Susceptibility of clinical isolates of Leishmania aethiopica to miltefosine, paromomycin, amphotericin B and sodium stibogluconate using amastigote-macrophage in vitro model.

Cutaneous Leishmaniasis (CL) caused by Leishmania aethiopica is a public health and social problem with a sequel of severe and mutilating skin lesions. It is manifested in three forms: localized CL (LCL), mucosal CL (MCL) and diffuse CL (DCL). Unresponsiveness to sodium stibogluconate (Sb(V)) is common in Ethiopian CL patients. Using the amastigote-macrophage in vitro model the susceptibility of 24 clinical isolates of L. aethiopica derived from untreated patients was investigated. Eight strains of LCL, 9 of MCL, and 7 of DCL patients together with a reference strain (MHOM/ET/82/117/82) were tested against four antileishmanial drugs: amphotericin B, miltefosine, Sb(V) and paromomycin. In the same order of drugs, IC(50) (μg/ml±SD) values for the 24 strains tested were 0.16±0.18, 5.88±4.79, 10.23±8.12, and 13.63±18.74. The susceptibility threshold of isolates originating from the 3 categories of patients to all 4 drugs was not different (p>0.05). Maximal efficacy was superior for miltefosine across all the strains. Further susceptibility test could validate miltefosine as a potential alternative drug in cases of sodium stibogluconate treatment failure in CL patients.

The number of planar central configurations for the 4-body problem is finite when 3 mass positions are fixed

In the n{body problem a central con guration is formed when the position vector of each particle with respect to the center of mass is a common scalar multiple of its acceleration vector. Lindstrom showed for n = 3 and for n > 4 that if n ? 1 masses are located at xed points in the plane, then there are only a nite number of ways to position the remaining nth mass in such a way that they de ne a central con guration. Lindstrom leaves open the case n = 4. In this paper we prove the case n = 4 using as variables the mutual distances between the particles.

Reciprocal Translocations in Cattle: frequency estimation

Chromosomal anomalies, like Robertsonian and reciprocal translocations represent a big problem in cattle breeding as their presence induces, in the carrier subjects, a well documented fertility reduction. In cattle reciprocal translocations (RCPs, a chromosome abnormality caused by an exchange of material between nonhomologous chromosomes) are considered rare as to date only 19 reciprocal translocations have been described. In cattle it is common knowledge that the Robertsonian translocations represent the most common cytogenetic anomalies, and this is probably due to the existence of the endemic 1;29 Robertsonian translocation. However, these considerations are based on data obtained using techniques that are unable to identify all reciprocal translocations and thus their frequency is clearly underestimated. The purpose of this work is to provide a first realistic estimate of the impact of RCPs in the cattle population studied, trying to eliminate the factors which have caused an underestimation of their frequency so far. We performed this work using a mathematical as well as a simulation approach and, as biological data, we considered the cytogenetic results obtained in the last 15 years. The results obtained show that only 16% of reciprocal translocations can be detected using simple Giemsa techniques and consequently they could be present in no less than 0,14% of cattle subjects, a frequency five times higher than that shown by de novo Robertsonian translocations. This data is useful to open a debate about the need to introduce a more efficient method to identify RCP in cattle.

Central configurations of three nested regular polyhedra for the spatial 3n–body problem

Three regular polyhedra are called nested if they have the same number of vertices n, the same center and the positions of the vertices of the inner polyhedron ri, the ones of the medium polyhedron Ri and the ones of the outer polyhedron Ri satisfy the relation Ri = ri and Ri = Rri for some scale factors R > > 1 and for all i = 1, . . . , n. We consider 3n masses located at the vertices of three nested regular polyhedra. We assume that the masses of the inner polyhedron are equal to m1, the masses of the medium one are equal to m2, and the masses of the outer one are equal to m3. We prove that if the ratios of the masses m2/m1 and m3/m1 and the scale factors and R satisfy two convenient relations, then this configuration is central for the 3n–body problem. Moreover there is some numerical evidence that, first, fixed two values of the ratios m2/m1 and m3/m1, the 3n–body problem has a unique central configuration of this type; and second that the number of nested regular polyhedra with the same number of vertices forming a central configuration for convenient masses and sizes is arbitrary.

