Histone Methylation Marks on Circulating Nucleosomes as Novel Blood-Based Biomarker in Colorectal Cancer

Circulating nucleic acids (CNAs) are under investigation as a liquid biopsy in cancer as potential non-invasive biomarkers, as stable structure in circulation nucleosomes could be valuable sources for detection of cancer-specific alterations in histone modifications. Our interest is in histone methylation marks with a focus on colorectal cancer, one of the leading cancers respective the incidence and mortality. Our previous work included the analysis of trimethylations of lysine 9 on histone 3 (H3K9me3) and of lysine 20 on histone 4 (H4K20me3) by chromatin immuno- precipitation-related PCR in circulating nucleosomes. Here we asked whether global immunologic measurement of histone marks in circulation could be a suitable approach to show their potential as biomarkers. In addition to H3K9me3 and H4K20me3 we also measured H3K27me3 in plasma samples from CRC patients (n = 63) and cancer free individuals (n = 40) by ELISA-based methylation assays. Our results show that of three marks, the amounts of H3K27me3 (p = 0.04) and H4K20me3 (p < 0.001) were significantly lower in CRC patients than in healthy controls. For H3K9me3 similar amounts were measured in both groups. Areas under the curve (AUC) in receiver operating characteristic (ROC) curves indicating the power of CRC detection were 0.620 for H3K27me3, 0.715 for H4K20me3 and 0.769 for the combination of both markers. In conclusion, findings of this preliminary study reveal the potential of blood-based detection of CRC by quantification of histone methylation marks and the additive effect of the marker combination.     

A hyperheuristic approach to examination timetabling problems: benchmarks and a new problem from practice

Many researchers studying examination timetabling problems focus on either benchmark problems or problems from practice encountered in their institutions. Hyperheuristics are proposed as generic optimisation methods which explore the search space of heuristics rather than direct solutions. In the present study, the performance of tournament-based hyperheuristics for the exam timetabling problem are investigated. The target instances include both the Toronto and ITC 2007 benchmarks and the examination timetabling problem at KAHO Sint-Lieven (Ghent, Belgium). The Toronto and ITC 2007 benchmarks are post-enrolment-based examination timetabling problems, whereas the KAHO Sint-Lieven case is a curriculum-based examination timetabling problem. We drastically improve the previous (manually created) solution for the KAHO Sint-Lieven problem by generating a timetable that satisfies all the hard and soft constraints. We also make improvements on the best known results in the examination timetabling literature for seven out of thirteen instances for the To ronto benchmarks. The results are competitive with those of the finalists of the examination timetabling track of the International Timetabling Competition.     

Using a conductive sphere as a probe to characterize the sensitivity of soft piezoresistive films

Flexible piezoresistive films, such as, carbon black/polydimethylsiloxane (C-PDMS) composites, are often used as skin analogs and integrated into complex array sensors for tactile sensing. The uniformity of the sensor characteristics heavily depends on the homogeneity of the composite. Therefore, the ability to locally characterize a film that will be integrated into a complex force sensor could be critical. Here, a method to characterize the local sensitivity of flexible piezoresistive films is presented. Using a conductive sphere, which was chosen over a flat probe to eliminate misalignment issues, the surface of a thin film composite is indented to characterize the change in resistivity in terms of average strain. Experiments were performed with 15 and 18 wt% carbon black C-PDMS films of varying thickness. The contact radius of the probe with the piezoresistive film was estimated using the Johnson-Roberts-Kendall contact theory. Theoretical contact area estimates were found to agree with contact radius measurements carried out using optically transparent PDMS films observed through an optical microscope. Results show that C-PDMS with 15 wt% carbon black exhibit a higher rate if change of resistivity and gauge factor than films of same thickness with 18 wt% carbon black. On the other hand, thicker films exhibit higher gauge factors for the two tested carbon black contents. Tests carried out at multiple locations yielded consistent sensitivity values, making these types of composites suitable for array type force sensors.     

Free convective flow on a vertical plate with a constant heat flux in the presence of one or more steps

We carried out an experimental investigation of free convective heat transfer on a vertical plate subjected to a constant heat flux in the presence of one or several rectangular steps. Temperature fields were investigated with the help of a Mach-Zehnder interferometer. During the experiment the Rayleigh number changed from zero to Ra=2.8·10³. The flow was observed by the method of track visualization by means of a laser knife. Durectly behind a step we observed a circulating free convective flow having the shape of two oppositely rotating vortices.Academic Scientific Complex A. V. Luikov Heat and Mass Transfer Institute of the Academy of Sciences of Belarus, Minsk, Belarus. Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 67, Nos. 3–4, pp. 190–196, September–October, 1994.     

