How to tell the difference between a positive image and a stereotype: reading Priscilla, Queen of the Desert

This paper intervenes in critical discussions about the representation of homosexuality. Rejecting the ‘manifest content’ of films, it turns to cultural history to map those public discourses which close down the ways in which films can be discussed. With relation to The Adventures of Priscilla, Queen of the Desert, it examines discussions of the film in Australian newspapers (both queer and mainstream) and finds that while there is disagreement about the interpretation to be made of the film, the terms within which those interpretations can be made are quite rigid. A matrix based on similarity, difference and value provides a series of positions and a vocabulary (transgression, assimilation, positive images and stereotypes) through which to make sense of this film. The article suggests that this matrix, and the idea that similarity and difference provide a suitable axis for making sense of homosexual identity, are problematic in discussing homosexual representation.

Learning the kernel matrix with semidefinite programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive semidefinite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space - classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semidefinite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -using the labeled part of the data one can learn an embedding also for the unlabeled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method for learning the 2-norm soft margin parameter in support vector machines, solving an important open problem.

Learning the Kernel Matrix with Semi-Definite Programming

Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is performed implicitly, by specifying the inner products between each pair of points in the embedding space. This information is contained in the so-called kernel matrix, a symmetric and positive definite matrix that encodes the relative positions of all points. Specifying this matrix amounts to specifying the geometry of the embedding space and inducing a notion of similarity in the input space -- classical model selection problems in machine learning. In this paper we show how the kernel matrix can be learned from data via semi-definite programming (SDP) techniques. When applied to a kernel matrix associated with both training and test data this gives a powerful transductive algorithm -- using the labelled part of the data one can learn an embedding also for the unlabelled part. The similarity between test points is inferred from training points and their labels. Importantly, these learning problems are convex, so we obtain a method for learning both the model class and the function without local minima. Furthermore, this approach leads directly to a convex method to learn the 2-norm soft margin parameter in support vector machines, solving another important open problem. Finally, the novel approach presented in the paper is supported by positive empirical results.

Pedigree-free animal models : the relatedness matrix reloaded

Animal models typically require a known genetic pedigree to estimate quantitative genetic parameters. Here we test whether animal models can alternatively be based on estimates of relatedness derived entirely from molecular marker data. Our case study is the morphology of a wild bird population, for which we report estimates of the genetic variance-covariance matrices (G) of six morphological traits using three methods: the traditional animal model; a molecular marker-based approach to estimate heritability based on Ritland's pairwise regression method; and a new approach using a molecular genealogy arranged in a relatedness matrix (R) to replace the pedigree in an animal model. Using the traditional animal model, we found significant genetic variance for all six traits and positive genetic covariance among traits. The pairwise regression method did not return reliable estimates of quantitative genetic parameters in this population, with estimates of genetic variance and covariance typically being very small or negative. In contrast, we found mixed evidence for the use of the pedigree-free animal model. Similar to the pairwise regression method, the pedigree-free approach performed poorly when the full-rank R matrix based on the molecular genealogy was employed. However, performance improved substantially when we reduced the dimensionality of the R matrix in order to maximize the signal to noise ratio. Using reduced-rank R matrices generated estimates of genetic variance that were much closer to those from the traditional model. Nevertheless, this method was less reliable at estimating covariances, which were often estimated to be negative. Taken together, these results suggest that pedigree-free animal models can recover quantitative genetic information, although the signal remains relatively weak. It remains to be determined whether this problem can be overcome by the use of a more powerful battery of molecular markers and improved methods for reconstructing genealogies.

Random projections on manifolds of symmetric positive definite matrices for image classification

Recent advances suggest that encoding images through Symmetric Positive Definite (SPD) matrices and then interpreting such matrices as points on Riemannian manifolds can lead to increased classification performance. Taking into account manifold geometry is typically done via (1) embedding the manifolds in tangent spaces, or (2) embedding into Reproducing Kernel Hilbert Spaces (RKHS). While embedding into tangent spaces allows the use of existing Euclidean-based learning algorithms, manifold shape is only approximated which can cause loss of discriminatory information. The RKHS approach retains more of the manifold structure, but may require non-trivial effort to kernelise Euclidean-based learning algorithms. In contrast to the above approaches, in this paper we offer a novel solution that allows SPD matrices to be used with unmodified Euclidean-based learning algorithms, with the true manifold shape well-preserved. Specifically, we propose to project SPD matrices using a set of random projection hyperplanes over RKHS into a random projection space, which leads to representing each matrix as a vector of projection coefficients. Experiments on face recognition, person re-identification and texture classification show that the proposed approach outperforms several recent methods, such as Tensor Sparse Coding, Histogram Plus Epitome, Riemannian Locality Preserving Projection and Relational Divergence Classification.