Risk factor profile and management of cerebrovascular patients in the REACH Registry.

BACKGROUND: Cerebrovascular disease (CVD) is a global public health problem. CVD patients are at high risk of recurrent stroke and other atherothrombotic events. Prevalence of risk factors, comorbidities, utilization of secondary prevention therapies and adherence to guidelines all influence the recurrent event rate. We assessed these factors in 18,992 CVD patients within a worldwide registry of stable outpatients. METHODS: The Reduction of Atherothrombosis for Continued Health Registry recruited >68,000 outpatients (44 countries). The subjects were mainly recruited by general practitioners (44%) and internists (29%) if they had symptomatic CVD, coronary artery disease, peripheral arterial disease (PAD) and/or >or=3 atherothrombotic risk factors. RESULTS: The 18,992 CVD patients suffered a stroke (53.7%), transient ischemic attack (TIA) (27.7%) or both (18.5%); 40% had symptomatic atherothrombotic disease in >or=1 additional vascular beds: 36% coronary artery disease; 10% PAD and 6% both. The prevalence of risk factors at baseline was higher in the TIA subgroup than in the stroke group: treated hypertension (83.5/82.0%; p = 0.02), body mass index >or=30 (26.7/20.8%; p < 0.0001), hypercholesterolemia (65.1/52.1%; p < 0.0001), atrial fibrillation (14.7/11.9%; p < 0.0001) and carotid artery disease (42.3/29.7%; p < 0.0001). CVD patients received antiplatelet agents (81.7%), oral anticoagulants (17.3%), lipid-lowering agents (61.2%) and antihypertensives (87.9%), but guideline treatment targets were frequently not achieved (54.5% had elevated blood pressure at baseline, while 4.5% had untreated diabetes). CONCLUSIONS: A high percentage of CVD patients have additional atherothrombotic disease manifestations. The risk profile puts CVD patients, especially the TIA subgroup, at high risk for future atherothrombotic events. Undertreatment is common worldwide and adherence to guidelines needs to be enforced.

Detection of smuggled cocaine in cargo using MDCT.

OBJECTIVE: Smuggling dissolved drugs, especially cocaine, in bottled liquids is an ongoing problem at borders. Common fluoroscopy of packages at the border cannot detect contaminated liquids. The objective of our study was to develop an MDCT screening method to detect cocaine-containing vessels that are hidden between uncontaminated ones in a shipment. MATERIALS AND METHODS: Studies were performed on three wine bottles containing cocaine solutions that were confiscated at the Swiss border. Reference values were obtained by scans of different sorts of commercially available wine and aqueous solutions of dissolved sugar. All bottles were scanned using MDCT, and data evaluation was performed by measuring the mean peak of Hounsfield units. To verify the method, simulated testing was performed. RESULTS: Using measurements of the mean peak of Hounsfield units enables the detection of dissolved cocaine in wine bottles in a noninvasive and rapid fashion. Increasing opacity corresponds well with the concentration of dissolved cocaine. Simulated testing showed that it is possible to distinguish between cocaine-contaminated and uncontaminated wine bottles. CONCLUSION: The described method is an efficacious screening method to detect cocaine-contaminated bottles that are hidden between untreated bottles in cargo. The noninvasive examination of cargo allows a questionable delivery to be tracked without arousing the suspicion of the smugglers.

Strategy selection: An introduction to the modeling challenge

Modeling the mechanisms that determine how humans and other agents choose among different behavioral and cognitive processes-be they strategies, routines, actions, or operators-represents a paramount theoretical stumbling block across disciplines, ranging from the cognitive and decision sciences to economics, biology, and machine learning. By using the cognitive and decision sciences as a case study, we provide an introduction to what is also known as the strategy selection problem. First, we explain why many researchers assume humans and other animals to come equipped with a repertoire of behavioral and cognitive processes. Second, we expose three descriptive, predictive, and prescriptive challenges that are common to all disciplines which aim to model the choice among these processes. Third, we give an overview of different approaches to strategy selection. These include cost‐benefit, ecological, learning, memory, unified, connectionist, sequential sampling, and maximization approaches. We conclude by pointing to opportunities for future research and by stressing that the selection problem is far from being resolved.

