The impact of an educational program in the management of patients with chronic hepatitis C

Introduction: This study was designed to measure the impact of lifestyle changes, involving a diet therapy and physical exercises in patients with chronic hepatitis C (CHC). Methods: The study was conducted during January 2008 - December 2009 at ”Prof. N. Paulescu” National Institute of Diabetes, Nutrition and Metabolic Diseases - Bucharest, Romania. We selected 67 patients (34 men/33 women). We performed anthropometric measurements (weight, height, BMI (body mass index), bioimpedance analysis (BIA) as well as fasting serum lipids (cholesterol, triglycerides, HDL-cholesterol), glucose profile (glucose, HbA1c), liver profile (ALT, AST, GGT, alkaline phosphatase, bilirubin, albumin, total protein), blood count for all patients at baseline. Results: The average age was 53.91±10.19 years. Obesity was present in 32.8% (n=22) of patients at baseline. Total fat mass decreased with weight loss 2.21 kg (p = 0.0001) respectively 3.17 kg (p = 0.0001). Weight loss was accompanied by decreased resting energy expenditure. Triglycerides decreased from 158.11±7.63 mg/dl to 134.88±6.1 mg/dl, cholesterol decreased from 187.3±6.8 mg/dl to 168.65±4.42 mg/dl and HDL-cholesterol increased from 45.13±1.9 mg/dl to 47.2±1.39 mg/dl after 12 months. Aspartaminotransferase, alaninaminotransferese, gamma-glutamil transpeptidase decreased with significant differences. Conclusions: Patients with hepatitis C undergoing an 1-year lifestyle intervention had significant improvements in fasting glucose, fasting insulin, HOMA-IR, lipidic profile, hepatic profile and adipose tissue distribution. The present study establishes the positive impact of an educational program in the management of patients with hepatitis C

Detecting filamentary pattern in the cosmic web : a catalogue of filaments for the SDSS

International audienceThe main feature of the spatial large-scale galaxy distribution is its intricate network of galaxy filaments. This network is spanned by the galaxy locations that can be interpreted as a three-dimensional point distribution. The global properties of the point process can be measured by different statistical methods, which, however, do not describe directly the structure elements. The morphology of the large-scale structure, on the other hand, is an important property of the galaxy distribution. Here, we apply an object point process with interactions (the Bisous model) to trace and extract the filamentary network in the presently largest galaxy redshift survey, the Sloan Digital Sky Survey (SDSS). We search for filaments in the galaxy distribution that have a radius of about 0.5 h −1 Mpc. We divide the detected network into single filament

Spontaneous Generation of Angular Momentum in Holographic Theories

The Schwarzschild black two-brane in four-dimensional anti–de Sitter space is dual to a finite temperature state in three-dimensional conformal field theory. We show that the solution acquires a nonzero angular momentum density when a gravitational Chern-Simons coupling is turned on in the bulk, even though the solution is not modified. A similar phenomenon is found for the Reissner-Nordström black two-brane with axionic coupling to the gauge field. We discuss interpretation of this phenomenon from the point of view of the boundary three-dimensional conformal field theory

POET: Training Neural Networks on Tiny Devices with Integrated Rematerialization and Paging

Fine-tuning models on edge devices like mobile phones would enable privacy-preserving personalization over sensitive data. However, edge training has historically been limited to relatively small models with simple architectures because training is both memory and energy intensive. We present POET, an algorithm to enable training large neural networks on memory-scarce battery-operated edge devices. POET jointly optimizes the integrated search search spaces of rematerialization and paging, two algorithms to reduce the memory consumption of backpropagation. Given a memory budget and a run-time constraint, we formulate a mixed-integer linear program (MILP) for energy-optimal training. Our approach enables training significantly larger models on embedded devices while reducing energy consumption while not modifying mathematical correctness of backpropagation. We demonstrate that it is possible to fine-tune both ResNet-18 and BERT within the memory constraints of a Cortex-M class embedded device while outperforming current edge training methods in energy efficiency. POET is an open-source project available at https://github.com/ShishirPatil/poetComment: Proceedings of the 39th International Conference on Machine Learning 2022 (ICML 2022

