Amostragem para inventário florestal com probabilidade de superposição de parcelas circulares.

Este trabalho teve o propósito de avaliar uma metodologia de amostragem que propõe o uso de parcelas circulares superpostas em inventários florestais, comparada à amostragem simples ao acaso convencional. Compararam-se os métodos com parcelas retangular e circular de raio fixo e variável (Bitterlich). Os resultados mostraram que o método de parcelas circulares superpostas pode ser aplicado com os estimadores da amostragem simples ao acaso, e o método de Bitterlich pode ser uma alternativa à parcela circular de raio fixo

Crescimento de raízes de leguminosas em camadas de solo compactadas artificialmente.

O experimento foi desenvolvido em casa de vegetacao da Universidade Federal de Vicosa em 1992. Testaram-se as leguminosas crotalaria juncea (Crotalaria juncea L.) guandu (Cajanus cajan (L.) Millps), feijao-de-porco (Canavalia ensiformes (L.) DC.), feijao-bravo do ceara (Canavalia brasiliensis M. e Benth) e mata-pasto (Senna occidentalis L.) quanto a capacidade de suas raizes de penetrar me camadas de um latossolo vermelho-amarelo alico, muito argiloso, com diferentes niveis de compactacao. As leguminosas, com excecao do mata-pasto, tiveram os sistemas radiculares significativamente reduzidos dentro da camada compactada e abaixo dela, e apresentaram um acumulo de raizes no anel superior do vaso, a medida que o nivel de compactacao aumentou. O mata-pasto sobressaiu como a especie com maior potencial para crescer em camadas compactadas de solo e o feijao-de-porco foi a leguminosa mais afetada pela compactacao

Tillering Dynamics of \u3ci\u3ePanicum maximum\u3c/i\u3e Jacq. cv. Tanzania-1 After Grazing

Tillering dynamics and tiller dry matter weight from Tanzania grass (Panicum maximum cv. Tanzania-1) were evaluated in two post-grazing stubbles (High Post-grazing Stubble – HPS-3.6 t of DM/ha and Low Post-grazing Stubble – LPS-2.3 t of DM/ha). There was no difference between post-grazing stubbles for decapitated axillary and basal remainder and new axillary tillers. The LPS presented greater number of new basal tillers. The rate of appearance of new basal and axillary tillers decreased with time after grazing. There were differences between the treatments on tiller dry matter weight, and greater values were found in the high post-graze stubble

Na+/Ca(2+ )Exchanger a Druggable Target to Promote beta -Cell Proliferation and Function

An important feature of type 2 diabetes is a decrease in <i>β</i> -cell mass. Therefore, it is essential to find new approaches to stimulate <i>β</i> -cell proliferation. We have previously shown that heterozygous inactivation of the Na <sup>+</sup> /Ca <sup>2+</sup> exchanger (isoform 1; NCX1), a protein responsible for Ca <sup>2+</sup> extrusion from cells, increases <i>β</i> -cell proliferation, mass, and function in mice. Here, we show that <i>Ncx</i> 1 inactivation also increases <i>β</i> -cell proliferation in 2-year-old mice and that NCX1 inhibition in adult mice by four small molecules of the benzoxyphenyl family stimulates <i>β</i> -cell proliferation both <i>in vitro</i> and <i>in vivo</i> . NCX1 inhibition by small interfering RNA or small molecules activates the calcineurin/nuclear factor of activated T cells (NFAT) pathway and inhibits apoptosis induced by the immunosuppressors cyclosporine A (CsA) and tacrolimus in insulin-producing cell. Moreover, NCX1 inhibition increases the expression of <i>β</i> -cell-specific genes, such as <i>Ins1, Ins2,</i> and <i>Pdx</i> 1, and inactivates/downregulates the tumor suppressors retinoblastoma protein (pRb) and miR-193a and the cell cycle inhibitor p53. Our data show that Na <sup>+</sup> /Ca <sup>2+</sup> exchange is a druggable target to stimulate <i>β</i> -cell function and proliferation. Specific <i>β</i> -cell inhibition of Na <sup>+</sup> /Ca <sup>2+</sup> exchange by phenoxybenzamyl derivatives may represent an innovative approach to promote <i>β</i> -cell regeneration in diabetes and improve the efficiency of pancreatic islet transplantation for the treatment of the disease

Circular RNAs as novel regulators of β-cell functions in normal and disease conditions.