Matrix metalloproteinase 13-deficient mice are resistant to osteoarthritic cartilage erosion but not chondrocyte hypertrophy or osteophyte development

Objective To investigate the role of matrix metalloproteinase 13 (MMP-13; collagenase 3) in osteoarthritis (OA). Methods OA was surgically induced in the knees of MMP-13-knockout mice and wild-type mice, and mice were compared. Histologic scoring of femoral and tibial cartilage aggrecan loss (0-3 scale), erosion (0-7 scale), and chondrocyte hypertrophy (0-1 scale), as well as osteophyte size (0-3 scale) and maturity (0-3 scale) was performed. Serial sections were stained for type X collagen and the MMP-generated aggrecan neoepitope DIPEN. Results Following surgery, aggrecan loss and cartilage erosion were more severe in the tibia than femur (P < 0.01) and tibial cartilage erosion increased with time (P < 0.05) in wild-type mice. Cartilaginous osteophytes were present at 4 weeks and underwent ossification, with size and maturity increasing by 8 weeks (P < 0.01). There was no difference between genotypes in aggrecan loss or cartilage erosion at 4 weeks. There was less tibial cartilage erosion in knockout mice than in wild-type mice at 8 weeks (P < 0.02). Cartilaginous osteophytes were larger in knockout mice at 4 weeks (P < 0.01), but by 8 weeks osteophyte maturity and size were no different from those in wild-type mice. Articular chondrocyte hypertrophy with positive type X collagen and DIPEN staining occurred in both wild-type and knockout mouse joints. Conclusion Our findings indicate that structural cartilage damage in a mouse model of OA is dependent on MMP-13 activity. Chondrocyte hypertrophy is not regulated by MMP-13 activity in this model and does not in itself lead to cartilage erosion. MMP-13 deficiency can inhibit cartilage erosion in the presence of aggrecan depletion, supporting the potential for therapeutic intervention in established OA with MMP-13 inhibitors.

Estimation in a multiplicative mixed model involving a genetic relationship matrix.

Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we employ these estimation methods for the more complex case involving the numerator relationship matrix. We examine the performance of differing genetic models for MET data with an embedded pedigree structure, and consider the magnitude of the non-additive variance. The capacity of existing software packages to fit these complex models is largely due to the use of the sparse matrix methodology and the average information algorithm. Here, we present an extension to the standard formulation necessary for estimation with a factor analytic structure across multiple environments.

The scientific basis and development of a matrix metalloproteinase (MMP) -8 specific chair-side test for monitoring of periodontal health and disease from gingival crevicular fluid

