G-quadruplex formation of FXYD1 pre-mRNA indicates the possiblity of regulating expression of its protein product

G-quadruplexes are higher-order nucleic acid structures formed of square-planar arrangements of four guanine bases held together by Hoogsteen-type hydrogen bonds. Stacks of guanine tetrads are stabilised by intercalating potassium ions. FXYD1 encodes for phospholemman, a regulatory subunit of the cardiac Na+/K+-ATPase. Computational sequence analysis of FXYD1 pre-mRNA predicted the formation of stable intramolecular G-quadruplexes in human and orthologue sequences. Multiple sequence alignment indicated that G-rich sequences are conserved in evolution suggesting a potential role of G-quadruplexes in FXYD1 gene expression. The existence of a non-functional alternative splicing product indicated that the G-quadruplex formation may control alternative splicing. Quadruplex formation of human and bovine oligonucleotides was confirmed in vitro by native polyacrylamide gel electrophoresis and intrinsic fluorescence emission spectroscopy. Taking together the evolutionary conservation of G-quadruplex forming sequences with the confirmation of G-quadruplex formation in vitro by two FXYD1 homologues the results point to a potential role of these structures in regulating the expression of FXYD1 and thus regulate indirectly the activity of the cardiac Na+/K+ -ATPase.Peer reviewe

Radiative transfer of acoustic waves in continuous complex media: Beyond the Helmholtz equation

Heterogeneity can be accounted for by a random potential in the wave equation. For acoustic waves in a fluid with fluctuations of both density and compressibility (as well as for electromagnetic waves in a medium with fluctuation of both permittivity and permeability) the random potential entails a scalar and an operator contribution. For simplicity, the latter is usually overlooked in multiple scattering theory: whatever the type of waves, this simplification amounts to considering the Helmholtz equation with a sound speed $c$ depending on position $\mathbf{r}$. In this work, a radiative transfer equation is derived from the wave equation, in order to study energy transport through a multiple scattering medium. In particular, the influence of the operator term on various transport parameters is studied, based on the diagrammatic approach of multiple scattering. Analytical results are obtained for fundamental quantities of transport theory such as the transport mean-free path $\ell^*$, scattering phase function $f$ and anisotropy factor $g$. Discarding the operator term in the wave equation is shown to have a significant impact on $f$ and $g$, yet limited to the low-frequency regime i.e., when the correlation length of the disorder $\ell_c$ is smaller than or comparable to the wavelength $\lambda$. More surprisingly, discarding the operator part has a significant impact on the transport mean-free path $\ell^*$ whatever the frequency regime. When the scalar and operator terms have identical amplitudes, the discrepancy on the transport mean-free path is around $300\,\%$ in the low-frequency regime, and still above $30\,\%$ for $\ell_c/\lambda=10^3$ no matter how weak fluctuations of the disorder are. Analytical results are supported by numerical simulations of the wave equation and Monte Carlo simulations

Water Splitting Using Cobalt-Based Amidopyridine Complexes

As part of the ongoing search for clean energy sources, splitting water into oxygen and hydrogen has emerged as a promising source of alternative energy. We are interested in developing electrocatalysts capable of performing water reduction and water oxidation. In this dissertation, a variety of catalytic platforms based on an amidopyridine framework are studied. A novel monomeric cobalt complex in an amidopyridine ligand environment, ([CoIII(L1)(pyrr)2]PF6), was investigated for electrocatalytic water reduction and found to have an onset overpotential of 0.54 V and an observed TOF of 23 min-1. The catalytic decomposition pathway was explored with the aim of designing more stable catalysts. Following the initial design, we prepared a modified catalyst in which the amidopyridine framework is extended over a phenylene tetraamine bridge to yield [(CoIII)2L2(pyrr)4](PF6)2. The bimetallic cobalt complex showed significant improvement in catalytic activity: onset overpotential decreased to 0.45 V and the TOF was found to be 60 min-1 per cobalt center under identical catalytic conditions. To the best of our knowledge this is one of the first examples where a dimeric catalyst is more active than its monomeric counterpart. Moreover, we showed that the dimer operates using a voltage-dependent mechanism, in which side reactions associated with deactivation are avoided at low applied potentials. Finally, we demonstrate that we can drive water oxidation by modification of conductive carbon black-based supports with the hydrophobic octadecyloxy substituted catalyst in an N2N2’ environment, [CoIII(LOC18H37)(pyrr)2]ClO4. The prepared assemblies can catalyze water oxidation at an onset overpotential of 0.32 V, and reach a current density of 10 mA/cm2 at an overpotential of 0.37 V. The molecular nature of the catalyst was ascertained using XPS analysis. A DFT-supported mechanism suggests the ligand is heavily involved in catalysis as an electron reservoir. The work presented in this dissertation emphasizes the importance of taking into account ligand involvement while designing novel catalysts. In the case of water reduction, we showed that ligand involvement had deleterious effects on catalysis, however for water oxidation we showed that ligand involvement can lower the activation barrier needed for catalysis. Future work will focus on using these lessons to design more active catalysts

