An overview of Cdk1-controlled targets and processes

The cyclin dependent kinase Cdk1 controls the cell cycle, which is best understood in the model organism S. cerevisiae. Research performed during the past decade has significantly improved our understanding of the molecular machinery of the cell cycle. Approximately 75 targets of Cdk1 have been identified that control critical cell cycle events, such as DNA replication and segregation, transcriptional programs and cell morphogenesis. In this review we discuss currently known targets of Cdk1 in the budding yeast S. cerevisiae and highlight the role of Cdk1 in several crucial processes including maintenance of genome stability

Combined and single effects of pesticide carbaryl and toxic Microcystis aeruginosa on the life history of Daphnia pulicaria

The combined influence of a pesticide (carbaryl) and a cyanotoxin (microcystin LR) on the life history of Daphnia pulicaria was investigated. At the beginning of the experiments animals were pulse exposed to carbaryl for 24 h and microcystins were delivered bound in Microcystis’ cells at different, sub-lethal concentrations (chronic exposure). In order to determine the actual carbaryl concentrations in the water LC–MS/MS was used. For analyses of the cyanotoxin concentration in Daphnia’s body enzyme-linked immunosorbent assay (ELISA) was used. Individual daphnids were cultured in a flow-through system under constant light (16 h of light: 8 h of dark), temperature (20°C), and food conditions (Scenedesmus obliquus, 1 mg of C l−1). The results showed that in the treatments with carbaryl egg numbers per female did not differ significantly from controls, but the mortality of newborns increased significantly. Increasing microcystin concentrations significantly delayed maturation, reduced size at first reproduction, number of eggs, and newborns. The interaction between carbaryl and Microcystis was highly significant. Animals matured later and at a smaller size than in controls. The number of eggs per female was reduced as well. Moreover, combined stressors caused frequent premature delivery of offspring with body deformations such as dented carapax or an undeveloped heart. This effect is concluded to be synergistic and could not be predicted from the effects of the single stressors.

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation

Cyclic AMP induces integrin-mediated cell adhesion through Epac and Rap1 upon stimulation of the β2-adrenergic receptor

cAMP controls many cellular processes mainly through the activation of protein kinase A (PKA). However, more recently PKA-independent pathways have been established through the exchange protein directly activated by cAMP (Epac), a guanine nucleotide exchange factor for the small GTPases Rap1 and Rap2. In this report, we show that cAMP can induce integrin-mediated cell adhesion through Epac and Rap1. Indeed, when Ovcar3 cells were treated with cAMP, cells adhered more rapidly to fibronectin. This cAMP effect was insensitive to the PKA inhibitor H-89. A similar increase was observed when the cells were transfected with Epac. Both the cAMP effect and the Epac effect on cell adhesion were abolished by the expression of Rap1–GTPase-activating protein, indicating the involvement of Rap1 in the signaling pathway. Importantly, a recently characterized cAMP analogue, 8-(4-chloro-phenylthio)-2′-O-methyladenosine-3′,5′-cyclic monophosphate, which specifically activates Epac but not PKA, induced Rap-dependent cell adhesion. Finally, we demonstrate that external stimuli of cAMP signaling, i.e., isoproterenol, which activates the Gαs-coupled β2-adrenergic receptor can induce integrin-mediated cell adhesion through the Epac-Rap1 pathway. From these results we conclude that cAMP mediates receptor-induced integrin-mediated cell adhesion to fibronectin through the Epac-Rap1 signaling pathway

The role of mentorship in protege performance

The role of mentorship on protege performance is a matter of importance to academic, business, and governmental organizations. While the benefits of mentorship for proteges, mentors and their organizations are apparent, the extent to which proteges mimic their mentors' career choices and acquire their mentorship skills is unclear. Here, we investigate one aspect of mentor emulation by studying mentorship fecundity---the number of proteges a mentor trains---with data from the Mathematics Genealogy Project, which tracks the mentorship record of thousands of mathematicians over several centuries. We demonstrate that fecundity among academic mathematicians is correlated with other measures of academic success. We also find that the average fecundity of mentors remains stable over 60 years of recorded mentorship. We further uncover three significant correlations in mentorship fecundity. First, mentors with small mentorship fecundity train proteges that go on to have a 37% larger than expected mentorship fecundity. Second, in the first third of their career, mentors with large fecundity train proteges that go on to have a 29% larger than expected fecundity. Finally, in the last third of their career, mentors with large fecundity train proteges that go on to have a 31% smaller than expected fecundity.Comment: 23 pages double-spaced, 4 figure

Evaluation and use of surveillance system data toward the identification of high-risk areas for potential cholera vaccination: a case study from Niger.

In 2008, Africa accounted for 94% of the cholera cases reported worldwide. Although the World Health Organization currently recommends the oral cholera vaccine in endemic areas for high-risk populations, its use in Sub-Saharan Africa has been limited. Here, we provide the principal results of an evaluation of the cholera surveillance system in the region of Maradi in Niger and an analysis of its data towards identifying high-risk areas for cholera

Measuring co-authorship and networking-adjusted scientific impact

Appraisal of the scientific impact of researchers, teams and institutions with productivity and citation metrics has major repercussions. Funding and promotion of individuals and survival of teams and institutions depend on publications and citations. In this competitive environment, the number of authors per paper is increasing and apparently some co-authors don't satisfy authorship criteria. Listing of individual contributions is still sporadic and also open to manipulation. Metrics are needed to measure the networking intensity for a single scientist or group of scientists accounting for patterns of co-authorship. Here, I define I1 for a single scientist as the number of authors who appear in at least I1 papers of the specific scientist. For a group of scientists or institution, In is defined as the number of authors who appear in at least In papers that bear the affiliation of the group or institution. I1 depends on the number of papers authored Np. The power exponent R of the relationship between I1 and Np categorizes scientists as solitary (R>2.5), nuclear (R=2.25-2.5), networked (R=2-2.25), extensively networked (R=1.75-2) or collaborators (R<1.75). R may be used to adjust for co-authorship networking the citation impact of a scientist. In similarly provides a simple measure of the effective networking size to adjust the citation impact of groups or institutions. Empirical data are provided for single scientists and institutions for the proposed metrics. Cautious adoption of adjustments for co-authorship and networking in scientific appraisals may offer incentives for more accountable co-authorship behaviour in published articles.Comment: 25 pages, 5 figure

Classification of the Universe of Immune Epitope Literature: Representation and Knowledge Gaps

A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continually updated by monitoring PubMed for new, potentially relevant references.Herein we detail the classification of all epitope-specific literature in over 100 different immunological domains representing Infectious Diseases and Microbes, Autoimmunity, Allergy, Transplantation and Cancer. The relative number of references in each category reflects past and present areas of research on immune reactivities. In addition to describing the overall landscape of data distribution, this particular characterization of the epitope reference data also allows for the exploration of possible correlations with global disease morbidity and mortality data.While in most cases diseases associated with high morbidity and mortality rates were amongst the most studied, a number of high impact diseases such as dengue, Schistosoma, HSV-2, B. pertussis and Chlamydia trachoma, were found to have very little coverage. The data analyzed in this fashion represents the first estimate of how reported immunological data corresponds to disease-related morbidity and mortality, and confirms significant discrepancies in the overall research foci versus disease burden, thus identifying important gaps to be pursued by future research. These findings may also provide a justification for redirecting a portion of research funds into some of the underfunded, critical disease areas