Alpha B-crystallin, a new independent marker for poor prognosis in head and neck cancer

Objectives. Gene expression profiling has provided many insights into tumor progression but translation to clinical practice has been limited. We have previously identified a list of potential markers by the differences of expression profiling of seven matched head and neck cancer (HNSCC) tumors with autologous normal oral mucosa (NOM). Alpha B-crystallin (CRYAB) was in the top 5% of genes identified with statistically significant differences in expression between tumor and NOM at the mRNA level. The objective was to confirm this in routine paraffin sections at the protein level. Study Design: The level of alpha B-crystallin was determined in tumors of 62 HNSCC patients whose prognosis was known for 5 years. Methods. Immunohistochemical detection of alpha B-crystallin expression was performed on HNSCC paraffin sections. Results. Univariate survival analysis identified lack of alpha B-crystallin staining as an independent prognostic marker for disease-free interval (P < 0.001) and overall survival (P < 0.002) of HNSCC patients over the 5-year observation period. Notably, all 13 patients (100%), including 5 patients with nodal disease whose tumors lacked alpha B-crystallin had no recurrences (P < 0.001). Nineteen of 27 node-negative patients stained positive for alpha B-crystallin and seven of the 19 (36.8%) had recurrences. Conclusion: Presence or absence of expression of alpha B-crystallin was a powerful marker for prognosis in this series of patients.

Comparison of virulence gene profiles of Escherichia coli strains isolated from healthy and diarrheic swine

A combination of uni- and multiplex PCR assays targeting 58 virulence genes (VGs) associated with Escherichia coli strains causing intestinal and extraintestinal disease in humans and other mammals was used to analyze the VG repertoire of 23 commensal E. coli isolates from healthy pigs and 52 clinical isolates associated with porcine neonatal diarrhea (ND) and postweaning diarrhea (PWD). The relationship between the presence and absence of VGs was interrogated using three statistical methods. According to the generalized linear model, 17 of 58 VGs were found to be significant (P < 0.05) in distinguishing between commensal and clinical isolates. Nine of the 17 genes represented by iha, hlyA, aidA, east1, aah, fimH, iroN(E).(coli), traT, and saa have not been previously identified as important VGs in clinical porcine isolates in Australia. The remaining eight VGs code for fimbriae (F4, F5, F18, and F41) and toxins (STa, STh, LT, and Stx2), normally associated with porcine enterotoxigenic E. coli. Agglomerative hierarchical algorithm analysis grouped E. coli strains into subclusters based primarily on their serogroup. Multivariate analyses of clonal relationships based on the 17 VGs were collapsed into two-dimensional space by principal coordinate analysis. PWD clones were distributed in two quadrants, separated from ND and commensal clones, which tended to cluster within one quadrant. Clonal subclusters within quadrants were highly correlated with serogroups. These methods of analysis provide different perspectives in our attempts to understand how commensal and clinical porcine enterotoxigenic E. coli strains have evolved and are engaged in the dynamic process of losing or acquiring VGs within the pig population.

Pathotypes and serogroups of enterotoxigenic Escherichia coli isolated from pre-weaning pigs in north Vietnam

The contribution of enterotoxigenic Escherichia coli (ETEC) to pre-weaning diarrhoea was investigated over a 6 month period at five selected commercial piggeries (CPs) in north Vietnam with at least 100 sows each. Diarrhoea was found to affect 71(.)5% of the litters born during the period of study. Of 406 faecal specimens submitted for bacteriological culture, 200 (49(.)3%) yielded a heavy pure culture of E coli and 126(31 %)were confirmed by PCR to carry at least one of eight porcine ETEC virulence genes. ETEC was responsible for 43% of cases of diarrhoea in neonatal pigs during the first 4 days of life and 23(.)9% of the remaining cases up until the age of weaning. Pathotypes were determined by PCR for the 126 ETEC isolates together with 44 ETEC isolates obtained from village pigs (VPs) raised by smallholder farmers. The CP isolates belonged to five pathotypes, four of which were also identified in VP isolates. Haemolytic serogroup O149: K91 isolates that belonged to F4/STa/STb/LT were most commonly identified in both CPs (33 % of isolates) and VPs (45(.)5%). Other combinations identified in both production systems included O64 (F5/STa), O101 (F4/STa/STb) and O-nontypable (F-/STb). A high proportion of CP isolates (22(.)3 %) possessed all three enterotoxins (STa/STWLT), lacked the genes for all five tested fimbriae (F4, F5, F6, F41 and F18) and belonged to serogroup O8. These unusual 08 F- isolates were haemolytic and were isolated from all ages of diarrhoeic piglets at each CP, suggesting that they have pathogenic potential.

