Design, synthesis, molecular modelling and in vitro screening of monoamine oxidase inhibitory activities of novel quinazolyl hydrazine derivatives

Funding: Deanship of Scientific Research at Taibah University, Al-Madinah Al-Munawarah, Saudi Arabia (project # 7101).A new series of N'-substituted benzylidene-2-(4-oxo-2-phenyl-1,4-dihydroquinazolin-3(2H)-yl)acetohydrazide (5a-5h) has been synthesized, characterized by FT-IR, NMR spectroscopy and mass spectrometry and tested against human monoamine oxidase (MAO) A and B. Only (3-methoxy-4-hydroxy)benzoyl substituted compounds gave submicromolar inhibition of MAO-A and MAO-B. Changing the phenyl substituent to methyl on the unsaturated quinazoline ring (12a-12d) decreased inhibition but a less flexible linker (14a-14d) resulted in selective micromolar inhibition of hMAO B providing insight for ongoing design.Publisher PDFPeer reviewe

Advanced Fluorescence Microscopy Techniques-FRAP, FLIP, FLAP, FRET and FLIM

Fluorescence microscopy provides an efficient and unique approach to study fixed and living cells because of its versatility, specificity, and high sensitivity. Fluorescence microscopes can both detect the fluorescence emitted from labeled molecules in biological samples as images or photometric data from which intensities and emission spectra can be deduced. By exploiting the characteristics of fluorescence, various techniques have been developed that enable the visualization and analysis of complex dynamic events in cells, organelles, and sub-organelle components within the biological specimen. The techniques described here are fluorescence recovery after photobleaching (FRAP), the related fluorescence loss in photobleaching (FLIP), fluorescence localization after photobleaching (FLAP), Forster or fluorescence resonance energy transfer (FRET) and the different ways how to measure FRET, such as acceptor bleaching, sensitized emission, polarization anisotropy, and fluorescence lifetime imaging microscopy (FLIM). First, a brief introduction into the mechanisms underlying fluorescence as a physical phenomenon and fluorescence, confocal, and multiphoton microscopy is given. Subsequently, these advanced microscopy techniques are introduced in more detail, with a description of how these techniques are performed, what needs to be considered, and what practical advantages they can bring to cell biological research

Stochastic climate theory and modeling

Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations (SSPs) as well as for model error representation, uncertainty quantification, data assimilation, and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large-scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochastic components and non-Markovian (memory) terms. Stochastic approaches in numerical weather and climate prediction models also lead to the reduction of model biases. Hence, there is a clear need for systematic stochastic approaches in weather and climate modeling. In this review, we present evidence for stochastic effects in laboratory experiments. Then we provide an overview of stochastic climate theory from an applied mathematics perspective. We also survey the current use of stochastic methods in comprehensive weather and climate prediction models and show that stochastic parameterizations have the potential to remedy many of the current biases in these comprehensive models

Antenatal allopurinol for reduction of birth asphyxia induced brain damage (ALLO-Trial); a randomized double blind placebo controlled multicenter study

<p>Abstract</p> <p>Background</p> <p>Hypoxic-ischaemic encephalopathy is associated with development of cerebral palsy and cognitive disability later in life and is therefore one of the fundamental problems in perinatal medicine. The xanthine-oxidase inhibitor allopurinol reduces the formation of free radicals, thereby limiting the amount of hypoxia-reperfusion damage. In case of suspected intra-uterine hypoxia, both animal and human studies suggest that maternal administration of allopurinol immediately prior to delivery reduces hypoxic-ischaemic encephalopathy.</p> <p>Methods/Design</p> <p>The proposed trial is a randomized double blind placebo controlled multicenter study in pregnant women at term in whom the foetus is suspected of intra-uterine hypoxia.</p> <p>Allopurinol 500 mg IV or placebo will be administered antenatally to the pregnant woman when foetal hypoxia is suspected. Foetal distress is being diagnosed by the clinician as an abnormal or non-reassuring foetal heart rate trace, preferably accompanied by either significant ST-wave abnormalities (as detected by the STAN-monitor) or an abnormal foetal blood scalp sampling (pH < 7.20).</p> <p>Primary outcome measures are the amount of S100B (a marker for brain tissue damage) and the severity of oxidative stress (measured by isoprostane, neuroprostane, non protein bound iron and hypoxanthine), both measured in umbilical cord blood. Secondary outcome measures are neonatal mortality, serious composite neonatal morbidity and long-term neurological outcome. Furthermore pharmacokinetics and pharmacodynamics will be investigated.</p> <p>We expect an inclusion of 220 patients (110 per group) to be feasible in an inclusion period of two years. Given a suspected mean value of S100B of 1.05 ug/L (SD 0.37 ug/L) in the placebo group this trial has a power of 90% (alpha 0.05) to detect a mean value of S100B of 0.89 ug/L (SD 0.37 ug/L) in the 'allopurinol-treated' group (z-test_2-sided). Analysis will be by intention to treat and it allows for one interim analysis.</p> <p>Discussion</p> <p>In this trial we aim to answer the question whether antenatal allopurinol administration reduces hypoxic-ischaemic encephalopathy in neonates exposed to foetal hypoxia.</p> <p>Trial registration number</p> <p>Clinical Trials, protocol registration system: NCT00189007</p

