Detection of competing DNA structures by thermal gradient gel electrophoresis: from self-association to triple helix formation by (G,A)-containing oligonucleotides

Sequence-specific recognition of DNA can be achieved by triple helix-forming oligonucleotides that bind to the major groove of double-helical DNA. These oligonucleotides have been used as sequence-specific DNA ligands for various purposes, including sequence-specific gene regulation in the so-called ‘antigene strategy’. In particular, (G,A)-containing oligonucleotides can form stable triple helices under physiological conditions. However, triplex formation may be in competition with self-association of these oligonucleotides. For biological applications it would be interesting to identify the conditions under which one structure is favoured as compared to the other(s). Here we have directly studied competition between formation of a parallel (G,A) homoduplex and that of a triple helix by a 13 nt (G,A)-containing oligonucleotide. Temperature gradient gel electrophoresis allows simultaneous detection of competition between the two structures, because of their different temperature dependencies and gel electrophoretic mobilities, and characterisation of this competition.

Fluorescent quenching-based quantitative detection of specific DNA/RNA using a BODIPY® FL-labeled probe or primer

We have developed a simple method for the quantitative detection of specific DNA or RNA molecules based on the finding that BODIPY® FL fluorescence was quenched by its interaction with a uniquely positioned guanine. This approach makes use of an oligonucleotide probe or primer containing a BODIPY® FL-modified cytosine at its 5′-end. When such a probe was hybridized with a target DNA, its fluorescence was quenched by the guanine in the target, complementary to the modified cytosine, and the quench rate was proportional to the amount of target DNA. This widely applicable technique will be used directly with larger samples or in conjunction with the polymerase chain reaction to quantify small DNA samples.

Detection of mitochondrial single nucleotide polymorphisms using a primer elongation reaction on oligonucleotide microarrays

We have developed a novel allele-specific primer elongation protocol using a DNA polymerase on oligonucleotide chips. Oligonucleotide primers carrying polymorphic sites at their free 3́end were covalently bound to glass slides. The generation of single-stranded targets of genomic DNA containing single nuclotide polymorphisms (SNPs) to be typed was achieved by an asymmetric PCR reaction or exonuclease treatment of phosphothioate (PTO)-modified PCR products. In the presence of DNA polymerase and all four dNTPs, with Cy3-dUTP replacing dTTP, allele-specific extension of the immobilized primers took place along a stretch of target DNA sequence. The yield of elongated products was increased by repeated reaction cycles. We performed multiplexed assays with many small DNA targets, or used single targets of up to 4.4 kb mitochondrial DNA (mtDNA) sequence to detect multiple SNPs in one reaction. The latter approach greatly simplifies preamplification of SNP-containing regions, thereby providing a framework for typing hundreds of mtDNA polymorphisms.

Detection and determination of oligonucleotide triplex formation-mediated transcription-coupled DNA repair in HeLa nuclear extracts

Transcription-coupled repair (TCR) plays an important role in removing DNA damage from actively transcribed genes. It has been speculated that TCR is the most important mechanism for repairing DNA damage in non-dividing cells such as neurons. Therefore, abnormal TCR may contribute to the development of many age-related and neurodegenerative diseases. However, the molecular mechanism of TCR is not well understood. Oligonucleotide DNA triplex formation provides an ideal system to dissect the molecular mechanism of TCR since triplexes can be formed in a sequence-specific manner to inhibit transcription of target genes. We have recently studied the molecular mechanism of triplex-forming oligonucleotide (TFO)-mediated TCR in HeLa nuclear extracts. Using plasmid constructs we demonstrate that the level of TFO-mediated DNA repair activity is directly correlated with the level of transcription of the plasmid in HeLa nuclear extracts. TFO-mediated DNA repair activity was further linked with transcription since the presence of rNTPs in the reaction was essential for AG30-mediated DNA repair activity in HeLa nuclear extracts. The involvement of individual components, including TFIID, TFIIH, RNA polymerase II and xeroderma pigmentosum group A (XPA), in the triplex-mediated TCR process was demonstrated in HeLa nuclear extracts using immunodepletion assays. Importantly, our studies also demonstrated that XPC, a component involved in global genome DNA repair, is involved in the AG30-mediated DNA repair process. The results obtained in this study provide an important new understanding of the molecular mechanisms involved in the TCR process in mammalian cells.