There is strong evidence for an involvement of different classes of non-coding RNAs, including microRNAs and long non-coding RNAs, in the regulation of β-cell activities and in diabetes development. Circular RNAs were recently discovered to constitute a substantial fraction of the mammalian transcriptome but the contribution of these non-coding RNAs in physiological and disease processes remains largely unknown. The goal of this study was to identify the circular RNAs expressed in pancreatic islets and to elucidate their possible role in the control of β-cells functions. We used a microarray approach to identify circular RNAs expressed in human islets and searched their orthologues in RNA sequencing data from mouse islets. We then measured the level of four selected circular RNAs in the islets of different Type 1 and Type 2 diabetes models and analyzed the role of these circular transcripts in the regulation of insulin secretion, β-cell proliferation, and apoptosis. We identified thousands of circular RNAs expressed in human pancreatic islets, 497 of which were conserved in mouse islets. The level of two of these circular transcripts, circHIPK3 and ciRS-7/CDR1as, was found to be reduced in the islets of diabetic db/db mice. Mimicking this decrease in the islets of wild type animals resulted in impaired insulin secretion, reduced β-cell proliferation, and survival. ciRS-7/CDR1as has been previously proposed to function by blocking miR-7. Transcriptomic analysis revealed that circHIPK3 acts by sequestering a group of microRNAs, including miR-124-3p and miR-338-3p, and by regulating the expression of key β-cell genes, such as Slc2a2, Akt1, and Mtpn. Our findings point to circular RNAs as novel regulators of β-cell activities and suggest an involvement of this novel class of non-coding RNAs in β-cell dysfunction under diabetic conditions

U.S. academic libraries: understanding their web presence and their relationship with economic indicators

