334 research outputs found

    Are we drawing the right conclusions from randomised placebo-controlled trials? A post-hoc analysis of data from a randomised controlled trial

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Assumptions underlying placebo controlled trials include that the placebo effect impacts on all study arms equally, and that treatment effects are additional to the placebo effect. However, these assumptions have recently been challenged, and different mechanisms may potentially be operating in the placebo and treatment arms. The objective of the current study was to explore the nature of placebo versus pharmacological effects by comparing predictors of the placebo response with predictors of the treatment response in a randomised, placebo-controlled trial of a phytotherapeutic combination for the treatment of menopausal symptoms. A substantial placebo response was observed but no significant difference in efficacy between the two arms.</p> <p>Methods</p> <p>A <it>post hoc </it>analysis was conducted on data from 93 participants who completed this previously published study. Variables at baseline were investigated as potential predictors of the response on any of the endpoints of flushing, overall menopausal symptoms and depression. Focused tests were conducted using hierarchical linear regression analyses. Based on these findings, analyses were conducted for both groups separately. These findings are discussed in relation to existing literature on placebo effects.</p> <p>Results</p> <p>Distinct differences in predictors were observed between the placebo and active groups. A significant difference was found for study entry anxiety, and Greene Climacteric Scale (GCS) scores, on all three endpoints. Attitude to menopause was found to differ significantly between the two groups for GCS scores. Examination of the individual arms found anxiety at study entry to predict placebo response on all three outcome measures individually. In contrast, <it>low </it>anxiety was significantly associated with improvement in the active treatment group. None of the variables found to predict the placebo response was relevant to the treatment arm.</p> <p>Conclusion</p> <p>This study was a <it>post hoc </it>analysis of predictors of the placebo versus treatment response. Whilst this study does not explore neurobiological mechanisms, these observations are consistent with the hypotheses that 'drug' effects and placebo effects are not necessarily additive, and that mutually exclusive mechanisms may be operating in the two arms. The need for more research in the area of mechanisms and mediators of placebo versus active responses is supported.</p> <p>Trial Registration</p> <p>International Clinical Trials Registry ISRCTN98972974.</p

    Major flaws in conflict prevention policies towards Africa : the conceptual deficits of international actors’ approaches and how to overcome them

    Get PDF
    Current thinking on African conflicts suffers from misinterpretations oversimplification, lack of focus, lack of conceptual clarity, state-centrism and lack of vision). The paper analyses a variety of the dominant explanations of major international actors and donors, showing how these frequently do not distinguish with sufficient clarity between the ‘root causes’ of a conflict, its aggravating factors and its triggers. Specifically, a correct assessment of conflict prolonging (or sustaining) factors is of vital importance in Africa’s lingering confrontations. Broader approaches (e.g. “structural stability”) offer a better analytical framework than familiar one-dimensional explanations. Moreover, for explaining and dealing with violent conflicts a shift of attention from the nation-state towards the local and sub-regional level is needed.Aktuelle Analysen afrikanischer Gewaltkonflikte sind hĂ€ufig voller Fehlinterpretationen (Mangel an Differenzierung, Genauigkeit und konzeptioneller Klarheit, Staatszentriertheit, fehlende mittelfristige Zielvorstellungen). Breitere AnsĂ€tze (z. B. das Modell der Strukturellen StabilitĂ€t) könnten die Grundlage fĂŒr bessere Analyseraster und Politiken sein als eindimensionale ErklĂ€rungen. hĂ€ufig differenzieren ErklĂ€rungsansĂ€tze nicht mit ausreichender Klarheit zwischen Ursachen, verschĂ€rfenden und auslösenden Faktoren. Insbesondere die richtige Einordnung konfliktverlĂ€ngernder Faktoren ist in den jahrzehntelangen gewaltsamen Auseinandersetzungen in Afrika von zentraler Bedeutung. Das Diskussionspapier stellt die große Variationsbreite dominanter ErklĂ€rungsmuster der wichtigsten internationalen Geber und Akteure gegenĂŒber und fordert einen Perspektivenwechsel zum Einbezug der lokalen und der subregionalen Ebene fĂŒr die ErklĂ€rung und Bearbeitung gewaltsamer Konflikte

