The influence of smoking status on malnutrition risk and 1-year mortality in outpatients with chronic obstructive pulmonary disease.

Introduction:  Smoking status in outpatients with chronic obstructive pulmonary disease (COPD) has been associated with a low body mass index (BMI) and reduced mid-arm muscle circumference (Cochrane & Afolabi, 2004). Individuals with COPD identified as malnourished have also been found to be twice as likely to die within 1 year compared to non-malnourished patients (Collins et al., 2010). Although malnutrition is both preventable and treatable, it is not clear what influence current smoking status, another modifiable risk factor, has on malnutrition risk. The current study aimed to establish the influence of smoking status on malnutrition risk and 1-year mortality in outpatients with COPD. Methods:  A prospective nutritional screening survey was carried out between July 2008 and May 2009 at a large teaching hospital (Southampton General Hospital) and a smaller community hospital within Hampshire (Lymington New Forest Hospital). In total, 424 outpatients with a diagnosis of COPD were routinely screened using the ‘Malnutrition Universal Screening Tool’, ‘MUST’ (Elia, 2003); 222 males, 202 females; mean (SD) age 73 (9.9) years; mean (SD) BMI 25.9 (6.4) kg m−2. Smoking status on the date of screening was obtained for 401 of the outpatients. Severity of COPD was assessed using the GOLD criteria, and social deprivation determined using the Index of Multiple Deprivation (Nobel et al., 2008). Results:  The overall prevalence of malnutrition (medium + high risk) was 22%, with 32% of current smokers at risk (who accounted for 19% of the total COPD population). In comparison, 19% of nonsmokers and ex-smokers were likely to be malnourished [odds ratio, 1.965; 95% confidence interval (CI), 1.133–3.394; P = 0.015]. Smoking status remained an independent risk factor for malnutrition even after adjustment for age, social deprivation and disease-severity (odds ratio, 2.048; 95% CI, 1.085–3.866; P = 0.027) using binary logistic regression. After adjusting for age, disease severity, social deprivation, smoking status, malnutrition remained a significant predictor of 1-year mortality [odds ratio (medium + high risk versus low risk), 2.161; 95% CI, 1.021–4.573; P = 0.044], whereas smoking status did not (odds ratio for smokers versus ex-smokers + nonsmokers was 1.968; 95% CI, 0.788–4.913; P = 0.147). Discussion:  This study highlights the potential importance of combined nutritional support and smoking cessation in order to treat malnutrition. The close association between smoking status and malnutrition risk in COPD suggests that smoking is an important consideration in the nutritional management of malnourished COPD outpatients. Conclusions:  Smoking status in COPD outpatients is a significant independent risk factor for malnutrition and a weaker (nonsignificant) predictor of 1-year mortality. Malnutrition significantly predicted 1 year mortality. References:  Cochrane, W.J. & Afolabi, O.A. (2004) Investigation into the nutritional status, dietary intake and smoking habits of patients with chronic obstructive pulmonary disease. J. Hum. Nutr. Diet.17, 3–11. Collins, P.F., Stratton, R.J., Kurukulaaratchym R., Warwick, H. Cawood, A.L. & Elia, M. (2010) ‘MUST’ predicts 1-year survival in outpatients with chronic obstructive pulmonary disease. Clin. Nutr.5, 17. Elia, M. (Ed) (2003) The ‘MUST’ Report. BAPEN. http://www.bapen.org.uk (accessed on March 30 2011). Nobel, M., McLennan, D., Wilkinson, K., Whitworth, A. & Barnes, H. (2008) The English Indices of Deprivation 2007. http://www.communities.gov.uk (accessed on March 30 2011).

