The micronucleus assay in radiation accidents

The cytokinesis-block micronucleus assay in peripheral blood lymphocytes is a standardised and validated technique for biodosimetry. Automated scoring of micronuclei allows large scale applications as in population triage in case of radiation accidents or malevolent use of radioactive sources. The dose detection limit (95% confidence) of the micronucleus assay for individual dose assessment is restricted to 0.2 Gy but can be decreased to 0.1 Gy by scoring centromeres in micronuclei using fluorescence in situ hybridization (FISH). In the past the micronucleus assay was applied for a number of large scale biomonitoring studies of nuclear power plant workers and hospital workers. Baseline micronucleus frequencies depend strongly on age and gender. The assay was also already used for biodosimetry of radiation accidents. In a multiple endpoint biodosimetry study for dose assessment of a worker exposed accidentally in 2003 to X-rays, a good agreement was obtained between dose estimates resulting from the micronucleus assay, the scoring of dicentrics and translocations. Automated scoring of micronuclei in combination with centromere signals, allowing systematic biodosimetry of exposed populations, remains a challenge for the future

Impact of digitalization of mammographic units on average glandular doses in the Flemish Breast Cancer Screening Program

The impact of digitalization on the average glandular doses in 49 mammographic units participating in the Flemish Breast Cancer Screening Program was studied. Screen-film was changed to direct digital radiography and computed radiography in 25 and 24 departments respectively. Average glandular doses were calculated before and after digitalization for different PMMA-phantom thicknesses and for groups of 50 successive patients. For the transition from screen-film to computed radiography both phantom and patient dose data show a significant increase of dose with digitalization. For the transition from screen-film to direct digital radiography the evolution of the average glandular dose depends on the phantom thickness. For 20mm PMMA a significant increase in dose was found, for 45mm and 70mm PMMA there was a significant decrease in dose. The median average glandular dose of the patient dosimetry showed a smaller but significant decrease

The micronucleus assay as a biological dosimeter of in vivo ionising radiation exposure

Biological dosimetry, based on the analysis of micronuclei (MN) in the cytokinesis-block micronucleus (CBMN) assay can be used as an alternative method for scoring dicentric chromosomes in the field of radiation protection. Biological dosimetry or Biodosimetry, is mainly performed, in addition to physical dosimetry, with the aim of individual dose assessment. Many studies have shown that the number of radiation-induced MN is strongly correlated with dose and quality of radiation. The CBMN assay has become, in the last years, a thoroughly validated and standardised technique to evaluate in vivo radiation exposure of occupational, medical and accidentally exposed individuals. Compared to the gold standard, the dicentric assay, the CBMN assay has the important advantage of allowing economical, easy and quick analysis. The main disadvantage of the CBMN assay is related to the variable micronucleus ( MN) background frequency, by which only in vivo exposures in excess of 0.2-0.3 Gy X-rays can be detected. In the last years, several improvements have been achieved, with the ultimate goals (i) of further increasing the sensitivity of the CBMN assay for low-dose detection by combining the assay with a fluorescence in situ hybridisation centromere staining technique, (ii) of increasing the specificity of the test for radiation by scoring nucleoplasmic bridges in binucleated cells and (iii) of making the assay optimally suitable for rapid automated analysis of a large number of samples, viz. in case of a large-scale radiation accident. The development of a combined automated MN-centromere scoring procedure remains a challenge for the future, as it will allow systematic biomonitoring of radiation workers exposed to low-dose radiation

On the complexity of hierarchical problem solving

Competent Genetic Algorithms can efficiently address problems in which the linkage between variables is limited to a small order k. Problems with higher order dependencies can only be addressed efficiently if further problem properties exist that can be exploited. An important class of problems for which this occurs is that of hierarchical problems. Hierarchical problems can contain dependencies between all variables (k = n) while being solvable in polynomial time. An open question so far is what precise properties a hierarchical problem must possess in order to be solvable efficiently. We study this question by investigating several features of hierarchical problems and determining their effect on computational complexity, both analytically and empirically. The analyses are based on the Hierarchical Genetic Algorithm (HGA), which is developed as part of this work. The HGA is tested on ranges of hierarchical problems, produced by a generator for hierarchical problems

Low doses of ionizing radiation induce immune-stimulatory responses in isolated human primary monocytes