Low immunoglobulin levels in patients with cystic fibrosis: reduced inflammation or sign of common variable immunodeficiency syndrome?

Introduction: In children with cystic fibrosis (CF), low immunoglobulin (IgG) levels have been reported to be associated with significantly less severe lung disease. However, decreased IgG can be a sign for common variable immunodeficiency (CVID) and affect clinical outcome. The aim of this study was to analyze clinical and serological data of patients having low IgG levels in routine blood tests at annual assessment, particularly their antibody response to polysaccharide antigens. Method: Retrospective chart review of demographic data of CF patients followed at the pediatric CF clinic throughout 2009. Clinical parameters (genotype, pancreas sufficiency, FEV1), presence of Pseudomonas aeruginosa (PA) and number of exacerbations per year were correlated with immunoglobulin and vaccination antibodies levels (antibodies to pneumococcal serotypes 14, 19, 23, 1, 5 and 7F measured by enzyme-linked immune-sorbent assay). Results: 4 out of 60 patients (6.7%) had lower IgG-levels for age. Ages ranged from 1 year 8 months to 11 years, 2 boys, 2 girls. Three patients were delF508 homozygotes, one heterozygote composite delF508/G542X. All were pancreatic insufficient. FEV1 ranged from 74 to 108%. One patient never had colonization by PA, 2 had intermittent PA colonization and one was chronically infected. After conjugated vaccination all patients had protective antibodies against serotypes 14, 19, 23F. For serotypes not included in the vaccine, only one patient had protective titers for 1 out of 3 serotypes. None of the patients had received unconjugated pneumococcal vaccine. There was no significant clinical difference in FEV1, PA colonization or number of exacerbations according to IgG and vaccination antibody levels. Conclusion: Cystic Fibrosis patients with low immunoglobulin levels have normal antibody response to protein antigens. However, despite recurrent infections, there seems to be delayed or deficient antibody response to polysaccharide antigens. Prospective studies are needed to evaluate the development of polysaccharide antibody responses in CF-patients to monitor for CVID. With early detection of CF by newborn screening program, long term follow up could be started early in childhood.

Liberties and constraints of the normative approach to evaluation and decision in forensic science: a discussion towards overcoming some common misconceptions

At a time when disciplined inference and decision making under uncertainty represent common aims to participants in legal proceedings, the scientific community is remarkably heterogenous in its attitudes as to how these goals ought to be achieved. Probability and decision theory exert a considerable influence, and we think by all reason rightly do so, but they go against a mainstream of thinking that does not embrace-or is not aware of-the 'normative' character of this body of theory. It is normative, in the sense understood in this article, in that it prescribes particular properties, typically (logical) coherence, to which reasoning and decision making ought to conform. Disregarding these properties can result in diverging views which are occasionally used as an argument against the theory, or as a pretext for not following it. Typical examples are objections according to which people, both in everyday life but also individuals involved at various levels in the judicial process, find the theory difficult to understand and to apply. A further objection is that the theory does not reflect how people actually behave. This article aims to point out in what sense these examples misinterpret the analytical framework in its normative perspective. Through examples borrowed mostly from forensic science contexts, it is argued that so-called intuitive scientific attitudes are particularly liable to such misconceptions. These attitudes are contrasted with a statement of the actual liberties and constraints of probability and decision theory and the view according to which this theory is normative.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Fastidious intracellular bacteria as causal agents of community-acquired pneumonia.

Intracellular bacteria are common causes of community-acquired pneumonia that grow poorly or not at all on standard culture media and do not respond to beta-lactam antibiotic therapy. Apart from well-established agents of pneumonia such as Legionella pneumophila, Mycoplasma pneumoniae, Chlamydia pneumoniae, Chlamydia psittaci and Coxiella burnetii, some new emerging pathogens have recently been recognized, mainly Parachlamydia acanthamoebae and Simkania negevensis, two Chlamydia-related bacteria. Most of them are causes of benign and self-limited infections. However, they may cause severe pneumonia in some cases (i.e., Legionnaires' disease) and they may cause outbreaks representing a public health problem deserving prompt recognition and appropriate therapy. Although extrapulmonary manifestations are often present, no clinical features allow them to be distinguished from classical bacterial agents of pneumonia such as Streptococcus pneumoniae. Thus, specific molecular diagnostic tools are very helpful for early recognition of the offending bacteria, whereas serology often only allows retrospective or late diagnosis. Macrolides remain the best empirical treatment of intracellular respiratory pathogens, although some observational studies suggest that quinolones may be superior for the treatment of legionellosis.

