Three small RNAs jointly ensure secondary metabolism and biocontrol in Pseudomonas fluorescens CHA0.

In many Gram-negative bacteria, the GacS/GacA two-component system positively controls the expression of extracellular products or storage compounds. In the plant-beneficial rhizosphere bacterium Pseudomonas fluorescens CHA0, the GacS/GacA system is essential for the production of antibiotic compounds and hence for biological control of root-pathogenic fungi. The small (119-nt) RNA RsmX discovered in this study, together with RsmY and RsmZ, forms a triad of GacA-dependent small RNAs, which sequester the RNA-binding proteins RsmA and RsmE and thereby antagonize translational repression exerted by these proteins in strain CHA0. This small RNA triad was found to be both necessary and sufficient for posttranscriptional derepression of biocontrol factors and for protection of cucumber from Pythium ultimum. The same three small RNAs also positively regulated swarming motility and the synthesis of a quorum-sensing signal, which is unrelated to N-acyl-homoserine lactones, and which autoinduces the Gac/Rsm cascade. Expression of RsmX and RsmY increased in parallel throughout cell growth, whereas RsmZ was produced during the late growth phase. This differential expression is assumed to facilitate fine tuning of GacS/A-controlled cell population density-dependent regulation in P. fluorescens.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Effects of adrenergic and cholinergic blockade on insulin-induced stimulation of calf blood flow in humans.

Euglycemic hyperinsulinemia stimulates both sympathetic nerve activity and blood flow to skeletal muscle, but the mechanism is unknown. Possible mechanisms that may stimulate muscle blood flow include neural, humoral, or metabolic effects of insulin. To determine whether such insulin-induced vasodilation is modulated by stimulation of adrenergic or cholinergic mechanisms, we obtained, in eight healthy lean subjects, plethysmographic measurements of calf blood flow during 3 h of hyperinsulinemic (1 mU.kg-1.min-1) euglycemic clamp performed alone or during concomitant beta-adrenergic (propranolol infusion), cholinergic (atropine infusion), or alpha-adrenergic (prazosin administration) blockade. Euglycemic hyperinsulinemia alone increased calf blood flow by 38 +/- 10% (means +/- SE) and decreased vascular resistance by 27 +/- 4% (P < 0.01). The principal new observation is that these insulin-induced vasodilatory responses were not attenuated by concomitant propranolol or atropine infusion, nor were they potentiated by prazosin administration. In conclusion, these findings provide evidence that during euglycemic hyperinsulinemia in lean healthy humans stimulation of muscle blood flow is not mediated primarily by beta-adrenergic or cholinergic mechanisms. Furthermore, alpha-adrenergic mechanisms do not markedly limit insulin-induced stimulation of muscle blood flow.

Low malathion concentrations influence metabolism in Chironomus sancticaroli (Diptera, Chironomidae) in acute and chronic toxicity tests

Low malathion concentrations influence metabolism in Chironomus sancticaroli (Diptera, Chironomidae) in acute and chronic toxicity tests. Organophosphate compounds are used in agro-systems, and in programs to control pathogen vectors. Because they are continuously applied, organophosphates often reach water sources and may have an impact on aquatic life. The effects of acute and chronic exposure to the organophosphate insecticide malathion on the midge Chironomus sancticaroli are evaluated. To that end, three biochemical biomarkers, acetylcholinesterase (AChE), alpha (EST-α) and beta (EST-β) esterase were used. Acute bioassays with five concentrations of malathion, and chronic bioassays with two concentrations of malathion were carried out. In the acute exposure test, AChE, EST-α and EST-β activities declined by 66, 40 and 37%, respectively, at 0.251 µg L-1 and more than 80% at 1.37, 1.96 and 2.51 µg L-1. In chronic exposure tests, AChE and EST-α activities declined by 28 and 15% at 0.251 µg L-1. Results of the present study show that low concentrations of malathion can influence larval metabolism, indicating high toxicity for Chironomus sancticaroli and environmental risk associated with the use of organophosphates.

