A Method to Identify and Analyze Biological Programs through Automated Reasoning.

Predictive biology is elusive because rigorous, data-constrained, mechanistic models of complex biological systems are difficult to derive and validate. Current approaches tend to construct and examine static interaction network models, which are descriptively rich but often lack explanatory and predictive power, or dynamic models that can be simulated to reproduce known behavior. However, in such approaches implicit assumptions are introduced as typically only one mechanism is considered, and exhaustively investigating all scenarios is impractical using simulation. To address these limitations, we present a methodology based on automated formal reasoning, which permits the synthesis and analysis of the complete set of logical models consistent with experimental observations. We test hypotheses against all candidate models, and remove the need for simulation by characterizing and simultaneously analyzing all mechanistic explanations of observed behavior. Our methodology transforms knowledge of complex biological processes from sets of possible interactions and experimental observations to precise, predictive biological programs governing cell function

LAPACK-Based Software for Subspace Identification

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Dynamic spin-lattice coupling and nematic fluctuations in NaFeAs

We use inelastic neutron scattering to study acoustic phonons and spin excitations in single crystals of NaFeAs, a parent compound of iron pnictide superconductors. NaFeAs exhibits a tetragonal-to-orthorhombic structural transition at $T_s\approx 58$ K and a collinear antiferromagnetic (AF) order at $T_N\approx 45$ K. While longitudinal and out-of-plane transverse acoustic phonons behave as expected, the in-plane transverse acoustic phonons reveal considerable softening on cooling to $T_s$, and then harden on approaching $T_N$ before saturating below $T_N$. In addition, we find that spin-spin correlation lengths of low-energy magnetic excitations within the FeAs layer and along the $c$-axis increase dramatically below $T_s$, and show weak anomaly across $T_N$. These results suggest that the electronic nematic phase present in the paramagnetic tetragonal phase is closely associated with dynamic spin-lattice coupling, possibly arising from the one-phonon-two-magnon mechanism

Pneumocéfalo Espontâneo Hipertensivo

info:eu-repo/semantics/publishedVersio

Hyperglycemia Induction in HepG2 Cell Line

Background: Hyperglycemia is one of the important featurs of diabetes. In cell culture studies different methods are used to mimic the hyperglycemia condition. In this study we investigate response of human liver cancer cell line (HepG2) to high insulin, high glucose, and high insulin/ high glucose medium exposure.Methods: HepG2 cells were settled in DMEM+0.1% FBS or DMEM free-serum medium with high concentrations of d-glucose (30 mm) and/or insulin (1μM) for 24h after an overnight starving in serum- free medium. The level of hyperglycemia was estimated in the supernatants via GOD-POD method.Results: Serum-free madium with high insulin/ high glucose consentration made the higher level of hypreglycemia in HepG2 cells.Conclusions: Our study interduced high insulin/ high glucose treatment as the best way to induction hyperglycemia.