Retinal Dystrophy Due to Paternal Isodisomy for Chromosome 1 or Chromosome 2, with Homoallelism for Mutations in RPE65 or MERTK, Respectively

Uniparental disomy (UPD) is a rare condition in which a diploid offspring carries a chromosomal pair from a single parent. We now report the first two cases of UPD resulting in retinal degeneration. We identified an apparently homozygous loss-of-function mutation of RPE65 (1p31) in one retinal dystrophy patient and an apparently homozygous loss-of-function mutation of MERTK (2q14.1) in a second retinal dystrophy patient. In both families, the gene defect was present in the patient's heterozygous father but not in the patient's mother. Analysis of haplotypes in each nuclear kindred, by use of DNA polymorphisms distributed along both chromosomal arms, indicated the absence of the maternal allele for all informative markers tested on chromosome 1 in the first patient and on chromosome 2 in the second patient. Our results suggest that retinal degeneration in these individuals is due to apparently complete paternal isodisomy involving reduction to homoallelism for RPE65 or MERTK loss-of-function alleles. Our findings provide evidence for the first time, in the case of chromosome 2, and confirm previous observations, in the case of chromosome 1, that there are no paternally imprinted genes on chromosomes 1 and 2 that have a major effect on phenotype.     

Alternating Magnetic Field Induced Membrane Permeability in Erythromycin Magneto-Liposomes A Potential Solution to Antibiotic Resistance

Biophysics - Antibiotic resistance is a serious problem facing the world; it is increasing every year due to over or misuse of antibiotics that led to developing new mechanisms of drug resistance...     

Antiviral Activity of a Small Molecule Deubiquitinase Inhibitor Occurs via Induction of the Unfolded Protein Response

Ubiquitin (Ub) is a vital regulatory component in various cellular processes, including cellular responses to viral infection. As obligate intracellular pathogens, viruses have the capacity to manipulate the ubiquitin (Ub) cycle to their advantage by encoding Ub-modifying proteins including deubiquitinases (DUBs). However, how cellular DUBs modulate specific viral infections, such as norovirus, is poorly understood. To examine the role of DUBs during norovirus infection, we used WP1130, a small molecule inhibitor of a subset of cellular DUBs. Replication of murine norovirus in murine macrophages and the human norovirus Norwalk virus in a replicon system were significantly inhibited by WP1130. Chemical proteomics identified the cellular DUB USP14 as a target of WP1130 in murine macrophages, and pharmacologic inhibition or siRNA-mediated knockdown of USP14 inhibited murine norovirus infection. USP14 is a proteasome-associated DUB that also binds to inositol-requiring enzyme 1 (IRE1), a critical mediator of the unfolded protein response (UPR). WP1130 treatment of murine macrophages did not alter proteasome activity but activated the X-box binding protein-1 (XBP-1) through an IRE1-dependent mechanism. In addition, WP1130 treatment or induction of the UPR also reduced infection of other RNA viruses including encephalomyocarditis virus, Sindbis virus, and La Crosse virus but not vesicular stomatitis virus. Pharmacologic inhibition of the IRE1 endonuclease activity partially rescued the antiviral effect of WP1130. Taken together, our studies support a model whereby induction of the UPR through cellular DUB inhibition blocks specific viral infections, and suggest that cellular DUBs and the UPR represent novel targets for future development of broad spectrum antiviral therapies.     

Novel insights into the interaction between long non-coding RNAs and microRNAs in glioma

Molecular and Cellular Biochemistry - Glioma is the most common brain tumor of the central nervous system. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been identified to play a vital...     

