Integrating testing techniques through process programming

Integration of multiple testing techniques is required to demonstrate high quality of software. Technique integration has three basic goals: incremental testing capabilities, extensive error detection, and cost-effective application. We are experimenting with the use of process programming as a mechanism of integrating testing techniques. Having set out to integrate DATA FLOW testing and RELAY, we proposed synergistic use of these techniques to achieve all three goals. We developed a testing process program much as we would develop a software product from requirements through design to implementation and evaluation. We found process programming to be effective for explicitly integrating the techniques and achieving the desired synergism. Used in this way, process programming also mitigates many of the other problems that plague testing in the software development process

Amplification of real-time high resolution melting analysis PCR method for polycystic kidney disease (PKD) gene mutations in autosomal dominant polycystic kidney disease patients

PKD1 and PKD2 are the two genes responsible for the development of autosomal dominant polycystic kidney disease (ADPKD). PKD1 gene mutations accounts for ≈85% of all ADPKD cases, while the remaining ≈15% of cases is caused by mutations in the PKD2 gene. Genotyping for PKD1 and PKD2 mutations was usually identified using conventional polymerase chain reaction (PCR) or PCR-single stranded conformation polymorphisms (SSCP) methods. In this study, we assessed the usefulness of eight common primers amplifying the respective genes in real-time high resolution melting analysis PCR (real-time HRMA PCR) in terms of time, cost and sensitivity with respect to PCR-SSCP method. We found that case sample can easily be differentiated from control sample by melting curve profile difference, although a primer was found to be less useful. We concluded that real-time HRMA PCR is a rapid and sensitive method to categorize samples based on the melting curve profiles with comparable sensitivity to conventional PCR-SSCP.Key words: Autosomal dominant polycystic kidney disease (ADPKD), real-time PCR, high resolution melting analysis, PKD1, PKD2

LC-MS analysis to determine the biodistribution of a polymer coated ilomastat ocular implant

Ilomastat is a matrix metalloproteinase inhibitor (MMPi) that has shown the potential to inhibit scarring (fibrosis) by mediating healing after injury or surgery. A long lasting ocular implantable pharmaceutical formulation of ilomastat is being developed to mediate the healing process to prevent scarring after glaucoma filtration surgery. The ilomastat implant was coated with water permeable and biocompatible phosphoryl choline polymer (PC1059) displayed extended slow release of ilomastat in vitro and in vivo. The ocular distribution of ilomastat from the implant in rabbits at day 30 post surgery was determined by the extraction of ilomastat and its internal standard marimastat from the ocular tissues, plasma, aqueous humour and vitreous fluid followed by capillary-flow liquid chromatography (cap-LC), the column effluent was directed into a triple quadrupole mass spectrometer operating in product scan mode. The lower limits of quantification (LLOQs) were 0.3 pg/μL for ocular fluids and plasma, and 3 pg/mg for ocular tissues. The extraction recoveries were 90-95% for ilomastat and its internal standard from ocular tissues. Ilomastat was found in ocular fluids and tissues at day 30 after surgery. The level of ilomastat was 18 times higher in the aqueous humour than vitreous humour. The concentration ranking of ilomastat in the ocular tissues was sclera > bleb conjunctiva > conjunctiva (rest of the eye) > cornea. Mass spectrometry analysis to confirm the presence of ilomastat in the ocular tissues and fluids at day 30 post-surgery establishes the extended release of ilomastat can be achieved in vivo, which is crucial information for optimisation of the ilomastat coated implant

An Ilomastat-CD Eye Drop Formulation to Treat Ocular Scarring

PURPOSE: The purpose of this study was to develop a topical matrix metalloproteinase inhibitor preparation for antiscarring therapy. METHODS: The broad spectrum matrix metalloproteinase inhibitor ilomastat was formulated using 2-hydroxypropyl-β-cyclodextrin in aqueous solution. In vitro activity of ilomastat-cyclodextrin (ilomastat-CD) was examined using fibroblasts seeded in collagen. Permeation of ilomastat-CD eye drop through pig eye conjunctiva was confirmed using Franz diffusion cells. Ilomastat-CD eye drop was applied to rabbit eyes in vivo, and the distribution of ilomastat in ocular tissues and fluids was determined by liquid chromatography-mass spectroscopy. RESULTS: The aqueous solubility of ilomastat-CD was ∼1000 μg/mL in water and 1400 μg/mL in PBS (pH 7.4), which is greater than ilomastat alone (140 and 160 μg/mL in water and PBS, respectively). The in vitro activity of ilomastat-CD to inhibit collagen contraction in the presence of human Tenon fibroblast cells was unchanged compared to uncomplexed ilomastat. Topically administered ilomastat-CD in vivo to rabbit eyes resulted in a therapeutic concentration of ilomastat being present in the sclera and conjunctiva and within the aqueous humor. CONCLUSIONS: Ilomastat-CD has the potential to be formulated as an eye drop for use as an antifibrotic, which may have implications for the prevention of scarring in many settings, for example glaucoma filtration surgery

