Chemoradiotherapy in malignant glioma: standard of care and future directions.

Glioma has been considered resistant to chemotherapy and radiation. Recently, concomitant and adjuvant chemoradiotherapy with temozolomide has become the standard treatment for newly diagnosed glioblastoma. Conversely (neo-)adjuvant PCV (procarbazine, lomustine, vincristine) failed to improve survival in the more chemoresponsive tumor entities of anaplastic oligoastrocytoma and oligodendroglioma. Preclinical investigations suggest synergism or additivity of radiotherapy and temozolomide in glioma cell lines. Although the relative contribution of the concomitant and the adjuvant chemotherapy, respectively, cannot be assessed, the early introduction of chemotherapy and the simultaneous administration with radiotherapy appear to be key for the improvement of outcome. Epigenetic inactivation of the DNA repair enzyme methylguanine methyltransferase (MGMT) seems to be the strongest predictive marker for outcome in patients treated with alkylating agent chemotherapy. Patients whose tumors do not have MGMT promoter methylation are less likely to benefit from the addition of temozolomide chemotherapy and require alternative treatment strategies. The predictive value of MGMT gene promoter methylation is being validated in ongoing trials aiming at overcoming this resistance by a dose-dense continuous temozolomide administration or in combination with MGMT inhibitors. Understanding of molecular mechanisms allows for rational targeting of specific pathways of repair, signaling, and angiogenesis. The addition of tyrosine kinase inhibitors vatalanib (PTK787) and vandetinib (ZD6474), the integrin inhibitor cilengitide, the monoclonal antibodies bevacizumab and cetuximab, the mammalian target of rapamycin inhibitors temsirolimus and everolimus, and the protein kinase C inhibitor enzastaurin, among other agents, are in clinical investigation, building on the established chemoradiotherapy regimen for newly diagnosed glioblastoma.

Lihahygienialainsäädännön omavalvontasäädökset ja käytäntö Oy Snellman Ab:n teurastamossa ja leikkaamossa, osa I Osa 1 : Owncontrol directions in meat hygiene legislation and their practical implementation in the slaughterhouse and cutting plant of Snellman Ltd, part I

Summary: Owncontrol directions in meat hygiene legislation and their practical implementation in the slaughterhouse and cutting plant of Snellman Ltd, part I

Current directions in DNA gel particles

A general understanding of interactions between DNA andoppositely charged compounds forms the basis for developing novelDNA-based materials, including gel particles. The association strength,which is altered by varying the chemical structure of the cationiccosolute, determines the spatial homogeneity of the gelation process,creating DNA reservoir devices and DNA matrix devices that can bedesigned to release either single- (ssDNA) or double-stranded(dsDNA) DNA. This paper reviews the preparation of DNA gelparticles using surfactants, proteins and polysaccharides. Particlemorphology, swelling/dissolution behaviour, degree of DNAentrapment and DNA release responses as a function of the nature ofthe cationic agent used are discussed. Current directions in thehaemocompatible and cytotoxic characterization of these DNA gelparticles have been also included.

New directions in Stochastic Multicriteria Acceptability Analysis

Decisions taken in modern organizations are often multi-dimensional, involving multiple decision makers and several criteria measured on different scales. Multiple Criteria Decision Making (MCDM) methods are designed to analyze and to give recommendations in this kind of situations. Among the numerous MCDM methods, two large families of methods are the multi-attribute utility theory based methods and the outranking methods. Traditionally both method families require exact values for technical parameters and criteria measurements, as well as for preferences expressed as weights. Often it is hard, if not impossible, to obtain exact values. Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods designed to help in this type of situations where exact values are not available. Different variants of SMAA allow handling all types of MCDM problems. They support defining the model through uncertain, imprecise, or completely missing values. The methods are based on simulation that is applied to obtain descriptive indices characterizing the problem. In this thesis we present new advances in the SMAA methodology. We present and analyze algorithms for the SMAA-2 method and its extension to handle ordinal preferences. We then present an application of SMAA-2 to an area where MCDM models have not been applied before: planning elevator groups for high-rise buildings. Following this, we introduce two new methods to the family: SMAA-TRI that extends ELECTRE TRI for sorting problems with uncertain parameter values, and SMAA-III that extends ELECTRE III in a similar way. An efficient software implementing these two methods has been developed in conjunction with this work, and is briefly presented in this thesis. The thesis is closed with a comprehensive survey of SMAA methodology including a definition of a unified framework.