Nuclear Effects on Bremsstrahlung Neutrino Rates of Astrophysical Interest

We calculate in this work the rates for the neutrino pair production by nucleon-nucleon bremsstrahlung taking into account the full contribution from a nuclear one-pion-exchange potential. It is shown that if the temperatures are low enough ($T \leq 20 MeV$), the integration over the nuclear part can be done for the general case, ranging from the completely degenerate (D) to the non-degenerate (ND) regime. We find that the inclusion of the full nuclear contribution enhances the neutrino pair production by $nn$ and $pp$ bremsstrahlung by a factor of about two in both the D and ND limits when compared with previous calculations. This result may be relevant for the physical conditions of interest in the semitransparent regions near the neutrinosphere in type II supernovae, cooling of neutron stars and other astrophysical situations.Comment: 11 pages, no figures, LaTex file. submitted to PR

The High-Flux Backscattering Spectrometer at the NIST Center for Neutron Research

We describe the design and current performance of the high-flux backscattering spectrometer located at the NIST Center for Neutron Research. The design incorporates several state-of-the-art neutron optical devices to achieve the highest flux on sample possible while maintaining an energy resolution of less than 1mueV. Foremost among these is a novel phase-space transformation chopper that significantly reduces the mismatch between the beam divergences of the primary and secondary parts of the instrument. This resolves a long-standing problem of backscattering spectrometers, and produces a relative gain in neutron flux of 4.2. A high-speed Doppler-driven monochromator system has been built that is capable of achieving energy transfers of up to +-50mueV, thereby extending the dynamic range of this type of spectrometer by more than a factor of two over that of other reactor-based backscattering instruments

Statin therapy in patients with diabetes and hepatitis C

The objective of this study was to determine the effects of statin therapy (atorvastatin) on serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels in patients with type 2 diabetes mellitus (T2DM) and chronic hepatitis C (CHC). A number of 77 patients with T2DM and CHC were selected, treated with atorvastatin, 20 mg, for 6 months, who underwent anthropometric measurements and biochemical tests (including fasting serum glucose, lipid profile, liver profile, cytokines profile) at baseline, after 1 month (clinical and biochemical profile for safety) and after 6 months of treatment. The patients’ average age was 52.53±9.7 years. Plasma low-density lipoprotein cholesterol (LDL-C) (-32.4 mg/dL), triglycerides (-29.7 mg/dL), total cholesterol (-32.8 mg/dL) decreased (p<0.05), and high-density lipoprotein cholesterol (HDL-C) (+3.04 mg/dL) increased (p<0.05), after 6 months. Atorvastatin treatment was associated with decreases of AST, ALT, and also leptin and interleukin-6 (IL-6) levels (all p<0.05) but we did not find any effect on plasma tumor necrosis factor-alpha (TNF-α) (p=0.119). Atorvastatin was an effective and well tolerated treatment for lowering total cholesterol, LDL-C, triglycerides in patients with CHC. Among patients with CHC there was no significant elevation of liver enzymes during statin treatment, and we even noticed an improvement of hepatic profile

Computational models for inferring biochemical networks

Biochemical networks are of great practical importance. The interaction of biological compounds in cells has been enforced to a proper understanding by the numerous bioinformatics projects, which contributed to a vast amount of biological information. The construction of biochemical systems (systems of chemical reactions), which include both topology and kinetic constants of the chemical reactions, is NP-hard and is a well-studied system biology problem. In this paper, we propose a hybrid architecture, which combines genetic programming and simulated annealing in order to generate and optimize both the topology (the network) and the reaction rates of a biochemical system. Simulations and analysis of an artificial model and three real models (two models and the noisy version of one of them) show promising results for the proposed method.The Romanian National Authority for Scientific Research, CNDI–UEFISCDI, Project No. PN-II-PT-PCCA-2011-3.2-0917

Isospin Character of the Pygmy Dipole Resonance in 124Sn

The pygmy dipole resonance has been studied in the proton-magic nucleus 124Sn with the (a,a'g) coincidence method at E=136 MeV. The comparison with results of photon-scattering experiments reveals a splitting into two components with different structure: one group of states which is excited in (a,a'g) as well as in (g,g') reactions and a group of states at higher energies which is only excited in (g,g') reactions. Calculations with the self-consistent relativistic quasiparticle time-blocking approximation and the quasiparticle phonon model are in qualitative agreement with the experimental results and predict a low-lying isoscalar component dominated by neutron-skin oscillations and a higher-lying more isovector component on the tail of the giant dipole resonance