Glycated proteome: From reaction to intervention

Glycation, a nonenzymatic reaction between reducing sugars and proteins, is a proteome wide phenomenon, predominantly observed in diabetes due to hyperglycemia. Glycated proteome of plasma, kidney, lens, and brain are implicated in the pathogenesis of various diseases, including diabetic complications, neurodegenerative diseases, cancer, and aging. This review discusses the strategies to characterize protein glycation, its functional implications in different diseases, and intervention strategies to protect the deleterious effects of protein glycation.     

Gestural systems for the voice: performance approaches and repertoire

ABSTRACT

Singing, like dance, emerges directly from the body. The voice, in combination with whole body movement, constitutes a potent form of self-expression. Gestural systems offer a specialized context in which to explore the intersection between voice and movement. The practice-based investigation presented in this article charts the development of an original musical work, Intangible Spaces, which gives form to the invisible aspects of voice and movement through gestural control, physical modelling synthesis and visual feedback. I draw on embodied and performative autoethnographic methods to capture the felt sensations and sound-movement associations that arise during the composition process. I also explore the performance approaches of key practitioners in the area to gain a broader understanding of the ways in which musicians leverage existing performance skills to uncover novel connections between movement and voice in gestural performance.     

Evaluation of Reorientation Techniques and Distractors for Walking in Large Virtual Environments

Vir tual Environments (VEs) that use a real-walking locomotion interface have typically been restricted in size to the area of the tracked lab space. Techniques proposed to lift this size constraint, enabling real walking in VEs that are larger than the tracked lab space, all require reorientation techniques (ROTs) in the worst-case situation—when a user is close to walking out of the tracked space. We propose a new ROT using visual and audial distractors—objects in the VE that the user focuses on while the VE rotates—and compare our method to current ROTs through three user studies. ROTs using distractors were preferred and ranked more natural by users. Our findings also suggest that improving visual realism and adding sound increased a user's feeling of presence. Users were also less aware of the rotating VE when ROTs with distractors were used.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.     

Design and Development of Flexible PDMS Antenna for UWB-WBAN Applications

Wireless Personal Communications - This paper presents the design and development of a flexible Ultra Wide Band (UWB) antenna using polydimethylsiloxane as a substrate. Copper foil having a...     

Mammogram Learning System for Breast Cancer Diagnosis Using Deep Learning SVM

The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces system complexity. The softmax layer in VGG assumes that the training samples belong to exactly only one class, which is not valid in a real situation, such as in medical image diagnosis. To overcome this situation, SVM is employed instead of the softmax layer in VGG. Data augmentation is also employed as DLA usually requires a large number of samples. VGG model with different SVM kernels is built to classify the mammograms. Results show that the VGG-SVM model has good potential for the classification of Mammographic Image Analysis Society (MIAS) database images with an accuracy of 98.67%, sensitivity of 99.32%, and specificity of 98.34%.     

Oxygen saturation-dependent effects on blood transverse relaxation at low fields

Objective

Blood oxygenation can be measured using magnetic resonance using the paramagnetic effect of deoxy-haemoglobin, which decreases the \(\textit{T}_{2}\) relaxation time of blood. This \(\textit{T}_{2}\) contrast has been well characterised at the \(\textit{B}_{{0}}\) fields used in MRI (1.5 T and above). However, few studies have characterised this effect at lower magnetic fields. Here, the feasibility of blood oximetry at low field based on \(\textit{T}_{2}\) changes that are within a physiological relevant range is explored. This study could be used for specifying requirements for construction of a monitoring device based on low field permanent magnet systems.

Methods

A continuous flow circuit was used to control parameters such as oxygen saturation and temperature in a sample of blood. It flowed through a variable field magnet, where CPMG experiments were performed to measure its \(\textit{T}_{2}\). In addition, the oxygen saturation was monitored by an optical sensor for comparison with the \(\textit{T}_{2}\) changes.

Results

These results show that at low \(\textit{B}_{{0}}\) fields, the change in blood \(\textit{T}_{2}\) due to oxygenation is small, but still detectable. The data measured at low fields are also in agreement with theoretical models for the oxy-deoxy \(\textit{T}_{2}\) effect.

Conclusion

\(\textit{T}_{2}\) changes in blood due to oxygenation were observed at fields as low as 0.1 T. These results suggest that low field NMR relaxometry devices around 0.3 T could be designed to detect changes in blood oxygenation.