The health effects arising from exposure to low doses of ionizing radiation are of particular concern, mainly due to the increased application of diagnostic and therapeutic X-ray modalities. The mechanisms behind the cell and tissue responses to low doses remain to be elucidated. Accumulating evidence suggests that low doses of ionizing radiation induce activation of the immune response; however, the processes involved have yet to be adequately investigated. Monocytes are key players in the induction of an immune response. Within the context of this study, we investigated the activation of toll-like receptors (TLRs), mitogen-activated protein kinases (MAPKs) and NF-B signaling in isolated human primary monocytes in response to low doses (0.05 and 0.1 Gy) and a high dose (1 Gy) of ionizing radiation. Using quantitative RT-PCR and ELISA techniques, our results showed a positive regulation of TLR signaling in response to low doses but a less significant response at high doses. This activation was demonstrated via the activation of TLR signaling molecules (HMGB1, TLR4, TLR9, MyD88 and IRAK1). Furthermore, and in contrast to the high dose, the low doses showed increased phosphorylation levels of the protein IB, and therefore positive signaling of the NF-B pathway. This result denotes pro-survival and pro-inflammatory responses. Additionally, MAPKs were activated in response to 0.05 Gy, while 0.1 and 1 Gy showed a downregulatory trend that may be related to activation of the PF4 gene. On the other hand, there was highly significant involvement of activated p53 and damaged genes in response to high but not low doses. In conclusion, this study addressed the need to re-evaluate health risks arising from exposure to low doses of ionizing radiation, particularly in view of the accumulating evidence reporting inflammatory and oncogenic consequences from these exposures

Generating the Ground Truth: Synthetic Data for Label Noise Research

Most real-world classification tasks suffer from label noise to some extent. Such noise in the data adversely affects the generalization error of learned models and complicates the evaluation of noise-handling methods, as their performance cannot be accurately measured without clean labels. In label noise research, typically either noisy or incomplex simulated data are accepted as a baseline, into which additional noise with known properties is injected. In this paper, we propose SYNLABEL, a framework that aims to improve upon the aforementioned methodologies. It allows for creating a noiseless dataset informed by real data, by either pre-specifying or learning a function and defining it as the ground truth function from which labels are generated. Furthermore, by resampling a number of values for selected features in the function domain, evaluating the function and aggregating the resulting labels, each data point can be assigned a soft label or label distribution. Such distributions allow for direct injection and quantification of label noise. The generated datasets serve as a clean baseline of adjustable complexity into which different types of noise may be introduced. We illustrate how the framework can be applied, how it enables quantification of label noise and how it improves over existing methodologies

Learning and exploiting mixed variable dependencies with a model-based EA

Mixed-integer optimization considers problems with both discrete and continuous variables. The ability to learn and process problem structure can be of paramount importance for optimization, particularly when faced with black-box optimization (BBO) problems, where no structural knowledge is known a priori. For such cases, model-based Evolutionary Algorithms (EAs) have been very successful in the fields of discrete and continuous optimization. In this paper, we present a model-based EA which integrates techniques from the discrete and continuous domains in order to tackle mixed-integer problems. We furthermore introduce the novel mechanisms to learn and exploit mixed-variable dependencies. Previous approaches only learned dependencies explicitly in either the discrete or the continuous domain. The potential usefulness of addressing mixed dependencies directly is assessed by empirically analyzing algorithm performance on a selection of mixed-integer problems with different types of variable interactions. We find substantially improved, scalable performance on problems that exhibit mixed dependencies

Oscillation Reduction for Knuckle Cranes

Boom cranes are among the most common material handling systems due to their simple design. Some boom cranes also have an auxiliary jib connected to the boom with a flexible joint to enhance the maneuverability and increase the workspace of the crane. Such boom cranes are commonly called knuckle boom cranes. Due to their underactuated properties, it is fairly challenging to control knuckle boom cranes. To the best of our knowledge, only a few techniques are present in the literature to control this type of cranes using approximate models of the crane. In this paper we present for the first time a complete mathematical model for this crane where it is possible to control the three rotations of the crane (known as luff, slew, and jib movement), and the cable length. One of the main challenges to control this system is how to reduce the oscillations in an effective way. In this paper we propose a nonlinear control based on energy considerations capable of guiding the crane to desired sets points while effectively reducing load oscillations. The corresponding stability and convergence analysis is proved using the LaSalle's invariance principle. Simulation results are provided to demonstrate the effectiveness and feasibility of the proposed method.Comment: This paper was published in 37th International Symposium on Automation and Robotics in Construction (ISARC 2020

Effects of Ionizing Radiation on the Size Distribution of Proteoglycan Aggregates Synthesized by Chondrocytes in Agarose

Effects of ionizing radiation on the structure and size-distribution of newly synthesized proteoglycan aggregates are studied in-vitro. Chondrocytes, isolated from embryonic chick sterna, are cultured for 7 days in a tri-dimensional agarose system. Single radiation doses of 10, 20 and 50 Gy are given before starting the culture. Digestion of the artificial agarose matrix liberates the newly synthesized proteoglycans. Spreading with cytochrome C allows electron microscopic investigations of the individual, newly synthesized molecules. The structure of aggregates synthesized by control and irradiated chondrocytes is comparable. However, radiation causes alterations in the size-distributions of the aggregate-populations. For the control cultures, an average aggregate contains 27 aggrecans per aggregate. 34 pro mille of the molecules contain more than 100 aggrecans per aggregate. Irradiation with 10 Gy doesn\u27t cause alterations. With radiation doses of 20 and 50 Gy, an average molecule contains 20 aggrecans. Only about 9 pro mille of the aggregates contain more than 100 aggrecans. Stimulation of lysosomal activity after irradiation could explain the observed alterations