1,721,009 research outputs found
Coronary artery calcification in obese youth: What are the phenotypic and metabolic determinants?
No full textOBJECTIVE: Obesity in adolescence has been associated with increased risk for coronary heart disease in adulthood. This study evaluated subclinical atherosclerosis in obese youth and the underlying risk factors. RESEARCH DESIGN AND METHODS Ninety obese adolescents (37 normal glucose tolerant, 27 prediabetes, and 26 type 2 diabetes) underwent evaluation of coronary artery calcifications (CACs) by electron beam computed tomography, aortic pulse wave velocity (PWV), carotid intima-Media thickness (IMT), lipids, leptin, inflammatory markers, and body composition (DEXA). A total of 68 underwent evaluation of insulin sensitivity (IS) (hyperinsulinemic-euglycemic clamp) and abdominal adiposity (computed tomography). RESULTS: A total of 50percent had CACs (CAC+: Agatston CAC score ≥1). CAC+ youth had higher BMI, fat mass, and abdominal fat, with no difference in sex, race, IS per fat-Free mass (ISFFM), glucose tolerance, PWV, or IMT compared with the CAC2 group. PWV was inversely related to IS. In multiple regression analyses with age, race, sex, HbA1c, BMI (or waist circumference), ISFFM, diastolic blood pressure, non-HDL cholesterol, and leptin as independent variables, BMI (or waist) (R2 = 0.41; P = 0.001) was the significant determinant of CAC; leptin (R2 = 0.37; P = 0.034) for PWV; and HbA1c, race, and age (R2 = 0.34; P = 0.02) for IMT. CONCLUSIONS: Early in the course of obesity, there is evidence of CAC independent of glycemia. The different biomarkers of subclinical atherosclerosis appear to be differentially modulated, adiposity being the major determinant of CAC, hyperglycemia, age, and race for IMT, and leptin and IS for arterial stiffness. These findings highlight the increased cardiovascular disease risk in obese youth and the need for early interventions to reverse obesity and atherosclerosis. © 2014 by the American Diabetes Association.AGATSTON AS, 1990, J AM COLL CARDIOL, V15, P827; American Diabetes Association, 2009, DIABETES CARE S1, V32, pS62, DOI DOI 10.2337-DC09-S062; Bacha F, 2010, DIABETES CARE, V33, P2225, DOI 10.2337-dc10-0004; Bacha F, 2004, DIABETES CARE, V27, P547, DOI 10.2337-diacare.27.2.547; Bacha F, 2009, DIABETES CARE, V32, P100, DOI 10.2337-dc08-1030; Bild DE, 2001, ARTERIOSCL THROM VAS, V21, P852; Cleary PA, 2006, DIABETES, V55, P3556, DOI 10.2337-db06-0653; Gidding SS, 1998, CIRCULATION, V98, P2580; Gungor N, 2005, DIABETES CARE, V28, P1219, DOI 10.2337-diacare.28.5.1219; Hamirani YS, 2008, ATHEROSCLEROSIS, V201, P1, DOI 10.1016-j.atherosclerosis.2008.04.045; Hartiala O, 2012, J AM COLL CARDIOL, V60, P1364, DOI 10.1016-j.jacc.2012.05.045; Jain T, 2004, J AM COLL CARDIOL, V44, P1011, DOI 10.1016-j.jacc.2004.05.069; Jousilahti P, 1996, CIRCULATION, V93, P1372; Khan UI, 2011, ATHEROSCLEROSIS, V217, P179, DOI 10.1016-j.atherosclerosis.2011.01.007; Kieltyka L, 2003, ATHEROSCLEROSIS, V170, P125, DOI 10.1016-S0021-9150(03)00244-2; Kondos GT, 2003, CIRCULATION, V107, P2571, DOI 10.1161-01.CIR.0000068341.61180.55; Kramer CK, 2013, BMJ-BRIT MED J, V346, DOI 10.1136-bmj.f1654; Kurihara O, 