Optimizing the detection of nascent transcripts by RNA fluorescence in situ hybridization

An unusual feature of the mammalian genome is the number of genes exhibiting monoallelic expression. Recently random monoallelic expression of autosomal genes has been reported for olfactory and Ly-49 NK receptor genes, as well as for Il-2, Il-4 and Pax5. RNA fluorescence in situ hybridization (FISH) has been exploited to monitor allelic expression by visualizing the number of sites of transcription in individual nuclei. However, the sensitivity of this technique is difficult to determine for a given gene. We show that by combining DNA and RNA FISH it is possible to control for the hybridization efficiency and the accessibility and visibility of fluorescent probes within the nucleus.

Immunohistochemical detection of 4-hydroxynonenal protein adducts in Parkinson disease.

There is growing evidence that oxidative stress and mitochondrial respiratory failure with attendant decrease in energy output are implicated in nigral neuronal death in Parkinson disease (PD). It is not known, however, which cellular elements (neurons or glial cells) are major targets of oxygen-mediated damage. 4-Hydroxy-2-nonenal (HNE) was shown earlier to react with proteins to form stable adducts that can be used as markers of oxidative stress-induced cellular damage. We report here results of immunochemical studies using polyclonal antibodies directed against HNE-protein conjugates to label the site of oxidative damage in control subjects (ages 18-99 years) and seven patients that died of PD (ages 57-78 years). All the nigral melanized neurons in one of the midbrain sections were counted and classified into three groups according to the intensity of immunostaining for HNE-modified proteins--i.e., no staining, weak staining, and intensely positive staining. On average, 58% of nigral neurons were positively stained for HNE-modified proteins in PD; in contrast only 9% of nigral neurons were positive in the control subjects; the difference was statistically significant (Mann-Whitney U test; P < 0.01). In contrast to the substantia nigra, the oculomotor neurons in the same midbrain sections showed no or only weak staining for HNE-modified proteins in both PD and control subjects; young control subjects did not show any immunostaining; however, aged control subjects showed weak staining in the oculomotor nucleus, suggesting age-related accumulation of HNE-modified proteins in the neuron. Our results indicate the presence of oxidative stress within nigral neurons in PD, and this oxidative stress may contribute to nigral cell death.

Early p53 alterations in mouse skin carcinogenesis by UVB radiation: immunohistochemical detection of mutant p53 protein in clusters of preneoplastic epidermal cells.

High levels of the p53 protein are immunohistochemically detectable in a majority of human nonmelanoma skin cancers and UVB-induced murine skin tumors. These increased protein levels are often associated with mutations in the conserved domains of the p53 gene. To investigate the timing of the p53 alterations in the process of UVB carcinogenesis, we used a well defined murine model (SKH:HR1 hairless mice) in which the time that tumors appear is predictable from the UVB exposures. The mice were subjected to a series of daily UVB exposures, either for 17 days or for 30 days, which would cause skin tumors to appear around 80 or 30 weeks, respectively. In the epidermis of these mice, we detected clusters of cells showing a strong immunostaining of the p53 protein, as measured with the CM-5 polyclonal antiserum. This cannot be explained by transient accumulation of the normal p53 protein as a physiological response to UVB-induced DNA damage. In single exposure experiments the observed transient CM-5 immunoreactivity lasted for only 3 days and was not clustered, whereas these clusters were still detectable as long as 56 days after 17 days of UVB exposure. In addition, approximately 70% of these patches reacted with the mutant-specific monoclonal antibody PAb240, whereas transiently induced p53-positive cells did not. In line with indicative human data, these experimental results in the hairless mouse model unambiguously demonstrate that constitutive p53 alterations are causally related to chronic UVB exposure and that they are a very early event in the induction of skin cancer by UVB radiation.

