434 research outputs found
Do Natural Proteins Differ from Random Sequences Polypeptides? Natural vs. Random Proteins Classification Using an Evolutionary Neural Network
Are extant proteins the exquisite result of natural selection or are they random sequences slightly edited by evolution? This question has puzzled biochemists for long time and several groups have addressed this issue comparing natural protein sequences to completely random ones coming to contradicting conclusions. Previous works in literature focused on the analysis of primary structure in an attempt to identify possible signature of evolutionary editing. Conversely, in this work we compare a set of 762 natural proteins with an average length of 70 amino acids and an equal number of completely random ones of comparable length on the basis of their structural features. We use an ad hoc Evolutionary Neural Network Algorithm (ENNA) in order to assess whether and to what extent natural proteins are edited from random polypeptides employing 11 different structure-related variables (i.e. net charge, volume, surface area, coil, alpha helix, beta sheet, percentage of coil, percentage of alpha helix, percentage of beta sheet, percentage of secondary structure and surface hydrophobicity). The ENNA algorithm is capable to correctly distinguish natural proteins from random ones with an accuracy of 94.36%. Furthermore, we study the structural features of 32 random polypeptides misclassified as natural ones to unveil any structural similarity to natural proteins. Results show that random proteins misclassified by the ENNA algorithm exhibit a significant fold similarity to portions or subdomains of extant proteins at atomic resolution. Altogether, our results suggest that natural proteins are significantly edited from random polypeptides and evolutionary editing can be readily detected analyzing structural features. Furthermore, we also show that the ENNA, employing simple structural descriptors, can predict whether a protein chain is natural or random
Scaling up self-stratifying supercapacitive microbial fuel cell
Self-stratifying microbial fuel cells with three different electrodes sizes and volumes were operated in supercapacitive mode. As the electrodes size increased, the equivalent series resistance decreased, and the overall power was enhanced (small: ESR = 7.2 Ω and Pmax = 13 mW; large: ESR = 4.2 Ω and Pmax = 22 mW). Power density referred to cathode geometric surface area and displacement volume of the electrolyte in the reactors. With regards to the electrode wet surface area, the large size electrodes (L-MFC) displayed the lowest power density (460 μW cm−2) whilst the small and medium size electrodes (S-MFC, M-MFC) showed higher densities (668 μW cm−2 and 633 μW cm−2, respectively). With regard to the volumetric power densities the S-MFC, the M-MFC and the L-MFC had similar values (264 μW mL−1, 265 μW mL−1 and 249 μW cm−1, respectively). Power density normalised in terms of carbon weight utilised for fabricating MFC cathodes-electrodes showed high output for smaller electrode size MFC (5811 μW g−1-C- and 3270 μW g−1-C- for the S-MFC and L-MFC, respectively) due to the fact that electrodes were optimised for MFC operations and not supercapacitive discharges. Apparent capacitance was high at lower current pulses suggesting high faradaic contribution. The electrostatic contribution detected at high current pulses was quite low. The results obtained give rise to important possibilities of performance improvements by optimising the device design and the electrode fabrication
Leishmania infantum Amastigotes Enhance HIV-1 Production in Cocultures of Human Dendritic Cells and CD4+ T Cells by Inducing Secretion of IL-6 and TNF-α
Visceral leishmaniasis (VL) is a potentially deadly parasitic disease afflicting millions worldwide. Although itself an important infectious illness, VL has also emerged as an opportunistic disease among patients infected with HIV-1. This is partly due to the increasing overlap between urban regions of high HIV-1 transmission and areas where Leishmania is endemic. Furthermore, VL increases the development and clinical progression of AIDS-related diseases. Conversely, HIV-1-infected individuals are at greater risk of developing VL or suffering relapse. Finally, HIV-1 and Leishmania can both productively infect cells of the macrophage-dendritic cell lineage, resulting in a cumulative deficiency of the immune response. We therefore studied the effect of Leishmania infantum on HIV-1 production when dendritic cells (DCs) are cocultured with autologous CD4+ T cells. We show that amastigotes promote virus replication in both DCs and lymphocytes, due to a parasite-mediated production of soluble factors by DCs. Micro-beads array analyses indicate that Leishmania infantum amastigotes infection induces a higher secretion of several cytokines in these cells, and use of specific neutralizing antibodies revealed that the Leishmania-induced increase in HIV-1 replication is due to IL-6 and TNF-α. These findings suggest that Leishmania's presence within DC/T-cell conjugates leads to an enhanced HIV-1 production
