A prospective randomised multi-centre controlled trial on tight glucose control by intensive insulin therapy in adult intensive care units: the Glucontrol study.

PURPOSE: An optimal target for glucose control in ICU patients remains unclear. This prospective randomized controlled trial compared the effects on ICU mortality of intensive insulin therapy (IIT) with an intermediate glucose control. METHODS: Adult patients admitted to the 21 participating medico-surgical ICUs were randomized to group 1 (target BG 7.8-10.0 mmol/L) or to group 2 (target BG 4.4-6.1 mmol/L). RESULTS: While the required sample size was 1,750 per group, the trial was stopped early due to a high rate of unintended protocol violations. From 1,101 admissions, the outcomes of 542 patients assigned to group 1 and 536 of group 2 were analysed. The groups were well balanced. BG levels averaged in group 1 8.0 mmol/L (IQR 7.1-9.0) (median of all values) and 7.7 mmol/L (IQR 6.7-8.8) (median of morning BG) versus 6.5 mmol/L (IQR 6.0-7.2) and 6.1 mmol/L (IQR 5.5-6.8) for group 2 (p < 0.0001 for both comparisons). The percentage of patients treated with insulin averaged 66.2 and 96.3%, respectively. Proportion of time spent in target BG was similar, averaging 39.5% and 45.1% (median (IQR) 34.3 (18.5-50.0) and 39.3 (26.2-53.6)%) in the groups 1 and 2, respectively. The rate of hypoglycaemia was higher in the group 2 (8.7%) than in group 1 (2.7%, p < 0.0001). ICU mortality was similar in the two groups (15.3 vs. 17.2%). CONCLUSIONS: In this prematurely stopped and therefore underpowered study, there was a lack of clinical benefit of intensive insulin therapy (target 4.4-6.1 mmol/L), associated with an increased incidence of hypoglycaemia, as compared to a 7.8-10.0 mmol/L target. (ClinicalTrials.gov # NCT00107601, EUDRA-CT Number: 200400391440).

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

Molecular Genetic Analysis of Multi-drug Resistance in Indian Isolates of Mycobacterium tuberculosis

A total of 116 isolates from patients attending the out-patient department at the All India Institute of Medical Sciences, New Delhi and the New Delhi Tuberculosis Centre, New Delhi, India were collected. They were analyzed for resistance to drugs prescribed in the treatment for tuberculosis. The drug resistance was initially determined by microbiological techniques. The Bactec 460TB system was employed to determine the type and level of resistance in each isolate. The isolates were further characterized at molecular level. The multi-drug loci corresponding to rpo b, gyr A, kat G were studied for mutation(s) by the polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) technique. The SSCP positive samples were sequenced to characterize the mutations in rpo b, and gyr A loci. While previously reported mutations in the gyr A and rpo b loci were found to be present, several novel mutations were also scored in the rpo b locus. Interestingly, analysis of the gyr A locus showed the presence of point mutation(s) that could not be detected by PCR-SSCP. Furthermore, rifampicin resistance was found to be an important marker for checking multi-drug resistance (MDR) in clinical isolates of Mycobacterium tuberculosis. This is the first report on molecular genetic analysis of MDR tuberculosis one from India, highlights the increasing incidence of MDR in the Indian isolates of M. tuberculosis.

Multi-segment foot kinematics after total ankle replacement and ankle arthrodesis during relatively long-distance gait.

This study aimed to investigate the influence of ankle osteoarthritis (AOA) treatments, i.e., ankle arthrodesis (AA) and total ankle replacement (TAR), on the kinematics of multi-segment foot and ankle complex during relatively long-distance gait. Forty-five subjects in four groups (AOA, AA, TAR, and control) were equipped with a wearable system consisting of inertial sensors installed on the tibia, calcaneus, and medial metatarsals. The subjects walked 50-m twice while the system measured the kinematic parameters of their multi-segment foot: the range of motion of joints between tibia, calcaneus, and medial metatarsals in three anatomical planes, and the peaks of angular velocity of these segments in the sagittal plane. These parameters were then compared among the four groups. It was observed that the range of motion and peak of angular velocities generally improved after TAR and were similar to the control subjects. However, unlike AOA and TAR, AA imposed impairments in the range of motion in the coronal plane for both the tibia-calcaneus and tibia-metatarsals joints. In general, the kinematic parameters showed significant correlation with established clinical scales (FFI and AOFAS), which shows their convergent validity. Based on the kinematic parameters of multi-segment foot during 50-m gait, this study showed significant improvements in foot mobility after TAR, but several significant impairments remained after AA.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Multi-stage oligopoly models with nested logit demand structures: A simplifying approach

