1,333 research outputs found

    Effect of GA 3 and paclobutrazol on adventitious shoot regeneration of two Pelargonium sp

    Get PDF
    This study had two aims. The first was to improve the regeneration efficiency of Pelargonium leaf discs by adventitious budding. The second was to test the effect of gibberellic acid (GA 3) and paclobutrazol (PBZ) on callus formation and adventitious shoot regeneration in Pelargonium before using genetic transformation of this species for functional validation of genes involved in the process of GA regulation. GA 3 and paclobutrazol (an inhibitor of GA synthesis pathway) were added (together or separately) in the shoot regeneration media of two Pelargonium species, Pelargonium * hortorum \u27Panache sud\u27 (\u27P.sud\u27) and Pelargonium * domesticum \u27Autumn haze\u27 (\u27 P.dom\u27). In both cases, GA 3 applied alone, completely inhibited the bud regeneration. Moreover, the rate of callus formation decreased drastically when 5 M of GA 3 was applied to \u27 P. dom\u27 explants. Similar result was obtained with \u27P.sud\u27 explants using 20 M GA 3. Paclobutrazol (0.3 M) applied at the same time as GA 3 (10 M) could partially restore regeneration process of \u27 P. dom\u27. For \u27 P. dom\u27, the use of paclobutrazol alone increased callus formation and slightly improved the rate of regeneration. Moreover, initiated buds had a better appearance. For \u27P. sud\u27, which had an abundant callusing, paclobutrazol did not improve regeneration and led to hyperhydric shoots

    Revascularization of transplanted pancreatic islets and role of the transplantation site

    Get PDF
    Since the initial reporting of the successful reversal of hyperglycemia through the transplantation of pancreatic islets, significant research efforts have been conducted in elucidating the process of revascularization and the influence of engraftment site on graft function and survival. During the isolation process the intrinsic islet vascular networks are destroyed, leading to impaired revascularization after transplant. As a result, in some cases a significant quantity of the beta cell mass transplanted dies acutely following the infusion into the portal vein, the most clinically used site of engraftment. Subsequently, despite the majority of patients achieving insulin independence after transplant, a proportion of them recommence small, supplemental exogenous insulin over time. Herein, this review considers the process of islet revascularization after transplant, its limiting factors, and potential strategies to improve this critical step. Furthermore, we provide a characterization of alternative transplant sites, analyzing the historical evolution and their role towards advancing transplant outcomes in both the experimental and clinical settings

    A new technique for precisely and accurately measuring lumbar spine bone mineral density in mice using clinical dual energy X-ray absorptiometry (DXA)

    Get PDF
    Dual Energy X-ray Absorptiometry (DXA) is effective in measuring bone mineral density (BMD) in mice for early detection of osteoporosis. However, scanners designed for use with small animals (i.e. PIXImus) are very expensive. Used human DXA machines are cheaper to obtain, but analysis of scans from these instruments is operator-dependent. Obtaining reliable data depends on having a single operator analyze the scans in a blinded fashion. Scan quality is improved by excising the bone prior to scanning, which does not allow serial measurements. This study describes a novel method of analyzing lumbar spine BMD in mice using whole body DXA. This non-invasive technique has a high degree of precision and reproducibility, with good correlation between multiple observers. Inter-observer variability (0.063 ± 0.00317 g/cm2 [mean ± SD], 5.05 [% coefficient of variation (CV)], repeat scan variability (0.063 ± 0.00364 g/cm2 [mean ± SD], 5.94 [%CV]) were very low compared to variability between different animals (0.063 ± 0.00588 g/cm2 [mean ± SD], 9.64 [%CV]) and variability seen in same animal over time (0.011 ± 0.00885 g/cm2 [mean ± SD], 80.68 [%CV]). The measurement error is thus smaller than the biological variation. Accuracy was determined by comparing average peak BMD from two scans per mouse in-vivo (0.066 g/cm2) versus excised spine (0.065 g/cm2). Furthermore, correlation between bone ash weights and whole body lumbar spine BMD measurements (p < 0.0001) was highly significant. This technique thus shows a high degree of precision and accuracy, even with multiple observers, for measuring BMD in mice using a DXA machine designed for clinical use

    Multifocal Transcranial Direct Current Stimulation in Primary Progressive Aphasia Does Not Provide a Clinical Benefit Over Speech Therapy

