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Diabetes mellitus (DM) cases are increasing worldwide, especially in Saudi Arabia. Previous studies suggested a positive relationship between body mass index (BMI) and bone mineral density (BMD) levels. Generally, patients with low BMI (<18.5 kg/m2) have reduced BMD levels and, thus, low T-scores; hence, they are categorized as osteopenic or osteoporotic. In this study, we aimed to determine whether a relationship between BMI and BMD T-scores in the hip and spine regions of patients with diabetes exists. This retrospective record review investigated older adult patients with diabetes in King Abdulaziz University Hospital (n=198; age 50–90 years) who underwent BMD scan between January 1, 2016, and June 25, 2018, regardless of their sex but limited to type 2 DM. The height and weight of all subjects were recorded, and BMI was calculated and categorized. We used SPSS version 21 for data analysis; measures of central tendencies, Pearson’s correlations, chi-square tests, and independent t-tests were employed. We found positive relationships between BMI and BMD T-scores in the hip and spine regions (right femoral neck: R=+0.214, P≤0.002; total right hip: R=+0.912, P≤0.001; left femoral neck: R=+0.939, P≤0.001; total left hip: R=+0.885, P≤0.001; and total lumbar region: R=+0.607, P≤0.001). Low BMI (<18.5 kg/m2) could be a risk factor for osteoporosis, whereas normal/high BMI could be protective against osteoporosis among adults with diabetes.

The eukaryotic translation initiation factor eIF4E is a potent oncogene elevated in many cancers, including the M4 and M5 subtypes of acute myeloid leukemia (AML). Although eIF4E RNA levels are elevated 3- to 10-fold in M4/M5 AML, the molecular underpinnings of this dysregulation were unknown. Here, we demonstrate that EIF4E is a direct transcriptional target of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) that is dysregulated preferentially in M4 and M5 AML. In primary hematopoietic cells and in cell lines, eIF4E levels are induced by NF-κB activating stimuli. Pharmacological or genetic inhibition of NF-κB represses this activation. The endogenous human EIF4E promoter recruits p65 and cRel to evolutionarily conserved κB sites in vitro and in vivo following NF-κB activation. Transcriptional activation is demonstrated by recruitment of p300 to the κB sites and phosphorylated Pol II to the coding region. In primary AML specimens, generally we observe that substantially more NF-κB complexes associate with eIF4E promoter elements in M4 and M5 AML specimens examined than in other subtypes or unstimulated normal primary hematopoietic cells. Consistently, genetic inhibition of NF-κB abrogates eIF4E RNA levels in this same population. These findings provide novel insights into the transcriptional control of eIF4E and a novel molecular basis for its dysregulation in at least a subset of M4/M5 AML specimens.

With the aim of enabling state-of-the-art gyrokinetic PIC codes to benefit from the performance of recent multithreaded devices, we developed an application from a platform called the \"PIC-engine\" [1, 2, 3] embedding simplified basic features of the PIC method. The application solves the gyrokinetic equations in a sheared plasma slab using B-spline finite elements up to fourth order to represent the self-consistent electrostatic field. Preliminary studies of the so-called Particle-In-Fourier (PIF) approach, which uses Fourier modes as basis functions in the periodic dimensions of the system instead of the real-space grid, show that this method can be faster than PIC for simulations with a small number of Fourier modes. Similarly to the PIC-engine, multiple levels of parallelism have been implemented using MPI+OpenMP [2] and MPI+OpenACC [1], the latter exploiting the computational power of GPUs without requiring complete code rewriting. It is shown that sorting particles [3] can lead to performance improvement by increasing data locality and vectorizing grid memory access. Weak scalability tests have been successfully run on the GPU-equipped Cray XC30 Piz Daint (at CSCS) up to 4,096 nodes. The reduced time-to-solution will enable more realistic and thus more computationally intensive simulations of turbulent transport in magnetic fusion devices.

