Differential SAGE analysis in Arabidopsis uncovers increased transcriptome complexity in response to low temperature

Abstract Background Abiotic stress, including low temperature, limits the productivity and geographical distribution of plants, which has led to significant interest in understanding the complex processes that allow plants to adapt to such stresses. The wide range of physiological, biochemical and molecular changes that occur in plants exposed to low temperature require a robust global approach to studying the response. We have employed Serial Analysis of Gene Expression (SAGE) to uncover changes in the transcriptome of Arabidopsis thaliana over a time course of low temperature stress. Results Five SAGE libraries were generated from A. thaliana leaf tissue collected at time points ranging from 30 minutes to one week of low temperature treatment (4°C). Over 240,000 high quality SAGE tags, corresponding to 16,629 annotated genes, provided a comprehensive survey of changes in the transcriptome in response to low temperature, from perception of the stress to acquisition of freezing tolerance. Interpretation of these data was facilitated by representing the SAGE data by gene identifier, allowing more robust statistical analysis, cross-platform comparisons and the identification of genes sharing common expression profiles. Simultaneous statistical calculations across all five libraries identified 920 low temperature responsive genes, only 24% of which overlapped with previous global expression analysis performed using microarrays, although similar functional categories were affected. Clustering of the differentially regulated genes facilitated the identification of novel loci correlated with the development of freezing tolerance. Analysis of their promoter sequences revealed subsets of genes that were independent of CBF and ABA regulation and could provide a mechanism for elucidating complementary signalling pathways. The SAGE data emphasised the complexity of the plant response, with alternate pre-mRNA processing events increasing at low temperatures and antisense transcription being repressed. Conclusion Alternate transcript processing appears to play an important role in enhancing the plasticity of the stress induced transcriptome. Novel genes and cis-acting sequences have been identified as compelling targets to allow manipulation of the plant's ability to protect against low temperature stress. The analyses performed provide a contextual framework for the interpretation of quantitative sequence tag based transcriptome analysis which will prevail with the application of next generation sequencing technology.</p

Neuroarthropathy in diabetes: pathogenesis of Charcot arthropathy.

Charcot neuroarthropathy is a rare but serious complication of diabetes, causing progressive destruction of the bones and joints of the foot leading to deformity, altered biomechanics and an increased risk of ulceration. Management is complicated by a lack of consensus on diagnostic criteria and an incomplete understanding of the pathogenesis. In this review, we consider recent insights into the development of Charcot neuroarthropathy. It is likely to be dependent on several interrelated factors which may include a genetic pre-disposition in combination with diabetic neuropathy. This leads to decreased neuropeptides (nitric oxide and calcitonin gene-related peptide), which may affect the normal coupling of bone formation and resorption, and increased levels of Receptor activator of nuclear factor kappa-B ligand, potentiating osteoclastogenesis. Repetitive unrecognized trauma due to neuropathy increases levels of pro-inflammatory cytokines (interleukin-1β, interleukin-6, tumour necrosis factor α) which could also contribute to increased bone resorption, in combination with a pre-inflammatory state, with increased autoimmune reactivity and a profile of monocytes primed to transform into osteoclasts - cluster of differentiation 14 (CD14). Increased blood glucose and loss of circulating Receptor for Advanced Glycation End-Products (AGLEPs), leading to increased non-enzymatic glycation of collagen and accumulation of AGLEPs in the tissues of the foot, may also contribute to the pathological process. An understanding of the relative contributions of each of these mechanisms and a final common pathway for the development of Charcot neuroarthropathy are still lacking. Cite this article: S. E. Johnson-Lynn, A. W. McCaskie, A. P. Coll, A. H. N. Robinson. Neuroarthropathy in diabetes: pathogenesis of Charcot arthropathy. Bone Joint Res 2018;7:373-378. DOI: 10.1302/2046-3758.75.BJR-2017-0334.R1

