Does successful treatment of constipation or faecal impaction resolve lower urinary tract symptoms? A structured review of the literature

Consensus guidelines advocate the treatment of constipation and faecal impaction in order to improve symptoms of urinary frequency, urgency and urinary incontinence and to promote bladder emptying in the absence of urinary tract obstruction. This structured review of the literature was undertaken to search for and appraise evidence to support or negate the hypothesis of this relationship. The search strategy was comprehensive and identified six relevant studies. Two of these had been conducted on an adult population and four studies involved children with constipation. These studies were appraised for methodological quality. It was found that sample sizes were small and evidence was inconsistent. Variable methods of reporting meant that data were not able to be pooled for meta-analysis.
Based on the limited and conflicting evidence, it is recommended that further research be undertaken to identify any correlation between bowel and bladder function.

Anion recongnition using preorganized thiourea functionalized [3]polynorbornane receptors

A new family of [3]polynorbornane frameworks exhibiting conformationally preorganized aromatic thiourea (cleft-like) receptors have been designed and synthesized for anion recognition. These show excellent affinity for the biologically relevant dihydrogenphosphate (H2PO4-) and dihydrogenpyrophosphate (H2P2O72-) anions (among others), which are bound in 1:1 and 2:1 (host:anion) ratio, respectively. Moreover, visually striking color changes accompany guest binding, enabling this family to act as colorimetric anion sensors.

Performance of statistical inference for block classification in reducing blocking artefact in video coded images

This paper presents a performance study of four statistical test algorithms used to identify smooth image blocks in order to filter the reconstructed image of a video coded image. The four algorithms considered are the Coefficient of Variation (CV), Exponential Entropy of Pal and Pal (E), Shannon's (Logarithmic) Entropy (H), and Quadratic Entropy (Q). These statistical algorithms are employed to distinguish between smooth and textured blocks in a reconstructed image. The linear filtering is carried out on the smooth blocks of the image to reduce the blocking artefact. The rationale behind applying the filter on the smooth blocks only is that the blocking artefact is visually more prominent in the smooth region of an image rather than in the textured region.

20 years on - have student evaluations made a difference?

This paper poses the question, what impact have student evaluations (SE’s) of teaching had on the improvement in teaching in Australian tertiary education. The paper proposes to assess the effectiveness of SE’s through an investigations of the ways in which have been used in Australian tertiary education over the last 20 years or so. Three approaches are discussed: a) quality assurance - student evaluations used to ensure the quality of the learning environment in which learning takes place; b) quality improvement - student evaluations used as a diagnostic tool for individual teaching staff; and c) student feedback – student evaluations used to provide prospective and current students with information to help inform their choices and expectations. The discussions reviews some of the research and known practise in Australian universities. It concludes that SE’s have had a profound impact on pedagological understandings of tertiary education by placing the student at centre stage of teaching and learning. However it suggests that we do not know how SE’s have impacted on teaching effectiveness and improvement. The paper concludes by recommending further research to define critical success factors, a better understanding of how to make the student feedback and evaluation tools and mechanisms more approachable and meaningful for students, and an assessment of the ‘survey industry’ as a sustainable enterprise.

Deakin family group at Point Lonsdale

From left to right: Alfred Deakin, Pattie Deakin (holding granddaughter Jessie Brookes), Miss Hodgson, Ivy Brookes (nee. Deakin); front row left to right: [hidden - possibly Aunt Kay], Wilfred Brookes, Sid Appleby.

c-Cbl-deficient mice have reduced adiposity, higher energy expenditure, and improved peripheral insulin action

Casitas b-lineage lymphoma (c-Cbl) is an E3 ubiquitin ligase that has an important role in regulating the degradation of cell surface receptors. In the present study we have examined the role of c-Cbl in whole-body energy homeostasis. c-Cb^-/- mice exhibited a profound increase in whole-body energy expenditure as determined by increased core temperature and whole-body oxygen consumption. As a consequence, these mice displayed a decrease in adiposity, primarily due to a reduction in cell size despite an increase in food intake. These changes were accompanied by a significant
increase in activity (2- to 3-fold). In addition, cc-Cb-/- mice displayed a marked improvement in whole-body insulin action, primarily due to changes in muscle metabolism. We observed increased protein levels of the insulin receptor (4-fold) and uncoupling protein-3 (2-fold) in skeletal muscle and a significant increase in the phosphorylation of AMP-activated protein kinase and acetyl-CoA carboxylase. These fmdings suggest that c-Cbl plays an integral role in whole-body fuel homeostasis by regulating whole-body energy expenditure and insulin action.

