Effects of lipopolysaccharide on blood-brain barrier permeability during pentylenetetrazole-induced epileptic seizures in rats

We investigated the effects of lipopolysachharide (LPS) on functional and structural properties of the blood-brain barrier (BBB) during pentylenetetrazole (PTZ)-induced epileptic seizures in rats. Arterial blood pressure was significantly elevated during epileptic seizures irrespective of LPS pretreatment. Plasma levels of interleukin (IL)-1, interleukin (IL)-6, nitric oxide (NO) and malondialdehyde (MDA) increased while catalase concentrations decreased in animals treated with LPS, PTZ and LPS plus PTZ. The significantly increased BBB permeability to Evans blue (EB) dye in the cerebral cortex, diencephalon and cerebellum regions of rats by PTZ-induced seizures was markedly reduced upon LPS pretreatment. Immunoreactivity for tight junction proteins, zonula occludens-1 and occludin, did not change in brain vessels of animals treated with PTZ and LPS plus PTZ. Glial fibrillary acidic protein immunoreactivity was increased in LPS, but not in PTZ and LPS plus PTZ. These results indicate that LPS pretreatment reduces the passage of EB dye bound to albumin into the brain, at least partly, by increasing plasma NO and IL-6 levels during PTZ-induced epileptic seizures. We suggest that LPS may provide protective effects on the BBB integrity during epileptic seizures through transcellular pathway, since the paracellular route remained unaffected by LPS and LPS plus PTZ.     

Free radical scavenging activity,total phenolic content,total antioxidant status,and total oxidant status of endemic Thermopsis turcica

Thermopsis turcica, endemic to Turkey, is in danger of extinction. Studies on this species are very few due to the fact that it was only discovered in 1983 and grows in a small circumscribed area in Turkey. In this study, free radical scavenging activity, total phenolic content, total oxidant status (TOS), and total antioxidant status (TAS) of methanol (TTM) and acetone (TTA) extracts of T. turcica were measured spectroscopically. Free radical scavenging activity was determined according to the elimination of DPPH radicals and total phenol content was determined by the Folin–Ciocalteu reaction. Total oxidant status (TOS) and total antioxidant status (TAS) were measured with commercially available kits. Methanol and acetone extracts of T. turcica were found to have a specific radical scavenging effect. This effect was found to be related to the total phenolic content of the extracts. Since the TTA had a higher phenolic content than the methanol extract, it had a stronger radical scavenging effect. In addition, the total antioxidant capacity of the methanol extract was observed to be higher than that of its acetone counterpart. As a result, due to its antioxidative properties, T. turcica is thought to be a natural source of antioxidants.     

Metabolic alteration of <Emphasis Type="Italic">Catharanthus roseus</Emphasis> cell suspension cultures overexpressing <Emphasis Type="Italic">geraniol synthase</Emphasis> in the plastids or cytosol

Previous studies showed that geraniol could be an upstream limiting factor in the monoterpenoid pathway towards the production of terpenoid indole alkaloid (TIA) in Catharanthus roseus cells and hairy root cultures. This shortage in precursor availability could be due to (1) limited expression of the plastidial geraniol synthase resulted in a low activity of the enzyme to catalyze the conversion of geranyl diphosphate to geraniol; or (2) the limitation of geraniol transport from plastids to cytosol. Therefore, in this study, C. roseus’s geraniol synthase (CrGES) gene was overexpressed in either plastids or cytosol of a non-TIA producing C. roseus cell line. The expression of CrGES in the plastids or cytosol was confirmed and the constitutive transformation lines were successfully established. A targeted metabolite analysis using HPLC shows that the transformed cell lines did not produce TIA or iridoid precursors unless elicited with jasmonic acid, as their parent cell line. This indicates a requirement for expression of additional, inducible pathway genes to reach production of TIA in this cell line. Interestingly, further analysis using NMR-based metabolomics reveals that the overexpression of CrGES impacts primary metabolism differently if expressed in the plastids or cytosol. The levels of valine, leucine, and some metabolites derived from the shikimate pathway, i.e. phenylalanine and tyrosine were significantly higher in the plastidial- but lower in the cytosolic-CrGES overexpressing cell lines. This result shows that overexpression of CrGES in the plastids or cytosol caused alteration of primary metabolism that associated to the plant cell growth and development. A comprehensive omics analysis is necessary to reveal the full effect of metabolic engineering.     

Phototherapy increases DNA damage in lymphocytes of hyperbilirubinemic neonates

Phototherapy is commonly used in the treatment of hyperbilirubinemia in newborns. No serious side effects related to phototherapy have been observed, but concerns regarding its potential to damage DNA have been expressed, based on animal or cell-culture studies. The aim of this study was to investigate, in neonates with hyperbilirubinemia, the possible relation between phototherapy and DNA damage. The study included 33 full-term newborns with non-physiological jaundice and 14 healthy newborns with physiological jaundice as controls. Phototherapy was performed with an array of six fluorescent lamps producing radiation with wavelengths of 480-520 nm at 12 microW/cm(2)/nm. DNA damage in lymphocytes was determined by use of the alkaline comet assay. The DNA damage increased significantly with the duration of phototherapy, as shown by measurements at 24, 48, and 72 h (P<0.001). These findings indicate that phototherapy, widely used in neonatology units, increases DNA damage in newborns. It remains to be seen whether the genotoxic effect observed in the present study can cause any long-term health effect in phototherapy-treated infants in later life.     

