compared with current standard care for the prevention of a composite of coronary events, cerebrovascular events, and all-cause mortality. Nevertheless, our findings suggest a potential benefit of an intensified intervention for the prevention of cerebrovascular events in patients with type 2 diabetes.
FUNDING: Ministry of Health, Labour and Welfare of Japan, Asahi Kasei Pharma, Astellas Pharma, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Eli Lilly, GlaxoSmithKline, Kissei Pharmaceutical, Kowa Pharmaceutical, Mitsubishi Tanabe Pharma, Mochida Pharmaceutical, MSD, Novartis Pharma, Novo Nordisk, Ono Pharmaceutical, Pfizer, Sanwa Kagaku Kenkyusho, Shionogi, Sumitomo Dainippon Pharma, Taisho Toyama Pharmaceutical, and Takeda.

PMID: 29079252 [PubMed - as supplied by publisher]

Growth hormone-releasing hormone attenuates cardiac hypertrophy and improves heart function in pressure overload-induced heart failure.

Proc Natl Acad Sci U S A. 2017 Oct 25;:

Authors: Gesmundo I, Miragoli M, Carullo P, Trovato L, Larcher V, Di Pasquale E, Brancaccio M, Mazzola M, Villanova T, Sorge M, Taliano M, Gallo MP, Alloatti G, Penna C, Hare JM, Ghigo E, Schally AV, Condorelli G, Granata R

Abstract
It has been shown that growth hormone-releasing hormone (GHRH) reduces cardiomyocyte (CM) apoptosis, prevents ischemia/reperfusion injury, and improves cardiac function in ischemic rat hearts. However, it is still not known whether GHRH would be beneficial for life-threatening pathological conditions, like cardiac hypertrophy and heart failure (HF). Thus, we tested the myocardial therapeutic potential of GHRH stimulation in vitro and in vivo, using GHRH or its agonistic analog MR-409. We show that in vitro, GHRH(1-44)NH2 attenuates phenylephrine-induced hypertrophy in H9c2 cardiac cells, adult rat ventricular myocytes, and human induced pluripotent stem cell-derived CMs, decreasing expression of hypertrophic genes and regulating hypertrophic pathways. Underlying mechanisms included blockade of Gq signaling and its downstream components phospholipase Cβ, protein kinase Cε, calcineurin, and phospholamban. The receptor-dependent effects of GHRH also involved activation of Gαs and cAMP/PKA, and inhibition of increase in exchange protein directly activated by cAMP1 (Epac1). In vivo, MR-409 mitigated cardiac hypertrophy in mice subjected to transverse aortic constriction and improved cardiac function. Moreover, CMs isolated from transverse aortic constriction mice treated with MR-409 showed improved contractility and reversal of sarcolemmal structure. Overall, these results identify GHRH as an antihypertrophic regulator, underlying its therapeutic potential for HF, and suggest possible beneficial use of its analogs for treatment of pathological cardiac hypertrophy.

PMID: 29078377 [PubMed - as supplied by publisher]

Genome of wild olive and the evolution of oil biosynthesis.

Proc Natl Acad Sci U S A. 2017 Oct 09;:

Authors: Unver T, Wu Z, Sterck L, Turktas M, Lohaus R, Li Z, Yang M, He L, Deng T, Escalante FJ, Llorens C, Roig FJ, Parmaksiz I, Dundar E, Xie F, Zhang B, Ipek A, Uranbey S, Erayman M, Ilhan E, Badad O, Ghazal H, Lightfoot DA, Kasarla P, Colantonio V, Tombuloglu H, Hernandez P, Mete N, Cetin O, Van Montagu M, Yang H, Gao Q, Dorado G, Van de Peer Y