    BRCA1 mutation carriers have a lower number of mature oocytes after ovarian stimulation for IVF/PGD

    Get PDF
    Purpose The aim of this study was to determine whether BRCA1/2 mutation carriers produce fewer mature oocytes after ovarian stimulation for in vitro fertilization (IVF) with preimplantation genetic diagnosis (PGD), in comparison to a PGD control group. Methods A retrospective, international, multicenter cohort study was performed on data of first PGD cycles performed between January 2006 and September 2015. Data were extracted from medical files. The study was performed in one PGD center and three affiliated IVF centers in the Netherlands and one PGD center in Belgium. Exposed couples underwent PGD because of a pathogenic BRCA1/2 mutation, controls for other monogenic conditions. Only couples treated in a long gonadotropin-releasing hormone (GnRH) agonist-suppressive protocol, stimulated with at least 150 IU follicle stimulating hormone (FSH), were included. Women suspected to have a diminished ovarian reserve status due to chemotherapy, auto-immune disorders, or genetic conditions (other than BRCA1/2 mutations) were excluded. A total of 106 BRCA1/2 mutation carriers underwent PGD in this period, of which 43 (20 BRCA1 and 23 BRCA2 mutation carriers) met the inclusion criteria. They were compared to 174 controls selected by frequency matching. Results Thirty-eight BRCA1/2 mutation carriers (18 BRCA1 and 20 BRCA2 mutation carriers) and 154 controls proceeded to oocyte pickup. The median number of mature oocytes was 7.0 (interquartile range (IQR) 4.0-9.0) in the BRCA group as a whole, 6.5 (IQR 4.0-8.0) in BRCA1 mutation carriers, 7.5 (IQR 5.5-9.0) in BRCA2 mutation carriers, and 8.0 (IQR 6.0-11.0) in controls. Multiple linear regression analysis with the number of mature oocytes as a dependent variable and adjustment for treatment center, female age, female body mass index (BMI), type of gonadotropin used, and the total dose of gonadotropins administered revealed a significantly lower yield of mature oocytes in the BRCA group as compared to controls (p = 0.04). This finding could be fully accounted for by the BRCA1 subgroup (BRCA1 mutation carriers versus controls p = 0.02, BRCA2 mutation carriers versus controls p = 0.50). Conclusions Ovarian response to stimulation, expressed as the number of mature oocytes, was reduced in BRCA1 but not in BRCA2 mutation carriers. Although oocyte yield was in correspondence to a normal response in all subgroups, this finding points to a possible negative influence of the BRCA1 gene on ovarian reserv

    Noninvasive Prenatal Test Results Indicative of Maternal Malignancies:A Nationwide Genetic and Clinical Follow-Up Study

    Get PDF
    PURPOSE: Noninvasive prenatal testing (NIPT) for fetal aneuploidy screening using cell-free DNA derived from maternal plasma can incidentally raise suspicion for cancer. Diagnostic routing after malignancy suspicious-NIPT faces many challenges. Here, we detail malignancy suspicious-NIPT cases, and describe the clinical characteristics, chromosomal aberrations, and diagnostic routing of the patients with a confirmed malignancy. Clinical lessons can be learned from our experience. METHODS: Patients with NIPT results indicative of a malignancy referred for tumor screening between April 2017 and April 2020 were retrospectively included from a Dutch nationwide NIPT implementation study, TRIDENT-2. NIPT profiles from patients with confirmed malignancies were reviewed, and the pattern of chromosomal aberrations related to tumor type was analyzed. We evaluated the diagnostic contribution of clinical and genetic examinations. RESULTS: Malignancy suspicious-NIPT results were reported in 0.03% after genome-wide NIPT, and malignancies confirmed in 16 patients (16/48, 33.3%). Multiple chromosomal aberrations were seen in 23 of 48 patients with genome-wide NIPT, and a malignancy was confirmed in 16 patients (16/23, 69.6%). After targeted NIPT, 0.005% malignancy suspicious-NIPT results were reported, in 2/3 patients a malignancy was confirmed. Different tumor types and stages were diagnosed, predominantly hematologic malignancies (12/18). NIPT data showed recurrent gains and losses in primary mediastinal B-cell lymphomas and classic Hodgkin lymphomas. Magnetic resonance imaging and computed tomography were most informative in diagnosing the malignancy. CONCLUSION: In 231,896 pregnant women, a low percentage (0.02%) of NIPT results were assessed as indicative of a maternal malignancy. However, when multiple chromosomal aberrations were found, the risk of a confirmed malignancy was considerably high. Referral for extensive oncologic examination is recommended, and may be guided by tumor-specific hallmarks in the NIPT profile