Biodegradable Microparticles for Simultaneous Detection of Counterfeit and Deteriorated Edible Products

In an era of globalized trade relations where food and pharmaceutical products cross borders effortlessly, consumers face counterfeit and deteriorated products at elevated rates. This paper presents multifunctional, biodegradable hydrogel microparticles that can provide information on the authenticity and the potential deterioration of the tagged food or pharmaceutical formulations. These microparticles integrate spatially patterned authenticity code with two sensors—the first one detects possible presence of pathogenic microbes through monitoring pH while the second one identifies products stored above optimal temperatures via optical monitoring of the microparticle degradation. Particles are synthesized from a biocompatible polymer and a photoinitiator, dextran modified with 2‐hydroxyethylmethacrylate and riboflavin, respectively, using a continuous, high throughput method stop‐flow lithography. The proposed synthesis approach also enables crosslinking with visible light bringing about additional flexibility to flow lithography. Model liquid and solid food and pharmaceutical products are successfully labeled with microparticles and the functionality of the sensors in aqueous solutions is demonstrated.     

A new perspective on data homogeneity in software cost estimation: a study in the embedded systems domain

Cost estimation and effort allocation are the key challenges for successful project planning and management in software development. Therefore, both industry and the research community have been working on various models and techniques to accurately predict the cost of projects. Recently, researchers have started debating whether the prediction performance depends on the structure of data rather than the models used. In this article, we focus on a new aspect of data homogeneity, “cross- versus within-application domain”, and investigate what kind of training data should be used for software cost estimation in the embedded systems domain. In addition, we try to find out the effect of training dataset size on the prediction performance. Based on our empirical results, we conclude that it is better to use cross-domain data for embedded software cost estimation and the optimum training data size depends on the method used.     

A comparative study for estimating software development effort intervals

Software cost/effort estimation is still an open challenge. Many researchers have proposed various methods that usually focus on point estimates. Until today, software cost estimation has been treated as a regression problem. However, in order to prevent overestimates and underestimates, it is more practical to predict the interval of estimations instead of the exact values. In this paper, we propose an approach that converts cost estimation into a classification problem and that classifies new software projects in one of the effort classes, each of which corresponds to an effort interval. Our approach integrates cluster analysis with classification methods. Cluster analysis is used to determine effort intervals while different classification algorithms are used to find corresponding effort classes. The proposed approach is applied to seven public datasets. Our experimental results show that the hit rate obtained for effort estimation are around 90–100%, which is much higher than that obtained by related studies. Furthermore, in terms of point estimation, our results are comparable to those in the literature although a simple mean/median is used for estimation. Finally, the dynamic generation of effort intervals is the most distinctive part of our study, and it results in time and effort gain for project managers through the removal of human intervention.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Investigation of parameters of an instrument for measuring high-temperature heat fluxes

Results of an experimental investigation of an instrument for measuring high-temperature heat fluxes with a density up to 800 kW/m² are presented.Notation q_inc, Q_inc incident heat flux density - A, , B, , x dimensionless parameters - T_a adiabatic combustion temperature of fuel - H_i instantaneous height of furnace chamber - H full height of furnace chamber - T_f temperature of gases at the furnace outlet - T_f increment in the temperature of gases at the furnace outlet - a_f emissivity of furnace - T_f temperature of flame - ₀ Stefan—Boltzmann constant - T temperature on the heat pipe body - Q supplied power - E_rad sensitivity of sensor - D hourly rate of fuel supplied to the boiler furnace - time Academic Scientific Complex A. V. Luikov Institute of Heat and Mass Transfer of the Academy of Sciences of Belarus, Minsk. I. I. Polzunov Central Boiler and Turbine Institute, St. Petersburg. Scientific and Technical Center Flame-Complex, Ust'-Ilimsk. Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 64, No. 3, pp. 324–329, March, 1993     

Clustering of high throughput gene expression data

High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level. Clearly, clustering can be used in many areas of biological data analysis. However, this paper presents a review of the current clustering algorithms designed especially for analyzing gene expression data. It is also intended to introduce one of the main problems in bioinformatics – clustering gene expression data – to the operations research community.