Matrix metalloproteinase (MMP) -8, collagenase-2, is a key mediator of irreversible tissue destruction in chronic periodontitis and detectable in gingival crevicular fluid (GCF). MMP-8 mostly originates from neutrophil leukocytes, the first line of defence cells which exist abundantly in GCF, especially in inflammation. MMP-8 is capable of degrading almost all extra-cellular matrix and basement membrane components and is especially efficient against type I collagen. Thus the expression of MMP-8 in GCF could be valuable in monitoring the activity of periodontitis and possibly offers a diagnostic means to predict progression of periodontitis. In this study the value of MMP-8 detection from GCF in monitoring of periodontal health and disease was evaluated with special reference to its ability to differentiate periodontal health and different disease states of the periodontium and to recognise the progression of periodontitis, i.e. active sites. For chair-side detection of MMP-8 from the GCF or peri-implant sulcus fluid (PISF) samples, a dip-stick test based on immunochromatography involving two monoclonal antibodies was developed. The immunoassay for the detection of MMP-8 from GCF was found to be more suitable for monitoring of periodontitis than detection of GCF elastase concentration or activity. Periodontally healthy subjects and individuals suffering of gingivitis or of periodontitis could be differentiated by means of GCF MMP-8 levels and dipstick testing when the positive threshold value of the MMP-8 chair-side test was set at 1000 µg/l. MMP-8 dipstick test results from periodontally healthy and from subjects with gingivitis were mainly negative while periodontitis patients sites with deep pockets ( 5 mm) and which were bleeding on probing were most often test positive. Periodontitis patients GCF MMP-8 levels decreased with hygiene phase periodontal treatment (scaling and root planing, SRP) and even reduced during the three month maintenance phase. A decrease in GCF MMP-8 levels could be monitored with the MMP-8 test. Agreement between the test stick and the quantitative assay was very good (κ = 0.81) and the test provided a baseline sensitivity of 0.83 and specificity of 0.96. During the 12-month longitudinal maintenance phase, periodontitis patients progressing sites (sites with an increase in attachment loss ≥ 2 mm during the maintenance phase) had elevated GCF MMP-8 levels compared with stable sites. General mean MMP-8 concentrations in smokers (S) sites were lower than in non-smokers (NS) sites but in progressing S and NS sites concentrations were at an equal level. Sites with exceptionally and repeatedly elevated MMP-8 concentrations during the maintenance phase were clustered in smoking patients with poor response to SRP (refractory patients). These sites especially were identified by the MMP-8 test. Subgingival plaque samples from periodontitis patients deep periodontal pockets were examined by polymerase chain reaction (PCR) to find out if periodontal lesions may serve as a niche for Chlamydia pneumoniae. Findings were compared with the clinical periodontal parameters and GCF MMP-8 levels to determine the correlation with periodontal status. Traces of C. pneumoniae were identified from one periodontitis patient s pooled subgingival plaque sample by means of PCR. After periodontal treatment (SRP) the sample was negative for C. pneumoniae. Clinical parameters or biomarkers (MMP-8) of the patient with the positive C. pneumoniae finding did not differ from other study patients. In this study it was concluded that MMP-8 concentrations in GCF of sites from periodontally healthy individuals, subjects with gingivitis or with periodontitis are at different levels. The cut-off value of the developed MMP-8 test is at an optimal level to differentiate between these conditions and can possibly be utilised in identification of individuals at the risk of the transition of gingivitis to periodontitis. In periodontitis patients, repeatedly elevated GCF MMP-8 concentrations may indicate sites at risk of progression of periodontitis as well as patients with poor response to conventional periodontal treatment (SRP). This can be monitored by MMP-8 testing. Despite the lower mean GCF MMP-8 concentrations in smokers, a fraction of smokers sites expressed very high MMP-8 concentrations together with enhanced periodontal activity and could be identified with MMP-8 specific chair-side test. Deep periodontal lesions may be niches for non-periodontopathogenic micro-organisms with systemic effects like C. pneumoniae and possibly play a role in the transmission from one subject to another.

Positive results in a real-time PCR for type A influenza associated with the use of an inactivated vaccine.

A real-time reverse transcription polymerase chain reaction (qRT-PCR) test for the matrix gene of type A influenza viruses was used during the 2007 Australian equine influenza (EI) outbreak in order to confirm diagnosis and, later, eradication of the virus. During the EI outbreak, horses being exported required vaccination and individual proof of freedom from EI. At the end of the outbreak, positive results were obtained from four horses destined for export, because of contamination of the samples with the vaccine. This report highlights the need for EI testing and vaccination to occur on separate days and with the collection of swabs for testing to precede vaccination.

Latent TGF-beta Binding Proteins : Adhesive functions and matrix association of LTBP-2 and potential functions of LTBP-1 and LTBP-3 in mesothelioma