Air Fraction Correction Optimisation in PET Imaging of Lung Disease

Accurate quantification of radiopharmaceutical uptake from lung PET/CT is challenging due to large variations in fractions of tissue, air, blood and water. Air fraction correction (AFC) uses voxel-wise air fractions, which can be determined from the CT acquired for attenuation correction (AC). However, resolution effects can cause artefacts in either of these corrections. In this work, we hypothesise that the resolution of the CT image used for AC should match that of the intrinsic resolution of the PET scanner but should approximate the reconstructed PET image resolution for AFC. Simulations and reconstructions were performed with the Synergistic Image Reconstruction Framework (SIRF) using phantoms with inhomogeneous attenuation (mu) maps, mimicking the densities observed in lung pathologies. Poisson noise was added to the projection data prior to OSEM reconstruction. AC was performed with a smoothed mu-map, the full-width-half-maximum (FWHM) of the 3D Gaussian kernel was varied (0 - 10 mm). Post-filters were applied to the reconstructed AC images (FWHM: 0 - 8 mm). The simulated mu-map was independently convolved with another set of 3D Gaussian kernels, of varying FWHM (0 - 12 mm), for AFC. The coefficient of variation (CV) in the lung region, designed to be homogeneous post-AFC with optimised kernels, and the mean AFC-standardized uptake value (AFC-SUV) in the regions of simulated pathologies were determined. The spatial resolution of each post-filtered image was determined via a point-source insertion-and-subtraction method on noiseless data. Results showed that the CV was minimised when the kernel applied to the mu-map for AC matched that for the simulated PET scanner and the kernel applied to the mu-map for AFC matched the spatial resolution of the reconstructed PET image. This was observed for all post-reconstruction filters and supports the hypothesis. Initial results from Monte Carlo simulations validate these findings

Penetration and intracellular uptake of poly(glycerol-adipate)nanoparticles into 3-dimensional brain tumour cell culture models

Nanoparticle (NP) drug delivery systems may potentially enhance the efficacy of therapeutic agents. It is difficult to characterise many important properties of NPs in vivo and therefore attempts have been made to use realistic in vitro multicellular spheroids instead. In this paper we have evaluated poly(glycerol-adipate) (PGA) NPs as a potential drug carrier for local brain cancer therapy. Various 3-dimensional (3-D) cell culture models have been used to investigate the delivery properties of PGA NPs. Tumour cells in 3-D culture showed a much higher level of endocytic uptake of NPs than a mixed normal neonatal brain cell population. Differences in endocytic uptake of NPs in 2-D and 3-D models strongly suggest that it is very important to use in vitro 3-D cell culture models for evaluating this parameter. Tumour penetration of NPs is another important parameter which could be studied in 3-D cell models. The penetration of PGA NPs through 3-D cell culture varied between models, which will therefore require further study to develop useful and realistic in vitro models. Further use of 3-D cell culture models will be of benefit in the future development of new drug delivery systems, particularly for brain cancers which are more difficult to study in vivo

Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch

Background: Increased pulmonary 18 F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image. Methods: Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, hpts ; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), hAFC ; iii) smoothing the GT image to match the reconstruction within the VOI, hPVC . The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, hPVC was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols. Results: The simulations demonstrated that at < 200 iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The hpts method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at ≥ 200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10% at ≥ 200i, while larger lung RMSEs were observed for the VOI–specific kernels. The global kernel approach was then employed with the hPVC method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated. Conclusions: Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The hPVC method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners

Feasibility of Image Reconstruction from Triple Modality Data of Yttrium-90

The recent implementation of the first clinical triple modality scanner in STIR enables investigation of the possibility of triple modality image reconstruction. Such a tool represents an important step toward the improvement of dosimetry for theranostics, where the exploitation of multi-modality imaging can have an impact on treatment planning and follow-up. To give a demonstration of triple modality image reconstruction we used data from a NEMA phantom that was filled with Yttrium-90 (90Y), which emits Bremsstrahlung photons detectable with SPECT as well as gamma rays that can go through pair production, therefore creating positrons that make PET acquisition possible. The data were acquired with the Mediso AnyScan SPECT/PET/CT. Different ways of including multiple side information using the kernelised expectation maximisation (KEM) and the Hybrid KEM (HKEM) were used and investigated in terms of ROI activity and noise suppression. This work presents an example of application with 90Y but it can be extended to any other radionuclide combination used in Theranostic applications

Comparison between Suitable Priors for Additive Bayesian Networks

Additive Bayesian networks are types of graphical models that extend the usual Bayesian generalized linear model to multiple dependent variables through the factorisation of the joint probability distribution of the underlying variables. When fitting an ABN model, the choice of the prior of the parameters is of crucial importance. If an inadequate prior - like a too weakly informative one - is used, data separation and data sparsity lead to issues in the model selection process. In this work a simulation study between two weakly and a strongly informative priors is presented. As weakly informative prior we use a zero mean Gaussian prior with a large variance, currently implemented in the R-package abn. The second prior belongs to the Student's t-distribution, specifically designed for logistic regressions and, finally, the strongly informative prior is again Gaussian with mean equal to true parameter value and a small variance. We compare the impact of these priors on the accuracy of the learned additive Bayesian network in function of different parameters. We create a simulation study to illustrate Lindley's paradox based on the prior choice. We then conclude by highlighting the good performance of the informative Student's t-prior and the limited impact of the Lindley's paradox. Finally, suggestions for further developments are provided.Comment: 8 pages, 4 figure

Tissue mimicking materials for imaging and therapy phantoms: a review

Tissue mimicking materials (TMMs), typically contained within phantoms, have been used for many decades in both imaging and therapeutic applications. This review investigates the specifications that are typically being used in development of the latest TMMs. The imaging modalities that have been investigated focus around CT, mammography, SPECT, PET, MRI and ultrasound. Therapeutic applications discussed within the review include radiotherapy, thermal therapy and surgical applications. A number of modalities were not reviewed including optical spectroscopy, optical imaging and planar x-rays. The emergence of image guided interventions and multimodality imaging have placed an increasing demand on the number of specifications on the latest TMMs. Material specification standards are available in some imaging areas such as ultrasound. It is recommended that this should be replicated for other imaging and therapeutic modalities. Materials used within phantoms have been reviewed for a series of imaging and therapeutic applications with the potential to become a testbed for cross-fertilization of materials across modalities. Deformation, texture, multimodality imaging and perfusion are common themes that are currently under development

Read-Right: a "web app" that improves reading speeds in patients with hemianopia

Effective behavioral therapies exist for patients with brain injury. The main issue is one of access. Can the internet be used as a resource so that suitable patients can build up enough practice to improve? We tested this hypothesis using a web-based application for patients with a right-sided hemianopia causing slow text reading. We studied 33 patients aged 26-81 years who fitted the entry criteria and accessed the therapy website between May 2010 and December 2011, in a longitudinal cohort study. The therapy consisted of reading animated, laterally scrolling text whose content and form was selected by the patients. Reading speeds on static text (main outcome) were assessed after every 5-h period of practice had been accrued. Statistical analysis was carried out using a repeated measures ANOVA. Read-Right therapy produced significant improvements in text reading speeds at all time points with a clear dose effect: 10 % at 5 h, 20 % at 10 h, 39 % at 15 h and 46 % at 20 h. Sub-analyses demonstrated that this was unlikely to be due to either multiple exposure to the testing materials (familiarity) or to the simple passage of time. This is the first example of a clinically proven therapy being delivered effectively to stroke patients over the internet. As therapists' time is more limited than patients' capacity to improve, carefully designed, web-based resources like Read-Right represent a realistic way of delivering a sufficient therapy dose to patients so they can obtain clinically meaningful improvements