2013, DIABETES CARE, V36, P729, DOI 10.2337-dc12-1635; LAAKSO M, 1991, ARTERIOSCLER THROMB, V11, P1068; Lee KK, 2009, AM HEART J, V157, P939, DOI 10.1016-j.ahj.2009.02.006; Lee S, 2007, DIABETES CARE, V30, P2091, DOI 10.2337-dc07-0203; Lee SJ, 2008, J PEDIATR, V152, P177, DOI [10.1016-j.jpeds.2007.07.053, 10.1016-j.jpeds.2007.07,053]; Lee TC, 2003, J AM COLL CARDIOL, V41, P39, DOI 10.1016-S0735-1097(02)02618-9; Mahoney LT, 1996, J AM COLL CARDIOL, V27, P277, DOI 10.1016-0735-1097(95)00461-0; McCullough PA, 2005, J AM SOC NEPHROL, V16, pS115, DOI 10.1681-ASN.2005060664; McGill HC, 2002, CIRCULATION, V105, P2712, DOI 10.1161-01.CIR.0000018121.67607.CE; Mielke CH, 2001, DIABETES RES CLIN PR, V53, P55, DOI 10.1016-S0168-8227(01)00239-X; Oda Akihiko, 2001, Kobe Journal of Medical Sciences, V47, P141; Olson JC, 2000, DIABETES, V49, P1571, DOI 10.2337-diabetes.49.9.1571; Oudkerk M, 2008, INT J CARDIOVAS IMAG, V24, P645, DOI 10.1007-s10554-008-9319-z; Qasim A, 2008, J AM COLL CARDIOL, V52, P231, DOI 10.1016-j.jacc.2008.04.016; Rutter MK, 2012, DIABETES CARE, V35, P1944, DOI 10.2337-dc11-1950; Schauer IE, 2011, DIABETES, V60, P306, DOI 10.2337-db10-0328; Sheu WHH, 2000, AM J MED SCI, V319, P84, DOI 10.1097-00000441-200002000-00003; Singhal A, 2002, CIRCULATION, V106, P1919, DOI 10.1161-01.CIR.0000033219.24717.52; Sutton-Tyrrell K, 2002, ATHEROSCLEROSIS, V160, P407, DOI 10.1016-S0021-9150(01)00591-3; Tirosh A, 2011, NEW ENGL J MED, V364, P1315, DOI 10.1056-NEJMoa1006992; Urbina EM, 2009, HYPERTENSION, V54, P919, DOI 10.1161-HYPERTENSIONAHA.109.192639; Urbina EM, 2012, DIABETOLOGIA, V55, P625, DOI 10.1007-s00125-011-2412-1; Urbina EM, 2009, CIRCULATION, V119, P2913, DOI 10.1161-CIRCULATIONAHA.108.830380; Wildman RP, 2003, HYPERTENSION, V42, P468, DOI 10.1161-01.HYP.0000090360.78539.CD1
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
HbA1c diagnostic categories and β-cell function relative to insulin sensitivity in overweight-obese adolescents
No full textOBJECTIVE - The recommended HbA1c diagnostic categories remain controversial and their utility in doubt in pediatrics. We hypothesized that alterations in the pathophysiologic mechanisms of type 2 diabetes may be evident in the American Diabetes Association recommended at-risk-prediabetes category (HbA1c 5.7 to andlt;6.5percent). RESEARCH DESIGN AND METHODS - We compared in vivo hepatic and peripheral insulin sensitivity by [6,6-2H 2] glucose and a 3-h hyperinsulinemic-euglycemic clamp and β-cell function by a 2-h hyperglycemic clamp (∼225 mg-dL) in overweight-obese (BMI ≥85th percentile) adolescents with prediabetes (HbA1c 5.7 to andlt;6.5percent) (n = 160) to those with normal HbA 1c (andlt;5.7percent) (n = 44). β-Cell function was expressed relative to insulin sensitivity (i.e., the disposition index = insulin sensitivity X first-phase insulin). RESULTS - In the prediabetes versus normal HbA 1c category, fasting glucose, insulin, and oral glucose tolerance test (OGTT) area under the curve for glucose and insulin were significantly higher; hepatic and peripheral insulin sensitivity were lower; and β-cell function relative to insulin sensitivity was lower (366 ± 48 vs. 524 ± 25 mg-kg-min; P = 0.005). A total of 