    Full text link
    Primary progressive aphasia (PPA) is a group of neurodegenerative disorders including Alzheimer's disease and frontotemporal dementia characterized by language deterioration. Transcranial direct current stimulation (tDCS) is a non-invasive intervention for brain dysfunction.To evaluate the tolerability and efficacy of tDCS combined with speech therapy in the three variants of PPA. We evaluate changes in fMRI activity in a subset of patients.Double-blinded, randomized, cross-over, and sham-controlled tDCS study. 15 patients with PPA were included. Each patient underwent two interventions: a) speech therapy + active tDCS and b) speech therapy + sham tDCS stimulation. A multifocal strategy with anodes placed in the left frontal and parietal regions was used to stimulate the entire language network. Efficacy was evaluated by comparing the results of two independent sets of neuropsychological assessments administered at baseline, immediately after the intervention, and at 1 month and 3 months after the intervention. In a subsample, fMRI scanning was performed before and after each intervention.The interventions were well tolerated. Participants in both arms showed clinical improvement, but no differences were found between active and sham tDCS interventions in any of the evaluations. There were trends toward better outcomes in the active tDCS group for semantic association and reading skills. fMRI identified an activity increase in the right frontal medial cortex and the bilateral paracingulate gyrus after the active tDCS intervention.We did not find differences between active and sham tDCS stimulation in clinical scores of language function in PPA patients

    APP-derived peptides reflect neurodegeneration in frontotemporal dementia

    Get PDF
    Altres ajuts: The Catalan frontotemporal initiative (CATFI) is funded by the Health Department of the Government of Catalonia (grant PERIS SLT002/16/00408 to Alberto Lleó and Raquel Sánchez-Valle). This work was also supported by research grants from the CIBERNED Program (Program 1, Alzheimer Disease to Alberto Lleó and SIGNAL study, file://www.signalstudy.es), partly funded by Fondo Europeo de Desarrollo Regional (FEDER), Unión Europea, "Una manera de hacer Europa." This work has also been supported by a "Marató TV3" grant (20141210 to Juan Fortea, 044412 to Rafael Blesa, 20143710 to Ricard Rojas-García and 20143810 to Raquel Sánchez-Valle) and Fundación BBVA (grant to A. Lleó) and a grant from the Fundació Bancaria La Caixa to Rafael Blesa. Ignacio Illán-Gala and Sergi Borrego-Écija are supported by the Rio Hortega grant from "Acción estratégica en Salud 2013-2016" and the European Social Fund. Ignacio Illán-Gala is supported by the Global Brain Health Institute (Atlantic Fellow for Equity in Brain Health). We acknowledge all the participants in this study and all the collaborators of the SPIN cohort. We also acknowledge Soraya Torres and Laia Muñoz for technical assistance. We thank EUROIMMUN for providing Aβ1-38 and Aβ1-40 ELISA assays for this study.Objective: We aimed to investigate the relationship between cerebrospinal fluid levels (CSF) of amyloid precursor protein (APP)-derived peptides related to the amyloidogenic pathway, cortical thickness, neuropsychological performance, and cortical gene expression profiles in frontotemporal lobar degeneration (FTLD)-related syndromes, Alzheimer's disease (AD), and healthy controls. Methods: We included 214 participants with CSF available recruited at two centers: 93 with FTLD-related syndromes, 57 patients with AD, and 64 healthy controls. CSF levels of amyloid β (Aβ)1-42, Aβ1-40, Aβ1-38, and soluble β fragment of APP (sAPPβ) were centrally analyzed. We compared CSF levels of APP-derived peptides between groups and, we studied the correlation between CSF biomarkers, cortical thickness, and domain-specific cognitive composites in each group. Then, we explored the relationship between cortical thickness, CSF levels of APP-derived peptides, and regional gene expression profile using a brain-wide regional gene expression data in combination with gene set enrichment analysis. Results: The CSF levels of Aβ1-40, Aβ1-38, and sAPPβ were lower in the FTLD-related syndromes group than in the AD and healthy controls group. CSF levels of all APP-derived peptides showed a positive correlation with cortical thickness and the executive cognitive composite in the FTLD-related syndromes group but not in the healthy control or AD groups. In the cortical regions where we observed a significant association between cortical thickness and CSF levels of APP-derived peptides, we found a reduced expression of genes related to synaptic function. Interpretation: APP-derived peptides in CSF may reflect FTLD-related neurodegeneration. This observation has important implications as Aβ1-42 levels are considered an indirect biomarker of cerebral amyloidosis

    Beta cell death by cell-free DNA and outcome after clinical islet transplantation