Deprivation is an independent predictor of 1-year mortality in outpatients with chronic obstructive pulmonary disease

Deprivation is linked to increased incidence in a number of chronic diseases but its relationship to chronic obstructive pulmonary disease (COPD) is uncertain despite suggestions that the socioeconomic gradient seen in COPD is as great, if not greater, than any other disease (Prescott and Vestbo).1 There is also a need to take into account the confounding effects of malnutrition which have been shown to be independently linked to increased mortality (Collins et al).2 The current study investigated the influence of social deprivation on 1-year survival rates in COPD outpatients, independently of malnutrition. 424 outpatients with COPD were routinely screened for malnutrition risk using the ‘Malnutrition Universal Screening Tool’; ‘MUST’ (Elia),3 between July and May 2009; 222 males and 202 females; mean age 73 (SD 9.9) years; body mass index 25.8 (SD 6.3) kg/m2. Each individual's deprivation was calculated using the index of multiple deprivation (IMD) which was established according to the geographical location of each patient's address (postcode). IMD includes a number of indicators covering economic, housing and social issues (eg, health, education and employment) into a single deprivation score (Nobel et al).4 The lower the IMD score, the lower an individual's deprivation. The IMD was assigned to each outpatient at the time of screening and related to1-year mortality from the date screened. Outpatients who died within 1-year of screening were significantly more likely to reside within a deprived postcode (IMD 19.7±SD 13.1 vs 15.4±SD 10.7; p=0.023, OR 1.03, 95% CI 1.00 to 1.06) than those that did not die. Deprivation remained a significant independent risk factor for 1-year mortality even when adjusted for malnutrition as well as age, gender and disease severity (binary logistic regression; p=0.008, OR 1.04, 95% CI 1.04 to 1.07). Deprivation was not associated with disease-severity (p=0.906) or body mass index, kg/m2 (p=0.921) using ANOVA. This is the first study to show that deprivation, assessed using IMD, is associated with increased 1-year mortality in outpatients with COPD independently of malnutrition, age and disease severity. Deprivation should be considered in the targeted management of these patients.

Risk of metabolic syndrome among children living in metropolitan Kuala Lumpur: A case control study

Background With the increasing prevalence of childhood obesity, the metabolic syndrome has been studied among children in many countries but not in Malaysia. Hence, this study aimed to compare metabolic risk factors between overweight/obese and normal weight children and to determine the influence of gender and ethnicity on the metabolic syndrome among school children aged 9-12 years in Kuala Lumpur and its metropolitan suburbs. Methods A case control study was conducted among 402 children, comprising 193 normal-weight and 209 overweight/obese. Weight, height, waist circumference (WC) and body composition were measured, and WHO (2007) growth reference was used to categorise children into the two weight groups. Blood pressure (BP) was taken, and blood was drawn after an overnight fast to determine fasting blood glucose (FBG) and full lipid profile, including triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and total cholesterol (TC). International Diabetes Federation (2007) criteria for children were used to identify metabolic syndrome. Results Participants comprised 60.9% (n = 245) Malay, 30.9% (n = 124) Chinese and 8.2% (n = 33) Indian. Overweight/obese children showed significantly poorer biochemical profile, higher body fat percentage and anthropometric characteristics compared to the normal-weight group. Among the metabolic risk factors, WC ≥90th percentile was found to have the highest odds (OR = 189.0; 95%CI 70.8, 504.8), followed by HDL-C≤1.03 mmol/L (OR = 5.0; 95%CI 2.4, 11.1) and high BP (OR = 4.2; 95%CI 1.3, 18.7). Metabolic syndrome was found in 5.3% of the overweight/obese children but none of the normal-weight children (p < 0.01). Overweight/obese children had higher odds (OR = 16.3; 95%CI 2.2, 461.1) of developing the metabolic syndrome compared to normal-weight children. Binary logistic regression showed no significant association between age, gender and family history of communicable diseases with the metabolic syndrome. However, for ethnicity, Indians were found to have higher odds (OR = 5.5; 95%CI 1.5, 20.5) compared to Malays, with Chinese children (OR = 0.3; 95%CI 0.0, 2.7) having the lowest odds. Conclusions We conclude that being overweight or obese poses a greater risk of developing the metabolic syndrome among children. Indian ethnicity is at higher risk compared to their counterparts of the same age. Hence, primary intervention strategies are required to prevent this problem from escalating.

