Mechanisms for Intracellular Calcium Regulation in Heart : I. Stopped-Flow Measurements of Ca++ Uptake by Cardiac Mitochondria

Initial velocities of energy-dependent Ca⁺⁺ uptake were measured by stopped-flow and dual-wavelength techniques in mitochondria isolated from hearts of rats, guinea pigs, squirrels, pigeons, and frogs. The rate of Ca⁺⁺ uptake by rat heart mitochondria was 0.05 nmol/mg/s at 5 µM Ca⁺⁺ and increased sigmoidally to 8 nmol/mg/s at 200 µM Ca⁺⁺. A Hill plot of the data yields a straight line with slope n of 2, indicating a cooperativity for Ca⁺⁺ transport in cardiac mitochondria. Comparable rates of Ca⁺⁺ uptake and sigmoidal plots were obtained with mitochondria from other mammalian hearts. On the other hand, the rates of Ca⁺⁺ uptake by frog heart mitochondria were higher at any Ca⁺⁺ concentrations. The half-maximal rate of Ca⁺⁺ transport was observed at 30, 60, 72, 87, 92 µM Ca⁺⁺ for cardiac mitochondria from frog, squirrel, pigeon, guinea pig, and rat, respectively. The sigmoidicity and the high apparent K_m render mitochondrial Ca⁺⁺ uptake slow below 10 µM. At these concentrations the rate of Ca⁺⁺ uptake by cardiac mitochondria in vitro and the amount of mitochondria present in the heart are not consistent with the amount of Ca⁺⁺ to be sequestered in vivo during heart relaxation. Therefore, it appears that, at least in mammalian hearts, the energy-linked transport of Ca⁺⁺ by mitochondria is inadequate for regulating the beat-to-beat Ca⁺⁺ cycle. The results obtained and the proposed cooperativity for mitochondrial Ca⁺⁺ uptake are discussed in terms of physiological regulation of intracellular Ca⁺⁺ homeostasis in cardiac cells.     

Computational protein design with side-chain conformational entropy

Recent advances in modeling protein structures at the atomic level have made it possible to tackle "de novo" computational protein design. Most procedures are based on combinatorial optimization using a scoring function that estimates the folding free energy of a protein sequence on a given main-chain structure. However, the computation of the conformational entropy in the folded state is generally an intractable problem, and its contribution to the free energy is not properly evaluated. In this article, we propose a new automated protein design methodology that incorporates such conformational entropy based on statistical mechanics principles. We define the free energy of a protein sequence by the corresponding partition function over rotamer states. The free energy is written in variational form in a pairwise approximation and minimized using the Belief Propagation algorithm. In this way, a free energy is associated to each amino acid sequence: we use this insight to rescore the results obtained with a standard minimization method, with the energy as the cost function. Then, we set up a design method that directly uses the free energy as a cost function in combination with a stochastic search in the sequence space. We validate the methods on the design of three superficial sites of a small SH3 domain, and then apply them to the complete redesign of 27 proteins. Our results indicate that accounting for entropic contribution in the score function affects the outcome in a highly nontrivial way, and might improve current computational design techniques based on protein stability.     

Interaction between Diclofenac and Soil Humic Acids

The interaction between the non-steroidal anti-inflammatory drug diclofenac and standard humic acids (HAs) in bulk solution was studied using two complementary analytical methods: UV-Visible spectroscopy and square wave voltammetry. The observed UV-Vis spectra and Ip/V curves suggested that, at our experimental conditions, albeit both substances being negatively charged at pH 6.5, interaction between the pharmaceutical and the soil humic acids may led to the formation of diclofenac-humic acids supramolecules.

Our results could contribute to give information on the behaviour of diclofenac into the soil environment, thus suggesting its migration as HAs-micelles through the coarse soil profile.     