    Get PDF
    Background: Optimizing engraftment and early survival after clinical islet transplantation is critical to long-term function, but there are no reliable, quantifiable measures to assess beta cell death. Circulating cell free DNA (cfDNA) derived from beta cells has been identified as a novel biomarker to detect cell loss, and was recently validated in new-onset type 1 diabetes and in islet transplant patients. Methods: Herein we report beta cell cfDNA measurements after allotransplantation in 37 subjects and the correlation with clinical outcomes. Results: A distinctive peak of cfDNA was observed 1hr after transplantation in 31/37 (83.8%) of subjects. The presence and magnitude of this signal did not correlate with transplant outcome. The 1hr signal represents dead beta cells carried over into the recipient after islet isolation and culture, combined with acute cell death post infusion. Beta cell cfDNA was also detected 24hrs post-transplant (8/37 subjects, 21.6%). This signal was associated with higher 1-month insulin requirements (p=0.04), lower 1-month stimulated C-peptide levels (p=0.01) and overall worse 3-month engraftment, by insulin independence (ROC:AUC=0.70, p=0.03) and Beta 2 score (ROC:AUC=0.77, p=0.006). Conclusions: cfDNA-based estimation of beta cell death 24hrs after islet allotransplantation correlates with clinical outcome and could predict early engraftment.B.G.-L. is supported through the Alberta Innovates :Health Solutions (AIHS) Clinician Fellowship and through the CNTRP. A.P. is supported through AIHS Postgraduate Fellowship and CNTRP. A.M.J.S. is supported through AIHS, and holds a Canada Research Chair in Transplantation Surgery and Regenerative Medicine funded through the Government of Canada. A.M.J.S. is also funded by AIHS Collaborative Research and Innovation Opportunity Team Award and the Diabetes Research Institute Foundation of Canada (DRIFCan). Supported by grants from the Juvenile Diabetes Research Foundation (JDRF) (3-SRA-2014-38-Q-R, to Y.D. and A.M.J.S.), National Institute of Health (NIH) (HIRN grant UC4 DK104216, to Y.D.), DON foundation (Stichting Diabetes Onderzoek Nederland) (to Y.D), the European Union (ELASTISLET project, to Y.D.) and the Kahn foundation (to Y.D., R.S., and B.G.). Supported in part by a grant from The United States Agency for International Development (USAID) American Schools and Hospitals Abroad Program for the upgrading of the Hebrew University sequencing core facilit

    Plasma Tau and Neurofilament Light in Frontotemporal Lobar Degeneration and Alzheimer Disease

    Get PDF
    Objective: To test the hypothesis that plasma total tau (t-tau) and neurofilament light chain (NfL) concentrations may have a differential role in the study of frontotemporal lobar degeneration syndromes (FTLD-S) and clinically diagnosed Alzheimer disease syndromes (AD-S), we determined their diagnostic and prognostic value in FTLD-S and AD-S and their sensitivity to pathologic diagnoses. Methods: We measured plasma t-tau and NfL with the Simoa platform in 265 participants: 167 FTLD-S, 43 AD-S, and 55 healthy controls (HC), including 82 pathology-proven cases (50 FTLD-tau, 18 FTLD-TDP, 2 FTLD-FUS, and 12 AD) and 98 participants with amyloid PET. We compared cross-sectional and longitudinal biomarker concentrations between groups, their correlation with clinical measures of disease severity, progression, and survival, and cortical thickness. Results: Plasma NfL, but not plasma t-tau, discriminated FTLD-S from HC and AD-S from HC. Both plasma NfL and t-tau were poor discriminators between FLTD-S and AD-S. In pathology-confirmed cases, plasma NfL was higher in FTLD than AD and in FTLD-TDP compared to FTLD-tau, after accounting for age and disease severity. Plasma NfL, but not plasma t-tau, predicted clinical decline and survival and correlated with regional cortical thickness in both FTLD-S and AD-S. The combination of plasma NfL with plasma t-tau did not outperform plasma NfL alone. Conclusion: Plasma NfL is superior to plasma t-tau for the diagnosis and prediction of clinical progression of FTLD-S and AD-S. Classification of Evidence: This study provides Class III evidence that plasma NfL has superior diagnostic and prognostic performance vs plasma t-tau in FTLD and AD

    Partial Activation of SA- and JA-Defensive Pathways in Strawberry upon Colletotrichum acutatum Interaction