Glucose sensors often measure s.c. interstitial fluid (ISF) glucose rather than blood or plasma glucose. Putative differences between plasma and ISF glucose include a protracted delay during the recovery from hypoglycaemia and an increased gradient during hyperinsulinaemia. These have often been investigated using sensor systems that have delays due to signal smoothing, or require long equilibration times. The aim of the present study was to define these relationships during hypoglycaemia in a well-equilibrated system with no smoothing. Hypoglycaemia was induced by i.v. insulin infusion (360 pmol.m(-2).min(-1)) in ten non-diabetic subjects. Glucose was sequentially clamped at approximately 5, 4.2 and 3.1 mmol/l and allowed to return to normoglycaemia. Subjects wore two s.c. glucose sensors (Medtronic MiniMed, Northridge, CA, USA) that had been inserted for more than 12 h. A two-compartment model was used to quantify the delay and gradient. The delay during the fall in plasma glucose was not different from the delay during recovery (8.3+/-0.67 vs 6.3+/-1.1 min; p=0.27) and no differences were observed in the ratio of sensor current to plasma glucose at basal insulin (2.7+/-0.25 nA.mmol(-1).l) compared with any of the hyperinsulinaemic clamp phases (2.8+/-0.18, 2.7+/-0.021, 2.9+/-0.21; p=NS). The ratio was significantly elevated following recovery to normoglycaemia (3.1+/-0.2 nA.mmol(-1).l; p<0.001). The elevated ratio suggests that the plasma to ISF glucose gradient was decreased following hypoglycaemia, possibly due to increased skin blood flow. Recovery from hypoglycaemia is not accompanied by a protracted delay and insulin does not increase the plasma to s.c. ISF glucose gradient.

In the fall 2016, GeantV went through a thorough community evaluation of the project status and of its strategy for sharing the R&D results with the LHC experiments and with the HEP simulation community in general. Following this discussion, GeantV has engaged onto an ambitious 2-year road-path aiming to deliver a beta version that has most of the final design and several performance features of the final product, partially integrated with some of the experiment's frameworks. The initial GeantV prototype has been updated to a vector-aware concurrent framework, which is able to deliver high-density floating-point computations for most of the performance-critical components such as propagation in field and physics models. Electromagnetic physics models were adapted for the specific GeantV requirements, aiming for the full demonstration of shower physics performance in the alpha release at the end of 2017. We have revisited and formalized GeantV user interfaces and helper protocols, allowing to: connect to user code, provide recipes to access efficiently MC truth and generate user data in a concurrent environment.

GeantV is a complex system based on the interaction of different modules needed for detector simulation, which include transport of particles in fields, physics models simulating their interactions with matter and a geometrical modeler library for describing the detector and locating the particles and computing the path length to the current volume boundary. The GeantV project is recasting the classical simulation approach to get maximum benefit from SIMD/MIMD computational architectures and highly massive parallel systems. This involves finding the appropriate balance between several aspects influencing computational performance (floating-point performance, usage of off-chip memory bandwidth, specification of cache hierarchy, etc.) and handling a large number of program parameters that have to be optimized to achieve the best simulation throughput. This optimization task can be treated as a black-box optimization problem, which requires searching the optimum set of parameters using only point-wise function evaluations. The goal of this study is to provide a mechanism for optimizing complex systems (high energy physics particle transport simulations) with the help of genetic algorithms and evolution strategies as tuning procedures for massive parallel simulations. One of the described approaches is based on introducing a specific multivariate analysis operator that could be used in case of resource expensive or time consuming evaluations of fitness functions, in order to speed-up the convergence of the black-box optimization problem.

Zonal flows (ZF) play a crucial role in regulating ion temperature gradient (ITG) turbulence. In previous global gyrokinetic simulations [1] using the ORB5 code with the adiabatic electron model, it was observed that long-lived ZF structures, leading to a corrugated transport and temperature gradient pattern, could develop in shaped tokamak plasmas much more than in circular shaped plasmas, resulting in reduced transport. These studies are extended to a hybrid electron model in which trapped electrons are kinetic while passing electrons are assumed to have a Boltzmann response for a case dominated by ITG modes. These confirm the results of the fully adiabatic electron model. Simulations done in \"gradient-driven\" mode, with a Krook-like relaxation towards a given profile, result in non-realistic corrugated heat source/sink profiles. However, after switching off completely the heat source/sink, it is shown that the ZF and transport corrugation remains. Thus the heat source corrugation is merely a consequence, not a cause, of the zonal structures and related radial transport pattern. Considering then core profiles with constant logarithmic gradients and pedestal profiles with linear gradients for L-mode plasmas, as in Ref.[2], we analyze how ITG transport and zonal structures react by independently varying the logarithmic gradients in the core and the linear gradients in the pedestal, using the adiabatic electron model. Results show the presence of large radial zones straddling the core-pedestal transition region. Avalanche-like events propagate over the radial zone at constant speed and repeat with a well defined frequency somewhat below the local geodesic acoustic mode (GAM) frequency. These avalanches are observed on the E × B ZFs, effective heat diffusivity and heat flux, thus a change of gradient in the core affects transport in the pedestal and vice versa. In spite of these non-local effects, attempt is made to characterize transport, and in particular its stiffness, quasi-locally. Global simulation results show that with increased input power the logarithmic gradient in the core is only slightly increased while the linear gradient in the pedestal is substantially enhanced.

