Deuteros 2.0: Peptide-level significance testing of data from hydrogen deuterium exchange mass spectrometry

Hydrogen deuterium exchange mass spectrometry (HDX-MS) is becoming increasing routine for monitoring changes in the structural dynamics of proteins. Differential HDX-MS allows comparison of protein states, such as in the absence or presence of a ligand. This can be used to attribute changes in conformation to binding events, allowing the mapping of entire conformational networks. As such, the number of necessary cross-state comparisons quickly increases as additional states are introduced to the system of study. There are currently very few software packages available that offer quick and informative comparison of HDX-MS datasets and even fewer which offer statistical analysis and advanced visualization. Following the feedback from our original software Deuteros, we present Deuteros 2.0 which has been redesigned from the ground up to fulfill a greater role in the HDX-MS analysis pipeline. Deuteros 2.0 features a repertoire of facilities for back exchange correction, data summarization, peptide-level statistical analysis and advanced data plotting features

Current paradigm of the 18-kDa translocator protein (TSPO) as a molecular target for PET imaging in neuroinflammation and neurodegenerative diseases

Neuroinflammation is a process characterised by drastic changes in microglial morphology and by marked upregulation of the 18-kDa translocator protein (TSPO) on the mitochondria. The continual increase in incidence of neuroinflammation and neurodegenerative diseases poses a major health issue in many countries, requiring more innovative diagnostic and monitoring tools. TSPO expression may constitute a biomarker for brain inflammation that could be monitored by using TSPO tracers as neuroimaging agents. From medical imaging perspectives, this review focuses on the current concepts related to the TSPO, and discusses briefly on the status of its PET imaging related to neuroinflammation and neurodegenerative diseases in humans

Exploratory 7-Tesla magnetic resonance spectroscopy in Huntington’s disease provides in vivo evidence for impaired energy metabolism

Huntington’s disease (HD) is a neurodegenerative genetic disorder that affects the brain. Atrophy of deep grey matter structures has been reported and it is likely that underlying pathologic processes occur before, or in concurrence with, volumetric changes. Measurement of metabolite concentrations in these brain structures has the potential to provide insight into pathological processes. We aim to gain understanding of metabolite changes with respect to the disease stage and pathophysiological changes. We studied five brain regions using magnetic resonance spectroscopy (MRS) using a 7-Tesla MRI scanner. Localized proton spectra were acquired to obtain six metabolite concentrations. MRS was performed in the caudate nucleus, putamen, thalamus, hypothalamus, and frontal lobe in 44 control subjects, premanifest gene carriers and manifest HD. In the caudate nucleus, HD patients display lower NAA (p = 0.009) and lower creatine concentration (p = 0.001) as compared to controls. In the putamen, manifest HD patients show lower NAA (p = 0.024), lower creatine concentration (p = 0.027), and lower glutamate (p = 0.013). Although absolute values of NAA, creatine, and glutamate were lower, no significant differences to controls were found in the premanifest gene carriers. The lower concentrations of NAA and creatine in the caudate nucleus and putamen of early manifest HD suggest deficits in neuronal integrity and energy metabolism. The changes in glutamate could support the excitotoxicity theory. These findings not only give insight into neuropathological changes in HD but also indicate that MRS can possibly be applied in future clinical trails to evaluate medication targeted at specific metabolic processes

Social cooperation and resource management dynamics among late hunter-fisher-gatherer societies in Tierra del Fuego (South America)

