1,721,021 research outputs found
Community detection in weighted brain connectivity networks beyond the resolution limit
Full text linkAbstractGraph theory provides a powerful framework to investigate brain functional connectivity networks and their modular organization. However, most graph-based methods suffer from a fundamental resolution limit that may have affected previous studies and prevented detection of modules, or "communities", that are smaller than a specific scale. Surprise, a resolution-limit-free function rooted in discrete probability theory, has been recently introduced and applied to brain networks, revealing a wide size-distribution of functional modules (Nicolini and Bifone, 2016), in contrast with many previous reports. However, the use of Surprise is limited to binary networks, while brain networks are intrinsically weighted, reflecting a continuous distribution of connectivity strengths between different brain regions. Here, we propose Asymptotical Surprise, a continuous version of Surprise, for the study of weighted brain connectivity networks, and validate this approach in synthetic networks endowed with a ground-truth modular structure. We compare Asymptotical Surprise with leading community detection methods currently in use and show its superior sensitivity in the detection of small modules even in the presence of noise and intersubject variability such as those observed in fMRI data. We apply our novel approach to functional connectivity networks from resting state fMRI experiments, and demonstrate a heterogeneous modular organization, with a wide distribution of clusters spanning multiple scales. Finally, we discuss the implications of these findings for the identification of connector hubs, the brain regions responsible for the integration of the different network elements, showing that the improved resolution afforded by Asymptotical Surprise leads to a different classification compared to current methods
Modular structure of brain functional networks: breaking the resolution limit by Surprise
Full text linkThe modular organization of brain networks has been widely investigated using graph theoretical approaches. Recently, it has been demonstrated that graph partitioning methods based on the maximization of global fitness functions, like Newman's Modularity, suffer from a resolution limit, as they fail to detect modules that are smaller than a scale determined by the size of the entire network. Here we explore the effects of this limitation on the study of brain connectivity networks. We demonstrate that the resolution limit prevents detection of important details of the brain modular structure, thus hampering the ability to appreciate differences between networks and to assess the topological roles of nodes. We show that Surprise, a recently proposed fitness function based on probability theory, does not suffer from these limitations. Surprise maximization in brain co-activation and functional connectivity resting state networks reveals the presence of a rich structure of heterogeneously distributed modules, and differences in networks' partitions that are undetectable by resolution-limited methods. Moreover, Surprise leads to a more accurate identification of the network's connector hubs, the elements that integrate the brain modules into a cohesive structure
Wiring transmission in the serotonergic system
No full textSerotonergic neurons are part of one of the most widely distributed systems of the mammalian brain. Indeed, serotonin is involved in a wide range of physiological processes, including the control of appetite, sleep, memory, mood, stress and sexual behavior. The raphe nuclei (B1-9) of the brain stem are the origin of serotonergic projections to the whole central nervous system. In the last years, several studies have unraveled the heterogeneity of serotonergic neurons, in terms of developmental programs, molecular and electrophysiological properties. Recently, a map of the complex topographical organization of the serotonergic fibers has been drawn using intersectional fate mapping strategy, as well as retrograde or anterograde tracing (Bang et al, 2012; Fernandez et al. 2015; Muzerelle et al, 2014). Serotonergic neurons have un-myelinated fiber varicosities, where the transmitter is synthesized, stored and released in a “volume transmission” (VT) mode (Agnati et al, 1995). To a lesser extent, serotonergic fibers also present synapse-like specializations where synaptic contacts are established by 5-HT terminals with specific neuronal targets acting in a conventional “wiring transmission” (WT) mode. However, experimental strategies used to map serotonergic projections so