Anti-infective photodynamic biomaterials for the prevention of intraocular lens-associated infectious endophthalmitis

Bacterial attachment onto intraocular lenses (IOLs) during cataract extraction and IOL implantation is a prominent aetiological factor in the pathogenesis of infectious endophthalmitis. Photodynamic therapy (PDT) and photodynamic antimicrobial chemotherapy (PACT) have shown that photosensitizers are effective treatments for cancer, and in the photoinactivation of bacteria, viruses, fungi and parasites, in the presence of light. To date, no method of localizing the photocytotoxic effect of a photosensitizer at a biomaterial surface has been demonstrated. Here we show a method for concentrating this effect at a material surface to prevent bacterial colonization by attaching a porphyrin photosensitizer at, or near to, that surface, and demonstrate the principle using IOL biomaterials. Anionic hydrogel copolymers were shown to permanently bind a cationic porphyrin through electrostatic interactions as a thin surface layer. The mechanical and thermal properties of the materials showed that the porphyrin acts as a surface cross-linking agent, and renders surfaces more hydrophilic. Importantly, Staphylococcus epidermidis adherence was reduced by up to 99.0 ± 0.42% relative to the control in intense light conditions and 91.7± 5.99% in the dark. The ability to concentrate the photocytotoxic effect at a surface, together with a significant dark effect, provides a platform for a range of light-activated anti-infective biomaterial technologies.

Robust face recognition using posterior union model based neural networks

Face recognition with unknown, partial distortion and occlusion is a practical problem, and has a wide range of applications, including security and multimedia information retrieval. The authors present a new approach to face recognition subject to unknown, partial distortion and occlusion. The new approach is based on a probabilistic decision-based neural network, enhanced by a statistical method called the posterior union model (PUM). PUM is an approach for ignoring severely mismatched local features and focusing the recognition mainly on the reliable local features. It thereby improves the robustness while assuming no prior information about the corruption. We call the new approach the posterior union decision-based neural network (PUDBNN). The new PUDBNN model has been evaluated on three face image databases (XM2VTS, AT&T and AR) using testing images subjected to various types of simulated and realistic partial distortion and occlusion. The new system has been compared to other approaches and has demonstrated improved performance.

Anti-Semitism in France: Past and present

This article discusses the so-called newness of today's antisemitism through the historical and social specificities of antisemitism in French society. It casts light on the continuities of antisemitic discourse in France, but also its transformation in relation to the French colonial heritage and the recent ‘communitarianisation’ of France's social life. This analysis of antisemitism is furthered by the presentation of two case-studies: the controversial discourses of comedian Dieudonné and Kémi Séba, leader of a black supremacist movement called Tribu KA which stirred controversies in the 2000s. These two examples emphasise the fact that antisemitic discourse is better understood as a narrative about downward social mobility and status, which hardly makes antisemitism new.

The Effects of Anti-Hypertensive Drugs Evaluated Using Markov Modelling for Northern Ireland Chronic Kidney Disease Patients

The aim of this paper is to use Markov modelling to
investigate survival for particular types of kidney patients
in relation to their exposure to anti-hypertensive treatment
drugs. In order to monitor kidney function an intuitive three
point assessment is proposed through the collection of blood
samples in relation to Chronic Kidney Disease for Northern
Ireland patients. A five state Markov Model was devised
using specific transition probabilities for males and
females over all age groups. These transition probabilities
were then adjusted appropriately using relative risk scores
for the event death for different subgroups of patients. The
model was built using TreeAge software package in order to
explore the effects of anti-hypertensive drugs on patients.