Three-dimensional radiobiological dosimetry of kidneys for treatment planning in peptide receptor radionuclide therapy.

PURPOSE: Peptide receptor radionuclide therapy (PRRT) delivers high absorbed doses to kidneys and may lead to permanent nephropathy. Reliable dosimetry of kidneys is thus critical for safe and effective PRRT. The aim of this work was to assess the feasibility of planning PRRT based on 3D radiobiological dosimetry (3D-RD) in order to optimize both the amount of activity to administer and the fractionation scheme, while limiting the absorbed dose and the biological effective dose (BED) to the renal cortex. METHODS: Planar and SPECT data were available for a patient examined with (111)In-DTPA-octreotide at 0.5 (planar only), 4, 24, and 48 h post-injection. Absorbed dose and BED distributions were calculated for common therapeutic radionuclides, i.e., (111)In, (90)Y and (177)Lu, using the 3D-RD methodology. Dose-volume histograms were computed and mean absorbed doses to kidneys, renal cortices, and medullae were compared with results obtained using the MIRD schema (S-values) with the multiregion kidney dosimetry model. Two different treatment planning approaches based on (1) the fixed absorbed dose to the cortex and (2) the fixed BED to the cortex were then considered to optimize the activity to administer by varying the number of fractions. RESULTS: Mean absorbed doses calculated with 3D-RD were in good agreement with those obtained with S-value-based SPECT dosimetry for (90)Y and (177)Lu. Nevertheless, for (111)In, differences of 14% and 22% were found for the whole kidneys and the cortex, respectively. Moreover, the authors found that planar-based dosimetry systematically underestimates the absorbed dose in comparison with SPECT-based methods, up to 32%. Regarding the 3D-RD-based treatment planning using a fixed BED constraint to the renal cortex, the optimal number of fractions was found to be 3 or 4, depending on the radionuclide administered and the value of the fixed BED. Cumulative activities obtained using the proposed simulated treatment planning are compatible with real activities administered to patients in PRRT. CONCLUSIONS: The 3D-RD treatment planning approach based on the fixed BED was found to be the method of choice for clinical implementation in PRRT by providing realistic activity to administer and number of cycles. While dividing the activity in several cycles is important to reduce renal toxicity, the clinical outcome of fractionated PRRT should be investigated in the future.

Rational design of 4-aryl-1,2,3-triazoles for indoleamine 2,3-dioxygenase 1 inhibition.

Indoleamine 2,3-dioxygenase 1 (IDO1) is an important therapeutic target for the treatment of diseases such as cancer that involve pathological immune escape. Starting from the scaffold of our previously discovered IDO1 inhibitor 4-phenyl-1,2,3-triazole, we used computational structure-based methods to design more potent ligands. This approach yielded highly efficient low molecular weight inhibitors, the most active being of nanomolar potency both in an enzymatic and in a cellular assay, while showing no cellular toxicity and a high selectivity for IDO1 over tryptophan 2,3-dioxygenase (TDO). A quantitative structure-activity relationship based on the electrostatic ligand-protein interactions in the docked binding modes and on the quantum chemically derived charges of the triazole ring demonstrated a good explanatory power for the observed activities.

A comparison of rapid bioassessment protocols used in 2 regions with Mediterranean climates, the Iberian Peninsula and South Africa