Latent transforming growth factor-beta (TGF-beta) binding proteins (LTBPs) -1, -3 and -4 are ECM components whose major function is to augment the secretion and matrix targeting of TGF-beta, a multipotent cytokine. LTBP-2 does not bind small latent TGF-beta but has suggested functions as a structural protein in ECM microfibrils. In the current work we focused on analyzing possible adhesive functions of LTBP-2 as well as on characterizing the kinetics and regulation of LTBP-2 secretion and ECM deposition. We also explored the role of TGF-beta binding LTBPs in endothelial cells activated to mimic angiogenesis as well as in malignant mesothelioma. We found that, unlike most adherent cells, several melanoma cell lines efficiently adhered to purified recombinant LTBP-2. Further characterization revealed that the adhesion was mediated by alpha3beta1 and alpha6beta1 integrins. Heparin also inhibited the melanoma cell adhesion suggesting a role for heparan sulphate proteoglycans. LTBP-2 was also identified as a haptotactic substrate for melanoma cell migration. We used cultured human embryonic lung fibroblasts to analyze the temporal and spatial association of LTBP-2 into ECM. By We found that LTBP-2 was efficiently assembled to the ECM only in confluent cultures following the deposition of fibronectin (FN) and fibrillin-1. In early, subconfluent cultures it remained primarily in soluble form after secretion. LTBP-2 colocalized transiently with FN and fibrillin-1. Silencing of fibrillin-1 expression by lentiviral shRNAs profoundly disrupted the deposition of LTBP-2 indicating that the ECM association of LTBP-2 depends on a pre-formed fibrillin-1 network. Considering the established role of TGF-beta as a regulator of angiogenesis we induced morphological activation of endothelial cells by phorbol 12-myristate 13-acetate (PMA) and followed the fate of LTBP-1 in the endothelial ECM. This resulted in profound proteolytic processing of LTBP-1 and release of latent TGF-beta complexes from the ECM. The processing was coupled with increased activation of MT-MMPs and specific upregulation of MT1-MMP. The major role of MT1-MMP in the proteolysis of LTBP-1 was confirmed by suppressing the expression with lentivirally induced short-hairpin RNAs as well as by various metalloproteinases inhibitors. TGF-beta can promote tumorigenesis of malignant mesothelioma (MM), which is an aggressive tumor of the pleura with poor prognosis. TGF-beta activity was analyzed in a panel of MM tumors by immunohistochemical staining of phosphorylated Smad-2 (P-Smad2). The tumor cells were strongly positive for P-Smad2 whereas LTBP-1 immunoreactivity was abundant in the stroma, and there was a negative correlation between LTBP-1 and P-Smad2 staining. In addition, the high P-Smad2 immunoreactivity correlated with shorter survival of patients. mRNA analysis revealed that TGF-beta1 was the most highly expressed isoform in both normal human pleura and MM tissue. LTBP-1 and LTBP-3 were both abundantly expressed. LTBP-1 was the predominant isoform in established MM cell lines whereas the expression of LTBP-3 was high in control cells. Suppression of LTBP-3 expression by siRNAs resulted in increased TGF-beta activity in MM cell lines accompanied by decreased proliferation. Our results suggest that decreased expression of LTBP-3 in MM could alter the targeting of TGF-beta to the ECM and lead to its increased activation. The current work emphasizes the coordinated process of the assembly and appropriate targeting of LTBPs with distinct adhesive or cytokine harboring properties into the ECM. The hierarchical assembly may have implications in the modulation of signaling events during morphogenesis and tissue remodeling.

The studies on micro-structural defects in deformed composite matrix of Al-Si-Mg and SiC

Detailed Fourier line shape analysis has been performed on three different compositions of the composite matrix of Al-Si-Mg and SiC. The alloy composition in wt% is Al-7%Si, 0.35%Mg, 0.14%Fe and traces of copper and titanium (similar to 0.01%) with SiC varying from 0 to 30wt% in three steps i.e., 0, 10 and 30wt%. The line shift analysis has been performed by considering 111, 200, 220, 311 and 222 reflections after estimating their relative shift. Peak asymmetry analysis has been performed considering neighbouring 111 and 200 reflections and Fourier line shape analysis has been performed after considering the multiple orders 111 and 222, 200 and 400 reflections. Combining all these three analyses it has been found that the deformation stacking faults both intrinsic alpha' and extrinsic alpha " are absent in this alloy system whereas the deformation twin beta has been found to be positive and increases with the increase of SiC concentration. So, like other Al-base alloys this ternary alloy also shows high stacking fault energy, and the addition of SiC introduces deformation twin which increases with its concentration in the deformed lattices.

Tracking and erosion resistance of silicone rubber nanocomposites under positive and negative dc voltages

ASTM D2303 standard provides a method for evaluating the tracking and erosion resistance of polymeric insulators under ac voltages. In this paper, the above method has been extended for evaluating the performance of the insulators under dc stresses. Tests were conducted on polymeric silicone rubber (SR) insulators under positive and negative dc stresses. Micron sized Alumina trihydrate (uATH) and nano sized Alumina (nALU) were used as fillers in SR matrix to improve the resistance to tracking and erosion. Results suggest that SR composites perform better under negative dc than under positive dc voltages. Eroded mass and leakage current data support the above result. Samples with low concentration of nano alumina fillers performed on par with the samples with large loadings of uATH.

A Fast Linear Separability Test by Projection of Positive Points on Subspaces

A geometric and non parametric procedure for testing if two finite set of points are linearly separable is proposed. The Linear Separability Test is equivalent to a test that determines if a strictly positive point h > 0 exists in the range of a matrix A (related to the points in the two finite sets). The algorithm proposed in the paper iteratively checks if a strictly positive point exists in a subspace by projecting a strictly positive vector with equal co-ordinates (p), on the subspace. At the end of each iteration, the subspace is reduced to a lower dimensional subspace. The test is completed within r ≤ min(n, d + 1) steps, for both linearly separable and non separable problems (r is the rank of A, n is the number of points and d is the dimension of the space containing the points). The worst case time complexity of the algorithm is O(nr3) and space complexity of the algorithm is O(nd). A small review of some of the prominent algorithms and their time complexities is included. The worst case computational complexity of our algorithm is lower than the worst case computational complexity of Simplex, Perceptron, Support Vector Machine and Convex Hull Algorithms, if d