far where not selective for VT versus WT, and the organization of WT is still the object of investigation. Taking advantage of the properties of the rabies virus, whose envelope can drive the infection of neurons exclusively through their presynaptic terminals, we have selectively mapped the serotonergic WT system originating in the raphe nuclei. We injected recombinant G-deleted rabies virus in several brain regions of Tph2::GFP knock-in mice, in which serotonergic neurons were clearly labeled by the expression of GFP (Migliarini et al, 2013). We also used monosynaptic tracing, coupling pseudotyped recombinant rabies virus with a helper adeno-associated virus (Wall et al, 2010). This experimental approach revealed that each brain district hereby investigated receives WT from a relatively small and region-specific number of serotonergic neurons, thus making it possible to establish a correlation map between specific serotonergic neurons in the raphe nuclei and distinct brain areas. Altogether, this study sheds new light on communication properties of serotonergic system, and may help understand the selective role of serotonergic WT in health and disease
Rotating-polarization CARS microscopy: combining chemical and molecular orientation sensitivity
Full text linkCoherent Anti-Stokes Raman Spectroscopy (CARS) is a non-linear process in which the energy difference of a pair of incoming photons matches the energy of the vibrational mode of a molecular bond of interest. This phonon population is coherently probed by a third photon and anti-Stokes radiation is emitted. Here a novel approach to CARS microscopy is presented yielding the intensity of the anti-Stokes emission, the directionality the molecular bonds of interest, and their average orientation. Myelinated axons in fixed mouse-brain slices have been imaged by RP-CARS. We were able to detect the local average direction of the acylic chains of membrane phospholipids and their spatial anisotropy. This novel method may impact the study of healthy brain circuitry as well as demyelinating diseases or other pathological states associated with altered neural connectivity
A rabies virus based approach to map serotonergic neurons innervating different brain structures
No full textSerotonergic neurons are part of one of the most widely distributed neural systems in the mammalian brain (Lauder and Bloom, 1974). Serotonergic neurons form the raphe nuclei in the brain stem, and are organized in distinct nuclei (B1-9) that project to the whole central nervous system. Consistently with such a broad innervation, serotonin is involved in a wide range of physiological processes including the control of appetite, sleep, memory, mood, stress and sexual behavior (Veenstra-Vanderweele et al, 2000). Several studies using anatomical tracing methods and anterograde viral tracers have led to the hypotheses of a topographic organization of the serotonergic system, with different projections from the caudal, median/central and dorsal raphe neurons to specific target districts in the rostral brain (Muzerelle et al. 2014). Experimental evidence suggests that clusters of serotonergic neurons within the raphe nuclei may have distinct functional properties, but the complex organization of serotonergic neuron projections remains poorly understood. The aim of the present study is to map at a finer scale the organization of serotonin neurons projecting to different target areas, thus contributing to understanding the functional role of specific serotonergic neuronal subpopulations. To this end, we used a Tph2::GFP knock-in mouse model, in which serotonergic neurons are clearly labeled by the expression of GFP (Migliarini et al, 2013), and the retrograde recombinant rabies viral tracer to map the serotonergic neurons innervating different brain structures. Moreover, we developed a conditional GFP expressing mouse model, in which the reporter is maintained under the transcriptional control of the Tph2 gene and activated upon an flp mediated somatic recombination, to map the organization of serotonergic neuron subgroups sharing common targets in the brain
Building better strategies to develop new medications in Alcohol Use Disorder: Learning from past success and failure to shape a brighter future
