Fluorescent carbon dioxide indicators

Over the last decade, fluorescence has become the dominant tool in biotechnology and medical imaging. These exciting advances have been underpinned by the advances in time-resolved techniques and instrumentation, probe design, chemical / biochemical sensing, coupled with our furthered knowledge in biology. Complementary volumes 9 and 10, Advanced Concepts of Fluorescence Sensing: Small Molecule Sensing and Advanced Concepts of Fluorescence Sensing: Macromolecular Sensing, aim to summarize the current state of the art in fluorescent sensing. For this reason, Drs. Geddes and Lakowicz have invited chapters, encompassing a broad range of fluorescence sensing techniques. Some chapters deal with small molecule sensors, such as for anions, cations, and CO2, while others summarize recent advances in protein-based and macromolecular sensors. The Editors have, however, not included DNA or RNA based sensing in this volume, as this were reviewed in Volume 7 and is to be the subject of a more detailed volume in the near future

A Historiometric Examination of Machiavellianism and a New Taxonomy of Leadership

Although researchers have extensively examined the relationship between charismatic leadership and Machiavellianism (Deluga, 2001; Gardner & Avolio, 1995; House & Howell, 1992), there has been a lack of investigation of Machiavellianism in relation to alternative forms of outstanding leadership. Thus, the purpose of this investigation was to examine the relationship between Machiavellianism and a new taxonomy of outstanding leadership comprised of charismatic, ideological, and pragmatic leaders. Using an historiometric approach, raters assessed Machiavellianism via the communications of 120 outstanding leaders in organizations across the domains of business, political, military, and religious institutions. Academic biographies were used to assess twelve general performance measures as well as twelve general controls and five communication specific controls. The results indicated that differing levels of Machiavellianism is evidenced across the differing leader types as well as differing leader orientation. Additionally, Machiavellianism appears negatively related to performance, though less so when type and orientation are taken into account.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline

Consumo de matéria seca e desempenho de novilhas das raças Girolando e Guzerá sob suplementação na caatinga, na época chuvosa, em Pernambuco, Brasil

Com os objetivos de estimar o consumo de matéria seca e avaliar a variação do peso vivo de novilhas, conduziu-se um experimento no período entre março e julho de 2003, com quatro estratégias de suplementação: sem suplementação (controle); torta de algodão (1 kg); palma-forrageira (10 kg); e de palma (5,0 kg) + torta de algodão (0,5 kg). O fornecimento de suplemento não influenciou o consumo de matéria seca (MS) do pasto nativo, no entanto afetou o consumo de MS total. O consumo de matéria seca total diferiu entre as raças, com valores de 5,44 e 6,75 kg/dia, respectivamente, para as raças Guzerá e Girolando. Nos animais sob suplementação com torta de algodão, o consumo de MS total foi superior ao do grupo controle (sem suplementação), porém semelhante ao daqueles sob suplementação com palma-forrageira e com torta de algodão + palma-forrageira. O ganho de peso vivo médio diário (de 517 e 434 g/animal, respectivamente, para os grupos Girolando e Guzerá) não diferiu entre as raças nem foi influenciado pela interação raça õ suplementação. Entre as estratégias de suplementação, no entanto, os valores tiveram diferença significativa e foram de 412, 620, 371 e 498 g/animal/dia, respectivamente, para os grupos controle e sob suplementação com torta de algodão; palma-forrageira; torta de algodão + palma-forrageira. No semiárido de Pernambuco, a suplementação com 1 kg de torta de algodão na época chuvosa do ano melhora o ganho de peso médio diário, independentemente da raça do animal

A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well

The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies in the pool, four dates were selected containing roughly 25%, 50%, 75% and 100% of the total number of participants. A bivariate random-effects model was fitted to studies up to and including each of these dates to jointly estimate sensitivity and specificity. Two-dimensional prediction regions were plotted in ROC-space. Subgroup analyses were carried out on sex and age, regardless of the date of the study. The dataset comprised 17,436 participants from 58 primary studies of which 2322 (13.3%) presented cases of major depression. Point estimates of sensitivity and specificity did not differ importantly as more studies were added to the model. However, correlation of the measures increased. As expected, standard errors of the logit pooled TPR and FPR consistently decreased as more studies were used, while standard deviations of the random-effects did not decrease monotonically. Subgroup analysis by sex did not reveal important contributions for observed heterogeneity; however, the shape of the prediction regions differed. Subgroup analysis by age did not reveal meaningful contributions to the heterogeneity and the prediction regions were similar in shape. Prediction intervals and regions reveal previously unseen trends in a dataset. In the context of a meta-analysis of diagnostic test accuracy, prediction regions can display the range of accuracy measures in different populations and settings