The Energy metabolism of China and India between 1971-2010: studying the bifurcation

This paper presents a comparison of the changes in the energetic metabolic pattern of China and India, the two most populated countries in the world, with two economies undergoing an important economic transition. The comparison of the changes in the energetic metabolic pattern has the scope to characterize and explain a bifurcation in their evolutionary path in the recent years, using the Multi-Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) approach. The analysis shows an impressive transformation of China’s energy metabolism determined by the joining of the WTO in 2001. Since then, China became the largest factory of the world with a generalized capitalization of all sectors ―especially the industrial sector― boosting economic labor productivity as well as total energy consumption. India, on the contrary, lags behind when considering these factors. Looking at changes in the household sector (energy metabolism associated with final consumption) in the case of China, the energetic metabolic rate (EMR) soared in the last decade, also thanks to a reduced growth of population, whereas in India it remained stagnant for the last 40 years. This analysis indicates a big challenge for India for the next decade. In the light of the data analyzed both countries will continue to require strong injections of technical capital requiring a continuous increase in their total energy consumption. When considering the size of these economies it is easy to guess that this may induce a dramatic increase in the price of energy, an event that at the moment will penalize much more the chance of a quick economic development of India.

Identification of optimal structural connectivity using functional connectivity and neural modeling.

The complex network dynamics that arise from the interaction of the brain's structural and functional architectures give rise to mental function. Theoretical models demonstrate that the structure-function relation is maximal when the global network dynamics operate at a critical point of state transition. In the present work, we used a dynamic mean-field neural model to fit empirical structural connectivity (SC) and functional connectivity (FC) data acquired in humans and macaques and developed a new iterative-fitting algorithm to optimize the SC matrix based on the FC matrix. A dramatic improvement of the fitting of the matrices was obtained with the addition of a small number of anatomical links, particularly cross-hemispheric connections, and reweighting of existing connections. We suggest that the notion of a critical working point, where the structure-function interplay is maximal, may provide a new way to link behavior and cognition, and a new perspective to understand recovery of function in clinical conditions.

Hemoglobin concentration and cerebral metabolism in patients with aneurysmal subarachnoid hemorrhage.

BACKGROUND AND PURPOSE: The optimal hemoglobin (Hgb) target after aneurysmal subarachnoid hemorrhage is not precisely known. We sought to examine the threshold of Hgb concentration associated with an increased risk of cerebral metabolic dysfunction in patients with poor-grade subarachnoid hemorrhage. METHODS: Twenty consecutive patients with poor-grade subarachnoid hemorrhage who underwent multimodality neuromonitoring (intracranial pressure, brain tissue oxygen tension, cerebral microdialysis) were studied prospectively. Brain tissue oxygen tension and extracellular lactate/pyruvate ratio were used as markers of cerebral metabolic dysfunction and the relationship between Hgb concentrations and the incidence of brain hypoxia (defined by a brain tissue oxygen tension <20 mm Hg) and cell energy dysfunction (defined by a lactate/pyruvate ratio >40) was analyzed. RESULTS: Compared with higher Hgb concentrations, a Hgb concentration <9 g/dL was associated with lower brain tissue oxygen tension (27.2 [interquartile range, 21.2 to 33.1] versus 19.9 [interquartile range, 7.1 to 33.1] mm Hg, P=0.02), higher lactate/pyruvate ratio (29 [interquartile range, 25 to 38] versus 36 [interquartile range, 26 to 59], P=0.16), and an increased incidence of brain hypoxia (21% versus 52%, P<0.01) and cell energy dysfunction (23% versus 43%, P=0.03). On multivariable analysis, a Hgb concentration <9 g/dL was associated with a higher risk of brain hypoxia (OR, 7.92; 95% CI, 2.32 to 27.09; P<0.01) and cell energy dysfunction (OR, 4.24; 95% CI, 1.33 to 13.55; P=0.02) after adjusting for cerebral perfusion pressure, central venous pressure, PaO(2)/FIO(2) ratio, and symptomatic vasospasm. CONCLUSIONS: A Hgb concentration <9 g/dL is associated with an increased incidence of brain hypoxia and cell energy dysfunction in patients with poor-grade subarachnoid hemorrhage.

