Recent radiopharmaceutical research at the AAEC Research Establishment.

During the past few years a large part of the radiochemical research carried out at Lucas Heights has been devoted to the synthesis of ligands capable of forming chelate complexes with technetium-99m as part of a search for tumour-localising radiopharmaceuticals. An account is given of the synthesis and biological evaluation of a range of these compounds and of the investigation of certain biochemical and biological properties affecting the clinical application of both ligands and radiopharmaceuticals. In addition to the search for novel Tc-99m radiopharmaceuticals major research programs on the development of Tc-99m generating systems have been in progress at Lucas Heights for several years. Work on the AAEC's Mark III Tc-99m technetium generator has been brought to a successful conclusion. A new type of Tc-99m generator which uses an insoluble zirconium molybdate gel and provides high yields of pertechnetate by a simple elution technique has also been developed. Studies are in progress on the osmium-iridium generator

Providing alternative measures for addressing adverse drug-drug interactions

First Online 30 March 2019Clinical Practice Guidelines (CPGs) are documents used in daily clinical practice that provide advice on how to best diagnose and treat diseases in the form of a list of clinical recommendations. When simultaneously applying multiple CPGs to patients, this can lead to complex multiple drug regimens (polypharmacy) with the potential for harmful combinations of drugs. The need to address these adverse drug events calls forth for systems capable of not only automatically represent the common potential conflicts or interactions that can happen when merging CPGs but also systems capable of providing conflict-free alternatives. This paper presents a solution that represents CPGs as Computer-Interpretable Guidelines (CIGs) and allows the automatic identification of drug conflicts and the provision of alternative measures to resolve these conflicts.This work has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope UID/CEC/ 00319/2013. The work of Tiago Oliveira was supported by JSPS KAKENHI Grant Number JP18K18115

MM Algorithms for Geometric and Signomial Programming

This paper derives new algorithms for signomial programming, a generalization of geometric programming. The algorithms are based on a generic principle for optimization called the MM algorithm. In this setting, one can apply the geometric-arithmetic mean inequality and a supporting hyperplane inequality to create a surrogate function with parameters separated. Thus, unconstrained signomial programming reduces to a sequence of one-dimensional minimization problems. Simple examples demonstrate that the MM algorithm derived can converge to a boundary point or to one point of a continuum of minimum points. Conditions under which the minimum point is unique or occurs in the interior of parameter space are proved for geometric programming. Convergence to an interior point occurs at a linear rate. Finally, the MM framework easily accommodates equality and inequality constraints of signomial type. For the most important special case, constrained quadratic programming, the MM algorithm involves very simple updates.Comment: 16 pages, 1 figur

Nemo: a computational tool for analyzing nematode locomotion

The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement. In this paper, we introduce Nemo (nematode movement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification. Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.Comment: 12 pages, 2 figures. accepted by BMC Neuroscience 2007, 8:8

Decentralized Estimation over Orthogonal Multiple-access Fading Channels in Wireless Sensor Networks - Optimal and Suboptimal Estimators

Optimal and suboptimal decentralized estimators in wireless sensor networks (WSNs) over orthogonal multiple-access fading channels are studied in this paper. Considering multiple-bit quantization before digital transmission, we develop maximum likelihood estimators (MLEs) with both known and unknown channel state information (CSI). When training symbols are available, we derive a MLE that is a special case of the MLE with unknown CSI. It implicitly uses the training symbols to estimate the channel coefficients and exploits the estimated CSI in an optimal way. To reduce the computational complexity, we propose suboptimal estimators. These estimators exploit both signal and data level redundant information to improve the estimation performance. The proposed MLEs reduce to traditional fusion based or diversity based estimators when communications or observations are perfect. By introducing a general message function, the proposed estimators can be applied when various analog or digital transmission schemes are used. The simulations show that the estimators using digital communications with multiple-bit quantization outperform the estimator using analog-and-forwarding transmission in fading channels. When considering the total bandwidth and energy constraints, the MLE using multiple-bit quantization is superior to that using binary quantization at medium and high observation signal-to-noise ratio levels

The dynamics of apparent horizons in Robinson-Trautman spacetimes

We present an alternative scheme of finding apparent horizons based on spectral methods applied to Robinson-Trautman spacetimes. We have considered distinct initial data such as representing the spheroids of matter and the head-on collision of two non-rotating black holes. The evolution of the apparent horizon is presented. We have obtained in some cases a mass gap between the final Bondi and apparent horizon masses, whose implications were briefly commented in the light of the thermodynamics of black holes.Comment: 9 pages, 7 figure

Should I Take Aspirin? (SITA): RCT of a decision aid for cancer chemoprevention.

Background Australian guidelines recommend that all people aged 50-70 years old consider taking low-dose aspirin to reduce the risk of colorectal cancer (CRC). Aim To determine the effect of a consultation with a researcher in general practice using a decision aid about taking low-dose aspirin to prevent CRC on informed decision-making and low-dose aspirin uptake compared to a general CRC prevention brochure. Design and Setting Individually randomised controlled trial in six general practices in Victoria, Australia, from October 2020 to March 2021. Method Patients aged 50-70 years attending a general practitioner (GP) were recruited consecutively. The intervention was a consultation using a decision aid to discuss taking aspirin to reduce CRC risk; control consultations discussed reducing CRC risk generally. The self-reported co-primary outcomes were informed choices about taking aspirin at one month and low-dose aspirin uptake at six months. Results 261 participants (86% of eligible patients) were randomised into trial arms (129 intervention, 132 control). 17.7% (20/113) of intervention and 7.6% (9/118) control participants reported making an informed choice at one month, an estimated 9.1% (95% CI 0.29% to 18.5) between-arm difference in proportions [odds ratio (OR) 2.47 (97.5% CI:0.94 to 6.52) p=0.074]. The proportions of individuals who reported using aspirin at six months were: 10.2% (12/118) intervention vs 13.8% (16/116) control (estimated between-arm difference: -4.0% (95% CI: -13.5 to 5.5); [OR= 0.68 (97.5% CI:0.27 to 1.70), p= 0.692]. Conclusion The decision aid improved informed decision-making; but has little effect on long-term regular use of aspirin to reduce CRC risk

Measuring persistent and transient energy efficiency in the US

The promotion of US energy efficiency policy is seen as a very important activity. Generally, the level of energy efficiency of a country or state is approximated by energy intensity, commonly calculated as the ratio of energy use to GDP. However, energy intensity is not an accurate proxy for energy efficiency given that changes in energy intensity are a function of changes in several factors including the structure of the economy, climate, efficiency in the use of resources, behaviour and technical change. The aim of this paper is to measure persistent and transient energy efficiency for the whole economy of 49 states in the US using a stochastic frontier energy demand approach. A total US energy demand frontier function is estimated using panel data for 49 states over the period 1995 to 2009 using two panel data models: the Mundlak version of the random effects model (which estimates the persistent part of the energy efficiency) and the true random effects model (which estimates the transient part of the energy efficiency). The analysis confirms that energy intensity is not a good indicator of energy efficiency, whereas, by controlling for a range of economic and other factors, the measures of energy efficiency obtained via the approach adopted here are. Moreover, the estimates show that although for some states energy intensity might give a reasonable indication of a state’s relative energy efficiency, this is not the case for all states.ISSN:1570-646XISSN:1570-647

Mammographic density, breast cancer risk and risk prediction

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models