    Get PDF
    [EN] Understanding the nature of pathogen host interaction may help improve strawberry (Fragaria x anahassa) cultivars. Plant resistance to pathogenic agents usually operates through a complex network of defense mechanisms mediated by a diverse array of signaling molecules. In strawberry, resistance to a variety of pathogens has been reported to be mostly polygenic and quantitatively inherited, making it difficult to associate molecular markers with disease resistance genes. Colletotrichum acutaturn spp. is a major strawberry pathogen, and completely resistant cultivars have not been reported. Moreover, strawberry defense network components and mechanisms remain largely unknown and poorly understood. Assessment of the strawberry response to C. acutatum included a global transcript analysis, and acidic hormones SA and JA measurements were analyzed after challenge with the pathogen. Induction of transcripts corresponding to the SA and JA signaling pathways and key genes controlling major steps within these defense pathways was detected. Accordingly, SA and JA accumulated in strawberry after infection. Contrastingly, induction of several important SA, JA, and oxidative stress-responsive defense genes, including FaPR1-1, FaLOX2, FaJAR1, FaPDF1, and FaGST1, was not detected, which suggests that specific branches in these defense pathways (those leading to FaPR1-2, FaPR2-1, FaPR2-2, FaAOS, FaPR5, and FaPR10) were activated. Our results reveal that specific aspects in SA and JA dependent signaling pathways are activated in strawberry upon interaction with C. acutatum. Certain described defense-associated transcripts related to these two known signaling pathways do not increase in abundance following infection. This finding suggests new insight into a specific putative molecular strategy for defense against this pathogen.Authors are grateful to Dr. JM Lopez-Aranda (IFAPA-Centro de Churriana) for providing micropropagated strawberry plants and to Nicolas Garcia-Caparros for technical assistance. Authors also want to thank Kevin M. Folta for his insightful comments on the paper. This work was supported by Junta de Andalucia, Spain [Proyectos de Excelencia P07-AGR-02482/P12-AGR-2174, and grants to Grupo-BIO278].Amil-Ruiz, F.; Garrido-Gala, J.; Gadea Vacas, J.; Blanco-Portales, R.; Munoz-Merida, A.; Trelles, O.; De Los Santos, B.... (2016). Partial Activation of SA- and JA-Defensive Pathways in Strawberry upon Colletotrichum acutatum Interaction. Frontiers in Plant Science. 7(1036). https://doi.org/10.3389/fpls.2016.01036S71036Acosta, I. F., & Farmer, E. E. (2010). Jasmonates. The Arabidopsis Book, 8, e0129. doi:10.1199/tab.0129Al-Shahrour, F., Diaz-Uriarte, R., & Dopazo, J. (2004). FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes. Bioinformatics, 20(4), 578-580. doi:10.1093/bioinformatics/btg455Altschul, S. F., Gish, W., Miller, W., Myers, E. W., & Lipman, D. J. (1990). Basic local alignment search tool. Journal of Molecular Biology, 215(3), 403-410. doi:10.1016/s0022-2836(05)80360-2Amil-Ruiz, F., Blanco-Portales, R., Muñoz-Blanco, J., & Caballero, J. L. (2011). The Strawberry Plant Defense Mechanism: A Molecular Review. Plant and Cell Physiology, 52(11), 1873-1903. doi:10.1093/pcp/pcr136Amil-Ruiz, F., Garrido-Gala, J., Blanco-Portales, R., Folta, K. M., Muñoz-Blanco, J., & Caballero, J. L. (2013). Identification and Validation of Reference Genes for Transcript Normalization in Strawberry (Fragaria × ananassa) Defense Responses. PLoS ONE, 8(8), e70603. doi:10.1371/journal.pone.0070603Arroyo, F. T., Moreno, J., García-Herdugo, G., Santos, B. D. los, Barrau, C., Porras, M., … Romero, F. (2005). Ultrastructure of the early stages of Colletotrichum acutatum infection of strawberry tissues. Canadian Journal of Botany, 83(5), 491-500. doi:10.1139/b05-022Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., … Sherlock, G. (2000). Gene Ontology: tool for the unification of biology. Nature Genetics, 25(1), 25-29. doi:10.1038/75556Aviv, D. H., Rustérucci, C., Iii, B. F. H., Dietrich, R. A., Parker, J. E., & Dangl, J. L. (2002). Runaway cell death, but not basal disease resistance, inlsd1is SA- andNIM1/NPR1-dependent. The Plant Journal, 29(3), 381-391. doi:10.1046/j.0960-7412.2001.01225.xBak, S., Beisson, F., Bishop, G., Hamberger, B., Höfer, R., Paquette, S., & Werck-Reichhart, D. (2011). Cytochromes