Análise cientométrica da atividade científica na área de solos: o caso da América Latina.

Os indicadores cientométricos em Ciência e Tecnologia surgem da necessidade mensuração da produção científica, partindo-se da premissa de que a ciência se encontra, em grande parte, incorporada em sua literatura. Sendo assim este estudo se insere nesse contexto, ao utilizar a Cientometria para mapear a produção científica na área de solos, área do conhecimento que tem se destacado devido à sua atuação fundamental na agricultura e, mais recentemente, em temas da agenda global de manejo e uso sustentável dos recursos naturais. O método empregado foi a análise bibliométrica automatizada em registros extraídos da base de dados Scopus, no período de 1999-2010. Os resultados demonstram a importância da disciplina no meio científico, ao comprovar o crescimento do número de artigos publicados, de temas envolvidos, dos principais periódicos e das instituições de pesquisa que se destacam na produção de conhecimento em solo na América Latina.bitstream/item/63701/1/BPD-172-Analise-cientometrica.pd

Análise bibliométrica da atividade científica da Embrapa Solos (1975-2009).

A mensuração do desempenho de núcleos de pesquisa vem recebendo cada vez mais atenção por parte dos organismos captadores e distribuidores de recursos, tornando a bibliometria uma importante ferramenta para a política científica e tecnológica. Este estudo apresenta a trajetória de publicação de um centro de pesquisa, demonstrando como a bibliometria afere o desempenho científico de instituições.bitstream/item/33162/1/Bol-PD-153.pd

Good practices for a literature survey are not followed by authors while preparing scientific manuscripts

The number of citations received by authors in scientific journals has become a major parameter to assess individual researchers and the journals themselves through the impact factor. A fair assessment therefore requires that the criteria for selecting references in a given manuscript should be unbiased with respect to the authors or the journals cited. In this paper, we advocate that authors should follow two mandatory principles to select papers (later reflected in the list of references) while studying the literature for a given research: i) consider similarity of content with the topics investigated, lest very related work should be reproduced or ignored; ii) perform a systematic search over the network of citations including seminal or very related papers. We use formalisms of complex networks for two datasets of papers from the arXiv repository to show that neither of these two criteria is fulfilled in practice

Impaired Mitochondrial Function and Insulin Resistance of Skeletal Muscle in Mitochondrial Diabetes

OBJECTIVE - Impaired muscular mitochondrial function is related to common insulin resistance in type 2 diabetes. Mitochondrial diseases frequently lead to diabetes, which is mostly attributed to defective beta-cell mitochondria and secretion. RESEARCH DESIGN AND METHODS - We assessed muscular mitochondrial function and lipid deposition in liver (hepatocellular lipids [HCLs]) and muscle (intramyocellular lipids [IMCLs]) using P-31/H-1 magnetic resonance spectroscopy and insulin sensitivity and endogenous glucose production (EGP) using hyperinsulinemic-euglycemic clamps combined with isotopic tracer dilution in one female patient suffering from MELAS(myopathy,encephalopathy, lactic acidosis, and stroke-like episodes) syndrome and in six control subjects. RESULTS - The MELAS patient showed impaired insulin sensitivity (4.3 vs. 8.6 +/- 0.5 mg . kg(-1) . min(-1)) and suppression of EGP (69 vs. 94 +/- 1%), and her baseline and insulin-stimulated ATP synthesis were reduced (7.3 and 8.9 vs. 10.6 +/- 1.0 and 12.8 +/- 1.3 mu mol . l(-1) . min(-1)) compared with those of the control subjects. HCLs and IMCLs were comparable between the MELAS patient and control subjects. CONCLUSIONS - Impairment of muscle mitochondrial fitness promotes insulin resistance and could thereby contribute to the development of diabetes in some patients with the MELAS syndrome

Clinical and genetic factors predicting response to therapy in patients with Crohn's disease

AIM:To identify clinical and/or genetic predictors of response to several therapies in Crohn's disease (CD) patients. METHODS:We included 242 patients with CD (133 females) aged (mean ± standard deviation) 39 ± 12 years and a disease duration of 12 ± 8 years. The single-nucleotide polymorphisms (SNPs) studied were ABCB1 C3435T and G2677T/A, IL23R G1142A, C2370A, and G9T, CASP9 C93T, Fas G670A and LgC844T, and ATG16L1 A898G. Genotyping was performed with real-time PCR with Taqman probes. RESULTS:Older patients responded better to 5-aminosalicylic acid (5-ASA) and to azathioprine (OR 1.07, p = 0.003 and OR 1.03, p = 0.01, respectively) while younger ones responded better to biologicals (OR 0.95, p = 0.06). Previous surgery negatively influenced response to 5-ASA compounds (OR 0.25, p = 0.05), but favoured response to azathioprine (OR 2.1, p = 0.04). In respect to genetic predictors, we observed that heterozygotes for ATGL16L1 SNP had a significantly higher chance of responding to corticosteroids (OR 2.51, p = 0.04), while homozygotes for Casp9 C93T SNP had a lower chance of responding both to corticosteroids and to azathioprine (OR 0.23, p = 0.03 and OR 0.08, p = 0.02,). TT carriers of ABCB1 C3435T SNP had a higher chance of responding to azathioprine (OR 2.38, p = 0.01), while carriers of ABCB1 G2677T/A SNP, as well as responding better to azathioprine (OR 1.89, p = 0.07), had a lower chance of responding to biologicals (OR 0.31, p = 0.07), which became significant after adjusting for gender (OR 0.75, p = 0.005). CONCLUSIONS:In the present study, we were able to identify a number of clinical and genetic predictors of response to several therapies which may become of potential utility in clinical practice. These are preliminary results that need to be replicated in future pharmacogenomic studies

Decision Tree Classifiers for Star/Galaxy Separation

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of $884,126$ SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: $14\le r\le21$ ($85.2$) and $r\ge19$ ($82.1$). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT and Ball et al. (2006). We find that our FT classifier is comparable or better in completeness over the full magnitude range $15\le r\le21$, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes ($r>19$), our classifier is the only one able to maintain high completeness ($>$80%) while still achieving low contamination ($\sim2.5$). Finally, we apply our FT classifier to separate stars from galaxies in the full set of $69,545,326$ SDSS photometric objects in the magnitude range $14\le r\le21$.Comment: Submitted to A