Multiple populations in globular clusters. Lessons learned from the Milky Way globular clusters

Recent progress in studies of globular clusters has shown that they are not simple stellar populations, being rather made of multiple generations. Evidence stems both from photometry and spectroscopy. A new paradigm is then arising for the formation of massive star clusters, which includes several episodes of star formation. While this provides an explanation for several features of globular clusters, including the second parameter problem, it also opens new perspectives about the relation between globular clusters and the halo of our Galaxy, and by extension of all populations with a high specific frequency of globular clusters, such as, e.g., giant elliptical galaxies. We review progress in this area, focusing on the most recent studies. Several points remain to be properly understood, in particular those concerning the nature of the polluters producing the abundance pattern in the clusters and the typical timescale, the range of cluster masses where this phenomenon is active, and the relation between globular clusters and other satellites of our Galaxy.Comment: In press (The Astronomy and Astrophysics Review

Detecting failure of climate predictions

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055

Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies

Endothelium-Based Biomarkers Are Associated with Cerebral Malaria in Malawian Children: A Retrospective Case-Control Study

Differentiating cerebral malaria (CM) from other causes of serious illness in African children is problematic, owing to the non-specific nature of the clinical presentation and the high prevalence of incidental parasitaemia. CM is associated with endothelial activation. In this study we tested the hypothesis that endothelium-derived biomarkers are associated with the pathophysiology of severe malaria and may help identify children with CM.Plasma samples were tested from children recruited with uncomplicated malaria (UM; n = 32), cerebral malaria with retinopathy (CM-R; n = 38), clinically defined CM without retinopathy (CM-N; n = 29), or non-malaria febrile illness with decreased consciousness (CNS; n = 24). Admission levels of angiopoietin-2 (Ang-2), Ang-1, soluble Tie-2 (sTie-2), von Willebrand factor (VWF), its propeptide (VWFpp), vascular endothelial growth factor (VEGF), soluble ICAM-1 (sICAM-1) and interferon-inducible protein 10 (IP-10) were measured by ELISA. Children with CM-R had significantly higher median levels of Ang-2, Ang-2:Ang-1, sTie-2, VWFpp and sICAM-1 compared to children with CM-N. Children with CM-R had significantly lower median levels of Ang-1 and higher median concentrations of Ang-2:Ang-1, sTie-2, VWF, VWFpp, VEGF and sICAM-1 compared to UM, and significantly lower median levels of Ang-1 and higher median levels of Ang-2, Ang-2:Ang-1, VWF and VWFpp compared to children with fever and altered consciousness due to other causes. Ang-1 was the best discriminator between UM and CM-R and between CNS and CM-R (areas under the ROC curve of 0.96 and 0.93, respectively). A comparison of biomarker levels in CM-R between admission and recovery showed uniform increases in Ang-1 levels, suggesting this biomarker may have utility in monitoring clinical response.These results suggest that endothelial proteins are informative biomarkers of malarial disease severity. These results require validation in prospective studies to confirm that this group of biomarkers improves the diagnostic accuracy of CM from similar conditions causing fever and altered consciousness

Combinations of Host Biomarkers Predict Mortality among Ugandan Children with Severe Malaria: A Retrospective Case-Control Study

