Young LMC clusters: the role of red supergiants and multiple stellar populations in their integrated light and CMDs

The optical integrated spectra of three LMC young stellar clusters (NGC 1984, NGC 1994 and NGC 2011) exhibit concave continua and prominent molecular bands which deviate significantly from the predictions of single stellar population (SSP) models. In order to understand the appearance of these spectra, we create a set of young stellar population (MILES) models, which we make available to the community. We use archival International Ultraviolet Explorer integrated UV spectra to independently constrain the cluster masses and extinction, and rule out strong stochastic effects in the optical spectra. In addition, we also analyze deep colour-magnitude diagrams of the clusters to provide independent age determinations based on isochrone fitting. We explore hypotheses including age-spreads in the clusters, a top-heavy initial mass function, different SSP models and the role of red supergiant stars (RSG). We find that the strong molecular features in the optical spectra can only be reproduced by modeling an increased fraction of about 20 per cent by luminosity of RSG above what is predicted by canonical stellar evolution models. Given the uncertainties in stellar evolution at Myr ages, we cannot presently rule-out the presence of Myr age-spreads in these clusters. Our work combines different wavelengths as well as different approaches (resolved data as well as integrated spectra for the same sample) in order to reveal the complete picture. We show that each approach provides important information but in combination can we better understand the cluster stellar populations.Comment: Accepted for publication in MNRA

Geometry of River Networks II: Distributions of Component Size and Number

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length-scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.Comment: 16 pages, 13 figures, 4 tables, Revtex4, submitted to PR

Cannabis and the Brain: Friend or Foe?

Legalization of cannabis in the US and other countries highlight the need to understand the health consequences of this substance use. Research indicates that some cannabis ingredients may play beneficial role in treating various medical conditions while other ingredients may pose health risks. This review is focused on the brain and mental health effects of cannabis use. The rationale for examining cannabis use in behavioral and neural conditions is that these conditions are highly widespread in the US and account for high level of medical healthcare and associated cost. The purpose of this review is to provide an overview of the known medicinal benefits of selected cannabis cannabinoids in conditions like pediatric epilepsy, attention deficit hyperactivity disorder, autism spectrum disorder, and the known side effects or contraindications in conditions such as addiction, cognition, and psychosis. Several recommendations are made as to studies that will help further understanding the increasing role of cannabis in neuropsychiatric health and disease

Adaptively Refined Hybrid FDM-RBF Meshless Scheme with Applications to Laminar and Turbulent Viscous Fluid Flows

The focus of this work is to demonstrate a novel approach to true CFD automation based on an adaptive Cartesian point distribution process coupled with a Mesh less flow solution algorithm. As Mesh less method solutions require only an underlying nodal distribution, this approach works well even for complex flow geometries with non-aligned domain boundaries. Through the addition of a so-called shadow layer of body-fitted nodes, application of boundary conditions is simplified considerably, eliminating the stair-casing issues of typical Cartesian-based techniques. This paper describes the approach taken to automatically generate the Mesh less nodal distribution, along with the details of an automatic local refinement process. Also, as the primary interest of this automated CFD solver is for aerospace applications, this work includes the development of standard two-equation turbulence models for use in this Mesh less based solver. Finally, results are shown for several relevant compressible, turbulent flows example configurations, demonstrating the benefits of the automatic refinement as well as the quality of the Mesh less solutions in high-speed flow applications

Using machine learning to characterize heart failure across the scales

Heart failure is a progressive chronic condition in which the heart undergoes detrimental changes in structure and function across multiple scales in time and space. Multiscale models of cardiac growth can provide a patient-specific window into the progression of heart failure and guide personalized treatment planning. Yet, the predictive potential of cardiac growth models remains poorly understood. Here, we quantify predictive power of a stretch-driven growth model using a chronic porcine heart failure model, subject-specific multiscale simulation, and machine learning techniques. We combine hierarchical modeling, Bayesian inference, and Gaussian process regression to quantify the uncertainty of our experimental measurements during an 8-week long study of volume overload in six pigs. We then propagate the experimental uncertainties from the organ scale through our computational growth model and quantify the agreement between experimentally measured and computationally predicted alterations on the cellular scale. Our study suggests that stretch is the major stimulus for myocyte lengthening and demonstrates that a stretch-driven growth model alone can explain 52.7% of the observed changes in myocyte morphology. We anticipate that our approach will allow us to design, calibrate, and validate a new generation of multiscale cardiac growth models to explore the interplay of various subcellular-, cellular-, and organ-level contributors to heart failure. Using machine learning in heart failure research has the potential to combine information from different sources, subjects, and scales to provide a more holistic picture of the failing heart and point toward new treatment strategies

Uranium/Vanadium Separation from El-Sahu Carnotite-Bearing Kaolin, Southwestern Sinai, Egypt

A working sample of the lower Carboniferous carnotite-bearing kaolin of wadi El Sahu, Southwestern, Sinai assaying 2.6% uranium and 1.2% vanadium species is subjected to sulfuric acid pug leaching. The extraction behavior of both metal values was first studied from their combined synthetic solution using DEHPA and Aliquat-336 extractants. The obtained results are then applied upon El-Sahu sulfuric acid leach liquor where after proper oxidation of the leach liquor, uranium was selectively extracted as cationic ions by DEHPA solvent, while the vanadium left behind was subsequently extracted as anionic ions using Aliquat-336

