Metabolic alterations during the growth of tumour spheroids

Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

Metabolic alterations during the growth of tumour spheroids

Solid tumours undergo considerable alterations in their metabolism of nutrients in order to generate sufficient energy and biomass for sustained growth and proliferation. During growth, the tumour microenvironment exerts a number of influences (e.g. hypoxia and acidity) that affect cellular biology and the flux or utilisation of fuels including glucose. The tumour spheroid model was used to characterise the utilisation of glucose and describe alterations to the activity and expression of key glycolytic enzymes during the tissue growth curve. Glucose was avidly consumed and associated with the production of lactate and an acidified medium, confirming the reliance on glycolytic pathways and a diminution of oxidative phosphorylation. The expression levels and activities of hexokinase, phosphofructokinase-1, pyruvate kinase and lactate dehydrogenase in the glycolytic pathway were measured to assess glycolytic capacity. Similar measurements were made for glucose-6-phosphate dehydrogenase, the entry point and regulatory step of the pentose-phosphate pathway (PPP) and for cytosolic malate dehydrogenase, a key link to TCA cycle intermediates. The parameters for these key enzymes were shown to undergo considerable variation during the growth curve of tumour spheroids. In addition, they revealed that the dynamic alterations were influenced by both transcriptional and posttranslational mechanisms

Targeting cancer metabolism: a therapeutic window opens

Genetic events in cancer activate signalling pathways that alter cell metabolism. Clinical evidence has linked cell metabolism with cancer outcomes. Together, these observations have raised interest in targeting metabolic enzymes for cancer therapy, but they have also raised concerns that these therapies would have unacceptable effects on normal cells. However, some of the first cancer therapies that were developed target the specific metabolic needs of cancer cells and remain effective agents in the clinic today. Research into how changes in cell metabolism promote tumour growth has accelerated in recent years. This has refocused efforts to target metabolic dependencies of cancer cells as a selective anticancer strategy.Burroughs Wellcome FundSmith Family FoundationStarr Cancer ConsortiumDamon Runyon Cancer Research FoundationNational Institutes of Health (U.S.

Landslide susceptibility mapping using support vector machine and GIS at the Golestan province, Iran

The main goal of this study is to produce landslide susceptibility map using GIS-based support vector machine (SVM) at Kalaleh Township area of the Golestan province, Iran. In this paper, six different types of kernel classifiers such as linear, polynomial degree of 2, polynomial degree of 3, polynomial degree of 4, radial basis function (RBF) and sigmoid were used for landslide susceptibility mapping. At the first stage of the study, landslide locations were identified by aerial photographs and field surveys, and a total of 82 landslide locations were extracted from various sources. Of this, 75% of the landslides (61 landslide locations) are used as training dataset and the rest was used as (21 landslide locations) the validation dataset. Fourteen input data layers were employed as landslide conditioning factors in the landslide susceptibility modelling. These factors are slope degree, slope aspect, altitude, plan curvature, profile curvature, tangential curvature, surface area ratio (SAR), lithology, land use, distance from faults, distance from rivers, distance from roads, topographic wetness index (TWI) and stream power index (SPI). Using these conditioning factors, landslide susceptibility indices were calculated using support vector machine by employing six types of kernel function classifiers. Subsequently, the results were plotted in ArcGIS and six landslide susceptibility maps were produced. Then, using the success rate and the prediction rate methods, the validation process was performed by comparing the existing landslide data with the six landslide susceptibility maps. The validation results showed that success rates for six types of kernel models varied from 79% to 87%. Similarly, results of prediction rates showed that RBF (85%) and polynomial degree of 3 (83%) models performed slightly better than other types of kernel (polynomial degree of 2 = 78%, sigmoid = 78%, polynomial degree of 4 = 78%, and linear = 77%) models. Based on our results, the differences in the rates (success and prediction) of the six models are not really significant. So, the produced susceptibility maps will be useful for general land-use planning

First measurement of the |t|-dependence of coherent J/ψ photonuclear production

The first measurement of the cross section for coherent J/ψ photoproduction as a function of |t|, the square of the momentum transferred between the incoming and outgoing target nucleus, is presented. The data were measured with the ALICE detector in ultra-peripheral Pb–Pb collisions at a centre-of-mass energy per nucleon pair sNN=5.02TeV with the J/ψ produced in the central rapidity region |y|<0.8, which corresponds to the small Bjorken-x range (0.3−1.4)×10−3. The measured |t|-dependence is not described by computations based only on the Pb nuclear form factor, while the photonuclear cross section is better reproduced by models including shadowing according to the leading-twist approximation, or gluon-saturation effects from the impact-parameter dependent Balitsky–Kovchegov equation. These new results are therefore a valid tool to constrain the relevant model parameters and to investigate the transverse gluonic structure at very low Bjorken-x.publishedVersio

Resolving the strange behavior of extraterrestrial potassium in the upper atmosphere

It has been known since the 1960s that the layers of Na and K atoms, which occur between 80 and 105 km in the Earth's atmosphere as a result of meteoric ablation, exhibit completely different seasonal behavior. In the extratropics Na varies annually, with a pronounced wintertime maximum and summertime minimum. However, K varies semiannually with a small summertime maximum and minima at the equinoxes. This contrasting behavior has never been satisfactorily explained. Here we use a combination of electronic structure and chemical kinetic rate theory to determine two key differences in the chemistries of K and Na. First, the neutralization of K+ ions is only favored at low temperatures during summer. Second, cycling between K and its major neutral reservoir KHCO3 is essentially temperature independent. A whole atmosphere model incorporating this new chemistry, together with a meteor input function, now correctly predicts the seasonal behavior of the K layer