Targeting histone deacetylases for the treatment of disease : Epigenetics Review Series

The 'histone code' is a well-established hypothesis describing the idea that specific patterns of post-translational modifications to histones act like a molecular 'code' recognized and used by non-histone proteins to regulate specific chromatin functions. One modification, which has received significant attention, is that of histone acetylation. The enzymes that regulate this modification are described as lysine acetyltransferases or KATs, and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. The pro-inflammatory environment is increasingly being recognized as a critical element for both degenerative diseases and cancer. The present review will discuss the current knowledge surrounding the clinical potential and current development of histone deacetylases for the treatment of diseases for which a pro-inflammatory environment plays important roles, and the molecular mechanisms by which such inhibitors may play important functions in modulating the pro-inflammatory environment. © 2009 Foundation for Cellular and Molecular Medicine/Blackwell Publishing Ltd.

A single institution experience of streptozocin/fluorouracil combination chemotherapy : a case series

Background The combination chemotherapy regimen of streptozocin and 5-fluorouracil (FU/STZ) has been used for the treatment of metastatic neuroendocrine tumours. Aim The aim of this study was to analyse the use of this regimen in a tertiary oncology referral centre over a 10-year period. Method We retrospectively analysed nine cases from February 2000 to May 2010. Patient demographics, chemotherapy schedule, toxicities, progression-free and overall survival were tabulated for each patient. Result The median progression-free survival was 17 months (range 3-48+ months), and overall survival 31 months (range 12-53+ months) with no toxicity related deaths. Conclusion FU/STZ was a well-tolerated regimen that produced significant benefit in the setting of metastatic and progressive disease. Our case series demonstrated comparable progression-free survival and overall survival in relation to randomized controlled studies and previous case series. © Royal Academy of Medicine in Ireland 2011.

A comparison of the histochemical and image-derived proteoglycan content of articular cartilage

There are several methods for determining the proteoglycan content of cartilage in biomechanics experiments. Many of these include assay-based methods and the histochemistry or spectrophotometry protocol where quantification is biochemically determined. More recently a method based on extracting data to quantify proteoglycan content has emerged using the image processing algorithms, e.g., in ImageJ, to process histological micrographs, with advantages including time saving and low cost. However, it is unknown whether or not this image analysis method produces results that are comparable to those obtained from the biochemical methodology. This paper compares the results of a well-established chemical method to those obtained using image analysis to determine the proteoglycan content of visually normal (n=33) and their progressively degraded counterparts with the protocols. The results reveal a strong linear relationship with a regression coefficient (R2) = 0.9928, leading to the conclusion that the image analysis methodology is a viable alternative to the spectrophotometry.

A suite of novel promoters and terminators for plant biotechnology II. The pPLEX series for use in monocots

A suite of plant expression vectors (pPLEX), constructed from the gene regulation signals from subterranean clover stunt virus (SCSV) genome, has previously been used in dicot transformation for a variety of applications in plant biotechnology. To assess their use for the transformation of monocots, a number of modifications were made to the basic vector series and assessed in rice. In their unmodified forms, the SCSV promoters directed low levels of gene expression, however, insertion of an intron between the promoter and the transgene open reading frame (analogous to the rice actin and maize ubiquitin promoter systems) increased transgene expression 50-fold. The expression patterns from the intron-modified SCSV (segments 4 and 7) promoters were very similar to those directed by the actin or ubiquitin promoters. All promoter systems investigated directed expression that appeared to be constitutive within leaf tissue, and localised to the epidermal and vascular tissues of the root. The pPLEX vectors described here are an important counterpart to the dicot pPLEX series and have the potential to be useful in monocot research and biotechnology.

Image segmentation and pose estimation of humans in video

This thesis introduces improved techniques towards automatically estimating the pose of humans from video. It examines a complete workflow to estimating pose, from the segmentation of the raw video stream to extract silhouettes, to using the silhouettes in order to determine the relative orientation of parts of the human body. The proposed segmentation algorithms have improved performance and reduced complexity, while the pose estimation shows superior accuracy during difficult cases of self occlusion.