    Unbearability of suffering at the end of life: the development of a new measuring device, the SOS-V

    Get PDF
    AbstractBackgroundUnbearable suffering is an important issue in end-of-life decisions. However, there has been no systematic, prospective, patient-oriented research which has focused on unbearable suffering, nor is there a suitable measurement instrument. This article describes the methodological development of a quantitative instrument to measure the nature and intensity of unbearable suffering, practical aspects of its use in end-stage cancer patients in general practice, and studies content validity and psychometric properties.MethodsRecognizing the conceptual difference between unbearability of suffering and extent or intensity of suffering, we developed an instrument. The compilation of aspects considered to be of importance was based on a literature search. Psychometric properties were determined on results of the first interviews with 64 end-stage cancer patients that participated in a longitudinal study in the Netherlands.ResultsThe instrument measures five domains: medical signs and symptoms, loss of function, personal aspects, aspects of environment, and nature and prognosis of the disease. Sixty nine aspects were investigated, and an overall score was asked. In 64 end-stage cancer patients the instrument was used in total 153 times with an average interview time varying from 20-40 minutes. Cronbachs alpha's of the subscales were in majority above 0.7. The sum scores of (sub)scales were correlated strongly to overall measures on suffering.ConclusionThe SOS-V is an instrument for measuring the unbearability of suffering in end-stage cancer patients with good content validity and psychometric properties, which is feasible to be used in practice. This structured instrument makes it possible to identify and study unbearable suffering in a quantitative and patient-oriented way

    Identification of superior reference genes for data normalisation of expression studies via quantitative PCR in hybrid roses (Rosa hybrida)

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Gene expression studies are a prerequisite for understanding the biological function of genes. Because of its high sensitivity and easy use, quantitative PCR (qPCR) has become the gold standard for gene expression quantification. To normalise qPCR measurements between samples, the most prominent technique is the use of stably expressed endogenous control genes, the so called reference genes. However, recent studies show there is no universal reference gene for all biological questions. Roses are important ornamental plants for which there has been no evaluation of useful reference genes for gene expression studies.</p> <p>Results</p> <p>We used three different algorithms (BestKeeper, geNorm and NormFinder) to validate the expression stability of nine candidate reference genes in different rose tissues from three different genotypes of <it>Rosa hybrida </it>and in leaves treated with various stress factors. The candidate genes comprised the classical "housekeeping genes" (<it>Actin, EF-1α, GAPDH</it>, <it>Tubulin </it>and <it>Ubiquitin</it>), and genes showing stable expression in studies in <it>Arabidopsis </it>(<it>PP2A, SAND, TIP </it>and <it>UBC</it>). The programs identified no single gene that showed stable expression under all of the conditions tested, and the individual rankings of the genes differed between the algorithms. Nevertheless the new candidate genes, specifically, <it>PP2A </it>and <it>UBC</it>, were ranked higher as compared to the other traditional reference genes. In general, <it>Tubulin </it>showed the most variable expression and should be avoided as a reference gene.</p> <p>Conclusions</p> <p>Reference genes evaluated as suitable in experiments with <it>Arabidopsis thaliana </it>were stably expressed in roses under various experimental conditions. In most cases, these genes outperformed conventional reference genes, such as <it>EF1-α </it>and <it>Tubulin</it>. We identified <it>PP2A</it>, <it>SAND </it>and <it>UBC </it>as suitable reference genes, which in different combinations may be used for normalisation in expression analyses via qPCR for different rose tissues and stress treatments. However, the vast genetic variation found within the genus <it>Rosa</it>, including differences in ploidy levels, might also influence expression stability of reference genes, so that future research should also consider different genotypes and ploidy levels.</p

    First RNA-seq approach to study fruit set and parthenocarpy in zucchini (Cucurbita pepo L.)