Strain and damage sensing properties on multifunctional cement composites with CNF admixture

Both strain and damage sensing properties on carbon nanofiber cement composites (CNFCC) are reported in the present paper. Strain sensing tests were first made on the material’s elastic range. The applied loading levels have been previously calculated from mechanical strength tests. The effect of several variables on the strain-sensing function was studied, e.g. cement pastes curing age, current density, loading rate or maximum stress applied. All these parameters were discussed using the gage factor as reference. After this first set of elastic experiments, the same specimens were gradually loaded until material’s failure. At the same time both strain and resistivity were measured. The former was controlled using strain gages, and the latter using a multimeter on a four probe setup. The aim of these tests was to prove the sensitivity of these CNF composites to sense their own damage, i.e. check the possibility of fabricating structural damage sensors with CNFCC’s. All samples with different CNF dosages showed good strain-sensing capacities for curing periods of 28 days. Furthermore, a 2%CNF reinforced cement paste has been sensitive to its own structural damage.

Using the damage from 2010 Haiti earthquake for calibrating vulnerability models of typical structures in Port-au-Prince (Haiti)

After the 2010 Haiti earthquake, that hits the city of Port-au-Prince, capital city of Haiti, a multidisciplinary working group of specialists (seismologist, geologists, engineers and architects) from different Spanish Universities and also from Haiti, joined effort under the SISMO-HAITI project (financed by the Universidad Politecnica de Madrid), with an objective: Evaluation of seismic hazard and risk in Haiti and its application to the seismic design, urban planning, emergency and resource management. In this paper, as a first step for a structural damage estimation of future earthquakes in the country, a calibration of damage functions has been carried out by means of a two-stage procedure. After compiling a database with observed damage in the city after the earthquake, the exposure model (building stock) has been classified and through an iteratively two-step calibration process, a specific set of damage functions for the country has been proposed. Additionally, Next Generation Attenuation Models (NGA) and Vs30 models have been analysed to choose the most appropriate for the seismic risk estimation in the city. Finally in a next paper, these functions will be used to estimate a seismic risk scenario for a future earthquake.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Detection and mapping of burnt areas from time series of MODIS-derived NDVI data in a Mediterranean region

Moderate resolution remote sensing data, as provided by MODIS, can be used to detect and map active or past wildfires from daily records of suitable combinations of reflectance bands. The objective of the present work was to develop and test simple algorithms and variations for automatic or semiautomatic detection of burnt areas from time series data of MODIS biweekly vegetation indices for a Mediterranean region. MODIS-derived NDVI 250m time series data for the Valencia region, East Spain, were subjected to a two-step process for the detection of candidate burnt areas, and the results compared with available fire event records from the Valencia Regional Government. For each pixel and date in the data series, a model was fitted to both the previous and posterior time series data. Combining drops between two consecutive points and 1-year average drops, we used discrepancies or jumps between the pre and post models to identify seed pixels, and then delimitated fire scars for each potential wildfire using an extension algorithm from the seed pixels. The resulting maps of the detected burnt areas showed a very good agreement with the perimeters registered in the database of fire records used as reference. Overall accuracies and indices of agreement were very high, and omission and commission errors were similar or lower than in previous studies that used automatic or semiautomatic fire scar detection based on remote sensing. This supports the effectiveness of the method for detecting and mapping burnt areas in the Mediterranean region.

Feature selection by multi-objective optimisation: Application to network anomaly detection by hierarchical self-organising maps

Feature selection is an important and active issue in clustering and classification problems. By choosing an adequate feature subset, a dataset dimensionality reduction is allowed, thus contributing to decreasing the classification computational complexity, and to improving the classifier performance by avoiding redundant or irrelevant features. Although feature selection can be formally defined as an optimisation problem with only one objective, that is, the classification accuracy obtained by using the selected feature subset, in recent years, some multi-objective approaches to this problem have been proposed. These either select features that not only improve the classification accuracy, but also the generalisation capability in case of supervised classifiers, or counterbalance the bias toward lower or higher numbers of features that present some methods used to validate the clustering/classification in case of unsupervised classifiers. The main contribution of this paper is a multi-objective approach for feature selection and its application to an unsupervised clustering procedure based on Growing Hierarchical Self-Organising Maps (GHSOMs) that includes a new method for unit labelling and efficient determination of the winning unit. In the network anomaly detection problem here considered, this multi-objective approach makes it possible not only to differentiate between normal and anomalous traffic but also among different anomalies. The efficiency of our proposals has been evaluated by using the well-known DARPA/NSL-KDD datasets that contain extracted features and labelled attacks from around 2 million connections. The selected feature sets computed in our experiments provide detection rates up to 99.8% with normal traffic and up to 99.6% with anomalous traffic, as well as accuracy values up to 99.12%.