Particle swarm control
International audienceControlling several and possibly independent moving agents in order to reach global goals is a tedious task that has applications in many engineering fields such as robotics or computer animation. Together, the different agents form a whole called swarm, which may display interesting collective behaviors. When the agents are driven by their own dynamics, controlling this swarm is known as the particle swarm control problem. In that context, several strategies, based on the control of individuals using simple rules, exist. This paper defends a new and original method based on a centralized approach. More precisely, we propose a framework to control several particles with constraints either expressed on a per-particle basis, or expressed as a function of their environment. We refer to these two categories as respectively Lagrangian or Eulerian constraints. The contributions of the paper are the following: (i) we show how to use optimal control recipes to express an optimization process over a large state space including the dynamic information of the particles; and (ii) the relation between the Lagrangian state space and Eulerian values is conveniently expressed with graph operators that make it possible to conduct all the mathematical operations required by the control process. We show the effectiveness of our approach on classical and more original particle swarm control problems
Right-Wing Politicians Prefer the Emotional Left
Physiological research suggests that social attitudes, such as political beliefs, may be partly hard-wired in the brain. Conservatives have heightened sensitivity for detecting emotional faces and use emotion more effectively when campaigning. As the left face displays emotion more prominently, we examined 1538 official photographs of conservative and liberal politicians from Australia, Canada, the United Kingdom and the United States for an asymmetry in posing. Across nations, conservatives were more likely than liberals to display the left cheek. In contrast, liberals were more likely to face forward than were conservatives. Emotion is important in political campaigning and as portraits influence voting decisions, conservative politicians may intuitively display the left face to convey emotion to voters
Normative modeling of brain morphometry in Clinical High-Risk for Psychosis
Importance: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.
Objective: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.
Design setting and participants: Clinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group.
Main outcomes and measures: For each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z1.96) scores.
Results: CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADS SA showed significant but weak associations (|β|<0.09; P FDR <0.05) with positive symptoms and IQ.
Conclusions and relevance: The study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk.
Key points: Question: Is the risk of psychosis associated with brain morphometric changes that deviate significantly from healthy variation?Findings: In this study of 1340 individuals high-risk for psychosis (CHR-P) and 1237 healthy participants, individual-level variation in macroscale neuromorphometric measures of the CHR-P group was largely nested within healthy variation and was not associated with the severity of positive psychotic symptoms or conversion to a psychotic disorder.Meaning: The findings suggest the macroscale neuromorphometric measures have limited utility as diagnostic biomarkers of psychosis risk
Downregulation of MIP-1α/CCL3 with praziquantel treatment in Schistosoma haematobium and HIV-1 co-infected individuals in a rural community in Zimbabwe
The results of our study show that the MIP-1alpha/CCL3 levels were positively associated with S. haematobium egg counts at baseline but not with HIV-1 infection status. MIP-1alpha/CCL3 levels were significantly reduced at three months post treatment with praziquantel. We therefore conclude that MIP-1alpha/CCL3 is produced during infection with S haematobium. S. haematobium infection is associated with increased MIP-1alpha/CCL3 levels in an egg intensity-dependent manner and treatment of S. haematobium is associated with a reduction in MIP-1alpha/CCL3
Stromal Down-Regulation of Macrophage CD4/CCR5 Expression and NF-κB Activation Mediates HIV-1 Non-Permissiveness in Intestinal Macrophages