    Full text link
    [EN] Background: Zucchini fruit set can be limited due to unfavourable environmental conditions in off-seasons crops that caused ineffective pollination/fertilization. Parthenocarpy, the natural or artificial fruit development without fertilization, has been recognized as an important trait to avoid this problem, and is related to auxin signalling. Nevertheless, differences found in transcriptome analysis during early fruit development of zucchini suggest that other complementary pathways could regulate fruit formation in parthenocarpic cultivars of this species. The development of next-generation sequencing technologies (NGS) as RNA-sequencing (RNA-seq) opens a new horizon for mapping and quantifying transcriptome to understand the molecular basis of pathways that could regulate parthenocarpy in this species. The aim of the current study was to analyze fruit transcriptome of two cultivars of zucchini, a non-parthenocarpic cultivar and a parthenocarpic cultivar, in an attempt to identify key genes involved in parthenocarpy. Results: RNA-seq analysis of six libraries (unpollinated, pollinated and auxin treated fruit in a non-parthenocarpic and parthenocarpic cultivar) was performed mapping to a new version of C. pepo transcriptome, with a mean of 92% success rate of mapping. In the non-parthenocarpic cultivar, 6479 and 2186 genes were differentially expressed (DEGs) in pollinated fruit and auxin treated fruit, respectively. In the parthenocarpic cultivar, 10,497 in pollinated fruit and 5718 in auxin treated fruit. A comparison between transcriptome of the unpollinated fruit for each cultivar has been performed determining that 6120 genes were differentially expressed. Annotation analysis of these DEGs revealed that cell cycle, regulation of transcription, carbohydrate metabolism and coordination between auxin, ethylene and gibberellin were enriched biological processes during pollinated and parthenocarpic fruit set. Conclusion: This analysis revealed the important role of hormones during fruit set, establishing the activating role of auxins and gibberellins against the inhibitory role of ethylene and different candidate genes that could be useful as markers for parthenocarpic selection in the current breeding programs of zucchini.Research worked is supported by the project RTA2014-00078 from the Spanish Institute of Agronomy Research INIA (Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria) and also PP.AVA.AVA201601.7, FEDER y FSE (Programa Operativo FSE de Andalucia 2007-2013 "Andalucia se mueve con Europa"). TPV is supported by a FPI scholarship from RTA2011-00044-C02-01/02 project of INIA. The funding agencies were not involved in the design of the study, collection, analysis, and interpretation of data and in writing the manuscript.Pomares-Viciana, T.; Del Rio-Celestino, M.; Roman, B.; Die, J.; PicĂł Sirvent, MB.; GĂłmez, P. (2019). First RNA-seq approach to study fruit set and parthenocarpy in zucchini (Cucurbita pepo L.). BMC Plant Biology. 19:1-20. https://doi.org/10.1186/s12870-019-1632-2S12019Varga A, Bruinsma J. Tomato. In: Monselise SP, editor. CRC Handbook of Fruit Set and Development. Boca Raton: CRC Press; 1986. p. 461–80.Nepi M, Cresti L, Guarnieri M, Pacini E. Effect of relative humidity on water content, viability and carbohydrate profile of Petunia hybrid and Cucurbita pepo pollen. Plant Syst Evol. 2010;284:57–64.Gustafson FG. Parthenocarpy: natural and artificial. Bot Rev. 1942;8:599–654.Robinson RW, Reiners S. Parthenocarpy in summer squash. Hortscience. 