Tracing the influence of non-narrative film and expanded cinema sound on experimental music

This study surveys and interrogates key conceptual frameworks and artistic practises that flow through the distinct but interconnected traditions of non-narrative film and experimental music, and examines how these are articulated in my own creative sound practise.

Circulating microRNAs involved in multiple sclerosis

Multiple sclerosis (MS) is an immune-mediated, demyelinating and neurodegenerative disease of the central nervous system. After traumatic brain injury, it is the leading cause of neurology disability in young adults. Considerable advances have been made in identifying genes involved in MS but the genetic and phenotypic complexity associated with this disease significantly hinders any progress. A novel class of small RNA molecules, microRNAs (miRNAs) has acquired much attention because they regulate the expression of up to 30% of protein-coding genes and may play a pivotal role in the development of many, if not all, complex diseases. Seven published studies investigated miRNAs from peripheral blood mononuclear cells, CD4+, CD8+ T cell, B lymphocytes, peripheral blood leukocytes, whole blood and brain astrocytes with MS risk. The absence of MS studies investigating plasma miRNA prompted the current investigation of identifying a circulating miRNA signature in MS. We conducted a microarray analysis of over 900 known miRNA transcripts from plasma samples collected from four MS individuals and four sex-aged and ethnicity matched healthy controls. We identified six plasma miRNA (miR-614, miR-572, miR-648, miR-1826, miR-422a and miR-22) that were significantly up-regulated and one plasma miRNA (miR-1979) that was significantly down-regulated in MS individuals. Both miR-422a and miR-22 have previously been implicated in MS. The present study is the first to show a circulating miRNA signature involved in MS that could serve as a potential prognostic and diagnostic biomarker for MS.

Quantitative proteomic approach to study subcellular localization of membrane proteins

As proteins within cells are spatially organized according to their role, knowledge about protein localization gives insight into protein function. Here, we describe the LOPIT technique (localization of organelle proteins by isotope tagging) developed for the simultaneous and confident determination of the steady-state distribution of hundreds of integral membrane proteins within organelles. The technique uses a partial membrane fractionation strategy in conjunction with quantitative proteomics. Localization of proteins is achieved by measuring their distribution pattern across the density gradient using amine-reactive isotope tagging and comparing these patterns with those of known organelle residents. LOPIT relies on the assumption that proteins belonging to the same organelle will co-fractionate. Multivariate statistical tools are then used to group proteins according to the similarities in their distributions, and hence localization without complete centrifugal separation is achieved. The protocol requires approximately 3 weeks to complete and can be applied in a high-throughput manner to material from many varied sources.

Transcutaneous immunization with a novel lipid-based adjuvant protects against Chlamydia genital and respiratory infections

Mucosal adjuvants are important to overcome the state of immune tolerance normally associated with mucosal delivery and to enhance adaptive immunity to often-weakly immunogenic subunit vaccine antigens. Unfortunately, adverse side effects of many experimental adjuvants limit the number of adjuvants approved for vaccination. Lipid C is a novel, non-toxic, lipid oral vaccine-delivery formulation, developed originally for oral delivery of the live Mycobacterium bovis Bacille Calmette-Guerin (BCG) vaccine. In the present study, murine models of chlamydial respiratory and genital tract infections were used to determine whether transcutaneous immunization (TCI) with Lipid C-incorporated protein antigens could elicit protective immunity at the genital and respiratory mucosae. BALB/c mice were immunized transcutaneously with Lipid C containing the chlamydial major outer membrane protein (MOMP), with and without addition of cholera toxin and CpG-ODN 1826 (CT/CpG). Both vaccine combinations induced mixed cell-mediated and mucosal antibody immune responses. Immunization with Lipid C-incorporated MOMP (Lipid C/MOMP), either alone or with CT/CpG resulted in partial protection following live challenge with Chlamydia muridarum as evidenced by a significant reduction in recoverable Chlamydia from both the genital secretions and lung tissue. Protection induced by immunization with Lipid C/MOMP alone was not further enhanced by the addition of CT/CpG. These results highlight the potential of Lipid C as a novel mucosal adjuvant capable of targeting multiple mucosal surfaces following TCI. Protection at both the respiratory and genital mucosae was achieved without the requirement for potentially toxic adjuvants, suggesting that Lipid C may provide a safe effective mucosal adjuvant for human vaccination.