Tissue macrophages are derived exclusively from blood monocytes, which as monocyte-derived macrophages support HIV-1 replication. However, among human tissue macrophages only intestinal macrophages are non-permissive to HIV-1, suggesting that the unique microenvironment in human intestinal mucosa renders lamina propria macrophages non-permissive to HIV-1. We investigated this hypothesis using blood monocytes and intestinal extracellular matrix (stroma)-conditioned media (S-CM) to model the exposure of newly recruited monocytes and resident macrophages to lamina propria stroma, where the cells take up residence in the intestinal mucosa. Exposure of monocytes to S-CM blocked up-regulation of CD4 and CCR5 expression during monocyte differentiation into macrophages and inhibited productive HIV-1 infection in differentiated macrophages. Importantly, exposure of monocyte-derived macrophages simultaneously to S-CM and HIV-1 also inhibited viral replication, and sorted CD4+ intestinal macrophages, a proportion of which expressed CCR5+, did not support HIV-1 replication, indicating that the non-permissiveness to HIV-1 was not due to reduced receptor expression alone. Consistent with this conclusion, S-CM also potently inhibited replication of HIV-1 pseudotyped with vesicular stomatitis virus glycoprotein, which provides CD4/CCR5-independent entry. Neutralization of TGF-β in S-CM and recombinant TGF-β studies showed that stromal TGF-β inhibited macrophage nuclear translocation of NF-κB and HIV-1 replication. Thus, the profound inability of intestinal macrophages to support productive HIV-1 infection is likely the consequence of microenvironmental down-regulation of macrophage HIV-1 receptor/coreceptor expression and NF-κB activation
Characterization of 4-HNE Modified L-FABP Reveals Alterations in Structural and Functional Dynamics
4-Hydroxynonenal (4-HNE) is a reactive α,β-unsaturated aldehyde produced during oxidative stress and subsequent lipid peroxidation of polyunsaturated fatty acids. The reactivity of 4-HNE towards DNA and nucleophilic amino acids has been well established. In this report, using proteomic approaches, liver fatty acid-binding protein (L-FABP) is identified as a target for modification by 4-HNE. This lipid binding protein mediates the uptake and trafficking of hydrophobic ligands throughout cellular compartments. Ethanol caused a significant decrease in L-FABP protein (P<0.001) and mRNA (P<0.05), as well as increased poly-ubiquitinated L-FABP (P<0.001). Sites of 4-HNE adduction on mouse recombinant L-FABP were mapped using MALDI-TOF/TOF mass spectrometry on apo (Lys57 and Cys69) and holo (Lys6, Lys31, His43, Lys46, Lys57 and Cys69) L-FABP. The impact of 4-HNE adduction was found to occur in a concentration-dependent manner; affinity for the fluorescent ligand, anilinonaphthalene-8-sulfonic acid, was reduced from 0.347 µM to Kd1 = 0.395 µM and Kd2 = 34.20 µM. Saturation analyses revealed that capacity for ligand is reduced by approximately 50% when adducted by 4-HNE. Thermal stability curves of apo L-FABP was also found to be significantly affected by 4-HNE adduction (ΔTm = 5.44°C, P<0.01). Computational-based molecular modeling simulations of adducted protein revealed minor conformational changes in global protein structure of apo and holo L-FABP while more apparent differences were observed within the internal binding pocket, revealing reduced area and structural integrity. New solvent accessible portals on the periphery of the protein were observed following 4-HNE modification in both the apo and holo state, suggesting an adaptive response to carbonylation. The results from this study detail the dynamic process associated with L-FABP modification by 4-HNE and provide insight as to how alterations in structural integrity and ligand binding may a contributing factor in the pathogenesis of ALD
Evolvable Neuronal Paths: A Novel Basis for Information and Search in the Brain
We propose a previously unrecognized kind of informational entity in the brain that is capable of acting as the basis for unlimited hereditary variation in neuronal networks. This unit is a path of activity through a network of neurons, analogous to a path taken through a hidden Markov model. To prove in principle the capabilities of this new kind of informational substrate, we show how a population of paths can be used as the hereditary material for a neuronally implemented genetic algorithm, (the swiss-army knife of black-box optimization techniques) which we have proposed elsewhere could operate at somatic timescales in the brain. We compare this to the same genetic algorithm that uses a standard ‘genetic’ informational substrate, i.e. non-overlapping discrete genotypes, on a range of optimization problems. A path evolution algorithm (PEA) is defined as any algorithm that implements natural selection of paths in a network substrate. A PEA is a previously unrecognized type of natural selection that is well suited for implementation by biological neuronal networks with structural plasticity. The important similarities and differences between a standard genetic algorithm and a PEA are considered. Whilst most experiments are conducted on an abstract network model, at the conclusion of the paper a slightly more realistic neuronal implementation of a PEA is outlined based on Izhikevich spiking neurons. Finally, experimental predictions are made for the identification of such informational paths in the brain
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