Abstract. The ability of 2 Rapid Bioassessment Protocols (RBPs) to assess stream water quality was compared in 2 Mediterranean-climate regions. The most commonly used RBPs in South Africa (SAprotocol) and the Iberian Peninsula (IB-protocol) are both multihabitat, field-based methods that use macroinvertebrates. Both methods use preassigned sensitivity weightings to calculate metrics and biotic indices. The SA- and IB-protocols differ with respect to sampling equipment (mesh size: 1000 lm vs 250 300 lm, respectively), segregation of habitats (substrate vs flow-type), and sampling and sorting procedures (variable time and intensity). Sampling was undertaken at 6 sites in South Africa and 5 sites in the Iberian Peninsula. Forty-four and 51 macroinvertebrate families were recorded in South Africa and the Iberian Peninsula, respectively; 77.3% of South African families and 74.5% of Iberian Peninsula families were found using both protocols. Estimates of community similarity compared between the 2 protocols were .60% similar among sites in South Africa and .54% similar among sites in the Iberian Peninsula (BrayCurtis similarity), and no significant differences were found between protocols (Multiresponse Permutation Procedure). Ordination based on Non-metric Multidimensional Scaling grouped macroinvertebrate samples on the basis of site rather than protocol. Biotic indices generated with the 2 protocols at each site did not differ. Thus, both RBPs produced equivalent results, and both were able to distinguish between biotic communities (mountain streams vs foothills) and detect water-quality impairment, regardless of differences in sampling equipment, segregation of habitats, and sampling and sorting procedures. Our results indicate that sampling a single habitat may be sufficient for assessing water quality, but a multihabitat approach to sampling is recommended where intrinsic variability of macroinvertebrate assemblages is high (e.g., in undisturbed sites in regions with Mediterranean climates). The RBP of choice should depend on whether the objective is routine biomonitoring of water quality or autecological or faunistic studies.

Natural malaria infection reduces starvation resistance of nutritionally stressed mosquitoes.

In disease ecology, there is growing evidence that environmental quality interacts with parasite and host to determine host susceptibility to an infection. Most studies of malaria parasites have focused on the infection costs incurred by the hosts, and few have investigated the costs on mosquito vectors. The interplay between the environment, the vector and the parasite has therefore mostly been ignored and often relied on unnatural or allopatric Plasmodium/vector associations. Here, we investigated the effects of natural avian malaria infection on both fecundity and survival of field-caught female Culex pipiens mosquitoes, individually maintained in laboratory conditions. We manipulated environmental quality by providing mosquitoes with different concentrations of glucose-feeding solution prior to submitting them to a starvation challenge. We used molecular-based methods to assess mosquitoes' infection status. We found that mosquitoes infected with Plasmodium had lower starvation resistance than uninfected ones only under low nutritional conditions. The effect of nutritional stress varied with time, with the difference of starvation resistance between optimally and suboptimally fed mosquitoes increasing from spring to summer, as shown by a significant interaction between diet treatment and months of capture. Infected and uninfected mosquitoes had similar clutch size, indicating no effect of infection on fecundity. Overall, this study suggests that avian malaria vectors may suffer Plasmodium infection costs in their natural habitat, under certain environmental conditions. This may have major implications for disease transmission in the wild.

Label-free cytotoxicity screening assay by digital holographic microscopy.

Abstract We introduce a label-free technology based on digital holographic microscopy (DHM) with applicability for screening by imaging, and we demonstrate its capability for cytotoxicity assessment using mammalian living cells. For this first high content screening compatible application, we automatized a digital holographic microscope for image acquisition of cells using commercially available 96-well plates. Data generated through both label-free DHM imaging and fluorescence-based methods were in good agreement for cell viability identification and a Z'-factor close to 0.9 was determined, validating the robustness of DHM assay for phenotypic screening. Further, an excellent correlation was obtained between experimental cytotoxicity dose-response curves and known IC values for different toxic compounds. For comparable results, DHM has the major advantages of being label free and close to an order of magnitude faster than automated standard fluorescence microscopy.