Tyrosinase expression during black truffle development: from free living mycelium to ripe fruit body

The present work studies the expression of tyrosinase (monophenol:diphenol oxygen oxidoreductase, EC 1.14.18.1) during the development of the black truffle Tuber melanosporum Vittad., an ectomycorrhizal fungus of great biological and economic interest. As widely reported in the literature, melanins and the enzymes that synthesize them, are of paramount importance in fungal development and sexual differentiation. Tyrosinase and laccase are the enzymes that produce melanins from monophenols and diphenols. We have detected tyrosinase expression from the stage of free living mycelium, through the mychorrizal stage and the six fruit body developmental stages by measuring the levels of tyrosinase mRNA by quantitative PCR (q-PCR), spectrophotometry, histochemistry, immunohistochemistry and electrophoresis. Tyrosinase is always expressed, from the free living mycelium to the ripe fruit body developmental stages, when it is very low. The switching off of the tyrosinase gene during T. melanosporum development when the fruit body is ripe and no more cell walls are to be built is discussed in relation of thioflavour production. Specific primers, prepared from the cloned T. melanosporum tyrosinase cDNA were used for the q-PCR and the deduced aminoacid sequences of the CuA and CuB binding sites were compared to those of various ascomycetes and basidiomycetes.     

Decrypting Financial Markets through E-Joint Attention Efforts: On-Line Adaptive Networks of Investors in Periods of Market Uncertainty

This paper looks at 800,000 messages on the Unicredit stock, exchanged by 7,500 investors in the Finanzaonline.com forum, between 2005 and 2012 and measured collective interpretations of stock market trends. We examined the correlation patterns between market uncertainty, bad news and investors'' network structure by measuring the investors'' communication patterns. Our results showed that the investors'' network reacted to market trends in different ways: While less turbulent market phases implied less communication, higher market volatility generated more complex communication patterns. While the information content of messages was less technical in situations of uncertainty, bad news caused more informative messages only when market volatility was lower. This meant that bad news had a different impact on network behaviour, depending on market uncertainty. By measuring the investors'' expertise, we found that their behaviour could help predict changes in daily stock returns. We also found that expert investors were more influential in communication processes during high volatility market phases, whereas they had less influence on the real-time forum''s reaction after bad news. Our findings confirm the crucial role of e-communication platforms. However, they also show the need to reconsider the fragility of these collective intelligence systems when under external shocks.     

Quantifying post-fire regrowth of remotely sensed mediterranean vegetation with percolation-based methods

ABSTRACT

Mediterranean landscapes are characterized by high stability to fire since regeneration of pre-existing spatial relationships among distinctive vegetation patches is quite rapid. The aim of this paper is to introduce a method based on percolation theory to quantitatively estimate structural variations in remotely sensed biomass data linked to post-fire dynamics of Mediterranean vegetation. The ability of the proposed method to estimate fire-induced variations in Mediterranean vegetation patterns made it appropriate to the monitoring of post five vegetation regrowth in Mediterranean landscapes at the Landsat TM scale.     

NMR-based metabolic profiling of human hepatoma cells in relation to cell growth by culture media analysis

Metabolic profiling is a metabolomic approach that allows the characterization of metabolic phenotypes under specific set of conditions. In the present paper we investigated the metabolism of sparse and high density cultures in relation to different cell growth phases. Changes in the metabolome were evaluated by using 1H-NMR spectroscopy, correlation map and Multivariate Data Analysis on the net balances of metabolites in the medium. This approach allowed us to identify two different metabolic profiles in relation to the cell growth phases in subconfluence and confluence cultures. The results have been interpreted on the basis of patterns of correlations obtained in the two physiological cell states. Cells almost arrested in G0/G1 phase by contact dependent growth inhibition underwent changes in the channeling of amino acids utilization from synthetic to energetic purpose and in anaplerosis/cataplerosis regulation of the TCA cycle.     

Effect of Transcranial Magnetic Stimulation (TMS) on Parietal and Premotor Cortex during Planning of Reaching Movements

Background

Cerebral activation during planning of reaching movements occurs both in the superior parietal lobule (SPL) and premotor cortex (PM), and their activation seems to take place in parallel.

Methodology

The activation of the SPL and PM has been investigated using transcranial magnetic stimulation (TMS) during planning of reaching movements under visual guidance.

Principal Findings

A facilitory effect was found when TMS was delivered on the parietal cortex at about half of the time from sight of the target to hand movement, independently of target location in space. Furthermore, at the same stimulation time, a similar facilitory effect was found in PM, which is probably related to movement preparation.

Conclusions

This data contributes to the understanding of cortical dynamics in the parieto-frontal network, and suggests that it is possible to interfere with the planning of reaching movements at different cortical points within a particular time window. Since similar effects may be produced at similar times on both the SPL and PM, parallel processing of visuomotor information is likely to take place in these regions.