Forward-secure hierarchical predicate encryption

Secrecy of decryption keys is an important pre-requisite for security of any encryption scheme and compromised private keys must be immediately replaced. \emph{Forward Security (FS)}, introduced to Public Key Encryption (PKE) by Canetti, Halevi, and Katz (Eurocrypt 2003), reduces damage from compromised keys by guaranteeing confidentiality of messages that were encrypted prior to the compromise event. The FS property was also shown to be achievable in (Hierarchical) Identity-Based Encryption (HIBE) by Yao, Fazio, Dodis, and Lysyanskaya (ACM CCS 2004). Yet, for emerging encryption techniques, offering flexible access control to encrypted data, by means of functional relationships between ciphertexts and decryption keys, FS protection was not known to exist.\smallskip In this paper we introduce FS to the powerful setting of \emph{Hierarchical Predicate Encryption (HPE)}, proposed by Okamoto and Takashima (Asiacrypt 2009). Anticipated applications of FS-HPE schemes can be found in searchable encryption and in fully private communication. Considering the dependencies amongst the concepts, our FS-HPE scheme implies forward-secure flavors of Predicate Encryption and (Hierarchical) Attribute-Based Encryption.\smallskip Our FS-HPE scheme guarantees forward security for plaintexts and for attributes that are hidden in HPE ciphertexts. It further allows delegation of decrypting abilities at any point in time, independent of FS time evolution. It realizes zero-inner-product predicates and is proven adaptively secure under standard assumptions. As the ``cross-product" approach taken in FS-HIBE is not directly applicable to the HPE setting, our construction resorts to techniques that are specific to existing HPE schemes and extends them with what can be seen as a reminiscent of binary tree encryption from FS-PKE.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Associations between infant temperament and early feeding practices. A cross-sectional study of Australian mother-infant dyads from the NOURISH randomised controlled trial

The purpose of this study was to investigate the association between temperament in Australian infants aged 2–7 months and feeding practices of their first-time mothers (n=698). Associations between feeding practices and beliefs (Infant Feeding Questionnaire) and infant temperament (easy-difficult continuous scale from the Short Temperament Scale for Infants) were tested using linear and binary logistic regression models adjusted for a comprehensive range of covariates. Mothers of infants with a more difficult temperament reported a lower awareness of infant cues, were more likely to use food to calm and reported high concern about overweight and underweight. The covariate maternal depression score largely mirrored these associations. Infant temperament may be an important variable to consider in future research on the prevention of childhood obesity. In practice, mothers of temperamentally difficult infants may need targeted feeding advice to minimise the adoption of undesirable feeding practices.

Many paths lead to discovery : analogical retrieval of cancer therapies

This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

Quality based frame selection for video face recognition

Quality based frame selection is a crucial task in video face recognition, to both improve the recognition rate and to reduce the computational cost. In this paper we present a framework that uses a variety of cues (face symmetry, sharpness, contrast, closeness of mouth, brightness and openness of the eye) to select the highest quality facial images available in a video sequence for recognition. Normalized feature scores are fused using a neural network and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face recognition system. Experiments on the Honda/UCSD database shows that the proposed method selects the best quality face images in the video sequence, resulting in improved recognition performance.

State cycles, initialization and the Trivium stream cipher

Trivium is a keystream generator for a binary additive synchronous stream cipher. It was selected in the final portfolio for the Profile 2 category of the eSTREAM project. The keystream generator is constructed using bit- based shift registers. In this paper we present an alternate representation of Trivium using word-based shift registers, with a word size of three bits. This representation is useful for determining cycles of internal state values. Under this representation it is clear that the state space can be partitioned into subspaces and that over some of these subspaces the state update function is effectively linear. The role of the initialization process is critical in ensuring the states used for generating keystream are updated nonlinearly at some point, as the state update function alone does not provide this.