1999;34:715–7.Pomares-Viciana T, Die J, Del RĂ­o-Celestino M, RomĂĄn B, GĂłmez P. Auxin signalling regulation during induced and parthenocarpic fruit set in zucchini. Mol Breeding. 2017;37:56.Ozga JA, Reinecke DM. Hormonal interactions in fruit development. J Plant Growth Regul. 2003;22:73–81.Kim IS, Okubo H, Fujieda K. Endogenous levels of IAA in relation to parthenocarpy in cucumber (Cucumis sativus L). Sci Hortic. 1992;52:1–8.Olimpieri I, Siligato F, Caccia R, Mariotti L, Ceccarelli N, Soressi GP, et al. Tomato fruit set driven by pollination or by the parthenocarpic fruit allele are mediated by transcriptionally regulated gibberellin biosynthesis. Planta. 2007;226:877–88.Cui L, Zhang T, Li J, Lou Q, Chen J. Cloning and expression analysis of Cs-TIR1/AFB2: the fruit development-related genes of cucumber (Cucumis sativus L.). Acta Physiol Plant. 2014;36:139–49.De Jong M, Wolters-Arts J, Feron R, Mariani C, Vriezen WH. The Solanum lycopersicum auxin response factor 7 (SlARF7) regulates auxin signalling during tomato fruit set and development. Plant J. 2009;57:160–70.Wang H, Jones B, Li Z, Frasse P, Delalande C, Regad F, Chaabouni S, LatchĂ© A, Pech JC, Bouzayen M. The tomato aux/IAA transcription factor IAA9 is involved in fruit development and leaf morphogenesis. Plant Cell. 2005;17(10):2676–92.Goetz M, Vivian-Smith A, Johnson SD, Koltunow AM. AUXIN RESPONSE FACTOR 8 is a negative regulator of fruit initiation in Arabidopsis. Plant Cell. 2006;18(8):1873–86.Mazzucato A, Cellini F, Bouzayen M, Zouine M, Mila I, Minoia S et al. A TILLING allele of the tomato aux/IAA9 gene offers new insights into fruit set mechanisms and perspectives for breeding seedless tomatoes. Mol Breeding. 2015; 35(22):1-15.Blanca J, Cañizares J, Roig C, Ziarsolo P, Nuez F, PicĂł B. Transcriptome characterization and high throughput SSRs and SNPs discovery in Cucurbita pepo (Cucurbitaceae). BMC Genomics. 2011;12:104.Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10(1):57–63.Da Fonseca RR, Albrechtsen A, Themudo GE, Ramos-Madrigal J, Sibbesen JA, Maretty L, et al. Next-generation biology: sequencing and data analysis approaches for non-model organisms. Mar Genomics. 2016;30:3–13.Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A, et al. A survey of best practices for RNA-seq data analysis. Genome Biol. 2016;17:13.Li J, Cui ZWJ, Zhang T, Guo Q, Xu J, Li J, et al. Transcriptome comparison of global distinctive features between pollination and parthenocarpic fruit set reveals transcriptional phytohormone cross-talk in cucumber (Cucumis sativus L). Plant Cell Physiol. 2014;55(7):1325–42.Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics. 2012;28(23):3150–2.Montero-Pau J, Blanca J, Bombarely A, Ziarsolo P, Esteras C, MartĂ­-GĂłmez C, et al. De novo assembly of the zucchini genome reveals a whole genome duplication associated with the origin of the Cucurbita genus. Plant Biotechnol J. 2017. https://doi.org/10.1111/pbi.12860 .Vriezen WH, Feron R, Maretto F, Keijman J, Mariani C. Changes in tomato ovary transcriptome demonstrate complex hormonal regulation of fruit set. New Phytol. 