P450. The Arabidopsis Book, 9, e0144. doi:10.1199/tab.0144Baniwal, S. K., Bharti, K., Chan, K. Y., Fauth, M., Ganguli, A., Kotak, S., … von Koskull-DÖring, P. (2004). Heat stress response in plants: a complex game with chaperones and more than twenty heat stress transcription factors. Journal of Biosciences, 29(4), 471-487. doi:10.1007/bf02712120Bhattacharjee, S. (2012). The Language of Reactive Oxygen Species Signaling in Plants. Journal of Botany, 2012, 1-22. doi:10.1155/2012/985298Birkenbihl, R. P., Diezel, C., & Somssich, I. E. (2012). Arabidopsis WRKY33 Is a Key Transcriptional Regulator of Hormonal and Metabolic Responses toward Botrytis cinerea Infection. Plant Physiology, 159(1), 266-285. doi:10.1104/pp.111.192641Caarls, L., Pieterse, C. M. J., & Van Wees, S. C. M. (2015). How salicylic acid takes transcriptional control over jasmonic acid signaling. Frontiers in Plant Science, 6. doi:10.3389/fpls.2015.00170Casado-Díaz, A., Encinas-Villarejo, S., Santos, B. de los, Schilirò, E., Yubero-Serrano, E.-M., Amil-Ruíz, F., … Caballero, J.-L. (2006). Analysis of strawberry genes differentially expressed in response to Colletotrichum infection. Physiologia Plantarum, 128(4), 633-650. doi:10.1111/j.1399-3054.2006.00798.xCharng, Y., Liu, H., Liu, N., Chi, W., Wang, C., Chang, S., & Wang, T. (2006). A Heat-Inducible Transcription Factor, HsfA2, Is Required for Extension of Acquired Thermotolerance in Arabidopsis. Plant Physiology, 143(1), 251-262. doi:10.1104/pp.106.091322Chung, S. H., Rosa, C., Scully, E. D., Peiffer, M., Tooker, J. F., Hoover, K., … Felton, G. W. (2013). Herbivore exploits orally secreted bacteria to suppress plant defenses. Proceedings of the National Academy of Sciences, 110(39), 15728-15733. doi:10.1073/pnas.1308867110Curry, K. J., Abril, M., Avant, J. B., & Smith, B. J. (2002). Strawberry Anthracnose: Histopathology of Colletotrichum acutatum and C. fragariae. Phytopathology®, 92(10), 1055-1063. doi:10.1094/phyto.2002.92.10.1055Debode, J., Van Hemelrijck, W., Baeyen, S., Creemers, P., Heungens, K., & Maes, M. (2009). Quantitative detection and monitoring ofColletotrichum acutatumin strawberry leaves using real-time PCR. Plant Pathology, 58(3), 504-514. doi:10.1111/j.1365-3059.2008.01987.xDempsey, D. A., & Klessig, D. F. (2012). SOS – too many signals for systemic acquired resistance? Trends in Plant Science, 17(9), 538-545. doi:10.1016/j.tplants.2012.05.011Dodds, P. N., & Rathjen, J. P. (2010). Plant immunity: towards an integrated view of plant–pathogen interactions. Nature Reviews Genetics, 11(8), 539-548. doi:10.1038/nrg2812Doehlemann, G., Wahl, R., Horst, R. J., Voll, L. M., Usadel, B., Poree, F., … Kämper, J. (2008). Reprogramming a maize plant: transcriptional and metabolic changes induced by the fungal biotroph Ustilago maydis. The Plant Journal, 56(2), 181-195. doi:10.1111/j.1365-313x.2008.03590.xDong, X. (2004). NPR1, all things considered. Current Opinion in Plant Biology, 7(5), 547-552. doi:10.1016/j.pbi.2004.07.005Durgbanshi, A., Arbona, V., Pozo, O., Miersch, O., Sancho, J. V., & Gómez-Cadenas, A. (2005). Simultaneous Determination of Multiple Phytohormones in Plant Extracts by Liquid Chromatography−Electrospray Tandem Mass Spectrometry. Journal of Agricultural and Food Chemistry, 53(22), 8437-8442. doi:10.1021/jf050884bEl Oirdi, M., El Rahman, T. A., Rigano, L., El Hadrami, A., Rodriguez, M. C., Daayf, F., … Bouarab, K. (2011). Botrytis cinerea Manipulates the Antagonistic Effects between Immune Pathways to Promote Disease Development in Tomato. The Plant Cell, 23(6), 2405-2421. doi:10.1105/tpc.111.083394Encinas-Villarejo, S., Maldonado, A. M., Amil-Ruiz, F., de los Santos, B., Romero, F., Pliego-Alfaro, F., … Caballero, J. L. (2009). Evidence for a positive regulatory role of strawberry (Fragaria×ananassa) Fa WRKY1 and Arabidopsis At WRKY75 proteins in resistance. Journal of Experimental Botany, 60(11), 3043-3065. doi:10.1093/jxb/erp152Freeman, S., Horowitz, S., & Sharon, A. (2001). Pathogenic and Nonpathogenic Lifestyles in Colletotrichum acutatum from Strawberry and Other Plants. Phytopathology®, 91(10), 986-992. doi:10.1094/phyto.2001.91.10.986Freeman, S., Katan, T., & Shabi, E. (1998). Characterization of Colletotrichum Species Responsible for Anthracnose Diseases