Expressing Measurement Uncertainty in OCL/UML Datatypes

Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, di cult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations de ned for the values of these types.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Fear balance is maintained by bodily feedback to the insular cortex in mice

How does the brain maintain fear within an adaptive range? We found that the insular cortex acts as a state-dependent regulator of fear that is necessary to establish an equilibrium between the extinction and maintenance of fear memories in mice. Whereas insular cortex responsiveness to fear-evoking cues increased with their certainty to predict harm, this activity was attenuated through negative bodily feedback that arose from heart rate decelerations during freezing. Perturbation of body-brain communication by vagus nerve stimulation disrupted the balance between fear extinction and maintenance similar to insular cortex inhibition. Our data reveal that the insular cortex integrates predictive sensory and interoceptive signals to provide graded and bidirectional teaching signals that gate fear extinction and illustrate how bodily feedback signals are used to maintain fear within a functional equilibrium

Applying ASP to UML model validation

We apply ASP to model validation in a CASE setting, where models are UML class diagrams and object diagrams are called \u201csnapshots\u201d. We present the design and implementation of MSG, a snapshot generator for UML models that employs DLV-Complex as a generator engine, the answer sets representing the legal snapshots

Specification-driven test generation for model transformations

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-30476-7_3Proceedings of 5th International Conference, ICMT 2012, Prague, Czech Republic, May 28-29, 2012Testing model transformations poses several challenges, among them the automatic generation of appropriate input test models and the specification of oracle functions. Most approaches to the generation of input models ensure a certain level of source meta-model coverage, whereas the oracle functions are frequently defined using query or graph languages. Both tasks are usually performed independently regardless their common purpose, and sometimes there is a gap between the properties exhibited by the generated input models and those demanded to the transformations (as given by the oracles). Recently, we proposed a formal specification language for the declarative formulation of transformation properties (invariants, pre- and postconditions) from which we generated partial oracle functions that facilitate testing of the transformations. Here we extend the usage of our specification language for the automated generation of input test models by constraint solving. The testing process becomes more intentional because the generated models ensure a certain coverage of the interesting properties of the transformation. Moreover, we use the same specification to consistently derive both the input test models and the oracle functions.Work funded by the Spanish Ministry of Economy and Competitivity (TIN2011-24139) and by the R&D programme of Madrid Region (S2009/TIC-1650

Inhibition of Bax protects neuronal cells from oligomeric Aβ neurotoxicity

Although oligomeric β-amyloid (Aβ) has been suggested to have an important role in Alzheimer disease (AD), the mechanism(s) of how Aβ induces neuronal cell death has not been fully identified. The balance of pro- and anti-apoptotic Bcl-2 family proteins (e.g., Bcl-2 and Bcl-w versus Bad, Bim and Bax) has been known to have a role in neuronal cell death and, importantly, expression levels of these proteins are reportedly altered in the vulnerable neurons in AD. However, the roles of apoptotic proteins in oligomeric Aβ-induced cell death remain unclear in vivo or in more physiologically relevant models. In addition, no study to date has examined whether Bax is required for the toxicity of oligomeric Aβ. Here, we found that treatment with oligomeric Aβ increased Bim levels but decreased Bcl-2 levels, leading to the activation of Bax and neuronal cell death in hippocampal slice culture and in vivo. Furthermore, the inhibition of Bax activity either by Bax-inhibiting peptide or bax gene knockout significantly prevented oligomeric Aβ-induced neuronal cell death. These findings are first to demonstrate that Bax has an essential role in oligomeric Aβ-induced neuronal cell death, and that the targeting of Bax may be a therapeutic approach for AD

High-Throughput Single-Cell Manipulation in Brain Tissue

The complexity of neurons and neuronal circuits in brain tissue requires the genetic manipulation, labeling, and tracking of single cells. However, current methods for manipulating cells in brain tissue are limited to either bulk techniques, lacking single-cell accuracy, or manual methods that provide single-cell accuracy but at significantly lower throughputs and repeatability. Here, we demonstrate high-throughput, efficient, reliable, and combinatorial delivery of multiple genetic vectors and reagents into targeted cells within the same tissue sample with single-cell accuracy. Our system automatically loads nanoliter-scale volumes of reagents into a micropipette from multiwell plates, targets and transfects single cells in brain tissues using a robust electroporation technique, and finally preps the micropipette by automated cleaning for repeating the transfection cycle. We demonstrate multi-colored labeling of adjacent cells, both in organotypic and acute slices, and transfection of plasmids encoding different protein isoforms into neurons within the same brain tissue for analysis of their effects on linear dendritic spine density. Our platform could also be used to rapidly deliver, both ex vivo and in vivo, a variety of genetic vectors, including optogenetic and cell-type specific agents, as well as fast-acting reagents such as labeling dyes, calcium sensors, and voltage sensors to manipulate and track neuronal circuit activity at single-cell resolution