In search for better pharmacological prophylaxis for acute mountain sickness: looking in other directions.

Despite decades of research, the exact pathogenic mechanisms underlying acute mountain sickness (AMS) are still poorly understood. This fact frustrates the search for novel pharmacological prophylaxis for AMS. The prevailing view is that AMS results from an insufficient physiological response to hypoxia and that prophylaxis should aim at stimulating the response. Starting off from the opposite hypothesis that AMS may be caused by an initial excessive response to hypoxia, we suggest that directly or indirectly blunting-specific parts of the response might provide promising research alternatives. This reasoning is based on the observations that (i) humans, once acclimatized, can climb Mt Everest experiencing arterial partial oxygen pressures (PaO2 ) as low as 25 mmHg without AMS symptoms; (ii) paradoxically, AMS usually develops at much higher PaO2 levels; and (iii) several biomarkers, suggesting initial activation of specific pathways at such PaO2 , are correlated with AMS. Apart from looking for substances that stimulate certain hypoxia triggered effects, such as the ventilatory response to hypoxia, we suggest to also investigate pharmacological means aiming at blunting certain other specific hypoxia-activated pathways, or stimulating their agonists, in the quest for better pharmacological prophylaxis for AMS.

Conclusions and future directions for sports events management scholarship

The book adopts a unique stakeholder perspective, structured around the groups and individuals who have an interest in and co-create sports events, including organising committees, promoters, sport organisations, spectators, community groups, sponsors, host governments, the media and NGOs. Each chapter addresses a specific stakeholder, defines that stakeholder and its relationships with sports events, describes the managerial requirements for a successful event, assesses current research and directions for future research, and outlines the normative dimensions of stakeholder engagement (such as sustainability and legacy)

Nonlinear principal and canonical directions from continuous extensions of multidimensional scaling

A continuous random variable is expanded as a sum of a sequence of uncorrelated random variables. These variables are principal dimensions in continuous scaling on a distance function, as an extension of classic scaling on a distance matrix. For a particular distance, these dimensions are principal components. Then some properties are studied and an inequality is obtained. Diagonal expansions are considered from the same continuous scaling point of view, by means of the chi-square distance. The geometric dimension of a bivariate distribution is defined and illustrated with copulas. It is shown that the dimension can have the power of continuum.

Forecasting of wind speeds and directions with artificial neural networks

In this master’s thesis, wind speeds and directions were modeled with the aim of developing suitable models for hourly, daily, weekly and monthly forecasting. Artificial Neural Networks implemented in MATLAB software were used to perform the forecasts. Three main types of artificial neural network were built, namely: Feed forward neural networks, Jordan Elman neural networks and Cascade forward neural networks. Four sub models of each of these neural networks were also built, corresponding to the four forecast horizons, for both wind speeds and directions. A single neural network topology was used for each of the forecast horizons, regardless of the model type. All the models were then trained with real data of wind speeds and directions collected over a period of two years in the municipal region of Puumala in Finland. Only 70% of the data was used for training, validation and testing of the models, while the second last 15% of the data was presented to the trained models for verification. The model outputs were then compared to the last 15% of the original data, by measuring the mean square errors and sum square errors between them. Based on the results, the feed forward networks returned the lowest generalization errors for hourly, weekly and monthly forecasts of wind speeds; Jordan Elman networks returned the lowest errors when used for forecasting of daily wind speeds. Cascade forward networks gave the lowest errors when used for forecasting daily, weekly and monthly wind directions; Jordan Elman networks returned the lowest errors when used for hourly forecasting. The errors were relatively low during training of the models, but shot up upon simulation with new inputs. In addition, a combination of hyperbolic tangent transfer functions for both hidden and output layers returned better results compared to other combinations of transfer functions. In general, wind speeds were more predictable as compared to wind directions, opening up opportunities for further research into building better models for wind direction forecasting.