Power profiles of multifocal contact lenses and their interpretation

Purpose Many contact lens (CL) manufacturers produce simultaneous-image lenses in which power varies either smoothly or discontinuously with zonal radius. We present in vitro measurements of some recent CLs and discuss how power profiles might be approximated in terms of nominal distance corrections, near additions, and on-eye visual performance. Methods Fully hydrated soft, simultaneous-image CLs from four manufacturers (Air Optix AQUA, Alcon; PureVision multifocal, Bausch & Lomb; Acuvue OASYS for Presbyopia, Vistakon; Biofinity multifocal- ‘‘D’’ design, Cooper Vision) were measured with a Phase focus Lens Profiler (Phase Focus Ltd., Sheffield,UK) in a wet cell and powerswere corrected to powers in air. All lenses had zero labeled power for distance. Results Sagittal power profiles revealed that the ‘‘low’’ add PureVision and Air Optix lenses exhibit smooth (parabolic) profiles, corresponding to negative spherical aberration. The ‘‘mid’’ and ‘‘high’’ add PureVision and Air Optix lenses have biaspheric designs, leading to different rates of power change for the central and peripheral portions. All OASYS lenses display a series of concentric zones, separated by abrupt discontinuities; individual profiles can be constrained between two parabolically decreasing curves, each giving a valid description of the power changes over alternate annular zones. Biofinity lenses have constant power over the central circular region of radius 1.5 mm, followed by an annular zone where the power increases approximately linearly, the gradient increasing with the add power, and finally an outer zone showing a slow, linear increase in power with a gradient being almost independent of the add power. Conclusions The variation in power across the simultaneous-image lenses produces enhanced depth of focus. The throughfocusnature of the image, which influences the ‘‘best focus’’ (distance correction) and the reading addition, will vary with several factors, including lens centration, the wearer’s pupil diameter, and ocular aberrations, particularly spherical aberration; visual performance with some designs may show greater sensitivity to these factors.

Dealing with shadows : capturing intrinsic scene appearance for image-based outdoor localisation

In outdoor environments shadows are common. These typically strong visual features cause considerable change in the appearance of a place, and therefore confound vision-based localisation approaches. In this paper we describe how to convert a colour image of the scene to a greyscale invariant image where pixel values are a function of underlying material property not lighting. We summarise the theory of shadow invariant images and discuss the modelling and calibration issues which are important for non-ideal off-the-shelf colour cameras. We evaluate the technique with a commonly used robotic camera and an autonomous car operating in an outdoor environment, and show that it can outperform the use of ordinary greyscale images for the task of visual localisation.

Optimal camera planning under versatile user constraints in multi-camera image processing systems

The selection of optimal camera configurations (camera locations, orientations, etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we propose a statistical framework of the problem as well as propose a trans-dimensional simulated annealing algorithm to effectively deal with it. We compare our approach with a state-of-the-art method based on binary integer programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than two alternative heuristics designed to deal with the scalability issue of BIP. Last, we show the versatility of our approach using a number of specific scenarios.

Training-free probability models for whole-image based place recognition

Whole-image descriptors such as GIST have been used successfully for persistent place recognition when combined with temporal filtering or sequential filtering techniques. However, whole-image descriptor localization systems often apply a heuristic rather than a probabilistic approach to place recognition, requiring substantial environmental-specific tuning prior to deployment. In this paper we present a novel online solution that uses statistical approaches to calculate place recognition likelihoods for whole-image descriptors, without requiring either environmental tuning or pre-training. Using a real world benchmark dataset, we show that this method creates distributions appropriate to a specific environment in an online manner. Our method performs comparably to FAB-MAP in raw place recognition performance, and integrates into a state of the art probabilistic mapping system to provide superior performance to whole-image methods that are not based on true probability distributions. The method provides a principled means for combining the powerful change-invariant properties of whole-image descriptors with probabilistic back-end mapping systems without the need for prior training or system tuning.

Impact of cognitive behaviour therapy via mail for cessation of benzodiazepine use : a series of case reports

Benzodiazepines are widely prescribed to manage sleep disorders, anxiety and muscular tension. While providing short-term relief, continued use induces tolerance and withdrawal, and in older users, increases the risk of falls. However, long-term prescription remains common, and effective interventions are not widely available. This study developed a self-managed cognitive behaviour therapy package for cessation of benzodiazepine use delivered to participants via mail (M-CBT) and trialled its effectiveness as an adjunct to a general practitioner (GP)-managed dose reduction schedule. In the pilot trial, participants were randomly assigned to GP management with immediate or delayed M-CBT. Significant recruitment and engagement problems were experienced, and only three participants were allocated to each condition. After immediate M-CBT, two participants ceased use, while none receiving delayed treatment reduced daily intake by more than 50%. Across the sample, doses at 12 months remained significantly lower than baseline, and qualitative feedback from participants was positive. While M-CBT may have promise, improved engagement of GPs and participants is needed for this approach to substantially impact on community-wide benzodiazepine use.