An intensive R&D and programming effort is required to accomplish new challenges posed by future experimental high-energy particle physics (HEP) programs. The GeantV project aims to narrow the gap between the performance of the existing HEP detector simulation software and the ideal performance achievable, exploiting latest advances in computing technology. The project has developed a particle detector simulation prototype capable of transporting in parallel particles in complex geometries exploiting instruction level microparallelism (SIMD and SIMT), task-level parallelism (multithreading) and high-level parallelism (MPI), leveraging both the multi-core and the many-core opportunities. We present preliminary verification results concerning the electromagnetic (EM) physics models developed for parallel computing architectures within the GeantV project. In order to exploit the potential of vectorization and accelerators and to make the physics model effectively parallelizable, advanced sampling techniques have been implemented and tested. In this paper we introduce a set of automated statistical tests in order to verify the vectorized models by checking their consistency with the corresponding Geant4 models and to validate them against experimental data.

Efforts are being directed to systematically analyze the non-coding regions of the genome for cancer-driving mutations 1 – 6 . cis-regulatory elements (CREs) represent a highly enriched subset of the non-coding regions of the genome in which to search for such mutations. Here we use high-throughput chromosome conformation capture techniques (Hi-C) for 19,023 promoter fragments to catalog the regulatory landscape of colorectal cancer in cell lines, mapping CREs and integrating these with whole-genome sequence and expression data from The Cancer Genome Atlas 7 , 8 . We identify a recurrently mutated CRE interacting with the ETV1 promoter affecting gene expression. ETV1 expression influences cell viability and is associated with patient survival. We further refine our understanding of the regulatory effects of copy-number variations, showing that RASL11A is targeted by a previously identified enhancer amplification 1 . This study reveals new insights into the complex genetic alterations driving tumor development, providing a paradigm for employing chromosome conformation capture to decipher non-coding CREs relevant to cancer biology. Promoter capture Hi-C in colorectal cancer cells integrated with cancer genome and expression data identifies a noncoding, cis-regulatory element that is recurrently mutated in cancer, affecting ETV1 expression, cell viability and patient survival.

Gestational diabetes mellitus is a commonly occurring metabolic disorder during pregnancy, affecting >4% of pregnant women. It is generally defined as the intolerance of glucose with the onset or initial diagnosis during pregnancy. This illness affects the placenta and poses a threat to the baby as it affects the supply of proper oxygen and nutrients. Due to the high percentage of affected pregnant women, it should be mandatory to evaluate glucose levels during pregnancy and there is a need for a continuous monitoring system. Herein, the investigators modified the interdigitated (di)electrodes (IDE) sensing surface to detect the glucose on covalently immobilized glucose oxidase (GOx) with the graphene. The characterization of graphene and gold nanoparticle (GNP) was performed by high-resolution microscopy. Sensitivity was found to be 0.06 mg/mL and to enhance the detection, GOx was complexed with GNP. GNP-GOx was improved the sensitive detection twofold from 0.06 to 0.03 mg/mL, and it also displayed higher levels of current changes at all the concentrations of glucose that were tested. High-performance of the above IDE sensing system was attested by the specificity, reproducibility and higher sensitivity detections. Further, the linear regression analysis indicated the limit of detection to be between 0.02 and 0.03 mg/mL. This study demonstrated the potential strategy with nanocomposite for diagnosing gestational diabetes mellitus.