Learning probabilistic interaction models

We live in a multi-modal world; therefore it comes as no surprise that the human brain is tailored for the integration of multi-sensory input. Inspired by the human brain, the multi-sensory data is used in Artificial Intelligence (AI) for teaching different concepts to computers. Autonomous Agents (AAs) are AI systems that sense and act autonomously in complex dynamic environments. Such agents can build up Self-Awareness (SA) by describing their experiences through multi-sensorial information with appropriate models and correlating them incrementally with the currently perceived situation to continuously expand their knowledge. This thesis proposes methods to learn such awareness models for AAs. These models include SA and situational awareness models in order to perceive and understand itself (self variables) and its surrounding environment (external variables) at the same time. An agent is considered self-aware when it can dynamically observe and understand itself and its surrounding through different proprioceptive and exteroceptive sensors which facilitate learning and maintaining a contextual representation by processing the observed multi-sensorial data. We proposed a probabilistic framework for generative and descriptive dynamic models that can lead to a computationally efficient SA system. In general, generative models facilitate the prediction of future states while descriptive models enable to select the representation that best fits the current observation. The proposed framework employs a Probabilistic Graphical Models (PGMs) such as Dynamic Bayesian Networks (DBNs) that represent a set of variables and their conditional dependencies. Once we obtain this probabilistic representation, the latter allows the agent to model interactions between itself, as observed through proprioceptive sensors, and the environment, as observed through exteroceptive sensors. In order to develop an awareness system, not only an agent needs to recognize the normal states and perform predictions accordingly, but also it is necessary to detect the abnormal states with respect to its previously learned knowledge. Therefore, there is a need to measure anomalies or irregularities in an observed situation. In this case, the agent should be aware that an abnormality (i.e., a non-stationary condition) never experienced before, is currently present. Due to our specific way of representation, which makes it possible to model multi-sensorial data into a uniform interaction model, the proposed work not only improves predictions of future events but also can be potentially used to effectuate a transfer learning process where information related to the learned model can be moved and interpreted by another body

The Effect of Parental Participation on the Academic Achievement of Female English as a Second Language Middle School Students in the Persian Gulf

A quantitative correlational study explored the relationship between parental participation and academic achievement. Data were collected from 42 parents of female ESL students in the Persian Gulf region. Although results indicated a non-significant correlation between reported parental involvement and students’ academic averages overall, it found significant correlation for a sub-sample of Saudi parents.https://scholarworks.waldenu.edu/archivedposters/1034/thumbnail.jp

Cannabinoid signalling in TNF-alpha induced IL-8 release

Original article can be found at: http://www.sciencedirect.com/science/journal/00142999 Copyright Elsevier B.V. DOI : 10.1016/j.ejphar.2006.04.015Peer reviewe

Community Outreach and Engagement in a Time of Crisis: The Peer Research Consultants Program

The Peer Research Consultants (PRC) program at the University of Miami Libraries (UML), was formed in 2016 as part of the Learning Commons initiative to collocate and centralize academic services at Richter Library. Although the program had a virtual component in the form of chat and phone services when founded, it was primarily a physical setup where library student workers assisted researchers using a peer-to-peer system. In this paper, we highlight the historical trajectory of the peer research consultant (PRC) program in academic libraries using Richter Library as a case study. We argue that the onset of the COVID-19 pandemic in March 2020 provided an opportunity to redefine the program when it shifted entirely to a virtual modality. The shift to online services gave PRC’s the opportunity to collaborate in-depth with library faculty and staff to support new outreach programs and community initiatives. In this paper, we highlight several examples whereby PRC’s collaborative efforts resulted in research guides that offered links to families during lockdown, provided resources on racial justice initiatives, and combatted misinformation. In so doing, we conclude that the PRC program has strengthened the Libraries’ visibility and ties to the university community, incorporated emerging trends in diversity, equity and inclusion, and provided trustworthy information during a time of crisis. We then offer future directions where library programs such as the PRC, can be leveraged for campus and community engagement

An experimental investigation of adhesive wear extension in fretting interface: application of the contact oxygenation concept

This paper investigates the transition from abrasive to adhesive wear in gross-slip fretting assuming contact oxygenation concept which suggests that adhesion appears in the inner part of the interface if the di-oxygen partial pressure is below a threshold value. In the lateral sides, where di-oxygen molecules are sufficient, oxidation and abrasion prevail. To assess this phenomenon, 34NiCrMo16 flat-on-flat contacts are tested. Contact oxygenation is quantified using the ''oxygen-distance, '' parameter defined as the averaged width of the external abrasion corona. Confirming this concept, decreases with contact pressure and frequency but remains constant versus sliding amplitude, fretting cycles and contact area. evolution is formalized using a power law formulation which allowed predicting wear transitions for plain and macro-textured surfaces