Weekly cisplatin concurrently with radiotherapy in head and neck squamous cell cancer : a retrospective analysis of a tertiary institute experience

Radiotherapy combined with three weekly 100 mg/m2 of cisplatin is the accepted standard of care in head and neck squamous cell carcinoma. However, this regimen is associated with severe toxicities with devastating effects on patients. Alternative protocols like weekly 40 mg/m2 have been used in an attempt to reduce toxicities. The main objective of the present study is to identify the dose intensities and toxicities of weekly cisplatin in patients treated in a tertiary centre over a 12 month period. Included patients had squamous cell carcinoma arising in the oral cavity, oropharynx, larynx, or hypopharynx. Patients were excluded if they had nasopharyngeal squamous cell carcinoma, distant metastasis or if they had prior treatment for head and neck cancer excluding neck dissection. During the study period, 52 patients met the inclusion criteria and their data were retrospectively obtained from the patients' database of St James hospital, Dublin. The median age of the study cohort was 54 years (range 33-73). Of the patients, 40 (76.9 %) were male and 12 (20.1 %) were female. The primary tumour sites were as follows: oral cavity and oropharynx in 38 (73 %), larynx in 10 (19 %), and hypopharynx in 4 (8 %). In total, 33 (63.5 %) patients had stage IV disease, while 19 (36.5 %) had stage III disease. Treatment was definitive in 35 (67 %) patients and adjuvant in 17 (35 %). Full-dose radiotherapy was achieved in 50 (96 %) patients. Only 22 (42.3 %) patients completed the intended six cycles of chemotherapy. Cumulative dose of 200 mg/m2 or more was reached in 37 (71 %) patients. The acute adverse effects included grades 3 and 4 mucositis, which occurred in 22 (43.3 %) and 6 patients (12 %), respectively. Grade 3 and 4 neutropenia occurred in six (11.5 %) and three (5.7 %) patients, respectively. The only other haematological toxicity was grade 3 anaemia in 20 (38.4 %) patients. There was no grade 3 or 4 renal toxicity among the study cohort, although grade 2 was observed in six (11.5 %) patients. Death occurred in one patient due to neutropenic septicaemia. In conclusion, weekly cisplatin is associated with moderate to severe toxicities and might lead to suboptimal chemotherapy delivery. More prospective clinical studies are required to determine the optimal chemoradiation regimen in head and neck squamous cell carcinoma.

Symptom control and quality of life in lux-lung 3 : a phase III study of afatinib or cisplatin/pemetrexed in patients with advanced lung adenocarcinoma with EGFR mutations

Purpose Patient-reported symptoms and health-related quality of life (QoL) benefits were investigated in a randomized, phase III trial of afatinib or cisplatin/pemetrexed. Patients and Methods Three hundred forty-five patients with advanced epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma were randomly assigned 2:1 to afatinib 40 mg per day or up to six cycles of cisplatin/pemetrexed. Lung cancer symptoms and health-related QoL were assessed every 21 days until progression using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire C30 and Lung Cancer-13 questionnaires. Analyses of cough, dyspnea, and pain were preplanned, including percentage of patients who improved on therapy, time to deterioration of symptoms, and change in symptoms over time. Results Questionnaire compliance was high. Compared with chemotherapy, afatinib significantly delayed the time to deterioration for cough (hazard ratio [HR], 0.60; 95% CI, 0.41 to 0.87; P = .007) and dyspnea (HR, 0.68; 95% CI, 0.50 to 0.93; P = .015), but not pain (HR, 0.83; 95% CI, 0.62 to 1.10; P = .19). More patients on afatinib (64%) versus chemotherapy (50%) experienced improvements in dyspnea scores (P lt; .010). Differences in mean scores over time significantly favored afatinib over chemotherapy for cough (P lt; .001) and dyspnea (P = .001). Afatinib showed significantly better mean scores over time in global health status/QoL (P = .015) and physical (P = .001), role (P = .004), and cognitive (P lt; .007) functioning compared with chemotherapy. Fatigue and nausea were worse with chemotherapy, whereas diarrhea, dysphagia, and sore mouth were worse with afatinib (all P = .01). Conclusion In patients with lung adenocarcinoma with EGFR mutations, first-line afatinib was associated with better control of cough and dyspnea compared with chemotherapy, although diarrhea, dysphagia, and sore mouth were worse. Global health status/QoL was also improved over time with afatinib compared with chemotherapy.

