Differential induction of 12-O-tetradecanoylphorbol 13-acetate sequence gene expression in murine melanocytes and melanoma cells

We previously showed that growth of the nontumorigenic, immortal murine melanocyte line Mel-ab correlates with the depletion of protein kinase C (PKC), whereas quiescence is associated with elevated levels of this enzyme (Brooks G, et al., Cancer Res 51: 3281–3288, 1991). Here we report responses that occur in these cells downstream of PKC activation or downregulation. We examined induction of 12-O-tetradecanoylphorbol-13-acetate (TPA)-inducible sequence (TIS) gene expression in Mel-ab melanocytes and in their transformed counterparts, B16 melanoma cells. Exposure of quiescent Mel-ab cells to the PKC-activating phorbol esters TPA or sapintoxin A at 81 nM for 2 h increased levels of mRNA for six of seven TIS genes examined (twofold to 80-fold increase in steady-state RNA levels for TIS 1, 7, 8, 11, 21, and 28 (c-fos); TIS 10 expression was not affected). No induction of 115 gene expression was observed either in growing Mel-ab cells maintained in 324 nM phorbol 12,13-dibutyrate or in B16 cells previously unexposed to phorbol esters, in which normal PKC levels were endogenously depressed. The cAMP-elevating agents choleratoxin (10 nM) and dibutyryl cyclic AMP (2.5 mM) increased levels of TIS mRNA (with the exception of TIS 10) in both proliferating Mel-ab and B16 cells, suggesting that downregulation of the PKC pathway is specific and not a consequence of a general inhibition of all signalling pathways.

Space partitioning for scalable K-means

K-Means is a popular clustering algorithm which adopts an iterative refinement procedure to determine data partitions and to compute their associated centres of mass, called centroids. The straightforward implementation of the algorithm is often referred to as `brute force' since it computes a proximity measure from each data point to each centroid at every iteration of the K-Means process. Efficient implementations of the K-Means algorithm have been predominantly based on multi-dimensional binary search trees (KD-Trees). A combination of an efficient data structure and geometrical constraints allow to reduce the number of distance computations required at each iteration. In this work we present a general space partitioning approach for improving the efficiency and the scalability of the K-Means algorithm. We propose to adopt approximate hierarchical clustering methods to generate binary space partitioning trees in contrast to KD-Trees. In the experimental analysis, we have tested the performance of the proposed Binary Space Partitioning K-Means (BSP-KM) when a divisive clustering algorithm is used. We have carried out extensive experimental tests to compare the proposed approach to the one based on KD-Trees (KD-KM) in a wide range of the parameters space. BSP-KM is more scalable than KDKM, while keeping the deterministic nature of the `brute force' algorithm. In particular, the proposed space partitioning approach has shown to overcome the well-known limitation of KD-Trees in high-dimensional spaces and can also be adopted to improve the efficiency of other algorithms in which KD-Trees have been used.

Caffeic acid, tyrosol and p-coumaric acid are potent inhibitors of 5-S-cysteinyl-dopamine induced neurotoxicity

Parkinson's disease is characterized by a progressive and selective loss of dopaminergic neurons in the substantia nigra. Recent investigations have shown that conjugates such as the 5-S-cysteinyl-dopamine, possess strong neurotoxicity and may contribute to the underlying progression of the disease pathology. Although the neuroprotective actions of flavonoids are well reported, that of hydroxycinnamates and other phenolic acids is less established. We show that the hydroxycinnamates caffeic acid and p-coumaric acid, the hydroxyphenethyl alcohol, tyrosol, and a Champagne wine extract rich in these components protect neurons against injury induced by 5-S-cysteinyl-dopamine in vitro. The protection induced by these polyphenols was equal to or greater than that observed for the flavonoids, (+)-catechin, (-)-epicatechin and quercetin. For example, p-coumaric acid evoked significantly more protection at 1muM (64.0+/-3.1%) than both (-)-epicatechin (46.0+/-4.1%, p<0.05) and (+)-catechin (13.1+/-3.0%, p<0.001) at the same concentration. These data indicate that hydroxycinnamates, phenolic acids and phenolic alcohol are also capable of inducing neuroprotective effects to a similar extent to that seen with flavonoids.

Trans fatty acids and weight gain

Increasing rates of obesity have stimulated research into possible contributing factors, including specific dietary components such as trans fatty acids (TFAs). This review considers the evidence for an association between TFA intake and weight gain. It concludes that there is limited but consistent evidence from epidemiological studies, and from a primate model, that increased TFA consumption may result in a small additional weight gain. Data from a long-term study in a primate model suggest that TFA may have a greater adipogenic effect than cis monounsaturated fatty acids; however, there are currently inadequate mechanistic data to provide a comprehensive and plausible explanation for any such metabolic differences between the types of fatty acids.

Enhancing model predictive control using dynamic data reconciliation

The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

Still water, hidden depths: the deposition of Bronze Age metalwork in the English Fenland

Finds of metalwork always raise the question of why they were deposited: a smith's collection, a concealed hoard or a votive offering? Findspots in water suggest offerings, since they would be awkward to retrieve. But understanding the context of deposition means knowing the prehistoric environment. The Fenland area of England has many Bronze Age sites, and deposits of metalwork and a well-mapped ancient environment too. Putting all three together the authors begin to assemble a grammar of deposition: swords and rapiers in rivers, some mixed collections placed in still water and others on once-dry land with burnt mounds.