Man-bites-dog business cycles

The newsworthiness of an event is partly determined by how unusual it isand this paper investigates the business cycle implications of this fact. In particular, weanalyze the consequences of information structures in which some types of signals are morelikely to be observed after unusual events. Such signals may increase both uncertainty anddisagreement among agents and when embedded in a simple business cycle model, can helpus understand why we observe (i) occasional large changes in macro economic aggregatevariables without a correspondingly large change in underlying fundamentals (ii) persistentperiods of high macroeconomic volatility and (iii) a positive correlation between absolutechanges in macro variables and the cross-sectional dispersion of expectations as measuredby survey data. These results are consequences of optimal updating by agents when theavailability of some signals is positively correlated with tail-events. The model is estimatedby likelihood based methods using individual survey responses and a quarterly time seriesof total factor productivity along with standard aggregate time series. The estimated modelsuggests that there have been episodes in recent US history when the impact on outputof innovations to productivity of a given magnitude was more than eight times as largecompared to other times.

Copy number variants, diseases and gene expression.

Copy number variation (CNV) has recently gained considerable interest as a source of genetic variation likely to play a role in phenotypic diversity and evolution. Much effort has been put into the identification and mapping of regions that vary in copy number among seemingly normal individuals in humans and a number of model organisms, using bioinformatics or hybridization-based methods. These have allowed uncovering associations between copy number changes and complex diseases in whole-genome association studies, as well as identify new genomic disorders. At the genome-wide scale, however, the functional impact of CNV remains poorly studied. Here we review the current catalogs of CNVs, their association with diseases and how they link genotype and phenotype. We describe initial evidence which revealed that genes in CNV regions are expressed at lower and more variable levels than genes mapping elsewhere, and also that CNV not only affects the expression of genes varying in copy number, but also have a global influence on the transcriptome. Further studies are warranted for complete cataloguing and fine mapping of CNVs, as well as to elucidate the different mechanisms by which they influence gene expression.

Cross-country differences in disclosure quality: a study of fair value disclosures by european real estate companies

Companies are under IAS 40 required to report fair values of investment properties on the balance sheet or to disclose them in the notes. The standard requires also that companies have to disclose the methods and significant assumptions applied in determining fair values of investment properties. However, IAS 40 does not include any illustrative examples or other guidance on how to apply the disclosure requirements. We use a sample with publicly traded companies from the real estate sector in the EU. We find that a majority of the companies use income based methods for the measurement of fair values but there are considerable cross-country variations in the level of disclosures about the assumptions used in determining fair values. More specifically, we find that Scandinavian and German origin companies disclose more than French and English origin companies. We also test whether disclosure quality is associated with enforcement quality measured with the “Rule of Law” index according to Kaufmann et al. (2010), and associated with a secrecy- versus transparency-measure based on Gray (1988). We find a positive association between disclosure and earnings quality and a negative association with secrecy.

ECIL recommendations for the use of biological markers for the diagnosis of invasive fungal diseases in leukemic patients and hematopoietic SCT recipients.

As culture-based methods for the diagnosis of invasive fungal diseases (IFD) in leukemia and hematopoietic SCT patients have limited performance, non-culture methods are increasingly being used. The third European Conference on Infections in Leukemia (ECIL-3) meeting aimed at establishing evidence-based recommendations for the use of biological tests in adult patients, based on the grading system of the Infectious Diseases Society of America. The following biomarkers were investigated as screening tests: galactomannan (GM) for invasive aspergillosis (IA); β-glucan (BG) for invasive candidiasis (IC) and IA; Cryptococcus Ag for cryptococcosis; mannan (Mn) Ag/anti-mannan (A-Mn) Ab for IC, and PCR for IA. Testing for GM, Cryptococcus Ag and BG are included in the revised EORTC/MSG (European Organization for Research and Treatment of Cancer/Mycoses Study Group) consensus definitions for IFD. Strong evidence supports the use of GM in serum (A II), and Cryptococcus Ag in serum and cerebrospinal fluid (CSF) (A II). Evidence is moderate for BG detection in serum (B II), and the combined Mn/A-Mn testing in serum for hepatosplenic candidiasis (B III) and candidemia (C II). No recommendations were formulated for the use of PCR owing to a lack of standardization and clinical validation. Clinical utility of these markers for the early management of IFD should be further assessed in prospective randomized interventional studies.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

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.

