Molecular crime and cellular punishment: active detoxification of misfolded and aggregated proteins in the cell by the chaperone and protease networks.

Labile or mutation-sensitised proteins may spontaneously convert into aggregation-prone conformations that may be toxic and infectious. This hazardous behavior, which can be described as a form of "molecular criminality", can be actively counteracted in the cell by a network of molecular chaperone and proteases. Similar to law enforcement agents, molecular chaperones and proteases can specifically identify, apprehend, unfold and thus neutralize "criminal" protein conformers, allowing them to subsequently refold into harmless functional proteins. Irreversibly damaged polypeptides that have lost the ability to natively refold are preferentially degraded by highly controlled ATP-consuming proteases. Damaged proteins that escape proteasomal degradation can also be "incarcerated" into dense amyloids, "evicted" from the cell, or internally "exiled" to the lysosome to be hydrolysed and recycled. Thus, remarkable parallels exist between molecular and human forms of criminality, as well as in the cellular and social responses to various forms of crime. Yet, differences also exist: whereas programmed death is the preferred solution chosen by aged and aggregation-stressed cells, collective suicide is seldom chosen by lawless societies. Significantly, there is no cellular equivalent for the role of familial care and of education in general, which is so crucial to the proper shaping of functional persons in the society. Unlike in the cell, humanism introduces a bias against radical solutions such as capital punishment, favouring crime prevention, reeducation and social reinsertion of criminals.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Effects of maintaining ditch networks on the development of Scots pine stands

Tiivistelmä: Kunnostusojituksen vaikutus rämemänniköiden kehitykseen

Regional deterministic characterization of fracture networks and its application to GIS-based rock fall risk assessment

The study investigates the possibility to incorporate fracture intensity and block geometry as spatially continuous parameters in GIS-based systems. For this purpose, a deterministic method has been implemented to estimate block size (Bloc3D) and joint frequency (COLTOP). In addition to measuring the block size, the Bloc3D Method provides a 3D representation of the shape of individual blocks. These two methods were applied using field measurements (joint set orientation and spacing) performed over a large field area, in the Swiss Alps. This area is characterized by a complex geology, a number of different rock masses and varying degrees of metamorphism. The spatial variability of the parameters was evaluated with regard to lithology and major faults. A model incorporating these measurements and observations into a GIS system to assess the risk associated with rock falls is proposed. The analysis concludes with a discussion on the feasibility of such an application in regularly and irregularly jointed rock masses, with persistent and impersistent discontinuities.

Discharge water quality from old ditch networks in Finnish peatland forests

Tiivistelmä: Vanhoilta metsäojitusalueilta valuvan veden ominaisuudet

A role for the alpha-chain connecting peptide motif in mediating TCR-CD8 cooperation.

To generate peripheral T cells that are both self-MHC restricted and self-MHC tolerant, thymocytes are subjected to positive and negative selection. How the TCR discriminates between positive and negative selection ligands is not well understood, although there is substantial evidence that the CD4 and CD8 coreceptors play an important role in this cell fate decision. We have previously identified an evolutionarily conserved motif in the TCR, the alpha-chain connecting peptide motif (alpha-CPM), which allows the TCR to deliver positive selection signals. Thymocytes expressing alpha-CPM-deficient receptors do not undergo positive selection, whereas their negative selection is not impaired. In this work we studied the ligand binding and receptor function of alpha-CPM-deficient TCRs by generating T cell hybridomas expressing wild-type or alpha-CPM-deficient forms of the T1 TCR. This K(d)-restricted TCR is specific for a photoreactive derivative of the Plasmodium berghei circumsporozoite peptide(252-260) IASA-YIPSAEK(ABA)I and is therefore amenable to TCR photoaffinity labeling. The experiments presented in this work show that alpha-CPM-deficient TCRs fail to cooperate with CD8 to enhance ligand binding and functional responses.

The co-evolution of social institutions, demography, and large-scale human cooperation.

Human cooperation is typically coordinated by institutions, which determine the outcome structure of the social interactions individuals engage in. Explaining the Neolithic transition from small- to large-scale societies involves understanding how these institutions co-evolve with demography. We study this using a demographically explicit model of institution formation in a patch-structured population. Each patch supports both social and asocial niches. Social individuals create an institution, at a cost to themselves, by negotiating how much of the costly public good provided by cooperators is invested into sanctioning defectors. The remainder of their public good is invested in technology that increases carrying capacity, such as irrigation systems. We show that social individuals can invade a population of asocials, and form institutions that support high levels of cooperation. We then demonstrate conditions where the co-evolution of cooperation, institutions, and demographic carrying capacity creates a transition from small- to large-scale social groups.