Overlap Between Common Genetic Polymorphisms Underpinning Kidney Traits and Cardiovascular Disease Phenotypes: The CKDGen Consortium.

BACKGROUND: Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits. STUDY DESIGN: We conducted 2 targeted analyses. First, we examined whether known single-nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5×10(-4) (0.05/325 tests). SETTING & PARTICIPANTS: Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395), and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium. PREDICTOR: We used 19 kidney SNPs and 64 vascular SNPs. OUTCOMES & MEASUREMENTS: Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber, and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria. RESULTS: In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were nonsignificant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (P = 9.3 ×10(-10)) and diastolic (P = 1.6 ×10(-14)) blood pressure and coronary artery disease (P = 2.2 ×10(-6)), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were nonsignificant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (P = 1.06 ×10(-07) and P = 7.05 ×10(-08)). LIMITATIONS: The combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations. CONCLUSIONS: Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.

Selection of common bean lines with high agronomic performance and high calcium and iron concentrations

The objective of this work was to evaluate the genetic variability of common bean lines for cycle, weight of 100 grains, grain yield, cooking time, and grain calcium and iron concentrations. Twenty-four common bean lines were evaluated in two crop cycles (2010 and 2011). The ¯Z index was used for the selection of superior lines for most of the traits. The DF 06-19, DF 06-03, DF 06-17, DF 06-20, DF 06-11, DF 06-14, DF 06-01, DF 06-08, DF 06-22, and DF 06-04 lines showed high grain yield. All lines were of semi-early cycle and of fast cooking. The DF 06-08 and DF 06-23 lines showed high calcium concentration in grains (>1.4 g kg-1 dry matter - DM), and the DF 06-09, DF 06-03, DF 06-04, and DF 06-06 lines presented high iron concentration in grains (>0.95 g kg-1 DM) in the two crop cycles. The DF 06-09 and DF 06-03 carioca lines present high agronomic performance and high iron concentration in grains. The DF 06-17 and DF 06-08 black lines present high agronomic performance and high calcium concentration in grains. The selection of the DF 06-09, DF 06-03, DF 06-17, and DF 06-08 lines is recommended.

Ryhmätyömenetelmät logistiikan strategisessa päätöksenteossa

Työ käsittelee strategisen päätöksenteon menetelmiä sekä ryhmien päätöksentekoprosessin tukemista ja organisointia. Lähtökohtana työssä oli tarve kehittää konkreettisia menetelmiä ja tekniikoitalogistiikan strategisten päätöksentekoryhmien toiminnan tukemiseksi. Päätavoitteena työssä oli selvittää, mitkä ovat päätöksentekoryhmien suurimmat ongelmat jahaasteet päätöksentekoprosessin eri vaiheissa. Tämän pohjalta tavoitteena oli ideoida, kuinka päätöksentekoryhmiä ja niiden toimintaa noissa haasteissa voidaanparhaiten tukea erilaisten apumenetelmien ja tekniikoiden avulla. Kirjallisuuskatsauksessa perehdytään strategisten päätösten luokittelutapoihin, päätöksentekoprosessin luonteeseen, ryhmätyöskentelyn merkitykseen päätöksenteossa sekä erilaisiin ryhmäpäätöksentekotekniikoihin. Näiden pohjalta työssä on mietitty, missä asioissa ja päätöksentekoprosessin vaiheissa ryhmät kaipaavat eniten tukea ja mihin olemassa olevilla tekniikoilla ja menetelmillä ei ole pystytty täysin vastaamaan. Näihin avoimiin alueisiin työssä on pyritty kehittämään menetelmiä ja tekniikoita. Menetelmät antavat tukea erityisesti päätöksentekoprosessin vaiheistamiseen, oikeiden asioiden esille nostamiseen sekä keskustelun ja ryhmän muun toiminnan organisointiin. Työssä on esitelty myös muutama mielenkiintoinen ja lupaavajatkotutkimuskohde aihealueelta.