The final publication is available at Springer via http://dx.doi.org/10.1007/s11192-013-1001-0The main goal of this research is to analyze the web structure and performance of units and services belonging to U.S. academic libraries in order to check their suitability for webometric studies. Our objectives include studying their possible correlation with economic data and assessing their use for complementary evaluation purposes. We conducted a survey of library homepages, institutional repositories, digital collections, and online catalogs (a total of 374 URLs) belonging to the 100 U.S. universities with the highest total expenditures in academic libraries according to data provided by the National Center for Education Statistics. Several data points were taken and analyzed, including web variables (page count, external links, and visits) and economic variables (total expenditures, expenditures on printed and electronic books, and physical visits). The results indicate that the variety of URL syntaxes is wide, diverse and complex, which produces a misrepresentation of academic libraries’ web resources and reduces the accuracy of web analysis. On the other hand, institutional and web data indicators are not highly correlated. Better results are obtained by correlating total library expenditures with URL mentions measured by Google (r = 0.546) and visits measured by Compete (r = 0.573), respectively. Because correlation values obtained are not highly significant, we estimate such correlations will increase if users can avoid linkage problems (due to the complexity of URLs) and gain direct access to log files (for more accurate data about visits).Orduña Malea, E.; Regazzi, JJ. (2014). U.S. academic libraries: understanding their web presence and their relationship with economic indicators. Scientometrics. 98(1):315-336. doi:10.1007/s11192-013-1001-0S315336981Adecannby, J. (2011). Web link analysis of interrelationship between top ten African universities and world universities. Annals of library and information studies, 58(2), 128–138.Aguillo, I. F. (2009). Measuring the institutions’ footprint in the web. Library Hi Tech, 27(4), 540–556.Aguillo, I. F., Ortega, J. L., & Fernández, M. (2008). Webometric Ranking of World Universities: Introduction, methodology, and future developments. Higher education in Europe, 33(2/3), 234–244.Aguillo, I. F., Ortega, J. L., Fernandez, M., & Utrilla, A. M. (2010). Indicators for a webometric ranking of open Access repositories. Scientometrics, 82(3), 477–486.Arakaki, M., & Willet, P. (2009). Webometric analysis of departments of librarianship and information science: A follow-up study. Journal of information science, 35(2), 143–152.Arlitsch, K., & O’Brian, P. S. (2012). Invisible institutional repositories: Addresing the low indexing ratios of IR in Google Scholar. Library Hi Tech, 30(1), 60–81.Bar-Ilan, J. (1999). Search engine results over time—A case study on search engine stability”. Cybermetrics, 2/3. Retrieved February 18, 2013 from http://www.cindoc.csic.es/cybermetrics/articles/v2i1p1.html.Bar-Ilan, J. (2001). Data collection methods on the Web for informetric purposes: A review and analysis. Scientometrics, 50(1), 7–32.Bermejo, F. (2007). The internet audience: Constitution & measurement. New York: Peter Lang Pub Incorporated.Buigues-Garcia, M., & Gimenez-Chornet, V. (2012). Impact of Web 2.0 on national libraries. International Journal of Information Management, 32(1), 3–10.Chu, H., He, S., & Thelwall, M. (2002). Library and information science schools in Canada and USA: A Webometric perspective. Journal of education for Library and Information Science, 43(2), 110–125.Chua, Alton, Y. K., & Goh, D. H. (2010). A study of Web 2.0 applications in library websites. Library and Information Science Research, 32(3), 203–211.Gallego, I., García, I.-M., & Rodríguez, L. (2009). Universities’ websites: Disclosure practices and the revelation of financial information. The International Journal of Digital Accounting Research, 9(15), 153–192.Gomes, B. & Smith, B. T. (2003). Detecting query-specific duplicate documents. [Patent]. Retrieved February 18, 2013 from http://www.patents.com/Detecting-query-specific-duplicate-documents/US6615209/en-US .Harinarayana, N. S., & Raju, N. V. (2010). Web 2.0 features in university library web sites. Electronic Library, 28(1), 69–88.Lewandowski, D., Wahlig, H., & Meyer-Bautor, G. (2006). The freshness of web search engine databases. Journal of Information Science, 32(2), 131–148.Mahmood, K., & Richardson, J. V, Jr. (2012). Adoption of Web 2.0 in US academic libraries: A survey of ARL library websites. Program, 45(4), 365–375.Orduña-Malea, E., & Ontalba-Ruipérez, J-A. (2012). Selective linking from social platforms to university websites: A case study of the Spanish academic system. Scientometrics. (in press).Ortega, J. L., & Aguillo, I. F. (2009). Mapping World-class universities on the Web. Information Processing and Management, 45(2), 272–279.Ortega, José L. & Aguillo, Isidro F. (2009b). North America Academic Web Space: Multicultural Canada vs. The United States Homogeneity. In: ASIST & ISSI pre-conference symposium on informetrics and scientometrics.Phan, T., Hardesty, L., Sheckells, C., & George, A. (2009). Documentation for the academic libraries survey (ALS) public-use data file: Fiscal year 2008. Washington DC: National Center for Education Statistics. Institute of Education Sciences U.S. Department of Education.Qiu, J., Cheng, J., & Wang, Z. (2004). An analysis of backlinks counts and web impact factors for Chinese university websites. Scientometrics, 60(3), 463–473.Regazzi, J. J. (2012a). Constrained?—An analysis of U.S. Academic Libraries and shifts in spending, staffing and utilization, 1998–2008. College and Research Libraries, 73(5), 449–468.Regazzi, J. J. (2012b). Comparing Academic Library Spending with Public Libraries, Public K-12 Schools, Higher Education Public Institutions, and Public Hospitals Between 1998–2008. Journal of Academic Librarianship, 38(4), 205–216.Rousseau, R. (1999). Daily time series of common single word searches in AltaVista and NorthernLight. Cybermetrics, 2/3. Retrieved February 18, 2013 from http://www.cindoc.csic.es/cybermetrics/articles/v2i1p2.html .Sato, S., & Itsumura, H. (2011). How do people use open access papers in non-academic activities? A link analysis of papers deposited in institutional repositories. Library, Information and Media Studies, 9(1), 51–64.Scholze, F. (2007). Measuring research impact in an open access environment. Liber Quarterly: The Journal of European Research Libraries, 17(1–4), 220–232.Smith, A. G. (2011). Wikipedia and institutional repositories: An academic symbiosis? In: Proceedings of the ISSI 2011 conference. Durban, South Africa, 4–7 July 2011. Retrieved February 18, 2013 from http://www.vuw.ac.nz/staff/alastair_smith/publns/SmithAG2011_ISSI_paper.pdf .Smith, A.G. (2012). Webometric evaluation of institutional repositories. In: Proceedings of the 8th international conference on webometrics informetrics and scientometrics & 13th collnet meeting. Seoul (Korea), 722–729.Smith, A., & Thelwall, M. (2002). Web impact factors for Australasian Universities. Scientometrics, 54(3), 363–380.Tang, R., & Thelwall, M. (2008). A hyperlink analysis of US public and academic libraries’ web sites. Library Quarterly, 78(4), 419–435.Thelwall, M. (2008). Extracting accurate and complete results from search engines: Case study Windows Live. Journal of the American Society for Information Science and Technology, 59(1), 38–50.Thelwall, M. (2009). Introduction to webometrics: Quantitative web research for the social sciences. San Rafael: Morgan & Claypool.Thelwall, M., & Sud, P. (2011). A comparison of methods for collecting web citation data for academic organisations. Journal of the American Society for Information Science and Technology, 62(8), 1488–1497.Thelwall, M., Sud, P., & Wilkinson, D. (2012). Link and co-inlink network diagrams with URL citations or title mentions. Journal of the American Society for Information Science and Technology, 63(10), 1960–1972.Thelwall, M., & Zuccala, A. (2008). A University-centred European Union link analysis. Scientometrics, 75(3), 407–442.Uyar, A. (2009a). Google stemming mechanisms. Journal of Information Science, 35(5), 499–514.Uyar, A. (2009b). Investigation of the accuracy of search engine hit counts. Journal of Information Science, 35(4), 469–480.Zuccala, A., Thelwall, M., Oppenheim, C., & Dhiensa, R. (2007). Web intelligence analyses of digital libraries: A case study of the National Electronic Library for Health (NeLH). Journal of Documentation, 63(4), 558–589