Generation of biological association networks: A novel strategy to detect new targets in cancer therapy

The aim of this work was to design a novel strategy to detect new targets for anticancer treatments. The rationale was to build Biological Association Networks from differentially expressed genes in drug-resistant cells to identify important nodes within the Networks. These nodes may represent putative targets to attack in cancer therapy, as a way to destabilize the gene network developed by the resistant cells to escape from the drug pressure. As a model we used cells resistant to methotrexate (MTX), an inhibitor of DHFR. Selected node-genes were analyzed at the transcriptional level and from a genotypic point of view. In colon cancer cells, DHFR, the AKR1 family, PKC¿, S100A4, DKK1, and CAV1 were overexpressed while E-cadherin was lost. In breast cancer cells, the UGT1A family was overexpressed, whereas EEF1A1 was overexpressed in pancreatic cells. Interference RNAs directed against these targets sensitized cells towards MTX.

Plastic modifications within inhibitory control networks induced by practicing a stop-signal task: an electrical neuroimaging study.

INTRODUCTION: Inhibitory control refers to our ability to suppress ongoing motor, affective or cognitive processes and mostly depends on a fronto-basal brain network. Inhibitory control deficits participate in the emergence of several prominent psychiatric conditions, including attention deficit/hyperactivity disorder or addiction. The rehabilitation of these pathologies might therefore benefit from training-based behavioral interventions aiming at improving inhibitory control proficiency and normalizing the underlying neurophysiological mechanisms. The development of an efficient inhibitory control training regimen first requires determining the effects of practicing inhibition tasks. METHODS: We addressed this question by contrasting behavioral performance and electrical neuroimaging analyses of event-related potentials (ERPs) recorded from humans at the beginning versus the end of 1 h of practice on a stop-signal task (SST) involving the withholding of responses when a stop signal was presented during a speeded auditory discrimination task. RESULTS: Practicing a short SST improved behavioral performance. Electrophysiologically, ERPs differed topographically at 200 msec post-stimulus onset, indicative of the engagement of distinct brain network with learning. Source estimations localized this effect within the inferior frontal gyrus, the pre-supplementary motor area and the basal ganglia. CONCLUSION: Our collective results indicate that behavioral and brain responses during an inhibitory control task are subject to fast plastic changes and provide evidence that high-order fronto-basal executive networks can be modified by practicing a SST.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Coworker networks in the labour market

This paper studies the role coworker-based networks play for individual labour marketoutcomes. I analyse how the provision of labour market relevant information by formercoworkers affects the employment probabilities and, if hired, the wages of male workerswho have previously become unemployed as the result of an establishment closure. Toidentify the causal effect of an individual worker's network on labour market outcomes, Iexploit exogenous variation in the strength of these networks that is due to the occurrenceof mass-layoffs in the establishments of former coworkers. The empirical analysis is basedon administrative data that comprise the universe of workers employed in Germany between1980 and 2001. The results suggest a strong positive effect of a higher employmentrate in a worker's network of former coworkers on his re-employment probability afterdisplacement: a 10 percentage point increase in the prevailing employment rate in thenetwork increases the re-employment probability by 7.5 percentage points. In contrast,there is no evidence of a statistically significant effect on wages.

The Impact of Cooperation on R&D, Innovation andProductivity: an Analysis of Spanish Manufacturing and Services Firms

This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations.

The Impact of Cooperation on R&D, Innovation and Productivity: an Analysis of Spanish Manufacturing and Services Firms

This paper investigates relationships between cooperation, R&D, innovation and productivity in Spanish firms. It uses a large sample of firm-level micro-data and applies an extended structural model that aims to explain the effects of cooperation on R&D investment, of R&D investment on output innovation, and of innovation on firms’ productivity levels. It also analyses the determinants of R&D cooperation. Firms’ technology level is taken into account in order to analyse the differences between high-tech and low-tech firms, both in the industrial and service sectors. The database used was the Technological Innovation Panel (PITEC) for the period 2004-2010. Empirical results show that firms which cooperate in innovative activities are more likely to invest in R&D in subsequent years. As expected, R&D investment has a positive impact on the probability of generating an innovation, in terms of both product and process, for manufacturing firms. Finally, innovation output has a positive impact on firms’ productivity, being greater in process innovations. Keywords: innovation sources; productivity; R&D Cooperation

The α1-adrenergic receptors: diversity of signaling networks and regulation.

The α(1)-adrenergic receptor (AR) subtypes (α(1a), α(1b), and α(1d)) mediate several physiological effects of epinephrine and norepinephrine. Despite several studies in recombinant systems and insight from genetically modified mice, our understanding of the physiological relevance and specificity of the α(1)-AR subtypes is still limited. Constitutive activity and receptor oligomerization have emerged as potential features regulating receptor function. Another recent paradigm is that β arrestins and G protein-coupled receptors themselves can act as scaffolds binding a variety of proteins and this can result in growing complexity of the receptor-mediated cellular effects. The aim of this review is to summarize our current knowledge on some recently identified functional paradigms and signaling networks that might help to elucidate the functional diversity of the α(1)-AR subtypes in various organs.