2008;177:60–76.Tang N, Deng W, Hu G, Hu N, Li Z. Transcriptome profiling reveals the regulatory mechanism underlying pollination dependent and parthenocarpic fruit set mainly mediated by auxin and gibberellin. PLoS One. 2015;10(4):e0125355.Li J, Yan S, Yang W, Li Y, Xia M, Chen Z, et al. Transcriptomic analysis reveals the roles of microtubule-related genes and transcription factors in fruit length regulation in cucumber (Cucumis sativus L.). Sci Rep. 2015;26(5):8031.Mironov V, De Veylder L, Van Montagu M, Inze D. Cyclin-dependent kinases and cell division in plants- the nexus. Plant Cell. 1999;11(4):509–22.Perrot-Rechenmann C. Cellular responses to auxin: division versus expansion. Cold Spring Harb Perspect Biol. 2010;2(5):a001446.De Veylder L, Beeckman T, Beemster GT, Krols L, Terras F, Landrieu I, et al. Functional analysis of cyclin-dependent kinase inhibitors of Arabidopsis. Plant Cell. 2001;13:1653–68.Nieuwland J, Menges M, Murray JAH. The plant cyclins. In: Inze D, editor. Cell cycle control and plant development, vol. 2007. Oxford: Wiley-Blackwell Publishing; 2007. p. 33–61.Menges M, Samland AK, Planchais S, Murray JA. The D-type cyclin CYCD3;1 is limiting for the G1-to-S-phasetransition in Arabidopsis. Plant Cell. 2006;18:893–906.Boruc J, Mylle E, Duda M, De Clercq R, Rombauts S, Geelen D, et al. Systematic localization of the Arabidopsis core cell cycle proteins reveals novel cell division complexes. Plant Physiol. 2010;152(2):553–65.Sampedro J, Cosgrove DJ. The expansin superfamily. Genome Biol. 2005;6:242.Esmon CA, Tinsley AG, Ljung K, Sandberg G, Hearne LB, Liscum E. A gradient of auxin and auxin-dependent transcription precedes tropic growth responses. Proc Natl Acad Sci. 2006;103:236–41.De Folter S, Busscher J, Colombo L, Losa A, Angenent GC. Transcript profiling of transcription factors genes during siliques development in Arabidopsis. Plant Mol Bio. 2004;56:351–3662004.Son O, Cho HY, Kim MR, Lee H, Lee MS, Song E, et al. Induction of a homeodomain-leucine zipper gene by auxin is inhibited by cytokinin in Arabidopsis roots. Biochem Biophys Res Commun. 2005;326(1):203–9.Olsson ASB, Engstroem P, Seoderman E. The homeobox genes ATHB12 and ATHB7 encode potential regulators of growth in response to water deficit in Arabidopsis. Plant Mol Biol. 2004;55:663–77.Merrow SB, Hopp RJ. Storage effects on winter squashes. Associations between the sugar and starch content of and the degree of preference for winter squashes. J Agric Food Chem. 1961;9:321–6.Berg JM, Tymoczko JL, Stryer L. Carbohydrates. In: Freeman WH, editor. Biochemistry. 5th ed. New York: W H Freeman; 2002.Prabhakar V, Löttgert T, Gigolashvili T, Bell K, FlĂŒgge UI, HĂ€usler RE. Molecular and functional characterization of the plastid-localized phosphoenolpyruvate enolase (ENO1) from Arabidopsis thaliana. FEBS Lett. 2009;583(6):983–91.Rius SP, Casati P, Iglesias AA, Gomez-Casati DF. Characterization of Arabidopsis lines deficient in GAPC-1, a cytosolic NAD-dependent glyceraldehyde-3-phosphate dehydrogenase. Plant Physiol. 2008;148(3):1655–67.Van der Linde K, Gutsche N, Leffers HM, Lindermayr C, MĂŒller B, Holtgrefe S, et al. Regulation of plant cytosolic aldolase functions by redox-modifications. Plant Physiol Biochem. 2011;49(9):946–57.Lim H, Cho MH, Jeon JS, Bhoo SH, Kwon YK, Hahn TR. Altered expression of pyrophosphate: fructose-6-phosphate 1-phosphotransferase affects the growth of transgenic Arabidopsis plants. Mol Cells. 