Abstract
Here we present the genome sequence and annotation of the wild olive tree (Olea europaea var. sylvestris), called oleaster, which is considered an ancestor of cultivated olive trees. More than 50,000 protein-coding genes were predicted, a majority of which could be anchored to 23 pseudochromosomes obtained through a newly constructed genetic map. The oleaster genome contains signatures of two Oleaceae lineage-specific paleopolyploidy events, dated at ∼28 and ∼59 Mya. These events contributed to the expansion and neofunctionalization of genes and gene families that play important roles in oil biosynthesis. The functional divergence of oil biosynthesis pathway genes, such as FAD2, SACPD, EAR, and ACPTE, following duplication, has been responsible for the differential accumulation of oleic and linoleic acids produced in olive compared with sesame, a closely related oil crop. Duplicated oleaster FAD2 genes are regulated by an siRNA derived from a transposable element-rich region, leading to suppressed levels of FAD2 gene expression. Additionally, neofunctionalization of members of the SACPD gene family has led to increased expression of SACPD2, 3, 5, and 7, consequently resulting in an increased desaturation of steric acid. Taken together, decreased FAD2 expression and increased SACPD expression likely explain the accumulation of exceptionally high levels of oleic acid in olive. The oleaster genome thus provides important insights into the evolution of oil biosynthesis and will be a valuable resource for oil crop genomics.

PMID: 29078332 [PubMed - as supplied by publisher]

Gut dysbiosis breaks immunological tolerance toward the central nervous system during young adulthood.

Proc Natl Acad Sci U S A. 2017 Oct 16;:

Authors: Yadav SK, Boppana S, Ito N, Mindur JE, Mathay MT, Patel A, Dhib-Jalbut S, Ito K

Abstract
Multiple sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) mainly in young adults, and a breakage of immune tolerance to CNS self-antigens has been suggested to initiate CNS autoimmunity. Age and microbial infection are well-known factors involved in the development of autoimmune diseases, including MS. Recent studies have suggested that alterations in the gut microbiota, referred to as dysbiosis, are associated with MS. However, it is still largely unknown how gut dysbiosis affects the onset and progression of CNS autoimmunity. In this study, we investigated the effects of age and gut dysbiosis on the development of CNS autoimmunity in humanized transgenic mice expressing the MS-associated MHC class II (MHC-II) gene, HLA-DR2a, and T-cell receptor (TCR) genes specific for MBP87-99/DR2a that were derived from an MS patient. We show here that the induction of gut dysbiosis triggers the development of spontaneous experimental autoimmune encephalomyelitis (EAE) during adolescence and early young adulthood, while an increase in immunological tolerance with aging suppresses disease onset after late young adulthood in mice. Furthermore, gut dysbiosis induces the expression of complement C3 and production of the anaphylatoxin C3a, and down-regulates the expression of the Foxp3 gene and anergy-related E3 ubiquitin ligase genes. Consequently, gut dysbiosis was able to trigger the development of encephalitogenic T cells and promote the induction of EAE during the age window of young adulthood.

PMID: 29078267 [PubMed - as supplied by publisher]

Overview of Ganoderma sinense polysaccharide-an adjunctive drug used during concurrent Chemo/Radiation therapy for cancer treatment in China.

Biomed Pharmacother. 2017 Oct 19;96:865-870

Authors: Jiang Y, Chang Y, Liu Y, Zhang M, Luo H, Hao C, Zeng P, Sun Y, Wang H, Zhang L

Abstract
Ganoderma sinense or "Chinese Lingzhi" is a well-known medicinal fungus in China for more than 2000 years. Polysaccharide is the main immunomodulatory and antitumor component in G. sinense. In 2010, G. sinense polysaccharide (GSP) tablet is approved as an adjunctive therapeutic drug in China for treating leukopenia and hematopoietic injury caused by concurrent chemo/radiation therapy during cancer treatment by the State Food and Drug Administration (SFDA). β-glucan, an established immunostimulant, is one of the components in GSP. Based on CNKI (China National Knowledge Infrastructure), VIP (Chongqing VIP Chinese Scientific Journals Database), Wanfang database, and PubMed searches, we have not only summarized but also translated all the basic and preclinical studies about GSP published in Chinese into English in this review article. Unfortunately, all the clinical studies about GSP tablet could not be found during the search or by contacting the drug manufacturers. However, both basic and preclinical studies showed that GSP has antitumor, antioxidant, anticytopenia, and unique mushroom-poison detoxification properties that are different from that of G. lucidum polysaccharide, another "Lingzhi" polysaccharide. The structure and molecular mechanisms of GSP are also discussed. This article urges availability of clinical study results of GSP tablet that would allow in-depth evaluation if the tablet is appropriate to serve as an immunomodulatory drug during cancer therapy at world stage.

PMID: 29078264 [PubMed - as supplied by publisher]

28 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/28

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

66 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/27

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

35 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/25

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

35 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"systems biology"

These pubmed results were generated on 2017/10/25

PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.