Full text linkAlcohol Use Disorder (AUD) is a chronic disease that develops over the years. The complexity of the neurobiological processes contributing to the emergence of AUD and the neuroadaptive changes occurring during disease progression make it difficult to improve treatments. On the other hand, this complexity offers researchers the possibility to explore new targets. Over years of intense research several molecules were tested in AUD; in most cases, despite promising preclinical data, the clinical efficacy appeared insufficient to justify futher development. A prototypical example is that of corticotropin releasing factor type 1 receptor (CRF1R) antagonists that showed significant effectiveness in animal models of AUD but were largely ineffective in humans. The present article attempts to analyze the most recent venues in the development of new medications in AUD with a focus on the most promising drug targets under current exploration. Moreover, we delineate the importance of using a more integrated translational framework approach to correlate preclinical findings and early clinical data to enhance the probability to validate biological targets of interest
The role of cytoskeleton networks on lipid-mediated delivery of DNA
Full text linkBackground: Lipid-mediated delivery of DNA is hindered by extracellular and intracellular barriers that significantly reduce the transfection efficiency of synthetic nonviral vectors. Results: In this study we investigated the role of the actin and microtubule networks on the uptake and cytoplasmic transport of multicomponent cationic liposome–DNA complexes in CHO-K1 live cells by means of confocal laser scanning microscopy and 3D single particle tracking. Treatment with actin (latrunculin B)- and microtubule-disrupting (nocodazole) reagents indicated that intracellular trafficking of complexes predominantly involves microtubule-dependent active transport. We found that the actin network has a major effect on the initial uptake of complexes, while the microtubule network is mainly responsible for the subsequent active transportation to the lysosomes. Conclusion: Collectively, a strategy to improve the efficiency of lipid gene vectors can be formulated. We could find a lipid formulation that allows the nanoparticles to avoid the microtubule pathway to lysosomes.Fil: Coppola, Stefano. Sapienza University of Rome. Dipartimento di Medicina Molecolare; ItaliaFil: Cardarelli, Francesco. Istituto Italiano di Tecnologia. Center for Nanotechnology Innovation at NEST; ItaliaFil: Pozzi, Daniela. Sapienza University of Rome. Dipartimento di Medicina Molecolare; ItaliaFil: Estrada, Laura Cecilia. University of California. Department of Biomedical Engineering. Laboratory for Fluorescence Dynamics; Estados Unidos. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Física. Laboratorio de Electrónica Cuántica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires; ArgentinaFil: Digman, Michelle. University of California. Department of Biomedical Engineering. Laboratory for Fluorescence Dynamics; Estados UnidosFil: Gratton, Enrico. University of California. Department of Biomedical Engineering. Laboratory for Fluorescence Dynamics; Estados UnidosFil: Bifone, Angelo . Istituto Italiano di Tecnologia. Center for Nanotechnology Innovation at NEST; ItaliaFil: Marianecci, Carlotta. Sapienza University of Rome. Dipartimento di Chimica e Tecnologie del Farmaco; ItaliaFil: Caracciolo, Giulio. Sapienza University of Rome. Dipartimento di Medicina Molecolare; Itali
Cholesterol-Dependent Macropinocytosis and Endosomal Escape Control the Transfection Efficiency of Lipoplexes in CHO Living Cells
No full textHere we investigate the cellular uptake mechanism and final intracellular fate of two cationic liposome formulations characterized by similar physicochemical properties but very different lipid composition and efficiency for intracellular delivery of DNA. The first formulation is made of cationic lipid 1,2-dioleoyl-3-trimethylammonium-propane (DOTAP) and the zwitterionic helper dioleoylphosphocholine (DOPC), while the second one is made of the cationic 3 beta-[N-(N,N-dimethylaminoethane)-carbamoyl] cholesterol (DC-Chol) and the zwitterionic lipid dioleoylphosphatidylethanolamine (DOPE). Combining pharmacological and imaging approaches we show that both DOTAP-DOPC/DNA and DC-Chol-DOPE/DNA lipoplexes are taken up in Chinese hamster ovary (CHO) living cells mainly through fluid-phase macropinocytosis. Our results also indicate that lipoplex macropinocytosis is a cholesterol-sensitive uptake mechanism. On the other side, both clathrin-mediated and caveolae-mediated endocytosis play a minor role, if any, in the cell uptake. Colocalization of fluorescently tagged lipoplexes and Lysosensor, a primary lysosome marker, reveals that poorly efficient DOTAP-DOPC/DNA lipoplexes are largely degraded in the lysosomes, while efficient DC-Chol-DOPE/DNA systems can efficiently escape from endosomal compartments
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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