of Various Fruits. Plant Disease, 82(6), 596-605. doi:10.1094/pdis.1998.82.6.596Gfeller, A., Dubugnon, L., Liechti, R., & Farmer, E. E. (2010). Jasmonate Biochemical Pathway. Science Signaling, 3(109), cm3-cm3. doi:10.1126/scisignal.3109cm3Grellet-Bournonville, C. F., Martinez-Zamora, M. G., Castagnaro, A. P., & Díaz-Ricci, J. C. (2012). Temporal accumulation of salicylic acid activates the defense response against Colletotrichum in strawberry. Plant Physiology and Biochemistry, 54, 10-16. doi:10.1016/j.plaphy.2012.01.019Guidarelli, M., Carbone, F., Mourgues, F., Perrotta, G., Rosati, C., Bertolini, P., & Baraldi, E. (2011). Colletotrichum acutatum interactions with unripe and ripe strawberry fruits and differential responses at histological and transcriptional levels. Plant Pathology, 60(4), 685-697. doi:10.1111/j.1365-3059.2010.02423.xHeidrich, K., Wirthmueller, L., Tasset, C., Pouzet, C., Deslandes, L., & Parker, J. E. (2011). Arabidopsis EDS1 Connects Pathogen Effector Recognition to Cell Compartment-Specific Immune Responses. Science, 334(6061), 1401-1404. doi:10.1126/science.1211641Horowitz, S., Freeman, S., & Sharon, A. (2002). Use of Green Fluorescent Protein-Transgenic Strains to Study Pathogenic and Nonpathogenic Lifestyles in Colletotrichum acutatum. Phytopathology®, 92(7), 743-749. doi:10.1094/phyto.2002.92.7.743Ikeda, M., Mitsuda, N., & Ohme-Takagi, M. (2011). Arabidopsis HsfB1 and HsfB2b Act as Repressors of the Expression of Heat-Inducible Hsfs But Positively Regulate the Acquired Thermotolerance. Plant Physiology, 157(3), 1243-1254. doi:10.1104/pp.111.179036Ikeda, M., & Ohme-Takagi, M. (2009). A Novel Group of Transcriptional Repressors in Arabidopsis. Plant and Cell Physiology, 50(5), 970-975. doi:10.1093/pcp/pcp048Khan, A. A., & Shih, D. S. (2004). Molecular cloning, characterization, and expression analysis of two class II chitinase genes from the strawberry plant. Plant Science, 166(3), 753-762. doi:10.1016/j.plantsci.2003.11.015Krinke, O., Ruelland, E., Valentová, O., Vergnolle, C., Renou, J.-P., Taconnat, L., … Zachowski, A. (2007). Phosphatidylinositol 4-Kinase Activation Is an Early Response to Salicylic Acid in Arabidopsis Suspension Cells. Plant Physiology, 144(3), 1347-1359. doi:10.1104/pp.107.100842Kubigsteltig, I., Laudert, D., & Weiler, E. W. (1999). Structure and regulation of the Arabidopsis thaliana allene oxide synthase gene. Planta, 208(4), 463-471. doi:10.1007/s004250050583Leandro, L. F. S., Gleason, M. L., Nutter, F. W., Wegulo, S. N., & Dixon, P. M. (2001). Germination and Sporulation of Colletotrichum acutatum on Symptomless Strawberry Leaves. Phytopathology®, 91(7), 659-664. doi:10.1094/phyto.2001.91.7.659Leon-Reyes, A., Van der Does, D., De Lange, E. S., Delker, C., Wasternack, C., Van Wees, S. C. M., … Pieterse, C. M. J. (2010). Salicylate-mediated suppression of jasmonate-responsive gene expression in Arabidopsis is targeted downstream of the jasmonate biosynthesis pathway. Planta, 232(6), 1423-1432. doi:10.1007/s00425-010-1265-zLi, J., Brader, G., Kariola, T., & Tapio Palva, E. (2006). WRKY70 modulates the selection of signaling pathways in plant defense. The Plant Journal, 46(3), 477-491. doi:10.1111/j.1365-313x.2006.02712.xLi, J., Brader, G., & Palva, E. T. (2004). The WRKY70 Transcription Factor: A Node of Convergence for Jasmonate-Mediated and Salicylate-Mediated Signals in Plant Defense. The Plant Cell, 16(2), 319-331. doi:10.1105/tpc.016980Liu, P.-P., von Dahl, C. C., Park, S.-W., & Klessig, D. F. (2011). Interconnection between Methyl Salicylate and Lipid-Based Long-Distance Signaling during the Development of Systemic Acquired Resistance in Arabidopsis and Tobacco. Plant Physiology, 155(4), 1762-1768. doi:10.1104/pp.110.171694Lodha, T. D., & Basak, J. (2011). Plant–Pathogen Interactions: What Microarray Tells About It? Molecular Biotechnology, 50(1), 87-97. doi:10.1007/s12033-011-9418-2López-Ráez, J. A., Verhage, A., Fernández, I., García, J. M., Azcón-Aguilar, C., Flors, V., & Pozo, M. J. (2010). Hormonal and transcriptional profiles highlight common and differential host responses to arbuscular mycorrhizal fungi and the regulation of the oxylipin pathway. Journal of Experimental Botany, 61(10), 2589-2601. doi:10.1093/jxb/erq089Maas, J. L. (Ed.). (1998). Compendium of Strawberry Diseases, Second