An Evidence-Based Combining Classifier for Brain Signal Analysis

Nowadays, brain signals are employed in various scientific and practical fields such as Medical Science, Cognitive Science, Neuroscience, and Brain Computer Interfaces. Hence, the need for robust signal analysis methods with adequate accuracy and generalizability is inevitable. The brain signal analysis is faced with complex challenges including small sample size, high dimensionality and noisy signals. Moreover, because of the non-stationarity of brain signals and the impacts of mental states on brain function, the brain signals are associated with an inherent uncertainty. In this paper, an evidence-based combining classifiers method is proposed for brain signal analysis. This method exploits the power of combining classifiers for solving complex problems and the ability of evidence theory to model as well as to reduce the existing uncertainty. The proposed method models the uncertainty in the labels of training samples in each feature space by assigning soft and crisp labels to them. Then, some classifiers are employed to approximate the belief function corresponding to each feature space. By combining the evidence raised from each classifier through the evidence theory, more confident decisions about testing samples can be made. The obtained results by the proposed method compared to some other evidence-based and fixed rule combining methods on artificial and real datasets exhibit the ability of the proposed method in dealing with complex and uncertain classification problems.     

Cultivation of newly isolated microalgae Coelastrum sp. in wastewater for simultaneous CO2 fixation,lipid production and wastewater treatment

Bioprocess and Biosystems Engineering - Cultivation of microalgae in wastewater is a promising and cost-effective approach for both CO2 biofixation and wastewater remediation. In this study, a new...     

Vibrio Trends in the Ecology of the Venice Lagoon

Vibrio is a very diverse genus that is responsible for different human and animal diseases. The accurate identification of Vibrio at the species level is important to assess the risks related to public health and diseases caused by aquatic organisms. The ecology of Vibrio spp., together with their genetic background, represents an important key for species discrimination and evolution. Thus, analyses of population structure and ecology association are necessary for reliable characterization of bacteria and to investigate whether bacterial species are going through adaptation processes. In this study, a population of Vibrionaceae was isolated from shellfish of the Venice lagoon and analyzed in depth to study its structure and distribution in the environment. A multilocus sequence analysis (MLSA) was developed on the basis of four housekeeping genes. Both molecular and biochemical approaches were used for species characterization, and the results were compared to assess the consistency of the two methods. In addition, strain ecology and the association between genetic information and environment were investigated through statistical models. The phylogenetic and population analyses achieved good species clustering, while biochemical identification was demonstrated to be imprecise. In addition, this study provided a fine-scale overview of the distribution of Vibrio spp. in the Venice lagoon, and the results highlighted a preferential association of the species toward specific ecological variables. These findings support the use of MLSA for taxonomic studies and demonstrate the need to consider environmental information to obtain broader and more accurate bacterial characterization.     

Three-Dimensional Numerical Model of Cell Morphology during Migration in Multi-Signaling Substrates

Cell Migration associated with cell shape changes are of central importance in many biological processes ranging from morphogenesis to metastatic cancer cells. Cell movement is a result of cyclic changes of cell morphology due to effective forces on cell body, leading to periodic fluctuations of the cell length and cell membrane area. It is well-known that the cell can be guided by different effective stimuli such as mechanotaxis, thermotaxis, chemotaxis and/or electrotaxis. Regulation of intracellular mechanics and cell’s physical interaction with its substrate rely on control of cell shape during cell migration. In this notion, it is essential to understand how each natural or external stimulus may affect the cell behavior. Therefore, a three-dimensional (3D) computational model is here developed to analyze a free mode of cell shape changes during migration in a multi-signaling micro-environment. This model is based on previous models that are presented by the same authors to study cell migration with a constant spherical cell shape in a multi-signaling substrates and mechanotaxis effect on cell morphology. Using the finite element discrete methodology, the cell is represented by a group of finite elements. The cell motion is modeled by equilibrium of effective forces on cell body such as traction, protrusion, electrostatic and drag forces, where the cell traction force is a function of the cell internal deformations. To study cell behavior in the presence of different stimuli, the model has been employed in different numerical cases. Our findings, which are qualitatively consistent with well-known related experimental observations, indicate that adding a new stimulus to the cell substrate pushes the cell to migrate more directionally in more elongated form towards the more effective stimuli. For instance, the presence of thermotaxis, chemotaxis and electrotaxis can further move the cell centroid towards the corresponding stimulus, respectively, diminishing the mechanotaxis effect. Besides, the stronger stimulus imposes a greater cell elongation and more cell membrane area. The present model not only provides new insights into cell morphology in a multi-signaling micro-environment but also enables us to investigate in more precise way the cell migration in the presence of different stimuli.