A practical approach for training dynamic recurrent neural networks: use of Apriori information

Presents a technique for incorporating a priori knowledge from a state space system into a neural network training algorithm. The training algorithm considered is that of chemotaxis and the networks being trained are recurrent neural networks. Incorporation of the a priori knowledge ensures that the resultant network has behaviour similar to the system which it is modelling.

A study of the atmospherically relevant reaction between molecular chlorine and dimethylsulfide (DMS): establishing the reaction intermediate and measurement of absolute photoionization cross-sections

In a study using UV photoelectron spectroscopy (PES) of the atmospherically relevant reaction CH3SCH3 + Cl2 → CH3SCH2Cl + HCl bands associated with a reaction intermediate have been observed. These have been assigned to ionization of the covalently bound molecule (CH3)2SCl2 on the basis of the intensity of the observed bands as a function of reaction time, molecular orbital calculations of vertical ionization energies and evidence from infrared spectroscopy. A method has also been developed, with the flow-tube/PE spectrometer combination used, to measure photoionization cross-sections of the reagents and products at the photon energy utilized and this has allowed the photoionization cross-section of the intermediate to be estimated. This work augments an earlier study in which the rate constant of the reaction between CH3SCH3 (DMS) and Cl2 has been measured at room temperature.

Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere

Satellite measurements and numerical forecast model reanalysis data are used to compute an updated estimate of the cloud radiative effect on the global multi-annual mean radiative energy budget of the atmosphere and surface. The cloud radiative cooling effect through reflection of shortwave radiation dominates over the longwave heating effect, resulting in a net cooling of the climate system of –21 Wm-2. The shortwave radiative effect of cloud is primarily manifest as a reduction in the solar radiation absorbed at the surface of -53 Wm-2. Clouds impact longwave radiation by heating the moist tropical atmosphere (up to around 40 Wm-2 for global annual means) while enhancing the radiative cooling of the atmosphere over other regions, in particular higher latitudes and sub-tropical marine stratocumulus regimes. While clouds act to cool the climate system during the daytime, the cloud greenhouse effect heats the climate system at night. The influence of cloud radiative effect on determining cloud feedbacks and changes in the water cycle are discussed.

Quantitative plant proteomics

Quantitation is an inherent requirement in comparative proteomics and there is no exception to this for plant proteomics. Quantitative proteomics has high demands on the experimental workflow, requiring a thorough design and often a complex multi-step structure. It has to include sufficient numbers of biological and technical replicates and methods that are able to facilitate a quantitative signal read-out. Quantitative plant proteomics in particular poses many additional challenges but because of the nature of plants it also offers some potential advantages. In general, analysis of plants has been less prominent in proteomics. Low protein concentration, difficulties in protein extraction, genome multiploidy, high Rubisco abundance in green tissue, and an absence of well-annotated and completed genome sequences are some of the main challenges in plant proteomics. However, the latter is now changing with several genomes emerging for model plants and crops such as potato, tomato, soybean, rice, maize and barley. This review discusses the current status in quantitative plant proteomics (MS-based and non-MS-based) and its challenges and potentials. Both relative and absolute quantitation methods in plant proteomics from DIGE to MS-based analysis after isotope labeling and label-free quantitation are described and illustrated by published studies. In particular, we describe plant-specific quantitative methods such as metabolic labeling methods that can take full advantage of plant metabolism and culture practices, and discuss other potential advantages and challenges that may arise from the unique properties of plants.

A review of the evidence for the effects of total dietary fat, SFA, MUFA and n-6 PUFA on vascular function, endothelial progenitor cells and microparticles

Vascular dysfunction is recognised as an integrative marker of CVD. While dietary strategies aimed at reducing CVD risk include reductions in the intake of SFA, there are currently no clear guidelines on what should replace SFA. The purpose of this review was to assess the evidence for the effects of total dietary fat and individual fatty acids (SFA, MUFA and n-6 PUFA) on vascular function, cellular microparticles and endothelial progenitor cells. Medline was systematically searched from 1966 until November 2010. A total of fifty-nine peer-reviewed publications (covering fifty-six studies), which included five epidemiological, eighteen dietary intervention and thirty-three test meal studies, were identified. The findings from the epidemiological studies were inconclusive. The limited data available from dietary intervention studies suggested a beneficial effect of low-fat diets on vascular reactivity, which was strongest when the comparator diet was high in SFA, with a modest improvement in measures of vascular reactivity when high-fat, MUFA-rich diets were compared with SFA-rich diets. There was consistent evidence from the test meal studies that high-fat meals have a detrimental effect on postprandial vascular function. However, the evidence for the comparative effects of test meals rich in MUFA or n-6 PUFA with SFA on postprandial vascular function was limited and inconclusive. The lack of studies with comparable within-study dietary fatty acid targets, a variety of different study designs and different methods for determining vascular function all confound any clear conclusions on the impact of dietary fat and individual fatty acids on vascular function.