Peter Korošec

let-7b and miR-126 are down-regulated in tumor tissue and correlate with microvessel density and survival outcomes in non--small--cell lung cancer.

Angiogenesis is a critical event in the development, progression, and spread of various human cancers, including lung cancer. Molecular mechanisms that underlie the complex regulation of angiogenic processes are poorly understood. However, an increasing body of evidence indicates miRNAs as important regulators of tumor angiogenesis. Forceps biopsies were collected from tumor tissue, surrounding tissue, and non-tumor tissue from 50 NSCLC patients. Lung tissue samples from individuals with no clinical evidence of a cancerous disease served as controls. Immunohistochemical staining for Factor VIII was used to evaluate microvessel density (MVD). TaqMan® primer-probe sets were used in quantitative real-time RT-PCR reactions to determine expression levels of let-7b, miR-126, miR-9, and miR-19a. We demonstrated significantly higher MVD and decreased expression levels of let-7b and miR-126 in tumor tissue and surrounding tissue in comparison to corresponding non-tumor tissue or lung tissue from the control group. In addition, no differences in MVD and expression levels of both miRNAs between tumor tissue and surrounding tissue from NSCLC patients were observed. Low expression of both miRNAs correlated with high MVD and worse progression-free survival and overall survival. These observations strongly suggest similar molecular alternations within tumor tissue and surrounding tissue that comprise a specific microenvironment. Low expression of let-7b and miR-126 seems to have a possible anti-angiogenic role in lung tumor tissue and significantly correlates with worse survival outcomes for lung cancer patients. Moreover, the regulation of let-7b and miR-126 expression could have therapeutic potential because it could reduce tumor angiogenesis and therefore suppress tumor growth in lung cancer patients.

High sensitivity of CAP-FEIA rVes v 5 and rVes v 1 for diagnosis of Vespula venom allergy

and proline, IgE produced against HWPs probably cross-reacts with natural wheat proteins. In fact, preincubation of sera with HWP-A clearly revealed a decreased binding of IgE to natural wheat proteins. In conclusion, measurement of basophil CD203c expression induced by various preparations of wheat proteins is highly useful in predicting causative allergens in patients with WDEIA. Furthermore, the basophil activation test based on the expression of CD203c might help determine causative allergens for a wide variety of food allergies.

Solving the mesh-partitioning problem with an ant-colony algorithm

Many real-world engineering problems can be expressed in terms of partial differential equations and solved by using the finite-element method, which is usually parallelised, i.e. the mesh is divided among several processors. To achieve high parallel efficiency it is important that the mesh is partitioned in such a way that workloads are well balanced and interprocessor communication is minimised. In this paper we present an enhancement of a technique that uses a nature-inspired metaheuristic approach to achieve higher-quality partitions. The so-called multilevel ant-colony algorithm, which is a relatively new metaheuristic search technique for solving optimisation problems, was applied and studied, and the possible parallelisation of this algorithm is discussed. The multilevel ant-colony algorithm performed very well and is superior to classical k-METIS and Chaco algorithms; it is even comparable with the combined evolutionary/multilevel scheme used in the JOSTLE evolutionary algorithm and returned solutions that are better than the currently available solutions in the Graph Partitioning Archive.

Differential evolution and differential ant-stigmergy on dynamic optimisation problems

Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm (jDE) and the differential ant-stigmergy algorithm (DASA). The performances of the jDE and the DASA are evaluated on the set of well-known benchmark problems provided for the special session on Evolutionary Computation in Dynamic and Uncertain Environments. We analyse the results for five algorithms presented by using the non-parametric statistical test procedure. The two proposed algorithms show a consistently superior performance over other recently proposed methods. The results show that both algorithms are appropriate candidates for DOPs.

Clinical Routine Utility of Basophil Activation Testing for Diagnosis of Hymenoptera-Allergic Patients with Emphasis on Individuals with Negative Venom-Specific IgE Antibodies

Background: Previous reports suggest the usefulness of basophil activation testing (BAT) in Hymenoptera-allergic patients with negative venom-specific IgE antibodies. We sought to evaluate the diagnostic utility of this testing in a routine clinical laboratory setting. Materials and Methods: Twenty-one patients with anaphylactic reactions to Hymenoptera sting (median grade III) and negative venom-specific IgE were routinely and prospectively tested with BAT. Results: We were able to diagnose 81% (17 of 21) of patients with BAT and 57% (12 of 21) with intradermal skin testing. Three wasp venom-allergic patients showed IgE positivity to rVes v 5. Four patients (19%) were negative for all tests. In the case of double-positive BAT, the culprit insect correlated with the venom that induced a significantly higher basophil response. Conclusions: BAT allows the identification of severe Hymenoptera-allergic patients with negative specific IgE and skin tests. The routine use of this cellular test should facilitate prescription of venom immunotherapy in complex cases with inconclusive diagnostic results.