A high-resolution binocular video-oculography system: assessment of pupillary light reflex and detection of an early incomplete blink and an upward eye movement

Background: The pupillary light reflex characterizes the direct and consensual response of the eye to the perceived brightness of a stimulus. It has been used as indicator of both neurological and optic nerve pathologies. As with other eye reflexes, this reflex constitutes an almost instantaneous movement and is linked to activation of the same midbrain area. The latency of the pupillary light reflex is around 200 ms, although the literature also indicates that the fastest eye reflexes last 20 ms. Therefore, a system with sufficiently high spatial and temporal resolutions is required for accurate assessment. In this study, we analyzed the pupillary light reflex to determine whether any small discrepancy exists between the direct and consensual responses, and to ascertain whether any other eye reflex occurs before the pupillary light reflex. Methods: We constructed a binocular video-oculography system two high-speed cameras that simultaneously focused on both eyes. This was then employed to assess the direct and consensual responses of each eye using our own algorithm based on Circular Hough Transform to detect and track the pupil. Time parameters describing the pupillary light reflex were obtained from the radius time-variation. Eight healthy subjects (4 women, 4 men, aged 24–45) participated in this experiment. Results: Our system, which has a resolution of 15 microns and 4 ms, obtained time parameters describing the pupillary light reflex that were similar to those reported in previous studies, with no significant differences between direct and consensual reflexes. Moreover, it revealed an incomplete reflex blink and an upward eye movement at around 100 ms that may correspond to Bell’s phenomenon. Conclusions: Direct and consensual pupillary responses do not any significant temporal differences. The system and method described here could prove useful for further assessment of pupillary and blink reflexes. The resolution obtained revealed the existence reported here of an early incomplete blink and an upward eye movement.

Decreased Perifoveal Sensitivity Detected by Microperimetry in Patients Using Hydroxychloroquine and without Visual Field and Fundoscopic Anomalies

Purpose. To evaluate the usefulness of microperimetry in the early detection of the ocular anomalies associated with the use of hydroxychloroquine. Methods. Prospective comparative case series study comprising 14 healthy eyes of 7 patients (group A) and 14 eyes of 7 patients under treatment with hydroxychloroquine for the treatment of rheumatologic diseases and without fundoscopic or perimetric anomalies (group B). A comprehensive ophthalmological examination including microperimetry (MP) and spectraldomain optical coherence tomography was performed in both groups. Results. No significant differences were found in mean MP foveal sensitivity between groups (P = 0.18). However, mean MP overall sensitivity was significantly higher in group A (29.05 ± 0.57 dB versus group B, 26.05 ± 2.75 dB; P < 0.001). Significantly higher sensitivity values were obtained in group A in comparison to group B for the three eccentric loci evaluated (P < 0.001). Conclusion. Microperimetry seems to be a useful tool for the early detection of retinal damage in patients treated with hydroxychloroquine.

Algorithm for the detection of outliers based on the theory of rough sets

Outliers are objects that show abnormal behavior with respect to their context or that have unexpected values in some of their parameters. In decision-making processes, information quality is of the utmost importance. In specific applications, an outlying data element may represent an important deviation in a production process or a damaged sensor. Therefore, the ability to detect these elements could make the difference between making a correct and an incorrect decision. This task is complicated by the large sizes of typical databases. Due to their importance in search processes in large volumes of data, researchers pay special attention to the development of efficient outlier detection techniques. This article presents a computationally efficient algorithm for the detection of outliers in large volumes of information. This proposal is based on an extension of the mathematical framework upon which the basic theory of detection of outliers, founded on Rough Set Theory, has been constructed. From this starting point, current problems are analyzed; a detection method is proposed, along with a computational algorithm that allows the performance of outlier detection tasks with an almost-linear complexity. To illustrate its viability, the results of the application of the outlier-detection algorithm to the concrete example of a large database are presented.