A clean bill of health: a state-of-the-art general, trauma and orthopaedic surgical centre

ABSTRACT: Potential drawbacks to the use of Ultra Clean Ventilation (UCV) technology in modern operating theatres include difficulties with locating pendant lighting, excessive noise levels and excessive operational costs. The main benefits of using UCV technology however, is a reduction in postoperative Surgical Site Infection (SSI) rates. To solve the above challenge a novel surgical theatre centre has been designed to accommodate three state-of-the-art theatre suites, a seven-bed recovery ward, a fifteen-bed orthopaedic ward and attendant ancillary spaces. At the heart of the complex, the three unique theatre environments utilize innovative skirt-less ultra-clean laminar-flow ventilation canopies to help control airborne infection during surgical procedures. The novel approach allows uninterrupted use of multi-flexible lighting and surgical pendants, has been designed to minimise noise levels and utilises heat recovery to minimise running costs. The innovative approach to infection control is continued through into the detailed design of the theatre wall, ceiling and floor systems, and integrates with the overall strategy of creating a dramatic and stimulating working environment where traditionally aesthetic sterility was de rigueur

Pleural Fluid Mesothelin as an Adjunct to the Diagnosis of Pleural Malignant Mesothelioma

Rationale:. The diagnosis of pleural malignant mesothelioma (MM) by effusion cytology may be difficult and is currently controversial. Effusion mesothelin levels are increased in patients with MM but the clinical role of this test is uncertain. Objectives:. To determine the clinical value of measuring mesothelin levels in pleural effusion supernatant to aid diagnosis of MM. Methods and Measurements. Pleural effusion samples were collected prospectively from 1331 consecutive patients. Mesothelin levels were determined by commercial ELISA in effusions and their relationship to concurrent pathology reporting and final clinical diagnosis was determined. Results:. 2156 pleural effusion samples from 1331 individuals were analysed. The final clinical diagnosis was 183 MM, 436 non-MM malignancy, and 712 nonmalignant effusions. Effusion mesothelin had a sensitivity of 67% for MM at 95% specificity. Mesothelin was elevated in over 47% of MM cases in effusions obtained before definitive diagnosis of MM was established. In the setting of inconclusive effusion cytology, effusion mesothelin had a positive predictive value of 79% for MM and 94% for malignancy. Conclusions:. A mesothelin-positive pleural effusion, irrespective of the identification of malignant cells, indicates the likely presence of malignancy and adds weight to the clinical rationale for further investigation to establish a malignant diagnosis

A Bayesian screening approach for hepatocellular carcinoma using multiple longitudinal biomarkers

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142917/1/biom12717.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142917/2/biom12717-sup-0001-SuppData.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142917/3/biom12717_am.pd

The summer games

As part of a nationally funded project, we have developed and used \u27games\u27 as student centred teaching resources to enrich the capacity for design in beginning students in architecture, landscape architecture and urban design. Students are encouraged to learn inter-actively in a milieu characterised by self-directed play in a low-risk computer modelling environment. Recently thirteen upper year design students, six from Adelaide University (Adelaide, South Australia, Australia), five from Deakin University (Geelong, Victoria, Australia), and two from Victoria University, (Wellington, New Zealand) were commissioned over a ten-week period of the 2000-2001 Australian summer to construct a new series of games. This paper discusses the process behind constructing these games.This paper discusses six topical areas:&ndash; what is a game;&ndash; specific goals of the summer games;&ndash; the structure of a game;&ndash; the game-making process;&ndash; key findings from the production unit; and&ndash; future directions.<br /