Object tracking via non-Euclidean geometry : a Grassmann approach

A robust visual tracking system requires an object appearance model that is able to handle occlusion, pose, and illumination variations in the video stream. This can be difficult to accomplish when the model is trained using only a single image. In this paper, we first propose a tracking approach based on affine subspaces (constructed from several images) which are able to accommodate the abovementioned variations. We use affine subspaces not only to represent the object, but also the candidate areas that the object may occupy. We furthermore propose a novel approach to measure affine subspace-to-subspace distance via the use of non-Euclidean geometry of Grassmann manifolds. The tracking problem is then considered as an inference task in a Markov Chain Monte Carlo framework via particle filtering. Quantitative evaluation on challenging video sequences indicates that the proposed approach obtains considerably better performance than several recent state-of-the-art methods such as Tracking-Learning-Detection and MILtrack.

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.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Multi-shot person re-identification via relational stein divergence

Person re-identification is particularly challenging due to significant appearance changes across separate camera views. In order to re-identify people, a representative human signature should effectively handle differences in illumination, pose and camera parameters. While general appearance-based methods are modelled in Euclidean spaces, it has been argued that some applications in image and video analysis are better modelled via non-Euclidean manifold geometry. To this end, recent approaches represent images as covariance matrices, and interpret such matrices as points on Riemannian manifolds. As direct classification on such manifolds can be difficult, in this paper we propose to represent each manifold point as a vector of similarities to class representers, via a recently introduced form of Bregman matrix divergence known as the Stein divergence. This is followed by using a discriminative mapping of similarity vectors for final classification. The use of similarity vectors is in contrast to the traditional approach of embedding manifolds into tangent spaces, which can suffer from representing the manifold structure inaccurately. Comparative evaluations on benchmark ETHZ and iLIDS datasets for the person re-identification task show that the proposed approach obtains better performance than recent techniques such as Histogram Plus Epitome, Partial Least Squares, and Symmetry-Driven Accumulation of Local Features.

Improved image set classification via joint sparse approximated nearest subspaces

Existing multi-model approaches for image set classification extract local models by clustering each image set individually only once, with fixed clusters used for matching with other image sets. However, this may result in the two closest clusters to represent different characteristics of an object, due to different undesirable environmental conditions (such as variations in illumination and pose). To address this problem, we propose to constrain the clustering of each query image set by forcing the clusters to have resemblance to the clusters in the gallery image sets. We first define a Frobenius norm distance between subspaces over Grassmann manifolds based on reconstruction error. We then extract local linear subspaces from a gallery image set via sparse representation. For each local linear subspace, we adaptively construct the corresponding closest subspace from the samples of a probe image set by joint sparse representation. We show that by minimising the sparse representation reconstruction error, we approach the nearest point on a Grassmann manifold. Experiments on Honda, ETH-80 and Cambridge-Gesture datasets show that the proposed method consistently outperforms several other recent techniques, such as Affine Hull based Image Set Distance (AHISD), Sparse Approximated Nearest Points (SANP) and Manifold Discriminant Analysis (MDA).