27percent of youth in the normal HbA1c category and 41percent in the prediabetes HbA1c category had dysglycemia (impaired fasting glucose and-or impaired glucose tolerance) by a 2-h OGTT. CONCLUSIONS - Overweight-obese adolescents with HbA1c in the at-risk-prediabetes category demonstrate impaired β-cell function relative to insulin sensitivity, a metabolic marker for heightened risk of type 2 diabetes. Thus, HbA1c may be a suitable screening tool in large-scale epidemiological observational and-or interventional studies examining the progression or reversal of type 2 diabetes risk. © 2012 by the American Diabetes Association.Abdul-Ghani MA, 2007, DIABETES CARE, V30, P1544, DOI 10.2337-dc06-1331; American Diabetes Association, 2010, DIABETES CARE S1, V33, pS11, DOI DOI 10.2337-DC10-S011; Arslanian SA, 2005, HORM RES, V64, P16, DOI 10.1159-000089313; Arslanian SA, 2002, DIABETES, V51, P3014, DOI 10.2337-diabetes.51.10.3014; Bacha F, 2010, DIABETES CARE, V33, P2225, DOI 10.2337-dc10-0004; Bacha F, 2008, J PEDIATR, V152, P618, DOI 10.1016-j.jpeds.2007.11.044; Bacha F, 2004, DIABETES CARE, V27, P547, DOI 10.2337-diacare.27.2.547; Bacha F, 2009, DIABETES CARE, V32, P100, DOI 10.2337-dc08-1030; Burns SF, 2009, DIABETES CARE, V32, P2087, DOI 10.2337-dc09-0380; Buse JB, 2010, DIABETES CARE, V33, pe175; Buse John B, 2010, Diabetes Care, V33, pe175, DOI 10.2337-dc10-1720; Cali AMG, 2009, DIABETES CARE, V32, P456, DOI 10.2337-dc08-1274; Cnop M, 2007, DIABETES CARE, V30, P677, DOI 10.2337-dc06-1834; D'Adamo E, 2011, DIABETES CARE, V34, pS161, DOI 10.2337-dc11-s212; Fonseca V, 2009, DIABETES CARE, V32, P1344, DOI 10.2337-dc09-9034; George L, 2011, J CLIN ENDOCR METAB, V96, P2136, DOI 10.1210-jc.2010-2813; Heianza Y, 2011, LANCET, V378, P147, DOI 10.1016-S0140-6736(11)60472-8; Herman WH, 2007, DIABETES CARE, V30, P2453, DOI 10.2337-dc06-2003; Nathan DM, 2009, DIABETES CARE, V32, P1327, DOI 10.2337-dc09-9033; Lee JM, 2011, J PEDIATR-US, V158, P947, DOI 10.1016-j.jpeds.2010.11.026; Lee JM, 2011, J PEDIAT, V158, pe1; Lee JM, 2011, DIABETES CARE, V34, P2597, DOI 10.2337-dc11-0827; Lee S, 2010, J CLIN ENDOCR METAB, V95, P2426, DOI 10.1210-jc.2009-2175; Libman IM, 2008, J CLIN ENDOCR METAB, V93, P4231, DOI 10.1210-jc.2008-0801; Lyssenko V, 2005, DIABETES, V54, P166, DOI 10.2337-diabetes.54.1.166; Malkani S, 2011, AM J MED, V124, P395, DOI 10.1016-j.amjmed.2010.11.025; Misra A, 2011, LANCET, V378, P104, DOI 10.1016-S0140-6736(11)60789-7; Nowicka P, 2011, DIABETES CARE, V34, P1306, DOI 10.2337-dc10-1984; Olson DE, 2010, DIABETES CARE, V33, P2184, DOI 10.2337-dc10-0433; Rosner B, 1998, J PEDIATR, V132, P211, DOI 10.1016-S0022-3476(98)70434-2; Selvin E, 2011, DIABETES CARE, V34, P84, DOI 10.2337-dc10-1235; Sjaarda LG, 2012, J PEDIATR-US, V161, P51, DOI 10.1016-j.jpeds.2011.12.050; Tanner J.M., 1969, ENDOCRINE GENETIC DI, P19; Tfayli H, 2009, DIABETES, V58, P738, DOI 10.2337-db08-1372; Tfayli H, 2010, DIABETES CARE, V33, P632, DOI 10.2337-dc09-0305; Utzschneider KM, 2009, DIABETES CARE, V32, P335, DOI 10.2337-dc08-14789121
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Measuring β-cell function relative to insulin sensitivity in youth: Does the hyperglycemic clamp suffice?