Ag@AgI, Core@Shell Structure in Agarose Matrix as Hybrid: Synthesis, Characterization, and Antimicrobial Activity

A novel in situ core@shell structure consisting of nanoparticles of Ag (Ag Nps) and AgI in agarose matrix (Ag@ AgI/agarose) has been synthesized as a hybrid, in order to have an efficient antibacterial agent for repetitive usage with no toxicity. The synthesized core@shell structure is very well characterized by XRD, UV-visible, photoluminescence, and TEM. A detailed antibacterial studies including repetitive cycles are carried out on Gram-negative Escherichia coli (E. coli) and Gram-positive Staphylococcus aureus (S. aureus) bacteria in saline water, both in dark and on exposure to visible light. The hybrid could be recycled for the antibacterial activity and is nontoxic toward human cervical cancer cells (HeLa cells). The water insoluble Ag@AgI in agarose matrix forms a good coating on quartz, having good mechanical strength. EPR and TEM studies are carried out on the Ag@AgI/agarose and the bacteria, respectively, to elucidate a possible mechanism for killing of the bacteria.

Caracterização de Bacilos Gram-Negativos Não Fermentadores não usuais em bacteremias pelas técnicas de Matrix-Assisted Laser Desorption IonizationTime of Flight Mass Spectrometry, sequenciamento de DNA e método fenotípico convencional

Alguns Bastonetes Gram-negativos não fermentadores (BGNNF) costumam ser considerados clinicamente pouco significantes e a sua implicação em infecções é subestimada. Devido à similaridade fenotípica, mudanças taxonômicas, baixa reatividade bioquímica e limitações nos bancos de dados em sistemas comerciais, a identificação de BGNNF é frequentemente equivocada, culminando com a denominação de diferentes micro-organismos apenas como BGNNF, por falta de melhor diferenciação. O objetivo desse estudo foi avaliar, por métodos fenotípico convencional, proteômico e molecular, a identificação de BGNNF incomuns isolados em hemoculturas de pacientes atendidos em um hospital universitário no Rio de Janeiro. Foram selecionadas 78 amostras isoladas de hemoculturas caracterizadas no laboratório clinico como BGNNF para a identificação por sequenciamento dos genes 16S RNA e recA, por um conjunto amplo de testes fenotípicos manuais e por MALDI-TOF MS. Os micro-organismos predominantes na amostragem foram genotipados pela técnica de eletroforese em gel de campo pulsado (PFGE). Pelo sequenciamento do gene 16S rRNA, a maioria das amostras (n=31; 40%) foi incluída no gênero Burkholderia, seguido de Pseudomonas stutzeri (10%) e Delftia acidovorans (4%). Os demais isolados foram agrupados em 27 diferentes espécies. O sequencimento do gene recA identificou a maioria das espécies de Burkholderia como Burkholderia contaminans (n=19; 24%). Os testes fenotípicos incluíram as 31 amostras apenas no CBc e para as outras 47 amostras, a concordância com o sequenciamento do gene 16S rRNA em nível de espécie foi de 64% (n=30) e apenas em gênero a concordância foi de 17% (n=8). A análise comparativa geral da identificação por MALDI-TOF MS com o sequenciamento do gene16S rRNA mostrou que 42% (n=33) das 78 amostras foram concordantes em nível de espécie e 45% (n=35) apenas em gênero. Excluindo as amostras do CBc, houve um aumento da concordância em nível de espécie para 60%. As discordâncias parecem ser devido às diferenças nos perfis proteicos das amostras em relação às amostras-referência do banco de dados do equipamento e podem ser aprimorados com a atualização de perfis no sistema. A análise do polimorfismo genético de B. contaminans mostrou a ausência de um clone disseminado causando surto, além da provável origem ambiental das infecções. Os setores de nefrologia e hemodiálise contribuíram com maior número de pacientes com amostras positivas (5 pacientes e 9 amostras). Os grupos clonais BcoD e BcoE foram encontrados em pacientes assistidos no mesmo setor com diferença de quatro meses (BcoD, nefrologia) e 1,5 ano (BcoE, hemodilálise), entre as culturas, respectivamente. As discordâncias entre as técnicas ocorreram principalmente devido a dificuldade de identificação das espécies do CBc. Os BGNNF incomuns são de difícil caracterização independente da metodologia usada e nenhum método por si só foi capaz de identificar todas as amostras.