Association of MMP-2 activation potential with metastatic progression in human breast cancer cell lines independent of MMP-2 production

Background: Expression of matrix metalloproteinase-2 (MMP-2), the 72-kd type IV collagenase/gelatinase, by cancer cells has been implicated in metastasis through cancer cell invasion of basement membranes mediated by degradation of collagen IV. However, the abundance of this latent proenzyme in normal tissues and fluids suggests that MMP-2 proenzyme utilization is limited by its physiological activation rather than expression alone. We previously reported activation of this proenzyme by normal and malignant fibroblastoid cells cultured on collagen I (vitrogen) gels. Purpose: Our purposes in this study were 1) to determine whether MMP-2 activation is restricted to the more invasive human breast cancer cell lines and 2) to localize the activating mechanism. Methods: Zymography was used to monitor MMP-2 activation through detection of latent MMP-2 (72 kd) and mature species of smaller molecular weight (59 or 62 kd). Human breast cancer cell lines cultured on plastic, vitrogen, and other matrices were thus screened for MMP- 2 activation. Collagen I-cultured cells were exposed to cycloheximide, a protein synthesis inhibitor, or to protease inhibitors to determine the nature of the MMP-2-activating mechanism. Triton X-114 (TX-114) detergent extracts from cells cultured on collagen I or plastic were incubated with latent MMP-2 and analyzed by zymography to localize the MMP-2 activator. Results: MMP-2 activation was only induced by collagen I culture in the more aggressive, highly invasive estrogen receptor-negative, vimentin-positive human breast cancer cell lines (Hs578T, MDA-MB-436, BT549, MDA-MB-231, MDA- MB-435, MCF-7(ADR)) and was independent of MMP-2 production. MMP-2 activation was detected in cells cultured on collagen I gels but not in those cultured on gelatin gels, Matrigel, or thin layers of collagen I or IV, gelatin, or fibronectin. Collagen-induced activation was specific for the enzyme species MMP-2, since MMP-9, the 92-kd type IV collagenase/gelatinase, was not activatable under similar conditions. MMP-2 activation was inhibited by cycloheximide and was sensitive to a metalloproteinase inhibitor but not to aspartyl, serine, or cysteinyl protease inhibitors. MMP-2 activation was detected in the hydrophobic, plasma membrane-enriched, TX-114 extracts from invasive collagen I-cultured cells. Conclusion: Collagen I-induced MMP-2 activation is restricted to highly invasive estrogen receptor-negative, vimentin-positive human breast cancer cell lines, is independent of MMP-2 production, and is associated with metastatic potential. Our findings are consistent with plasma membrane localization of the activator. Implications: The MMP-2 activation mechanism may represent a new target for diagnosis, prognosis, and treatment of human breast cancer.

The impact of mobile phone distraction on the braking behaviour of young drivers : a hazard-based duration model

Braking is a crucial driving task with a direct relationship with crash risk, as both excess and inadequate braking can lead to collisions. The objective of this study was to compare the braking profile of young drivers distracted by mobile phone conversations to non-distracted braking. In particular, the braking behaviour of drivers in response to a pedestrian entering a zebra crossing was examined using the CARRS-Q Advanced Driving Simulator. Thirty-two licensed drivers drove the simulator in three phone conditions: baseline (no phone conversation), hands-free, and handheld. In addition to driving the simulator, each participant completed questionnaires related to driver demographics, driving history, usage of mobile phones while driving, and general mobile phone usage history. The drivers were 18–26 years old and split evenly by gender. A linear mixed model analysis of braking profiles along the roadway before the pedestrian crossing revealed comparatively increased decelerations among distracted drivers, particularly during the initial 20 kph of deceleration. Drivers’ initial 20 kph deceleration time was modelled using a parametric accelerated failure time (AFT) hazard-based duration model with a Weibull distribution with clustered heterogeneity to account for the repeated measures experiment design. Factors found to significantly influence the braking task included vehicle dynamics variables like initial speed and maximum deceleration, phone condition, and driver-specific variables such as licence type, crash involvement history, and self-reported experience of using a mobile phone whilst driving. Distracted drivers on average appear to reduce the speed of their vehicle faster and more abruptly than non-distracted drivers, exhibiting excess braking comparatively and revealing perhaps risk compensation. The braking appears to be more aggressive for distracted drivers with provisional licenses compared to drivers with open licenses. Abrupt or excessive braking by distracted drivers might pose significant safety concerns to following vehicles in a traffic stream.