Human high-density lipoprotein particles prevent activation of the JNK pathway induced by human oxidised low-density lipoprotein particles in pancreatic beta cells

Aims/hypothesis: We explored the potential adverse effects of pro-atherogenic oxidised LDL-cholesterol particles on beta cell function. Materials and methods: Isolated human and rat islets and different insulin-secreting cell lines were incubated with human oxidised LDL with or without HDL particles. The insulin level was monitored by ELISA, real-time PCR and a rat insulin promoter construct linked to luciferase gene reporter. Cell apoptosis was determined by scoring cells displaying pycnotic nuclei. Results: Prolonged incubation with human oxidised LDL particles led to a reduction in preproinsulin expression levels, whereas the insulin level was preserved in the presence of native LDL-cholesterol. The loss of insulin production occurred at the transcriptional levels and was associated with an increase in activator protein-1 transcriptional activity. The rise in activator protein-1 activity resulted from activation of c-Jun N-terminal kinases (JNK, now known as mitogen-activated protein kinase 8 [MAPK8]) due to a subsequent decrease in islet-brain 1 (IB1; now known as MAPK8 interacting protein 1) levels. Consistent with the pro-apoptotic role of the JNK pathway, oxidised LDL also induced a twofold increase in the rate of beta cell apoptosis. Treatment of the cells with JNK inhibitor peptides or HDL countered the effects mediated by oxidised LDL. Conclusions/interpretation: These data provide strong evidence that oxidised LDL particles exert deleterious effects in the progression of beta cell failure in diabetes and that these effects can be countered by HDL particle

Scrt1, a transcriptional regulator of β-cell proliferation identified by differential chromatin accessibility during islet maturation.

Glucose-induced insulin secretion, a hallmark of mature β-cells, is achieved after birth and is preceded by a phase of intense proliferation. These events occurring in the neonatal period are decisive for establishing an appropriate functional β-cell mass that provides the required insulin throughout life. However, key regulators of gene expression involved in functional maturation of β-cells remain to be elucidated. Here, we addressed this issue by mapping open chromatin regions in newborn versus adult rat islets using the ATAC-seq assay. We obtained a genome-wide picture of chromatin accessible sites (~ 100,000) among which 20% were differentially accessible during maturation. An enrichment analysis of transcription factor binding sites identified a group of transcription factors that could explain these changes. Among them, Scrt1 was found to act as a transcriptional repressor and to control β-cell proliferation. Interestingly, Scrt1 expression was controlled by the transcriptional repressor RE-1 silencing transcription factor (REST) and was increased in an in vitro reprogramming system of pancreatic exocrine cells to β-like cells. Overall, this study led to the identification of several known and unforeseen key transcriptional events occurring during β-cell maturation. These findings will help defining new strategies to induce the functional maturation of surrogate insulin-producing cells

Functional significance of repressor element 1 silencing transcription factor (REST) target genes in pancreatic beta cells

Aims/hypothesis: The expression of several neuronal genes in pancreatic beta cells is due to the absence of the transcription factor repressor element 1 (RE-1) silencing transcription factor (REST). The identification of these traits and their functional significance in beta cells has only been partly elucidated. Herein, we investigated the biological consequences of a repression of REST target genes by expressing REST in beta cells. Methods: The effect of REST expression on glucose homeostasis, insulin content and release, and beta cell mass was analysed in transgenic mice selectively expressing REST in beta cells. Relevant target genes were identified in INS-1E and primary beta cells expressing REST. Results: Transgenic mice featuring a beta cell-targeted expression of REST exhibited glucose intolerance and reduced beta cell mass. In primary beta cells, REST repressed several proteins of the exocytotic machinery, including synaptosomal-associated protein (SNAP) 25, synaptotagmin (SYT) IV, SYT VII, SYT IX and complexin II; it impaired first and second phases of insulin secretion. Using RNA interference in INS-1E cells, we showed that SYT IV and SYT VII were implicated in the control of insulin release. Conclusions/interpretation: The data document the critical role of REST target genes in pancreatic beta cells. Specifically, we provide evidence that the downregulation of these genes is detrimental for the exocytosis of large dense core vesicles, thus contributing to beta cell dysfunction and impaired glucose homeostasi