Using image quality metrics to detect smoke-affected laser data

Field robots often rely on laser range finders (LRFs) to detect obstacles and navigate autonomously. Despite recent progress in sensing technology and perception algorithms, adverse environmental conditions, such as the presence of smoke, remain a challenging issue for these robots. In this paper, we investigate the possibility to improve laser-based perception applications by anticipating situations when laser data are affected by smoke, using supervised learning and state-of-the-art visual image quality analysis. We propose to train a k-nearest-neighbour (kNN) classifier to recognise situations where a laser scan is likely to be affected by smoke, based on visual data quality features. This method is evaluated experimentally using a mobile robot equipped with LRFs and a visual camera. The strengths and limitations of the technique are identified and discussed, and we show that the method is beneficial if conservative decisions are the most appropriate.

Perception Quality Evaluation with Visual and Infrared Cameras in Challenging Environmental Conditions

This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.

Synthesis, photophysical and electrochemical properties of aza-boron-diquinomethene complexes

A series of aza-boron-diquinomethene (aza-BODIQU) complexes with different aryl-substituents (B1–B6) were synthesized and characterized. Their photophysical properties were investigated systematically via spectroscopic and theoretical methods. All complexes exhibit strong 1π–π* absorption bands and intense fluorescent emission bands in the visible spectral region at room temperature. The fluorescence spectra in solution show the mirror image features of the S0→S1 absorption bands, which can be assigned to the 1π–π*/1ICT (intramolecular charge transfer) emitting states. Except for B6, all complexes exhibit high photoluminescence quantum yields (ΦPL = 0.47–0.93). The spectroscopic studies and theoretical calculations indicate that the photophysical properties of these aza-BODIQUs can be tuned by the appended aryl-substituents, which would be useful for rational design of boron–fluorine complexes with high emission quantum yield for organic light-emitting applications.

Choroidal thickness in myopic and non-myopic children assessed with enhanced depth imaging optical coherence tomography

Purpose To examine choroidal thickness (ChT) and its topographical variation across the posterior pole in myopic and non-myopic children. Methods One hundred and four children aged 10-15 years of age (mean age 13.1 ± 1.4 years) had ChT measured using enhanced depth imaging optical coherence tomography (OCT). Forty one children were myopic (mean spherical equivalent -2.4 ± 1.5 D) and 63 non-myopic (mean +0.3 ± 0.3 D). Two series of 6 radial OCT line scans centred on the fovea were assessed for each child. Subfoveal ChT and ChT across a series of parafoveal zones over the central 6mm of the posterior pole were determined through manual image segmentation. Results Subfoveal ChT was significantly thinner in myopes (mean 303 ± 79 µm) compared to non-myopes (mean 359 ± 77 µm) (p<0.0001). Multiple regression analysis revealed both refractive error (r = 0.39, p<0.001) and age (r = 0.21, p = 0.02) were positively associated with subfoveal ChT. ChT also exhibited significant topographical variations, with the choroid being thicker in more central regions. The thinnest choroid was typically observed in nasal (mean 286 ± 77 µm) and inferior-nasal (306 ± 79 µm) locations, and the thickest in superior (346 ± 79 µm) and superior-temporal (341 ± 74 µm) locations. The difference in ChT between myopic and non-myopic children was significantly greater in central foveal regions compared to more peripheral regions (>3 mm diameter) (p<0.001). Conclusions Myopic children have significantly thinner choroids compared to non-myopic children of similar age, particularly in central foveal regions. The magnitude of difference in choroidal thickness associated with myopia appears greater than would be predicted by a simple passive choroidal thinning with axial elongation.

Towards training-free appearance-based localization : probabilistic models for whole-image descriptors

Whole image descriptors have recently been shown to be remarkably robust to perceptual change especially compared to local features. However, whole-image-based localization systems typically rely on heuristic methods for determining appropriate matching thresholds in a particular environment. These environment-specific tuning requirements and the lack of a meaningful interpretation of these arbitrary thresholds limits the general applicability of these systems. In this paper we present a Bayesian model of probability for whole-image descriptors that can be seamlessly integrated into localization systems designed for probabilistic visual input. We demonstrate this method using CAT-Graph, an appearance-based visual localization system originally designed for a FAB-MAP-style probabilistic input. We show that using whole-image descriptors as visual input extends CAT-Graph’s functionality to environments that experience a greater amount of perceptual change. We also present a method of estimating whole-image probability models in an online manner, removing the need for a prior training phase. We show that this online, automated training method can perform comparably to pre-trained, manually tuned local descriptor methods.