The discriminative bilateral filter: An enhanced denoising filter for electron microscopy data

Advances in three-dimensional (313) electron microscopy (EM) and image processing are providing considerable improvements in the resolution of subcellular volumes, macromolecular assemblies and individual proteins. However, the recovery of high-frequency information from biological samples is hindered by specimen sensitivity to beam damage. Low dose electron cryo-microscopy conditions afford reduced beam damage but typically yield images with reduced contrast and low signal-to-noise ratios (SNRs). Here, we describe the properties of a new discriminative bilateral (DBL) filter that is based upon the bilateral filter implementation of Jiang et al. (Jiang, W., Baker, M.L., Wu, Q., Bajaj, C., Chin, W., 2003. Applications of a bilateral denoising filter in biological electron microscopy. J. Struc. Biol. 128, 82-97.). In contrast to the latter, the DBL filter can distinguish between object edges and high-frequency noise pixels through the use of an additional photometric exclusion function. As a result, high frequency noise pixels are smoothed, yet object edge detail is preserved. In the present study, we show that the DBL filter effectively reduces noise in low SNR single particle data as well as cellular tomograms of stained plastic sections. The properties of the DBL filter are discussed in terms of its usefulness for single particle analysis and for pre-processing cellular tomograms ahead of image segmentation. (c) 2006 Elsevier Inc. All rights reserved.

The human genome and gene expression profiling

The mapping and sequencing of the human genome has generated a large resource for answering questions about human disease. This achievement is akin in scientific importance to developing the periodic table of elements. Plastic surgery has always been at the frontier medical research. This resource will help us to improve our understanding on the many unknown physiological and pathogical conditions we deal with daily, such as wound heating keloid scar formation, Dupuytren's disease, rheumatoid arthritis, vascular malformation and carcinogenesis. We are primed in obtaining both disease and normal tissues to use this resource and applying it to clinical use. This review is about the human genome, the basis of gene expression profiling and how it will affect our clinical and research practices in the future and for those embarking on the use of this new technology as a research tool, we provide a brief insight on its limitations and pitfalls. (C) 2006 The British Association of Plastic Surgeons. Published by Elsevier Ltd. All rights reserved.

Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.

Oscar Asche's Modernisms: Flesh, Colour and Light

The article examines the early 20th century Australian actor, theater director, and writer Oscar Asche and how various aspects of his work are expressive of an aesthetic modernism. His theatrical productions with his wife Lily Brayton are discussed, as well as his solo projects like the highly acclaimed musical "Chu Chin Chow." Asche is described as a "vitalist."

Head and neck cancer: past, present and future

Head and neck cancer consists of a diverse group of cancers that ranges from cutaneous, lip, salivary glands, sinuses, oral cavity, pharynx and larynx. Each group dictates different management. In this review, the primary focus is on head and neck squamous cell carcinoma (HNSCC) arising from the mucosal lining of the oral cavity and pharynx, excluding nasopharyngeal cancer. Presently, HNSCC is the sixth most prevalent neoplasm in the world, with approximately 900,000 cases diagnosed worldwide. Prognosis has improved little in the past 30 years. In those who have survived, pain, disfigurement and physical disability from treatment have had an enormous psychosocial impact on their lives. Management of these patients remains a challenge, especially in developing countries where this disease is most common. Of all human cancers, HNSCC is the most distressing since the head and neck is the site of the most complex functional anatomy in the human body. Its areas of responsibility include breathing, the CNS, vision, hearing, balance, olfaction, taste, swallowing, voice, endocrine and cosmesis. Cancers that occur in this area impact on these important human functions. Consequently, in treating cancers of the head and neck, the effects of the treatment on the functional outcome of the patient need the most serious consideration. In assessing the success of HNSCC treatment, consideration of both the survival and functional deficits that the patient may suffer as a consequence of their treatment are of paramount importance. For this reason, the modern-day management of head and neck patients should be carried out in a multidisciplinary head and neck clinic.

A new indexing method for high dimensional dataset

Indexing high dimensional datasets has attracted extensive attention from many researchers in the last decade. Since R-tree type of index structures are known as suffering curse of dimensionality problems, Pyramid-tree type of index structures, which are based on the B-tree, have been proposed to break the curse of dimensionality. However, for high dimensional data, the number of pyramids is often insufficient to discriminate data points when the number of dimensions is high. Its effectiveness degrades dramatically with the increase of dimensionality. In this paper, we focus on one particular issue of curse of dimensionality; that is, the surface of a hypercube in a high dimensional space approaches 100% of the total hypercube volume when the number of dimensions approaches infinite. We propose a new indexing method based on the surface of dimensionality. We prove that the Pyramid tree technology is a special case of our method. The results of our experiments demonstrate clear priority of our novel method.

BM+-tree: A hyperplane-based index method for high-dimensional metric spaces

In this paper, we propose a novel high-dimensional index method, the BM+-tree, to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a rotary binary hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the M+-tree. Compared with the key dimension concept in the M+-tree, the binary hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Experimental results using two types of real data sets illustrate a significantly improved filtering efficiency.