Marginal reversible jump Markov chain Monte Carlo with application to motor unit number estimation

Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).

Setting up a platform for plant-based influenza virus vaccine production in South Africa

Background During a global influenza pandemic, the vaccine requirements of developing countries can surpass their supply capabilities, if these exist at all, compelling them to rely on developed countries for stocks that may not be available in time. There is thus a need for developing countries in general to produce their own pandemic and possibly seasonal influenza vaccines. Here we describe the development of a plant-based platform for producing influenza vaccines locally, in South Africa. Plant-produced influenza vaccine candidates are quicker to develop and potentially cheaper than egg-produced influenza vaccines, and their production can be rapidly upscaled. In this study, we investigated the feasibility of producing a vaccine to the highly pathogenic avian influenza A subtype H5N1 virus, the most generally virulent influenza virus identified to date. Two variants of the haemagglutinin (HA) surface glycoprotein gene were synthesised for optimum expression in plants: these were the full-length HA gene (H5) and a truncated form lacking the transmembrane domain (H5tr). The genes were cloned into a panel of Agrobacterium tumefaciens binary plant expression vectors in order to test HA accumulation in different cell compartments. The constructs were transiently expressed in tobacco by means of agroinfiltration. Stable transgenic tobacco plants were also generated to provide seed for stable storage of the material as a pre-pandemic strategy. Results For both transient and transgenic expression systems the highest accumulation of full-length H5 protein occurred in the apoplastic spaces, while the highest accumulation of H5tr was in the endoplasmic reticulum. The H5 proteins were produced at relatively high concentrations in both systems. Following partial purification, haemagglutination and haemagglutination inhibition tests indicated that the conformation of the plant-produced HA variants was correct and the proteins were functional. The immunisation of chickens and mice with the candidate vaccines elicited HA-specific antibody responses. Conclusions We managed, after synthesis of two versions of a single gene, to produce by transient and transgenic expression in plants, two variants of a highly pathogenic avian influenza virus HA protein which could have vaccine potential. This is a proof of principle of the potential of plant-produced influenza vaccines as a feasible pandemic response strategy for South Africa and other developing countries.

Optimization of human papillomavirus type 16 (HPV-16) L1 expression in plants: Comparison of the suitability of different HPV-16 L1 gene variants and different cell-compartment localization

Virus-like particle-based vaccines for high-risk human papillomaviruses (HPVs) appear to have great promise; however, cell culture-derived vaccines will probably be very expensive. The optimization of expression of different codon-optimized versions of the HPV-16 L1 capsid protein gene in plants has been explored by means of transient expression from a novel suite of Agrobacterium tumefaciens binary expression vectors, which allow targeting of recombinant protein to the cytoplasm, endoplasmic reticulum (ER) or chloroplasts. A gene resynthesized to reflect human codon usage expresses better than the native gene, which expresses better than a plant-optimized gene. Moreover, chloroplast localization allows significantly higher levels of accumulation of L1 protein than does cytoplasmic localization, whilst ER retention was least successful. High levels of L1 (>17% total soluble protein) could be produced via transient expression: the protein assembled into higher-order structures visible by electron microscopy, and a concentrated extract was highly immunogenic in mice after subcutaneous injection and elicited high-titre neutralizing antibodies. Transgenic tobacco plants expressing a human codon-optimized gene linked to a chloroplast-targeting signal expressed L1 at levels up to 11% of the total soluble protein. These are the highest levels of HPV L1 expression reported for plants: these results, and the excellent immunogenicity of the product, significantly improve the prospects of making a conventional HPV vaccine by this means. © 2007 SGM.