Local Ugandan Production of Stable 0.2% Chlorhexidine Eye Drops

Purpose: The purpose of this study was to develop a protocol to prepare buffered chlorhexidine (CHX) eye drops (0.2% w/v) in the United Kingdom that can be reproduced at a production facility in Uganda. Buffered CHX eye drops can prevent CHX degradation and improve ocular tolerability during the treatment of fungal keratitis. Methods: Buffered CHX eye drops in amber glass containers were prepared using sodium acetate buffer at pH 5.90 to 6.75. Two commercial CHX solutions and CHX in water were used as controls. Eye drops were stored at 40°C (70% humidity, 21 months) in the United Kingdom and at ambient temperature in Uganda (30 months). High-performance liquid chromatography was used to determine CHX stability over time, and pH was monitored. Sterility was achieved using an autoclave (121°C, 15 minutes) and water bath (100°C, 30 minutes). Results: The pH of acetate-buffered CHX eye drops did not change over 21 months a40°C or at ambient temperature (30 months), whereas the pH of the unbuffered aqueouCHX displayed significant fluctuations, with an increase in acidity. The CHX concentration remained the same in both buffered and unbuffered eye-drop solutions. Eye dropsterilization was successful using an autoclave and a water bath. Conclusions: Stable, sterile, buffered CHX eye drops (pH 6.75) were successfully prepared first in the United Kingdom and then reproducibly in Uganda. This eye drops can be prepared in a hospital or pharmacy setting with limited resources, thus providing a cost-effective treatment for fungal keratitis. Translational Relevance: A protocol has been developed to prepare buffered CHX eydrops in low-and middle-income countries to treat fungal keratitis

The Cyborg Astrobiologist: Testing a Novelty-Detection Algorithm on Two Mobile Exploration Systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah

(ABRIDGED) In previous work, two platforms have been developed for testing computer-vision algorithms for robotic planetary exploration (McGuire et al. 2004b,2005; Bartolo et al. 2007). The wearable-computer platform has been tested at geological and astrobiological field sites in Spain (Rivas Vaciamadrid and Riba de Santiuste), and the phone-camera has been tested at a geological field site in Malta. In this work, we (i) apply a Hopfield neural-network algorithm for novelty detection based upon color, (ii) integrate a field-capable digital microscope on the wearable computer platform, (iii) test this novelty detection with the digital microscope at Rivas Vaciamadrid, (iv) develop a Bluetooth communication mode for the phone-camera platform, in order to allow access to a mobile processing computer at the field sites, and (v) test the novelty detection on the Bluetooth-enabled phone-camera connected to a netbook computer at the Mars Desert Research Station in Utah. This systems engineering and field testing have together allowed us to develop a real-time computer-vision system that is capable, for example, of identifying lichens as novel within a series of images acquired in semi-arid desert environments. We acquired sequences of images of geologic outcrops in Utah and Spain consisting of various rock types and colors to test this algorithm. The algorithm robustly recognized previously-observed units by their color, while requiring only a single image or a few images to learn colors as familiar, demonstrating its fast learning capability.Comment: 28 pages, 12 figures, accepted for publication in the International Journal of Astrobiolog

Empirical Evaluation of the Difficulty of Finding a Good Value of k for the Nearest Neighbor

As an analysis of the classification accuracy bound for the Nearest Neighbor technique, in this work we have studied if it is possible to find a good value of the parmeter k for each example according to their attribute values. Or at least, if there is a pattern for the parameter k in the original search space. We have carried out different approaches based onthe Nearest Neighbor technique and calculated the prediction accuracy for a group of databases from the UCI repository. Based on the experimental results of our study, we can state that, in general, it is not possible to know a priori a specific value of k to correctly classify an unseen example

Data Mining and Machine Learning in Astronomy

We review the current state of data mining and machine learning in astronomy. 'Data Mining' can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding the potential to fully exploit the exponentially increasing amount of available data, promising great scientific advance. However, if misused, it can be little more than the black-box application of complex computing algorithms that may give little physical insight, and provide questionable results. Here, we give an overview of the entire data mining process, from data collection through to the interpretation of results. We cover common machine learning algorithms, such as artificial neural networks and support vector machines, applications from a broad range of astronomy, emphasizing those where data mining techniques directly resulted in improved science, and important current and future directions, including probability density functions, parallel algorithms, petascale computing, and the time domain. We conclude that, so long as one carefully selects an appropriate algorithm, and is guided by the astronomical problem at hand, data mining can be very much the powerful tool, and not the questionable black box.Comment: Published in IJMPD. 61 pages, uses ws-ijmpd.cls. Several extra figures, some minor additions to the tex

Improving the minimum description length inference of phrase-based translation models

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-19390-8_25We study the application of minimum description length (MDL) inference to estimate pattern recognition models for machine translation. MDL is a theoretically-sound approach whose empirical results are however below those of the state-of-the-art pipeline of training heuristics. We identify potential limitations of current MDL procedures and provide a practical approach to overcome them. Empirical results support the soundness of the proposed approach.Work supported by the EU 7th Framework Programme (FP7/2007–2013) under the CasMaCat project (grant agreement no 287576), by Spanish MICINN under grant TIN2012-31723, and by the Generalitat Valenciana under grant ALMPR (Prometeo/2009/014).Gonzalez Rubio, J.; Casacuberta Nolla, F. (2015). Improving the minimum description length inference of phrase-based translation models. En Pattern Recognition and Image Analysis: 7th Iberian Conference, IbPRIA 2015, Santiago de Compostela, Spain, June 17-19, 2015, Proceedings. Springer International Publishing. 219-227. https://doi.org/10.1007/978-3-319-19390-8 25S21922