This paper presents the theoretical basis and first results of an agent-based model (ABM) computer simulation that is being developed to explore cooperation in hunter–gatherer societies. Specifically, we focus here on Yamana, a hunter-fisher-gatherer society that inhabited the islands of the southernmost part of Tierra del Fuego (Argentina–Chile). Ethnographical and archaeological evidence suggests the existence of sporadic aggregation events, triggered by a public call through smoke signals of an extraordinary confluence of resources under unforeseeable circumstances in time and space (a beached whale or an exceptional accumulation of fish after a low tide, for example). During these aggregation events, the different social units involved used to develop and improve production, distribution and consumption processes in a collective way. This paper attempts to analyse the social dynamics that explain cooperative behaviour and resource-sharing during aggregation events using an agent-based model of indirect reciprocity. In brief, agents make their decisions based on the success of the public strategies of other agents. Fitness depends on the resource captured and the social capital exchanged in aggregation events, modified by the agent’s reputation. Our computational results identify the relative importance of resources with respect to social benefits and the ease in detecting—and hence punishing—a defector as key factors to promote and sustain cooperative behaviour among populationSpanish Ministerio de Ciencia e Innovación (projects CONSOLIDER-INGENIO 2010 SimulPast-CSD2010-00034 and HAR2009-06996) as well as from the Argentine Consejo Nacional de Investigaciones Científicas y Técnicas (project PIP-0706) and the Wenner-Gren Foundation for Anthropological Research (project GR7846)

A novel RING finger protein, Znf179, modulates cell cycle exit and neuronal differentiation of P19 embryonal carcinoma cells

Znf179 is a member of the RING finger protein family. During embryogenesis, Znf179 is expressed in a restricted manner in the brain, suggesting a potential role in nervous system development. In this report, we show that the expression of Znf179 is upregulated during P19 cell neuronal differentiation. Inhibition of Znf179 expression by RNA interference significantly attenuated neuronal differentiation of P19 cells and a primary culture of cerebellar granule cells. Using a microarray approach and subsequent functional annotation analysis, we identified differentially expressed genes in Znf179-knockdown cells and found that several genes are involved in development, cellular growth, and cell cycle control. Flow cytometric analyses revealed that the population of G0/G1 cells decreased in Znf179-knockdown cells. In agreement with the flow cytometric data, the number of BrdU-incorporated cells significantly increased in Znf179-knockdown cells. Moreover, in Znf179-knockdown cells, p35, a neuronal-specific Cdk5 activator that is known to activate Cdk5 and may affect the cell cycle, and p27, a cell cycle inhibitor, also decreased. Collectively, these results show that induction of the Znf179 gene may be associated with p35 expression and p27 protein accumulation, which lead to cell cycle arrest in the G0/G1 phase, and is critical for neuronal differentiation of P19 cells

Dynamic Effective Connectivity of Inter-Areal Brain Circuits

Anatomic connections between brain areas affect information flow between neuronal circuits and the synchronization of neuronal activity. However, such structural connectivity does not coincide with effective connectivity (or, more precisely, causal connectivity), related to the elusive question “Which areas cause the present activity of which others?”. Effective connectivity is directed and depends flexibly on contexts and tasks. Here we show that dynamic effective connectivity can emerge from transitions in the collective organization of coherent neural activity. Integrating simulation and semi-analytic approaches, we study mesoscale network motifs of interacting cortical areas, modeled as large random networks of spiking neurons or as simple rate units. Through a causal analysis of time-series of model neural activity, we show that different dynamical states generated by a same structural connectivity motif correspond to distinct effective connectivity motifs. Such effective motifs can display a dominant directionality, due to spontaneous symmetry breaking and effective entrainment between local brain rhythms, although all connections in the considered structural motifs are reciprocal. We show then that transitions between effective connectivity configurations (like, for instance, reversal in the direction of inter-areal interactions) can be triggered reliably by brief perturbation inputs, properly timed with respect to an ongoing local oscillation, without the need for plastic synaptic changes. Finally, we analyze how the information encoded in spiking patterns of a local neuronal population is propagated across a fixed structural connectivity motif, demonstrating that changes in the active effective connectivity regulate both the efficiency and the directionality of information transfer. Previous studies stressed the role played by coherent oscillations in establishing efficient communication between distant areas. Going beyond these early proposals, we advance here that dynamic interactions between brain rhythms provide as well the basis for the self-organized control of this “communication-through-coherence”, making thus possible a fast “on-demand” reconfiguration of global information routing modalities