Synthesis,Molecular Modeling,and Biological Evaluation of Novel Chiral Thiosemicarbazone Derivatives as Potent Anticancer Agents

A series of new chiral thiosemicarbazones derived from homochiral amines in both enantiomeric forms were synthesized and evaluated for their in vitro antiproliferative activity against A549 (human alveolar adenocarcinoma), MCF‐7 (human breast adenocarcinoma), HeLa (human cervical adenocarcinoma), and HGC‐27 (human stomach carcinoma) cell lines. Some of compounds showed inhibitory activities on the growth of cancer cell lines. Especially, compound 17b exhibited the most potent activity (IC₅₀ 4.6 μM) against HGC‐27 as compared with the reference compound, sindaxel (IC₅₀ 10.3 μM), and could be used as a lead compound to search new chiral thiosemicarbazone derivatives as antiproliferative agents. Chirality 27:177–188, 2015. © 2014 Wiley Periodicals, Inc.     

IMMOBILIZATION OF BOVINE CATALASE ONTO MAGNETIC NANOPARTICLES

The scope of this study is to achieve carrier-bound immobilization of catalase onto magnetic particles (Fe₃O₄ and Fe₂O₃NiO₂ · H₂O) to specify the optimum conditions of immobilization. Removal of H₂O₂ and the properties of immobilized sets were also investigated. To that end, adsorption and then cross-linking methods onto magnetic particles were performed. The optimum immobilization conditions were found for catalase: immobilization time (15 min for Fe₃O₄; 10 min for Fe₂O₃NiO₂ · H₂O), the initial enzyme concentration (1 mg/mL), amount of magnetic particles (25 mg), and glutaraldehyde concentration (3%). The activity reaction conditions (optimum temperature, optimum pH, pH stability, thermal stability, operational stability, and reusability) were characterized. Also kinetic parameters were calculated by Lineweaver–Burk plots. The optimum pH values were found to be 7.0, 7.0, and 8.0 for free enzyme, Fe₃O₄-immobilized catalases, and Fe₂O₃NiO₂ · H₂O-immobilized catalases, respectively. All immobilized catalase systems displayed the optimum temperature between 25 and 35°C. Reusability studies showed that Fe₃O₄-immobilized catalase can be used 11 times with 50% loss in original activity, while Fe₂O₃NiO₂ · H₂O-immobilized catalase lost 67% of activity after the same number of uses. Furthermore, immobilized catalase systems exhibited improved thermal and pH stability. The results transparently indicate that it is possible to have binding between enzyme and magnetic nanoparticles.     

Reverse engineering: the architecture of biological networks

We adopt a control theory approach to reverse engineer the complexity of a known system--the bacterial heat shock response. Using a computational dynamic model, we explore the organization of the heat shock system and elucidate its various regulation strategies. We show that these strategies are behind much of the complexity of the network. We propose that complexity is a necessary outcome of robustness and performance requirements that are achieved by the heat shock system's exquisite regulation modules. The techniques we use rely on dynamic computational models and principles from the field of control theory.     

DeepCME: A deep learning framework for computing solution statistics of the chemical master equation

Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogorov’s forward equation is called the chemical master equation (CME), and it is a fundamental system of linear ordinary differential equations (ODEs) that describes the evolution of the probability distribution of the random state-vector representing the copy-numbers of all the reacting species. The size of this system is given by the number of states that are accessible by the chemical system, and for most examples of interest this number is either very large or infinite. Moreover, approximations that reduce the size of the system by retaining only a finite number of important chemical states (e.g. those with non-negligible probability) result in high-dimensional ODE systems, even when the number of reacting species is small. Consequently, accurate numerical solution of the CME is very challenging, despite the linear nature of the underlying ODEs. One often resorts to estimating the solutions via computationally intensive stochastic simulations. The goal of the present paper is to develop a novel deep-learning approach for computing solution statistics of high-dimensional CMEs by reformulating the stochastic dynamics using Kolmogorov’s backward equation. The proposed method leverages superior approximation properties of Deep Neural Networks (DNNs) to reliably estimate expectations under the CME solution for several user-defined functions of the state-vector. This method is algorithmically based on reinforcement learning and it only requires a moderate number of stochastic simulations (in comparison to typical simulation-based approaches) to train the “policy function”. This allows not just the numerical approximation of various expectations for the CME solution but also of its sensitivities with respect to all the reaction network parameters (e.g. rate constants). We provide four examples to illustrate our methodology and provide several directions for future research.