Electron petrography of fine-grained matrix in the Karoonda C4 carbonaceous chondrite

The study of matrices of rare Type 4 carbonaceous chondrites can reveal important information on parent body rnetamorp~ic processes and provide a comparison with processes on parent bodies of ordinary chc-idrites. Reflectance spectra (Tholen, 1984) from the two largest asteroids in the asteroid belt, Ceres and Pallas, suggest that they may be metamorphosed carbonaceous chondrites. These two asteroids constitute - onethird of the mass in the asteroid belt implying that type 4-6 carbonaceous chondrites are poorly represented in the meteorite collection and may be of considerable importance. The matrix of the C4 chondrite Karoonda has been investigated using a JEOL 2000FX analytical electron microscope (AEM) with an attached Tracor-Northem TN5500 energy dispersive spectrometer (EDS). In previous studies (Scott and Taylor, 1985; Fitzgerald, 1979; Van Schmus, 1969), the petrography of the Karoonda matrix has been described as consisting largely of coarse-grained (50-200 urn in size) olivine and plagioclase (20-100 um in size), associated with micrometer sized magnetite and rare sulphides. AEM observations on matrix show that in addition to these large grains, there is a significant fraction (10 vol%) of interstitial fine grained phases « 5 urn). The mineralogy of these fine-grained phases differs in some respects from that of the coarser-grained matrix identified by optical and SEM techniques (Scott and Taylor, 1985; Fitzgerald, 1979; Van Schmus, 1969). I~ particular crystals of two compositionally distinct pyroxenes « 2 urn in size) have been identified which have not been previously observed in Karoonda by other analytical techniques. Thin film microanalyses (Mackinnon et al., 1986) of these two pyroxenes indicate compositions consistent with augite and low-Ca pyroxene (- Fs27). Fine-grained anhedral olivine « 2 urn size) is the most abundant phase with composition -Fa29' This composition is essentially indistinguishable from that determined for coarser-grained matrix olivines using an electron microprobe (Scott and Taylor, 1985; Fitzgerald, 1979; Van Schmus, 1969). All olivines are associated with subhedral magnetites « 1 urn size) which contain significant Cr (- 2%) and Al (- 1%) as was also noted for larger sized Karoonda magnetites by Delaney et al. (1985). It has recently been suggested (Burgess et al., 1987) on the basis of sulphur release profiles for S-isotope analyses of Karoonda that CaS04 (anhydrite) may be present. However, no sulphate phase has, as yet, been identified in the matrix of Karoonda. Low magnification contrast images suggest that Karoonda may have a significant porosity within the fine-grained matrix fraction. Most crystals are anhedral and do not show evidence for significant compaction. Individual grains often show single point contact with other grains which result in abundant intergranular voids. These voids frequently contain epoxy which was used as part of the specimen preparation procedure due to the friable nature of the bulk sample.

Analytical electron microscopy of fine-grained phases in primitive interplanetary dust particles and carbonaceous chondrites

In order to describe the total mineralogical diversity within primitive extraterrestrial materials, individual interplanetary dust particles (IDPs) collected from the stratosphere as part of the JSC Cosmic Dust Curatorial Program were analyzed using a var ...

Candidate radial-inflow turbines and high-density working fluids for geothermal power systems

Optimisation of Organic Rankine Cycle (ORCs) for binary-cycle geothermal applications could play a major role in determining the competitiveness of low to moderate temperature geothermal resources. Part of this optimisation process is matching cycles to a given resource such that power output can be maximised. Two major and largely interrelated components of the cycle are the working fluid and the turbine. Both components need careful consideration: the selection of working fluid and appropriate operating conditions as well as optimisation of the turbine design for those conditions will determine the amount of power that can be extracted from a resource. In this paper, we present the rationale for the use of radial-inflow turbines for ORC applications and the preliminary design of several radial-inflow machines based on a number of promising ORC systems that use five different working fluids: R134a, R143a, R236fa, R245fa and n-Pentane. Preliminary meanline analysis lead to the generation of turbine designs for the various cycles with similar efficiencies (77%) but large differences in dimensions (139–289 mm rotor diameter). The highest performing cycle, based on R134a, was found to produce 33% more net power from a 150 °C resource flowing at 10 kg/s than the lowest performing cycle, based on n-Pentane.