Serum leptin level and microvascular complications in type 2 diabetes

Background. Type 2 diabetes (T2DM) and its complications are highly prevalent in Egypt and are considered a major health problem. Insulin resistance arising from visceral obesity is the main pathological mechanism of T2DM. Leptin is an adipokine secreted from visceral adipose tissue and its level is proved to be higher in patients with T2DM, but its association with microvascular complications is not yet well-established, for this aim the present study was conducted. Methods. This cross-sectional study was conducted among 120 participants with T2DM recruited from the diabetes outpatient clinic of Alexandria Main Uni­versity Hospital, Alexandria, Egypt. Each participant was subjected to full history taking, complete physical examination and laboratory investigations. Results. Serum leptin level was significantly positively correlated with diabetes duration, BMI, WC, systolic and diastolic blood pressure, FPG, HbA1c, serum insu­lin level, HOMA-IR, total cholesterol, triglycerides and LDL-C. Regarding microvascular complications, serum leptin level was highly significantly positively correlated with UACR, peripheral neuropathy and retinopathy (P < 0.001) and significantly negatively correlated with e-GFR (P = 0.003). Conclusions. Serum leptin level is significantly correlated with microvascular complications in patients with T2DM in Alexandria, Egypt

Engaging patients and clinicians through simulation: rebalancing the dynamics of care

This paper proposes simulation-based enactment of care as an innovative and fruitful means of engaging patients and clinicians to create collaborative solutions to healthcare issues. This use of simulation is a radical departure from traditional transmission models of education and training. Instead, we frame simulation as co-development, through which professionals, patients and publics share their equally (though differently) expert perspectives. The paper argues that a process of participatory design can bring about new insights and that simulation offers understandings that cannot easily be expressed in words. Drawing on more than a decade of our group’s research on simulation and engagement, the paper summarises findings from studies relating to clinician-patient collaboration and proposes a novel approach to address the current need. The paper outlines a mechanism whereby pathways of care are jointly created, shaped, tested and refined by professionals, patients, carers and others who are affected and concerned by clinical care

Current practice in the removal of benign endometrial polyps: a Dutch survey

The purpose of this study is to evaluate the current practice of Dutch gynecologists in the removal of benign endometrial polyps and compare these results with the results of a previous study from 2003. In 2009 Dutch gynecologists were surveyed by a mailed questionnaire about polypectomy. Gynecologists answered questions about their individual performance of polypectomy: setting, form of anesthesia, method, and instrument use. The results were compared with the results from the previous survey. The response rate was 70% (585 of 837 gynecologists). Among the respondents, 455 (78%) stated to remove endometrial polyps themselves. Polyps were mostly removed in an inpatient setting (337; 74%) under general or regional anesthesia (247; 54%) and under direct hysteroscopic vision (411; 91%). Gynecologists working in a teaching hospital removed polyps more often in an outpatient setting compared with gynecologists working in a nonteaching hospital [118 (43%) vs. 35 (19%) p < 0.001]. These results are in accordance with the results from 2003. Compared to 2003 there was an increase in the number of gynecologists performing polypectomies with local or no anesthesia [211 (46%) vs. 98 (22%), p < 0.001]. An increase was also noted in the number of gynecologists using direct hysteroscopic vision [411 (91%) vs. 290 (64%), p < 0.001] and 5 Fr electrosurgical instruments [181 (44%) vs. 56 (19%), p < 0.001]. Compared to the situation in 2003, there is an increase in removal under direct hysteroscopic vision, with 5 Fr electrosurgical instruments, using local or no anesthesia. This implies there is progress in outpatient hysteroscopic polypectomy in the Netherlands

Phospho-MEK1/2 and uPAR Expression Determine Sensitivity of AML Blasts to a Urokinase-Activated Anthrax Lethal Toxin (PrAgU2/LF)

In this study, we attempt to target both the urokinase plasminogen activator and the mitogen-activated protein kinase pathway in acute myeloid leukemia (AML) cell lines and primary AML blasts using PrAgU2/LF, a urokinase-activated anthrax lethal toxin. PrAgU2/LF was cytotoxic to five out of nine AML cell lines. Cytotoxicity of PrAgU2/LF appeared to be nonapoptotic and was associated with MAPK activation and urokinase activity because all the PrAgU2/LF-sensitive cell lines showed both uPAR expression and high levels of MEK1/2 phosphorylation. Inhibition of uPAR or desensitization of cells to MEK1/2 inhibition blocked toxicity of PrAgU2/LF, indicating requirement for both uPAR expression and MAPK activation for activity. PrAgU2/LF was also cytotoxic to primary blasts from AML patients, with blasts from four out of five patients showing a cytotoxic response to PrAgU2/LF. Cytotoxicity of primary AML blasts was also dependent on uPAR expression and phos-MEK1/2 levels. CD34+ bone marrow blasts and peripheral blood mononuclear cells lacked uPAR expression and were resistant to PrAgU2/LF, demonstrating the lack of toxicity to normal hematological cells and, therefore, the tumor selectivity of this approach. Dose escalation in mice revealed that the maximal tolerated dose of PrAgU2/LF is at least 5.7-fold higher than that of the wild-type anthrax lethal toxin, PrAg/LF, further demonstrating the increased safety of this molecule. We have shown, in this study, that PrAgU2/LF is a novel, dual-specific molecule for the selective targeting of AML