Rapid detection of bacterial resistance to antibiotics using AFM cantilevers as nanomechanical sensors.

The widespread misuse of drugs has increased the number of multiresistant bacteria, and this means that tools that can rapidly detect and characterize bacterial response to antibiotics are much needed in the management of infections. Various techniques, such as the resazurin-reduction assays, the mycobacterial growth indicator tube or polymerase chain reaction-based methods, have been used to investigate bacterial metabolism and its response to drugs. However, many are relatively expensive or unable to distinguish between living and dead bacteria. Here we show that the fluctuations of highly sensitive atomic force microscope cantilevers can be used to detect low concentrations of bacteria, characterize their metabolism and quantitatively screen (within minutes) their response to antibiotics. We applied this methodology to Escherichia coli and Staphylococcus aureus, showing that live bacteria produced larger cantilever fluctuations than bacteria exposed to antibiotics. Our preliminary experiments suggest that the fluctuation is associated with bacterial metabolism.

Ylisoonisen yksivaiheisen aksiaaliturbiinin suunnittelu

Tässä diplomityössä suunnitellaan yksivaiheisen turbiinin ylisooninen staattori ja alisooninen roottori, tulo-osa ja diffuusori. Työn alussa tarkastellaan aksiaaliturbiinin käyttökohteita ja teoriaa, jonka jälkeen esitetään suunnittelun perustana olevat menetelmät ja periaatteet. Perussuunnittelu tehdään Traupelinmenetelmällä WinAxtu 1.1 suunnitteluohjelmalla ja hyötysuhde arvioidaan lisäksiExcel-pohjaisella laskennalla. Ylisooninen staattori suunnitellaan perussuunnittelun tuloksiin perustuen, soveltamalla karakteristikoiden menetelmää suuttimen laajenevaan osaan ja pinta-alasuhteita suppenevaan osaan. Roottorin keskiviiva piirretään Sahlbergin menetelmällä ja siiven muoto määritetään A3K7 paksuusjakauman sekä tiheän siipihilan muotoilun periaatteita yhdistämällä. Tulo-osa suunnitellaan mahdollisimman jouhevaksi geometriatietojen ja kirjallisuuden esimerkkien mukaisesti. Lopuksi tulo-osaa mallinnetaan CFD-laskennalla. Diffuusori suunnitellaan käyttämällä soveltuvin osin kirjallisuudessa esitettyjätietoja, tulo-osan geometriaa ja CFD-laskentaa. Suunnittelutuloksia verrataan lopuksi kirjallisuudessa esitettyihin tuloksiin ja arvioidaan suunnittelun onnistumista sekä mahdollisia ongelmakohtia.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Lossless compression of hyperspectral images

Technological progress has made a huge amount of data available at increasing spatial and spectral resolutions. Therefore, the compression of hyperspectral data is an area of active research. In somefields, the original quality of a hyperspectral image cannot be compromised andin these cases, lossless compression is mandatory. The main goal of this thesisis to provide improved methods for the lossless compression of hyperspectral images. Both prediction- and transform-based methods are studied. Two kinds of prediction based methods are being studied. In the first method the spectra of a hyperspectral image are first clustered and and an optimized linear predictor is calculated for each cluster. In the second prediction method linear prediction coefficients are not fixed but are recalculated for each pixel. A parallel implementation of the above-mentioned linear prediction method is also presented. Also,two transform-based methods are being presented. Vector Quantization (VQ) was used together with a new coding of the residual image. In addition we have developed a new back end for a compression method utilizing Principal Component Analysis (PCA) and Integer Wavelet Transform (IWT). The performance of the compressionmethods are compared to that of other compression methods. The results show that the proposed linear prediction methods outperform the previous methods. In addition, a novel fast exact nearest-neighbor search method is developed. The search method is used to speed up the Linde-Buzo-Gray (LBG) clustering method.