A comparative study of stochastic optimization methods in electric motor design

The efficiency of universal electric motors that are widely used in home appliances can be improved by optimizing the geometry of the rotor and the stator. Expert designers traditionally approach this task by iteratively evaluating candidate designs and improving them according to their experience. However, the existence of reliable numerical simulators and powerful stochastic optimization techniques make it possible to automate the design procedure. We present a comparative study of six stochastic optimization algorithms in designing optimal rotor and stator geometries of a universal electric motor where the primary objective is to minimize the motor power losses. We compare three methods from the domain of evolutionary computation, generational evolutionary algorithm, steady-state evolutionary algorithm and differential evolution, two particle-based methods, particle-swarm optimization and electromagnetism-like algorithm, and a recently proposed multilevel ant stigmergy algorithm. By comparing their performance, the most efficient method for solving the problem is identified and an explanation of its success is offered.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

BackgroundWe address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods.ResultsWe apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input.ConclusionsOverall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and artificial data, for all observability scenarios considered, and for all amounts of noise added to the artificial data. In sum, the meta-heuristic methods considered are suitable for estimating the parameters in the ODE model of the dynamics of endocytosis under a range of conditions: With the model and conditions being representative of parameter estimation tasks in ODE models of biochemical systems, our results clearly highlight the promise of bio-inspired meta-heuristic methods for parameter estimation in dynamic system models within system biology.

The Relevance of Basophil Allergen Sensitivity Testing to Distinguish between Severe and Mild Peanut-Allergic Children

Background: Peanut sensitization is common in children. However, it is difficult to assess which children will react mildly and which severely. This study evaluated the relevance of basophil allergen sensitivity testing to distinguish the severity of peanut allergy in children. Methods: Twenty-seven peanut-sensitized children with symptoms varying from mild symptoms to severe anaphylaxis underwent peanut CD63 dose-response curve analysis with the inclusion of basophil allergen sensitivity calculation (CD-sens) and peanut component immunoglobulin E (IgE) testing. Results: Eleven children who had experienced anaphylaxis to peanuts showed a markedly higher peanut CD63 response at submaximal allergen concentrations and CD-sens (median 1,667 vs. 0.5; p < 0.0001) than 16 children who experienced a milder reaction. Furthermore, a negative or low CD-sens to peanuts unambiguously excluded anaphylactic peanut allergy. Children with anaphylaxis have higher levels of Ara h 1, 2, 3 and 9 IgE, but comparable levels of IgE to Ara h 8 and whole-peanut extract. The diagnostic specificity calculated with a receiver operating characteristic analysis reached 100% for CD-sens and 73% for Ara h 2. Conclusions: We demonstrated that severe peanut allergy is significantly associated with higher basophil allergen sensitivity. This cellular test should facilitate a more accurate diagnosis of peanut allergy.

Immunological and clinical factors associated with adverse systemic reactions during the build-up phase of honeybee venom immunotherapy.

Adverse systemic reactions (SRs) are more common in honeybee venom immunotherapy (VIT) than in wasp VIT. Factors that might be associated with SRs during the honeybee VIT are poorly understood.

Hereditary Angioedema Nationwide Study in Slovenia Reveals Four Novel Mutations in SERPING1 Gene

Hereditary angioedema (HAE) is a rare autosomal dominant disease characterized by swelling of the face, lips, tongue, larynx, genitalia, or extremities, with abdominal pain caused by intra-abdominal edema. HAE is caused by mutations affecting the C1 inhibitor gene, SERPING1, resulting in low levels of C1 inhibitor (Type I HAE) or normal levels of ineffective C1 inhibitor (Type II HAE). A nationwide survey identified nine unrelated families with HAE in Slovenia, among whom 17 individuals from eight families were recruited for genetic analyses. A diagnosis of HAE was established in the presence of clinical and laboratory criteria (low C1 inhibitor antigenic levels and/or function), followed up by a positive family history. Genetic studies were carried out using PCR and sequencing to detect SERPING1 mutations in promoter, noncoding exon 1, the 7 coding exons, and exon-intron boundaries. Multiplex ligation-dependent probe amplification was performed in order to search for large deletions/duplications in SERPING1 gene. A mutation responsible for HAE was identified in patients from seven families with the disease. In HAE type I families, one previously reported substitution (Gln67Stop, c.265C>T) and four novel mutations were identified. The new mutations included two missense substitutions, Ser128Phe (c.449C>T), and Glu429Lys (c.1351G>A), together with two frameshift mutations, indel (c.49delGinsTT) and deletion (c.593_594delCT). Both families with HAE type II harbored the two well-known substitutions affecting the arginyl residue at the reactive center in exon 8, Arg444Cys (c.1396C>T) and Arg444His (c.1397G>A), respectively. In one patient only the homozygous variant g.566T>C (c.-21T>C) was identified. Our study identified four novel mutations in the Slovenian HAE population, highlighting the heterogeneity of mutations in the SERPING1 gene causing C1 inhibitor deficiency and HAE. In a single patient with HAE a homozygous variant g.566T>C (c.-21T>C) might be responsible for the disease.