The role of matrix metalloproteinase mmp-9 in peripheral neural system regeneration

Multiple lines of evidence show that matrix metalloproteinases (MMPs) are involved in the peripheral neural system degenerative and regenerative processes. MMP-9 was suggested in particular to play a role in the peripheral nerve after injury or during Wallerian degeneration. Interestingly, our previous analysis of Lpin1 mutant mice (which present morphological signs of active demyelination and acute inflammatory cell migration, similar to processes present in the PNS undergoing Wallerian degeneration) revealed an accumulation of MMP-9 in the endoneurium of affected animals. We therefore generated a mouse line lacking both the Lpin1 and the MMP-9 genes in order to determine if MMP-9 plays a role in either inhibition or potentiation of the demyelinating phenotype present in Lpin1 knockout mice. The inactivation of MMP-9 alone did not lead to defects in PNS structure or function. Interestingly we observed that the double mutant animals showed reduced nerve conduction velocity, lower myelin protein mRNA expressions, and had more histological abnormalities as compared to the Lpin1 single mutants. In addition, based on immunohistochemical analysis and macrophage markers mRNA expression, we found a lower macrophage content in the sciatic nerve of the double mutant animals. Together our data indicate that MMP-9 plays a role in macrophage recruitment during postinjury PNS regeneration processes and suggest that slower macrophage infiltration delays regenerative processes in PNS.

Fuel metabolism during exercise in euglycaemia and hyperglycaemia in patients with type 1 diabetes mellitus--a prospective single-blinded randomised crossover trial.

Aims/hypothesis We assessed systemic and local muscle fuel metabolism during aerobic exercise in patients with type I diabetes at euglycaemia and hyperglycaemia with identical insulin levels.Methods This was a single-blinded randomised crossover study at a university diabetes unit in Switzerland. We studied seven physically active men with type I diabetes (mean +/- SEM age 33.5 +/- 2.4 years, diabetes duration 20.1 +/- 3.6 years, HbA(1c) 6.7 +/- 0.2% and peak oxygen uptake [VO2peak] 50.3 +/- 4.5 ml min(-1) kg(-1)). Men were studied twice while cycling for 120 min at 55 to 60% of VO2peak, with a blood glucose level randomly set either at 5 or 11 mmol/l and identical insulinaemia. The participants were blinded to the glycaemic level; allocation concealment was by opaque, sealed envelopes. Magnetic resonance spectroscopy was used to quantify intramyocellular glycogen and lipids before and after exercise. Indirect calorimetry and measurement of stable isotopes and counter-regulatory hormones complemented the assessment of local and systemic fuel metabolism.Results The contribution of lipid oxidation to overall energy metabolism was higher in euglycaemia than in hyperglycaemia (49.4 +/- 4.8 vs 30.6 +/- 4.2%; p<0.05). Carbohydrate oxidation accounted for 48.2 +/- 4.7 and 66.6 +/- 4.2% of total energy expenditure in euglycaemia and hyperglycaemia, respectively (p<0.05). The level of intramyocellular glycogen before exercise was higher in hyperglycaemia than in euglycaemia (3.4 +/- 0.3 vs 2.7 +/- 0.2 arbitrary units [AU]; p<0.05). Absolute glycogen consumption tended to be higher in hyperglycaemia than in euglycaemia (1.3 +/- 0.3 vs 0.9 +/- 0.1 AU). Cortisol and growth hormone increased more strongly in euglycaemia than in hyperglycaemia (levels at the end of exercise 634 52 vs 501 +/- 32 nmol/l and 15.5 +/- 4.5 vs 7.4 +/- 2.0 ng/ml, respectively; p<0.05).Conclusions/interpretation Substrate oxidation in type I diabetic patients performing aerobic exercise in euglycaemia is similar to that in healthy individuals revealing a shift towards lipid oxidation during exercise. In hyperglycaemia fuel metabolism in these patients is dominated by carbohydrate oxidation. Intramyocellular glycogen was not spared in hyperglycaemia.

Incremental neural networks for function approximation

A new strategy for incremental building of multilayer feedforward neural networks is proposed in the context of approximation of functions from R-p to R-q using noisy data. A stopping criterion based on the properties of the noise is also proposed. Experimental results for both artificial and real data are performed and two alternatives of the proposed construction strategy are compared.