Edition. doi:10.1094/9780890546178Makowski, R. M. D., & Mortensen, K. (1998). Latent infections and penetration of the bioherbicide agent Colletotrichum gloeosporioides f. sp. malvae in non-target field crops under controlled environmental conditions. Mycological Research, 102(12), 1545-1552. doi:10.1017/s0953756298006960Maleck, K., Levine, A., Eulgem, T., Morgan, A., Schmid, J., Lawton, K. A., … Dietrich, R. A. (2000). The transcriptome of Arabidopsis thaliana during systemic acquired resistance. Nature Genetics, 26(4), 403-410. doi:10.1038/82521Marcel, S., Sawers, R., Oakeley, E., Angliker, H., & Paszkowski, U. (2010). Tissue-Adapted Invasion Strategies of the Rice Blast Fungus Magnaporthe oryzae. The Plant Cell, 22(9), 3177-3187. doi:10.1105/tpc.110.078048Ndamukong, I., Abdallat, A. A., Thurow, C., Fode, B., Zander, M., Weigel, R., & Gatz, C. (2007). SA-inducible Arabidopsis glutaredoxin interacts with TGA factors and suppresses JA-responsive PDF1.2 transcription. The Plant Journal, 50(1), 128-139. doi:10.1111/j.1365-313x.2007.03039.xPajerowska-Mukhtar, K. M., Wang, W., Tada, Y., Oka, N., Tucker, C. L., Fonseca, J. P., & Dong, X. (2012). The HSF-like Transcription Factor TBF1 Is a Major Molecular Switch for Plant Growth-to-Defense Transition. Current Biology, 22(2), 103-112. doi:10.1016/j.cub.2011.12.015Pe�a-Cort�s, H., Barrios, P., Dorta, F., Polanco, V., S�nchez, C., S�nchez, E., & Ram�rez, I. (2004). Involvement of Jasmonic Acid and Derivatives in Plant Response to Pathogen and Insects and in Fruit Ripening. Journal of Plant Growth Regulation, 23(3), 246-260. doi:10.1007/s00344-004-0035-1Pernas, M., Ryan, E., & Dolan, L. (2010). SCHIZORIZA Controls Tissue System Complexity in Plants. Current Biology, 20(9), 818-823. doi:10.1016/j.cub.2010.02.062Pieterse, C. M. J., Leon-Reyes, A., Van der Ent, S., & Van Wees, S. C. M. (2009). Networking by small-molecule hormones in plant immunity. Nature Chemical Biology, 5(5), 308-316. doi:10.1038/nchembio.164Rahman, T. A. E., Oirdi, M. E., Gonzalez-Lamothe, R., & Bouarab, K. (2012). Necrotrophic Pathogens Use the Salicylic Acid Signaling Pathway to Promote Disease Development in Tomato. Molecular Plant-Microbe Interactions®, 25(12), 1584-1593. doi:10.1094/mpmi-07-12-0187-rRen, C.-M., Zhu, Q., Gao, B.-D., Ke, S.-Y., Yu, W.-C., Xie, D.-X., & Peng, W. (2008). Transcription Factor WRKY70 Displays Important but No Indispensable Roles in Jasmonate and Salicylic Acid Signaling. Journal of Integrative Plant Biology, 50(5), 630-637. doi:10.1111/j.1744-7909.2008.00653.xRietz, S., Stamm, A., Malonek, S., Wagner, S., Becker, D., Medina-Escobar, N., … Parker, J. E. (2011). Different roles of Enhanced Disease Susceptibility1 (EDS1) bound to and dissociated from Phytoalexin Deficient4 (PAD4) in Arabidopsis immunity. New Phytologist, 191(1), 107-119. doi:10.1111/j.1469-8137.2011.03675.xRobert-Seilaniantz, A., Grant, M., & Jones, J. D. G. (2011). Hormone Crosstalk in Plant Disease and Defense: More Than Just JASMONATE-SALICYLATE Antagonism. Annual Review of Phytopathology, 49(1), 317-343. doi:10.1146/annurev-phyto-073009-114447Cristina, M., Petersen, M., & Mundy, J. (2010). Mitogen-Activated Protein Kinase Signaling in Plants. Annual Review of Plant Biology, 61(1), 621-649. doi:10.1146/annurev-arplant-042809-112252Rouhier, N. (2006). Genome-wide analysis of plant glutaredoxin systems. Journal of Experimental Botany, 57(8), 1685-1696. doi:10.1093/jxb/erl001Ruepp, A. (2004). The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucleic Acids Research, 32(18), 5539-5545. doi:10.1093/nar/gkh894Rusterucci, C. (2001). The Disease Resistance Signaling Components EDS1 and PAD4 Are Essential Regulators of the Cell Death Pathway Controlled by LSD1 in Arabidopsis. THE PLANT CELL ONLINE, 13(10), 2211-2224. doi:10.1105/tpc.13.10.2211Sarowar, S., Zhao, Y., Soria-Guerra, R. E., Ali, S., Zheng, D., Wang, D., & Korban, S. S. (2011). Expression profiles of differentially regulated genes during the early stages of apple flower infection with Erwinia amylovora. Journal of Experimental Botany, 62(14), 4851-4861. doi:10.1093/jxb/err147Sasaki, Y. (2001). Monitoring of Methyl Jasmonate-responsive Genes in Arabidopsis by cDNA Macroarray: Self-activation of Jasmonic Acid Biosynthesis and Crosstalk with Other Phytohormone Signaling Pathways. DNA Research, 8(4), 