2009;27(6):641–9.Baud S, WuillĂšme S, Dubreucq B, De Almeida A, Vuagnat C, Lepiniec L, et al. Function of plastidial pyruvate kinases in seeds of Arabidopsis thaliana. Plant J. 2007;52:405–19.De Jong M, Mariani C, Vriezen WH. The role of auxin and gibberellin in tomato fruit set. J Exp Bot. 2009;60(5):1523–32.MartĂ­nez C, Manzano S, MegĂ­as Z, Garrido D, PicĂł B, Jamilena M. Involvement of ethylene biosynthesis and signalling in fruit set and early fruit development in zucchini squash (Cucurbita pepo L.). BMC Plant Biol. 2013;13:139.Serrani JC, Fos M, AtarĂ©s A, Garcia-martinez JL. Effect of gibberellin and auxin on parthenocarpic fruit growth induction in the cv. micro-tom of tomato. J Plant Growth Regul. 2007;26:211–21.Mapelli S. Changes in cytokinin in the fruits of parthenocarpic and normal tomatoes. Plant Sci Lett. 1981;22:227–33.Ulmasov T, Hagen G, Guilfoyle TJ. Activation and repression of transcription by auxin-response factors. Proc Natl Acad Sci U S A. 1999;96:5844–9.Ulmasov T, Hagen G, Guilfoyle TJ. Dimerization and DNA binding of auxin response factors. Plant J. 1999;19:309–19.Tiwari SB, Hagen G, Guilfoyle TJ. Aux/IAA proteins contain a potent transcriptional repression domain. Plant Cell. 2004;16:533–43.Switzenberg JA, Beaudry RM, Grumet R. Effect of CRC:: etr1-1 transgene expression on ethylene production, sex expression, fruit set and fruit ripening in transgenic melon (Cucumis melo L.). Transgenic Res. 2015;24(3):497-507.Nitsch LM, Oplaat C, Feron R, Ma Q, Wolters-Arts M, Hedden P, et al. Abscisic acid levels in tomato ovaries are regulated by LeNCED1 and SlCYP707A1. Planta. 2009;229(6):1335–46.Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat Methods. 2008;5(7):621–8.Robinson MD, McCarthy DJ, Smyth GK. Edger: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2008;26(1):139–40.Raza K, Mishra A. A novel anticlustering filtering algorithm for the prediction of genes as a drug target. Am J Bio Engi. 2012;2(5):206–11.Van Iterson M, Boer JM, Menezes RX. Filtering, FDR and power. BMCBioinformatics. 2010;11:450.Conesa A, Götz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21:3674–6.Berardini TZ, Reiser L, Li D, Mezheritsky Y, Muller R, Strait E, Huala E. The Arabidopsis information resource: making and mining the “gold standard” annotated reference plant genome. Genesis. 2015. https://doi.org/10.1002/dvg.22877 .Bairoch A, Apweiler R. The SWISS-PROT protein sequence database and its supplement TrEMBL. Nucleic Acids Res. 2000;28(1):45–8.Johnson M, Zaretskaya I, Raytselis Y, Merezhuk Y, McGinnis S, Madden TL. NCBI BLAST: a better web interface. Nucleic Acids Res. 2008;36:W5–9.Wyatt LE, Strickler SR, Mueller LA, Mazourek M. An acorn squash (Cucurbita pepo ssp. ovifera) fruit and seed transcriptome as a resource for the study of fruit traits in Cucurbita. Hortic Res. 2015;2:14070. https://doi.org/10.1038/hortres.2014.70 .Zhang A, Ren GA, Sun YA, Guo H, Zhang SA, Zhang FA, et al. A high-density genetic map for anchoring genome sequences and identifying QTLs associated with dwarf vine in pumpkin (Cucurbita maxima Duch.). BMC Genomics. 2015;16:1101.Finn RD, Attwood TK, Babbit AB, Bork P, Bridge AJ, Chang HY. InterPro in 2017-beyond protein family and domain annotations. Nucleic Acids Res. https://doi.org/10.1093/nar/gkw1107 .Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Sherlock G. Gene ontology: tool for the unification of biology. Nat Genet. 2000;25(1):25–9.Kanehisa M, Araki M, Goto S, et al. KEGG for linking genomes to life and the environment. Nucleic Acids Res. 2008;36:480–4
    • 

    corecore