Solving multi-stage oligopoly models by backward induction can easily become a com- plex task when rms are multi-product and demands are derived from a nested logit frame- work. This paper shows that under the assumption that within-segment rm shares are equal across segments, the analytical expression for equilibrium pro ts can be substantially simpli ed. The size of the error arising when this condition does not hold perfectly is also computed. Through numerical examples, it is shown that the error is rather small in general. Therefore, using this assumption allows to gain analytical tractability in a class of models that has been used to approach relevant policy questions, such as for example rm entry in an industry or the relation between competition and location. The simplifying approach proposed in this paper is aimed at helping improving these type of models for reaching more accurate recommendations.

Profitability, uncertainty and multi-product firm product proliferation: The Spanish car industry

This article studies how product introduction decisions relate to profitability and uncertainty in the context of multi-product firms and product differentiation. These two features, common to many modern industries, have not received much attention in the literature as compared to the classical problem of firm entry, even if the determinants of firm and product entry are quite different. The theoretical predictions about the sign of the impact of uncertainty on product entry are not conclusive. Therefore, an econometric model relating firms’ product introduction decisions with profitability and profit uncertainty is proposed. Firm’s estimated profits are obtained from a structural model of product demand and supply, and uncertainty is proxied by profits’ variance. The empirical analysis is carried out using data on the Spanish car industry for the period 1990-2000. The results show a positive relationship between product introduction and profitability, and a negative one with respect to profit variability. Interestingly, the degree of uncertainty appears to be a driving force of entry stronger than profitability, suggesting that the product proliferation process in the Spanish car market may have been mainly a consequence of lower uncertainty rather than the result of having a more profitable market. Keywords: Product introduction, entry, uncertainty, multiproduct firms, automobile JEL codes: L11, L13

Construcción de un modelo Multi- Regional Input-Output (MRIO) medioambiental para Cataluña y el resto de España: Estudio del balance en CO2 incorporado en el comercio

El objetivo de este estudio es analizar el impacto, en emisiones de CO2, de la demanda final de Cataluña en relación a los vínculos comerciales interregionales con el resto de España y el resto del mundo. Este proceso implica el análisis del balance en CO2 incorporado para Cataluña, lo que permitirá evaluar la responsabilidad de la economía catalana respecto a estas emisiones. Para este propósito se construye, para esta determinada desagregación regional, un modelo Multi-Regional Input-Output (MRIO) extendido al medioambiente con sectores verticalmente integrados. La incorporación de la técnica de la integración vertical nos permite un enfoque alternativo para el Balance Neto y un análisis más detallado de los vínculos interregionales entre los diversos sectores productivos, centrado en la responsabilidad última de la demanda final de cada sector en cada región. Hasta el momento, los estudios previos sobre los impactos medioambientales incorporados al comercio español se han centrado principalmente en el ámbito nacional. No obstante, por un lado el comercio interregional con el resto de España en términos monetarios representa cerca de la mitad del comercio exterior catalán. Por otro lado, los distintos metabolismos energéticos de ambas economías tienen como consecuencia una importante diferencia en la intensidad de emisión en la producción de bienes y servicios. Esta situación genera para Cataluña un déficit en el Balance Neto estimado con el resto de España, aún teniendo un importante superávit monetario. De esto se desprende la importancia de integrar el nivel interregional en los estudios de los impactos medioambientales incorporados en el comercio y, en consecuencia, en la planificación y formalización de políticas económicas y ambientales a nivel nacional.

Including the workload effect in the parallel program signature

Performance prediction and application behavior modeling have been the subject of exten- sive research that aim to estimate applications performance with an acceptable precision. A novel approach to predict the performance of parallel applications is based in the con- cept of Parallel Application Signatures that consists in extract an application most relevant parts (phases) and the number of times they repeat (weights). Executing these phases in a target machine and multiplying its exeuction time by its weight an estimation of the application total execution time can be made. One of the problems is that the performance of an application depends on the program workload. Every type of workload affects differently how an application performs in a given system and so affects the signature execution time. Since the workloads used in most scientific parallel applications have dimensions and data ranges well known and the behavior of these applications are mostly deterministic, a model of how the programs workload affect its performance can be obtained. We create a new methodology to model how a program’s workload affect the parallel application signature. Using regression analysis we are able to generalize each phase time execution and weight function to predict an application performance in a target system for any type of workload within predefined range. We validate our methodology using a synthetic program, benchmarks applications and well known real scientific applications.