153-161. doi:10.1093/dnares/8.4.153Schenk, P. M., Kazan, K., Manners, J. M., Anderson, J. P., Simpson, R. S., Wilson, I. W., … Maclean, D. J. (2003). Systemic Gene Expression in Arabidopsis during an Incompatible Interaction with Alternaria brassicicola. Plant Physiology, 132(2), 999-1010. doi:10.1104/pp.103.021683Simpson, D. W. (1991). Resistance toBotrytis cinereain pistillate genotypes of the cultivated strawberryFragaria ananassa. Journal of Horticultural Science, 66(6), 719-723. doi:10.1080/00221589.1991.11516203Shulaev, V., Sargent, D. J., Crowhurst, R. N., Mockler, T. C., Folkerts, O., Delcher, A. L., … Mane, S. P. (2010). The genome of woodland strawberry (Fragaria vesca). Nature Genetics, 43(2), 109-116. doi:10.1038/ng.740Song, W. C., Funk, C. D., & Brash, A. R. (1993). Molecular cloning of an allene oxide synthase: a cytochrome P450 specialized for the metabolism of fatty acid hydroperoxides. Proceedings of the National Academy of Sciences, 90(18), 8519-8523. doi:10.1073/pnas.90.18.8519Spoel, S. H., & Dong, X. (2012). How do plants achieve immunity? Defence without specialized immune cells. Nature Reviews Immunology, 12(2), 89-100. doi:10.1038/nri3141Spoel, S. H., Johnson, J. S., & Dong, X. (2007). Regulation of tradeoffs between plant defenses against pathogens with different lifestyles. Proceedings of the National Academy of Sciences, 104(47), 18842-18847. doi:10.1073/pnas.0708139104Staswick, P. E., & Tiryaki, I. (2004). The Oxylipin Signal Jasmonic Acid Is Activated by an Enzyme That Conjugates It to Isoleucine in Arabidopsis. The Plant Cell, 16(8), 2117-2127. doi:10.1105/tpc.104.023549Ten Hove, C. A., Willemsen, V., de Vries, W. J., van Dijken, A., Scheres, B., & Heidstra, R. (2010). SCHIZORIZA Encodes a Nuclear Factor Regulating Asymmetry of Stem Cell Divisions in the Arabidopsis Root. Current Biology, 20(5), 452-457. doi:10.1016/j.cub.2010.01.018Turner, J. G., Ellis, C., & Devoto, A. (2002). The Jasmonate Signal Pathway. The Plant Cell, 14(suppl 1), S153-S164. doi:10.1105/tpc.000679Tusher, V. G., Tibshirani, R., & Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences, 98(9), 5116-5121. doi:10.1073/pnas.091062498Uknes, S., Mauch-Mani, B., Moyer, M., Potter, S., Williams, S., Dincher, S., … Ryals, J. (1992). Acquired resistance in Arabidopsis. The Plant Cell, 4(6), 645-656. doi:10.1105/tpc.4.6.645Vargas, W. A., Martín, J. M. S., Rech, G. E., Rivera, L. P., Benito, E. P., Díaz-Mínguez, J. M., … Sukno, S. A. (2012). Plant Defense Mechanisms Are Activated during Biotrophic and Necrotrophic Development of Colletotricum graminicola in Maize. Plant Physiology, 158(3), 1342-1358. doi:10.1104/pp.111.190397Venugopal, S. C., Jeong, R.-D., Mandal, M. K., Zhu, S., Chandra-Shekara, A. C., Xia, Y., … Kachroo, P. (2009). Enhanced Disease Susceptibility 1 and Salicylic Acid Act Redundantly to Regulate Resistance Gene-Mediated Signaling. PLoS Genetics, 5(7), e1000545. doi:10.1371/journal.pgen.1000545Vlot, A. C., Liu, P.-P., Cameron, R. K., Park, S.-W., Yang, Y., Kumar, D., … Klessig, D. F. (2008). Identification of likely orthologs of tobacco salicylic acid-binding protein 2 and their role in systemic acquired resistance inArabidopsis thaliana. The Plant Journal, 56(3), 445-456. doi:10.1111/j.1365-313x.2008.03618.xWang, D., Amornsiripanitch, N., & Dong, X. (2006). A Genomic Approach to Identify Regulatory Nodes in the Transcriptional Network of Systemic Acquired Resistance in Plants. PLoS Pathogens, 2(11), e123. doi:10.1371/journal.ppat.0020123Wang, D. (2005). Induction of Protein Secretory Pathway Is Required for Systemic Acquired Resistance. Science, 308(5724), 1036-1040. doi:10.1126/science.1108791Wang, G.-F., Seabolt, S., Hamdoun, S., Ng, G., Park, J., & Lu, H. (2011). Multiple Roles of WIN3 in Regulating Disease Resistance, Cell Death, and Flowering Time in Arabidopsis. Plant Physiology, 156(3), 1508-1519. doi:10.1104/pp.111.176776Wiermer, M., Feys, B. J., & Parker, J. E. (2005). Plant immunity: the EDS1 regulatory node. Current Opinion in Plant Biology, 8(4), 383-389. doi:10.1016/j.pbi.2005.05.010Windram, O., Madhou, P., McHattie, S., Hill, C., Hickman, R., Cooke, E., … Denby, K. J. (2012). Arabidopsis Defense against Botrytis cinerea: Chronology and Regulation Deciphered by High-Resolution Temporal Transcriptomic Analysis. Th
    • …
    corecore