No full textOBJECTIVE - To compare β-cell function relative to insulin sensitivity, disposition index (DI), calculated from two clamps (2cDI, insulin sensitivity from the hyperinsulinemic-euglycemic clamp and first-phase insulin from the hyperglycemic clamp) with the DI calculated from the hyperglycemic clamp alone (hcDI). RESEARCH DESIGN AND METHODS - Complete data from hyperglycemic and hyperinsulinemic-euglycemic clamps were available for 330 youth: 73 normal weight, 168 obese with normal glucose tolerance, 57 obese with impaired glucose tolerance, and 32 obese with type 2 diabetes. The correlation between hcDI and 2cDI and Bland-Altman analysis of agreement between the two were examined. RESULTS - Insulin sensitivity and first-phase insulin fromhcDI showed a hyperbolic relationship. The hcDI correlated significantly with 2cDI in the groups combined (r = 0.85, P 0.001) and within each group separately ( r ≥ 62, P 0.001). Similar to 2cDI, hcDI showed a declining pattern of β-cell function across the glucose-tolerance groups. Overall, hcDI values were 27percent greater than 2cDI, due to the hyperglycemic versus euglycemic conditions, reflected in a positive bias with Bland-Altman analysis. CONCLUSIONS - β-Cell function relative to insulin sensitivity could be accurately evaluated from a single hyperglycemic clamp, obviating the need for two separate clamp experiments, when lessening participant burden and reducing research costs are important considerations. © 2013 by the American Diabetes Association.Ader M, 1997, J CLIN INVEST, V99, P1187, DOI 10.1172-JCI119275; Ahren B, 2004, EUR J ENDOCRINOL, V150, P97, DOI 10.1530-eje.0.1500097; ALZAID AA, 1994, J CLIN INVEST, V94, P2341, DOI 10.1172-JCI117599; American Diabetes Association, 2010, DIABETES CARE S1, V33, pS11, DOI DOI 10.2337-DC10-S011; Arslanian SA, 2005, HORM RES, V64, P16, DOI 10.1159-000089313; Arslanian SA, 2002, DIABETES, V51, P3014, DOI 10.2337-diabetes.51.10.3014; Bacha F, 2010, DIABETES CARE, V33, P2225, DOI 10.2337-dc10-0004; Bacha F, 2008, J PEDIATR, V152, P618, DOI 10.1016-j.jpeds.2007.11.044; Bacha F, 2009, DIABETES CARE, V32, P100, DOI 10.2337-dc08-1030; Bergman RN, 2002, DIABETES, V51, pS212, DOI 10.2337-diabetes.51.2007.S212; BERGMAN RN, 1981, J CLIN INVEST, V68, P1456, DOI 10.1172-JCI110398; BEST JD, 1981, DIABETES, V30, P847, DOI 10.2337-diabetes.30.10.847; BONORA E, 1989, J CLIN ENDOCR METAB, V68, P374; Bums SF, 2009, DIABETES CARE, V32, P2087; Cali AMG, 2009, DIABETES CARE, V32, P456, DOI 10.2337-dc08-1274; Cnop M, 2007, DIABETES CARE, V30, P677, DOI 10.2337-dc06-1834; Cobelli C, 2007, AM J PHYSIOL-ENDOC M, V293, pE1, DOI 10.1152-ajpendo.00421.2006; Cobelli C, 1999, AM J PHYSIOL-ENDOC M, V277, pE481; D'Adamo E, 2011, DIABETES CARE, V34, pS161, DOI 10.2337-dc11-s212; DEFRONZO RA, 1979, AM J PHYSIOL, V237, pE214; Denti P, 2012, AM J PHYSIOL-ENDOC M, V303, pE576, DOI 10.1152-ajpendo.00139.2011; George L, 2011, J CLIN ENDOCR METAB, V96, P2136, DOI 10.1210-jc.2010-2813; Goran MI, 2002, DIABETES CARE, V25, P2184, DOI 10.2337-diacare.25.12.2184; Gungor N, 2005, DIABETES CARE, V28, P638, DOI 10.2337-diacare.28.3.638; KAHN SE, 1993, DIABETES, V42, P1663, DOI 10.2337-diabetes.42.11.1663; Kahn SE, 1996, DIABETES REV, V4, P372; Lee S, 2010, J CLIN ENDOCR METAB, V95, P2426, DOI 10.1210-jc.2009-2175; Libman IM, 2008, J CLIN ENDOCR METAB, V93, P4231, DOI 10.1210-jc.2008-0801; MITRAKOU A, 1992, J CLIN ENDOCR METAB, V75, P379, DOI 10.1210-jc.75.2.379; Ode KL, 2009, REV ENDOCR METAB DIS, V10, P167, DOI 10.1007-s11154-009-9115-7; Retnakaran R, 2009, DIABETIC MED, V26, P1198, DOI 10.1111-j.1464-5491.2009.02841.x; Retnakaran R, 2008, OBESITY, V16, P1901, DOI 10.1038-oby.2008.307; RIGGS DS, 1978, LIFE SCI, V22, P1305, DOI 10.1016-0024-3205(78)90098-X; Sjaarda LA, 2012, DIABETES CARE, V35, P2559, DOI 10.2337-dc12-0747; Sjaarda LG, 2012, J PEDIATR-US, V161, P51, DOI 10.1016-j.jpeds.2011.12.050; Tfayli H, 2009, DIABETES, V58, P738, DOI 10.2337-db08-1372; Tfayli H, 2010, DIABETES CARE, V33, P632, DOI 10.2337-dc09-0305; Tfayli H, 2010, DIABETES CARE, V33, P2024, DOI 10.2337-dc09-2292; Utzschneider KM, 2009, DIABETES CARE, V32, P335, DOI 10.2337-dc08-1478; Uwaifo GI, 2002, J CLIN ENDOCR METAB, V87, P2899, DOI 10.1210-jc.87.6.289921
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