Lightweight String Reasoning for OCL

International audienceModels play a key role in assuring software quality in the modeldriven approach. Precise models usually require the definition of OCL expressions to specify model constraints that cannot be expressed graphically. Techniques that check the satisfiability of such models and find corresponding instances of them are important in various activities, such as model-based testing and validation. Several tools to check model satisfiability have been developed but to our knowledge, none of them yet supports the analysis of OCL expressions including operations on Strings in general terms. As, in contrast, many industrial models do contain such operations, there is evidently a gap. There has been much research on formal reasoning on strings in general, but so far the results could not be included into model finding approaches. For model finding, string reasoning only contributes a sub-problem, therefore, a string reasoning approach for model finding should not add up front too much computational complexity to the global model finding problem. We present such a lightweight approach based on constraint satisfaction problems and constraint rewriting. Our approach efficiently solves several common kinds of string constraints and it is integrated into the EMFtoCSP model finder

Blocking human fear memory with the matrix metalloproteinase inhibitor doxycycline

Learning to predict threat is a fundamental ability of many biological organisms, and a laboratory model for anxiety disorders. Interfering with such memories in humans would be of high clinical relevance. On the basis of studies in cell cultures and slice preparations, it is hypothesised that synaptic remodelling required for threat learning involves the extracellular enzyme matrix metalloproteinase (MMP) 9. However, in vivo evidence for this proposal is lacking. Here we investigate human Pavlovian fear conditioning under the blood-brain barrier crossing MMP inhibitor doxycyline in a pre-registered, randomised, double-blind, placebo-controlled trial. We find that recall of threat memory, measured with fear-potentiated startle 7 days after acquisition, is attenuated by ~60% in individuals who were under doxycycline during acquisition. This threat memory impairment is also reflected in increased behavioural surprise signals to the conditioned stimulus during subsequent re-learning, and already late during initial acquisition. Our findings support an emerging view that extracellular signalling pathways are crucially required for threat memory formation. Furthermore, they suggest novel pharmacological methods for primary prevention and treatment of posttraumatic stress disorder.Molecular Psychiatry advance online publication, 4 April 2017; doi:10.1038/mp.2017.65

Experience-Dependent Plasticity and Modulation of Growth Regulatory Molecules at Central Synapses

Structural remodeling or repair of neural circuits depends on the balance between intrinsic neuronal properties and regulatory cues present in the surrounding microenvironment. These processes are also influenced by experience, but it is still unclear how external stimuli modulate growth-regulatory mechanisms in the central nervous system. We asked whether environmental stimulation promotes neuronal plasticity by modifying the expression of growth-inhibitory molecules, specifically those of the extracellular matrix. We examined the effects of an enriched environment on neuritic remodeling and modulation of perineuronal nets in the deep cerebellar nuclei of adult mice. Perineuronal nets are meshworks of extracellular matrix that enwrap the neuronal perikaryon and restrict plasticity in the adult CNS. We found that exposure to an enriched environment induces significant morphological changes of Purkinje and precerebellar axon terminals in the cerebellar nuclei, accompanied by a conspicuous reduction of perineuronal nets. In the animals reared in an enriched environment, cerebellar nuclear neurons show decreased expression of mRNAs coding for key matrix components (as shown by real time PCR experiments), and enhanced activity of matrix degrading enzymes (matrix metalloproteinases 2 and 9), which was assessed by in situ zymography. Accordingly, we found that in mutant mice lacking a crucial perineuronal net component, cartilage link protein 1, perineuronal nets around cerebellar neurons are disrupted and plasticity of Purkinje cell terminal is enhanced. Moreover, all the effects of environmental stimulation are amplified if the afferent Purkinje axons are endowed with enhanced intrinsic growth capabilities, induced by overexpression of GAP-43. Our observations show that the maintenance and growth-inhibitory function of perineuronal nets are regulated by a dynamic interplay between pre- and postsynaptic neurons. External stimuli act on this interaction and shift the balance between synthesis and removal of matrix components in order to facilitate neuritic growth by locally dampening the activity of inhibitory cues