Improved glusoce homeostasis and enhanced insulin signalling in Grb 14-deficient mice

Gene targeting was used to characterize the physiological role of growth factor receptor-bound (Grb)14, an adapter-type signalling protein that associates with the insulin receptor (IR). Adult male Grb14^-/- mice displayed improved glucose tolerance, lower circulating insulin levels, and increased incorporation of glucose into glycogen in the liver and skeletal muscle. In ex vivo studies, insulin-induced 2-deoxyglucose uptake was enhanced in soleus muscle, but not in epididymal adipose tissue. These metabolic effects correlated with tissue-specific alterations in insulin signalling. In the liver, despite lower IR autophosphorylation, enhanced insulin-induced tyrosine phosphorylation of insulin receptor substrate (IRS)-1 and activation of protein kinase B (PKB) was observed. In skeletal muscle, IR tyrosine phosphorylation was normal, but signalling via IRS-1 and PKB was increased. Finally, no effect of Grb14 ablation was observed on insulin signalling in white adipose tissue. These findings demonstrate that Grb14 functions in vivo as a tissue-specific modulator of insulin action, most likely via repression of IR-mediated IRS-1 tyrosine phosphorylation, and highlight this protein as a potential target for therapeutic intervention.

Bit of preparation will help you remain stress-free

For those waiting for tertiary offers and start dates, the next couple of months can be stressful. There is no "right" way to spend this time, but the following suggestions might be helpful in preparing for uni and keeping that stress at a minimum.

Time-resolved fluorescence microscopy of gunshot residue: an application to forensic science

Time-resolved fluorescence microscopy has rapidly emerged as the technique of choice for many researchers aiming to gain specific insights into the dynamics of intricate biological systems. Although the unique advantages the technique provides over other methods have proven to be particularly useful in the biosciences, to date they have been largely unexploited by other research disciplines. In this paper, we demonstrate the capacity of time-resolved fluorescence microscopy as a practical analytical tool in the forensic sciences via the imaging of gunshot residues that are expelled when a firearm is discharged. This information may prove to be useful for determination of the true sequence of events that took place in a firearm related crime.

Dynamic feature selection for spam filtering using support vector machine

Spam is commonly defined as unsolicited email messages and the goal of spam filtering is to differentiate spam from legitimate email. Much work have been done to filter spam from legitimate emails using machine learning algorithm and substantial performance has been achieved with some amount of false positive (FP) tradeoffs. In this paper, architecture of spam filtering has been proposed based on support vector machine (SVM,) which will get better accuracy by reducing FP problems. In this architecture an innovative technique for feature selection called dynamic feature selection (DFS) has been proposed which is enhanced the overall performance of the architecture with reduction of FP problems. The experimental result shows that the proposed technique gives better performance compare to similar existing techniques.

Finding motifs in miRNA sequences

Recently, the emergence of non-coding miRNA has attracted biology and computer researchers. miRNA plays an important role in regulation of genes. Finding motifs in RNA is one of important topics. In our work, we attempt to find motifs in mature miRNA from combinations ranging from two to ten nucleotides. Interestingly, we have found several motifs only appear in mature miRNA but not appear in other regions of primary miRNA sequences taken from latest miRNA datasets. The findings of our investigation may help in the building model to predict all possible miRNAs in genomes

Acoustic features extraction for emotion recognition

In the last decade, the efforts of spoken language processing have achieved significant advances, however, the work with emotional recognition has not progressed so far, and can only achieve 50% to 60% in accuracy. This is because a majority of researchers in this field have focused on the synthesis of emotional speech rather than focusing on automating human emotion recognition. Many research groups have focused on how to improve the performance of the classifier they used for emotion recognition, and few work has been done on data pre-processing, such as the extraction and selection of a set of specifying acoustic features instead of using all the possible ones they had in hand. To work with well-selected acoustic features does not mean to delay the whole job, but this will save much time and resources by removing the irrelative information and reducing the high-dimension data calculation. In this paper, we developed an automatic feature selector based on a RF2TREE algorithm and the traditional C4.5 algorithm. RF2TREE applied here helped us to solve the problems that did not have enough data examples. The ensemble learning technique was applied to enlarge the original data set by building a bagged random forest to generate many virtual examples, and then the new data set was used to train a single decision tree, which selects the most efficient features to represent the speech signals for the emotion recognition. Finally, the output of the selector was a set of specifying acoustic features, produced by RF2TREE and a single decision tree.

A composite descriptor for shape retrieval

In this paper, a composite descriptor for shape retrieval has been proposed. The proposed descriptor is obtained from Generic Fourier Descriptors (GFD) for the shape region and the shape contour. A composite descriptor derived from GFD of the shape region and the shape contour is used for indexing and retrieval of shapes. Difference between two images is computed as the Euclidean distance between their composite descriptors. Experiments are performed to test the effectiveness of the proposed descriptor for retrieval of 2d images. Sets of composite descriptors, obtained by assigning different weights to the region component and the contour component, are also evaluated. Item S8 within the MPEG-7 Still Images Content Set is used for performing experiments; this dataset consists of 3621 still images. Experimental results show that the proposed descriptor is effective.