Predicting climate change using response theory: global averages and spatial patterns

The provision of accurate methods for predicting the climate response to anthropogenic and natural forcings is a key contemporary scientific challenge. Using a simplified and efficient open-source general circulation model of the atmosphere featuring O(105105) degrees of freedom, we show how it is possible to approach such a problem using nonequilibrium statistical mechanics. Response theory allows one to practically compute the time-dependent measure supported on the pullback attractor of the climate system, whose dynamics is non-autonomous as a result of time-dependent forcings. We propose a simple yet efficient method for predicting—at any lead time and in an ensemble sense—the change in climate properties resulting from increase in the concentration of CO22 using test perturbation model runs. We assess strengths and limitations of the response theory in predicting the changes in the globally averaged values of surface temperature and of the yearly total precipitation, as well as in their spatial patterns. The quality of the predictions obtained for the surface temperature fields is rather good, while in the case of precipitation a good skill is observed only for the global average. We also show how it is possible to define accurately concepts like the inertia of the climate system or to predict when climate change is detectable given a scenario of forcing. Our analysis can be extended for dealing with more complex portfolios of forcings and can be adapted to treat, in principle, any climate observable. Our conclusion is that climate change is indeed a problem that can be effectively seen through a statistical mechanical lens, and that there is great potential for optimizing the current coordinated modelling exercises run for the preparation of the subsequent reports of the Intergovernmental Panel for Climate Change

Structural Elements Regulating Amyloidogenesis: A Cholinesterase Model System

Polymerization into amyloid fibrils is a crucial step in the pathogenesis of neurodegenerative syndromes. Amyloid assembly is governed by properties of the sequence backbone and specific side-chain interactions, since fibrils from unrelated sequences possess similar structures and morphologies. Therefore, characterization of the structural determinants driving amyloid aggregation is of fundamental importance. We investigated the forces involved in the amyloid assembly of a model peptide derived from the oligomerization domain of acetylcholinesterase (AChE), AChE586-599, through the effect of single point mutations on β-sheet propensity, conformation, fibrilization, surfactant activity, oligomerization and fibril morphology. AChE586-599 was chosen due to its fibrilization tractability and AChE involvement in Alzheimer's disease. The results revealed how specific regions and residues can control AChE586-599 assembly. Hydrophobic and/or aromatic residues were crucial for maintaining a high β-strand propensity, for the conformational transition to β-sheet, and for the first stage of aggregation. We also demonstrated that positively charged side-chains might be involved in electrostatic interactions, which could control the transition to β-sheet, the oligomerization and assembly stability. Further interactions were also found to participate in the assembly. We showed that some residues were important for AChE586-599 surfactant activity and that amyloid assembly might preferentially occur at an air-water interface. Consistently with the experimental observations and assembly models for other amyloid systems, we propose a model for AChE586-599 assembly in which a steric-zipper formed through specific interactions (hydrophobic, electrostatic, cation-π, SH-aromatic, metal chelation and polar-polar) would maintain the β-sheets together. We also propose that the stacking between the strands in the β-sheets along the fiber axis could be stabilized through π-π interactions and metal chelation. The dissection of the specific molecular recognition driving AChE586-599 amyloid assembly has provided further knowledge on such poorly understood and complicated process, which could be applied to protein folding and the targeting of amyloid diseases

Translating upwards: linking the neural and social sciences via neuroeconomics

The social and neural sciences share a common interest in understanding the mechanisms that underlie human behaviour. However, interactions between neuroscience and social science disciplines remain strikingly narrow and tenuous. We illustrate the scope and challenges for such interactions using the paradigmatic example of neuroeconomics. Using quantitative analyses of both its scientific literature and the social networks in its intellectual community, we show that neuroeconomics now reflects a true disciplinary integration, such that research topics and scientific communities with interdisciplinary span exert greater influence on the field. However, our analyses also reveal key structural and intellectual challenges in balancing the goals of neuroscience with those of the social sciences. To address these challenges, we offer a set of prescriptive recommendations for directing future research in neuroeconomics