Thioflavin T indicates mitochondrial membrane potential in mammalian cells

The fluorescent benzothiazole dye thioflavin T (ThT) is widely used as a marker for protein aggregates, most commonly in the context of neurodegenerative disease research and diagnosis. Recently, this same dye was shown to indicate membrane potential in bacteria due to its cationic nature. This finding prompted a question whether ThT fluorescence is linked to the membrane potential in mammalian cells, which would be important for appropriate utilization of ThT in research and diagnosis. Here, we show that ThT localizes into the mitochondria of HeLa cells in a membrane-potential-dependent manner. Specifically, ThT colocalized in cells with the mitochondrial membrane potential indicator tetramethylrhodamine methyl ester (TMRM) and gave similar temporal responses as TMRM to treatment with a protonophore, carbonyl cyanide-4-(trifluoromethoxy) phenylhydrazone (FCCP). Additionally, we found that presence of ThT together with exposure to blue light (λ = 405 nm), but neither factor alone, caused depolarization of mitochondrial membrane potential. This additive effect of the concentration and blue light was recapitulated by a mathematical model implementing the potential-dependent distribution of ThT and its effect on mitochondrial membrane potential through photosensitization. These results show that ThT can act as a mitochondrial membrane potential indicator in mammalian cells, when used at low concentrations and with low blue light exposure. However, it causes dissipation of the mitochondrial membrane potential depending additively on its concentrations and blue light exposure. This conclusion motivates a re-evaluation of ThT’s use at micromolar range in live-cell analyses and indicates that this dye can enable future studies on the potential connections between mitochondrial membrane potential dynamics and protein aggregation

Mixtures of large-scale dynamic functional brain network modes

Accurate temporal modelling of functional brain networks is essential in the quest for understanding how such networks facilitate cognition. Researchers are beginning to adopt time-varying analyses for electrophysiological data that capture highly dynamic processes on the order of milliseconds. Typically, these approaches, such as clustering of functional connectivity profiles and Hidden Markov Modelling (HMM), assume mutual exclusivity of networks over time. Whilst a powerful constraint, this assumption may be compromising the ability of these approaches to describe the data effectively. Here, we propose a new generative model for functional connectivity as a time-varying linear mixture of spatially distributed statistical “modes”. The temporal evolution of this mixture is governed by a recurrent neural network, which enables the model to generate data with a rich temporal structure. We use a Bayesian framework known as amortised variational inference to learn model parameters from observed data. We call the approach DyNeMo (for Dynamic Network Modes), and show using simulations it outperforms the HMM when the assumption of mutual exclusivity is violated. In resting-state MEG, DyNeMo reveals a mixture of modes that activate on fast time scales of 100–150 ms, which is similar to state lifetimes found using an HMM. In task MEG data, DyNeMo finds modes with plausible, task-dependent evoked responses without any knowledge of the task timings. Overall, DyNeMo provides decompositions that are an approximate remapping of the HMM’s while showing improvements in overall explanatory power. However, the magnitude of the improvements suggests that the HMM’s assumption of mutual exclusivity can be reasonable in practice. Nonetheless, DyNeMo provides a flexible framework for implementing and assessing future modelling developments

Novel Risk Models for early detection and screening of Ovarian Cancer

Purpose: Ovarian cancer (OC) is the most lethal gynaecological cancer. Early detection is required to improve patient survival. Risk estimation models were constructed for Type I (Model I) and Type II (Model II) OC from analysis of Protein Z, Fibronectin, C-reactive protein and CA125 levels in prospectively collected samples from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Results: Model I identifies cancers earlier than CA125 alone, with a potential lead time of 3-4 years. Model II detects a number of high grade serous cancers at an earlier stage (Stage I/II) than CA125 alone, with a potential lead time of 2-3 years and assigns high risk to patients that the ROCA Algorithm classified as normal. Materials and Methods: This nested case control study included 418 individual serum samples serially collected from 49 OC cases and 31 controls up to six years pre-diagnosis. Discriminatory logit models were built combining the ELISA results for candidate proteins with CA125 levels. Conclusions: These models have encouraging sensitivities for detecting pre-clinical ovarian cancer, demonstrating improved sensitivity compared to CA125 alone. In addition we demonstrate how the models improve on ROCA for some cases and outline their potential future use as clinical tools