Background: Severe malaria is a leading cause of childhood mortality in Africa. However, at presentation, it is difficult to predict which children with severe malaria are at greatest risk of death. Dysregulated host inflammatory responses and endothelial activation play central roles in severe malaria pathogenesis. We hypothesized that biomarkers of these processes would accurately predict outcome among children with severe malaria. Methodology/Findings: Plasma was obtained from children with uncomplicated malaria (n = 53), cerebral malaria (n = 44) and severe malarial anemia (n = 59) at time of presentation to hospital in Kampala, Uganda. Levels of angiopoietin-2, von Willebrand Factor (vWF), vWF propeptide, soluble P-selectin, soluble intercellular adhesion molecule-1 (ICAM-1), soluble endoglin, soluble FMS-like tyrosine kinase-1 (Flt-1), soluble Tie-2, C-reactive protein, procalcitonin, 10 kDa interferon gamma-induced protein (IP-10), and soluble triggering receptor expressed on myeloid cells-1 (TREM-1) were determined by ELISA. Receiver operating characteristic (ROC) curve analysis was used to assess predictive accuracy of individual biomarkers. Six biomarkers (angiopoietin-2, soluble ICAM-1, soluble Flt-1, procalcitonin, IP-10, soluble TREM-1) discriminated well between children who survived severe malaria infection and those who subsequently died (area under ROC curve>0.7). Combinational approaches were applied in an attempt to improve accuracy. A biomarker score was developed based on dichotomization and summation of the six biomarkers, resulting in 95.7% (95% CI: 78.1-99.9) sensitivity and 88.8% (79.7-94.7) specificity for predicting death. Similar predictive accuracy was achieved with models comprised of 3 biomarkers. Classification tree analysis generated a 3-marker model with 100% sensitivity and 92.5% specificity (cross-validated misclassification rate: 15.4%, standard error 4.9%). Conclusions: We identified novel host biomarkers of pediatric severe and fatal malaria (soluble TREM-1 and soluble Flt-1) and generated simple biomarker combinations that accurately predicted death in an African pediatric population. While requiring validation in further studies, these results suggest the utility of combinatorial biomarker strategies as prognostic tests for severe malaria

Macrophage Migration Inhibitory Factor Induces Autophagy via Reactive Oxygen Species Generation

Autophagy is an evolutionarily conserved catabolic process that maintains cellular homeostasis under stress conditions such as starvation and pathogen infection. Macrophage migration inhibitory factor (MIF) is a multifunctional cytokine that plays important roles in inflammation and tumorigenesis. Cytokines such as IL-1β and TNF-α that are induced by MIF have been shown to be involved in the induction of autophagy. However, the actual role of MIF in autophagy remains unclear. Here, we have demonstrated that incubation of human hepatoma cell line HuH-7 cells with recombinant MIF (rMIF) induced reactive oxygen species (ROS) production and autophagy formation, including LC3-II expression, LC3 punctae formation, autophagic flux, and mitochondria membrane potential loss. The autophagy induced by rMIF was inhibited in the presence of MIF inhibitor, ISO-1 as well as ROS scavenger N-acetyl-L-cysteine (NAC). In addition, serum starvation-induced MIF release and autophagy of HuH-7 cells were partly blocked in the presence of NAC. Moreover, diminished MIF expression by shRNA transfection or inhibition of MIF by ISO-1 decreased serum starvation-induced autophagy of HuH-7 cells. Taken together, these data suggest that cell autophagy was induced by MIF under stress conditions such as inflammation and starvation through ROS generation

Elevated Plasma Von Willebrand Factor and Propeptide Levels in Malawian Children with Malaria

In children with malaria plasma VWF and propeptide levels are markedly elevated in both cerebral and mild paediatric malaria, with levels matching disease severity, and these normalize upon recovery. High levels of both markers also occur in retinopathy-negative 'cerebral malaria' cases, many of whom are thought to be suffering from diseases other than malaria, indicating that further studies of these markers will be required to determine their sensitivity and specificity

Anthropometric measures at different ages and endometrial cancer risk

BACKGROUND: Endometrial cancer is strongly associated with body mass index (BMI), but the influence of BMI history and of different types of obesity is uncertain. METHODS: A case\u2013control study was carried out in Italy including 454 cases and 908 controls admitted to hospital for acute non-hormone-related conditions. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed using multivariate logistic and spline regression models. RESULTS: The OR for BMI 430 at diagnosis compared with 20 to o25 kgm 2 was 4.08 (95% CI: 2.90\u20135.74). The association for BMI was monotonic with a possible steeper increase for BMI above 28. Conversely, waist-to-hip ratio (WHR) showed a bell shaped curve with increased OR (2.10; 95% CI: 1.43\u20133.09) in the intermediate tertile only. After stratification by BMI at diagnosis, history of weight loss and BMI at age 30 did not influence endometrial cancer risk. History of obesity in middle age had a weak and not significant adverse effect among obese women (OR\ubc1.60; 95% CI: 0.52\u20134.96). CONCLUSION: The predominant importance of recent weight compared to lifetime history, justifies encouraging weight reduction in women at any age