Functional and molecular characterization of hyposensitive underactive bladder tissue and urine in streptozotocin-induced diabetic rat

Background: The functional and molecular alterations of nerve growth factor (NGF) and Prostaglandin E2 (PGE2) and its receptors were studied in bladder and urine in streptozotocin (STZ)-induced diabetic rats. Methodology/Principal Findings: Diabetes mellitus was induced with a single dose of 45 mg/kg STZ Intraperitoneally (i.p) in female Sprague-Dawley rats. Continuous cystometrogram were performed on control rats and STZ treated rats at week 4 or 12 under urethane anesthesia. Bladder was then harvested for histology, expression of EP receptors and NGF by western blotting, PGE2 levels by ELISA, and detection of apoptosis by TUNEL staining. In addition, 4-hr urine was collected from all groups for urine levels of PGE2, and NGF assay. DM induced progressive increase of bladder weight, urine production, intercontraction interval (ICI) and residual urine in a time dependent fashion. Upregulation of Prostaglandin E receptor (EP)1 and EP3 receptors and downregulation of NGF expression, increase in urine NGF and decrease levels of urine PGE2 at week 12 was observed. The decrease in ICI by intravesical instillation of PGE2 was by 51% in control rats and 31.4% in DM group at week 12. Conclusions/Significance: DM induced hyposensitive underactive bladder which is characterized by increased inflammatory reaction, apoptosis, urine NGF levels, upregulation of EP1 and EP3 receptors and decreased bladder NGF and urine PGE2. The data suggest that EP3 receptor are potential targets in the treatment of diabetes induced underactive bladder. © 2014 Nirmal et al

Fingerprint oxygen redox reactions in batteries through high-efficiency mapping of resonant inelastic X-ray scattering

Realizing reversible reduction-oxidation (redox) reactions of lattice oxygen in batteries is a promising way to improve the energy and power density. However, conventional oxygen absorption spectroscopy fails to distinguish the critical oxygen chemistry in oxide-based battery electrodes. Therefore, high-efficiency full-range mapping of resonant inelastic X-ray scattering (mRIXS) has been developed as a reliable probe of oxygen redox reactions. Here, based on mRIXS results collected from a series of Li Ni Co Mn O electrodes at different electrochemical states and its comparison with peroxides, we provide a comprehensive analysis of five components observed in the mRIXS results. While all the five components evolve upon electrochemical cycling, only two of them correspond to the critical states associated with oxygen redox reactions. One is a specific feature at 531.0 eV excitation and 523.7 eV emission energy, the other is a low-energy loss feature. We show that both features evolve with electrochemical cycling of Li Ni Co Mn O electrodes, and could be used for characterizing oxidized oxygen states in the lattice of battery electrodes. This work provides an important benchmark for a complete assignment of all mRIXS features collected from battery materials, which sets a general foundation for future studies in characterization, analysis, and theoretical calculation for probing and understanding oxygen redox reactions. 1.17 0.21 0.08 0.54 2 1.17 0.21 0.08 0.54

A motor imagery based brain-computer interface system via swarm-optimized fuzzy integral and its application

© 2016 IEEE. A brain-computer interface (BCI) system provides a convenient means of communication between the human brain and a computer, which is applied not only to healthy people but also for people that suffer from motor neuron diseases (MNDs). Motor imagery (MI) is one well-known basis for designing Electroencephalography (EEG)-based real-life BCI systems. However, EEG signals are often contaminated with severe noise and various uncertainties, imprecise and incomplete information streams. Therefore, this study proposes spectrum ensemble based on swam-optimized fuzzy integral for integrating decisions from sub-band classifiers that are established by a sub-band common spatial pattern (SBCSP) method. Firstly, the SBCSP effectively extracts features from EEG signals, and thereby the multiple linear discriminant analysis (MLDA) is employed during a MI classification task. Subsequently, particle swarm optimization (PSO) is used to regulate the subject-specific parameters for assigning optimal confidence levels for classifiers used in the fuzzy integral during the fuzzy fusion stage of the proposed system. Moreover, BCI systems usually tend to have complex architectures, be bulky in size, and require time-consuming processing. To overcome this drawback, a wireless and wearable EEG measurement system is investigated in this study. Finally, in our experimental result, the proposed system is found to produce significant improvement in terms of the receiver operating characteristic (ROC) curve. Furthermore, we demonstrate that a robotic arm can be reliably controlled using the proposed BCI system. This paper presents novel insights regarding the possibility of using the proposed MI-based BCI system in real-life applications

Blending using ODE swept surfaces with shape control and C1 continuity

Surface blending with tangential continuity is most widely applied in computer aided design, manufacturing systems, and geometric modeling. In this paper, we propose a new blending method to effectively control the shape of blending surfaces, which can also satisfy the blending constraints of tangent continuity exactly. This new blending method is based on the concept of swept surfaces controlled by a vector-valued fourth order ordinary differential equation (ODE). It creates blending surfaces by sweeping a generator along two trimlines and making the generator exactly satisfy the tangential constraints at the trimlines. The shape of blending surfaces is controlled by manipulating the generator with the solution to a vector-valued fourth order ODE. This new blending methods have the following advantages: 1). exact satisfaction of 1C continuous blending boundary constraints, 2). effective shape control of blending surfaces, 3). high computing efficiency due to explicit mathematical representation of blending surfaces, and 4). ability to blend multiple (more than two) primary surfaces

The Antioxidant Potential of the Mediterranean Diet in Patients at High Cardiovascular Risk: An In-Depth Review of the PREDIMED

Cardiovascular disease (CVD) is the leading global cause of death. Diet is known to be important in the prevention of CVD. The PREDIMED trial tested a relatively low-fat diet versus a high-fat Mediterranean diet (MedDiet) for the primary prevention of CVD. The resulting reduction of the CV composite outcome resulted in a paradigm shift in CV nutrition. Though many dietary factors likely contributed to this effect, this review focuses on the influence of the MedDiet on endogenous antioxidant systems and the effect of dietary polyphenols. Subgroup analysis of the PREDIMED trial revealed increased endogenous antioxidant and decreased pro-oxidant activity in the MedDiet groups. Moreover, higher polyphenol intake was associated with lower incidence of the primary outcome, overall mortality, blood pressure, inflammatory biomarkers, onset of new-onset type 2 diabetes mellitus (T2DM), and obesity. This suggests that polyphenols likely contributed to the lower incidence of the primary event in the MedDiet groups. In this article, we summarize the potential benefits of polyphenols found in the MedDiet, specifically the PREDIMED cohort. We also discuss the need for further research to confirm and expand the findings of the PREDIMED in a non-Mediterranean population and to determine the exact mechanisms of action of polyphenols

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON