Should we reconsider competition in residential electricity supply? Survey results in North Carolina

Retail competition has been introduced in many states as part of electricity industry deregulation. Following problems in the electricity market in California in 2000/01 many states, including NC, put deregulation plans on hold. Where retail competition is allowed consumers can choose their electricity supplier, and companies can compete for customers on the basis of rates and/or other options such as green energy choices. The welfare benefits of retail competition depend on consumers’ willingness to switch suppliers, and in many cases people choose to stay with their current supplier even though rivals offer savings. In that sense consumers are ‘sticky’ in the same way they are with other services such as banking and credit. The question then becomes: should states reconsider retail competition or stay with the status quo? To help answer this question we survey residents in two North Carolina counties. Our survey focuses on: (i) households’ knowledge of and interest in retail competition (ii) factors that would encourage them to switch suppliers, with an emphasis on smart meters and (iii) how large the potential savings would have to be to encourage switching. Key Words: electricity supply, retail competition, switching

Maturation of the gilt\u27s uterus before puberty: response to progesterone at different ages

We determined the age at which progesterone induced certain responses in the gilt\u27s uterus. The prepubertal maturation permitting each response is being studied currently with the intent of using the information to develop methods to improve litter size in pigs, perhaps by identifying markers for uterine function that could be used before gilts enter the breeding herd.; Swine Day, Manhattan, KS, November 16, 199

MO4 - Using AHP weights to fill missing gaps in Markov decision models

OBJECTIVES:\ud We propose to combine the versatility of the analytic hierarchy process (AHP) with the decision-analytic sophistication of health-economic modeling in a new methodology for early technology assessment. As an illustration, we apply this methodology to a new technology to diagnose breast cancer.\ud \ud METHODS:\ud The AHP is a technique for multicriteria analysis, relatively new in the fi eld of technology assessment. It can integrate both quantitative and qualitative criteria in the assessment of alternative technologies. We applied the AHP to prioritize a more versatile set of outcome measures than most Markov models do. These outcome measures include clinical effectiveness and costs, but also weighted estimates of patient comfort and safety. Furthermore, as no clinical data are available for this technology yet, the AHP is applied to predict the performance of the new technology with regard to all these outcome measures. Results of the AHP are subsequently integrated in a Markov model to make an early assessment of the expected incremental cost-effectiveness of alternative technologies.\ud \ud RESULTS:\ud We systematically estimated priors on the clinical effectiveness and wider impacts of the new technology using AHP. In our illustration, AHP estimates for sensitivity and specifi city of the new diagnostic technology were used as probability parameters in the Markov model. Moreover, the prioritized outcome measures including clinical effectiveness (weight = 0.61), patient comfort (weight = 0.09), and safety (weight = 0.30) were integrated into one outcome measure in the Markov model.\ud \ud CONCLUSIONS:\ud Combining AHP and Markov modelling is particularly valuable in early technology assessment when evidence about the effectiveness of health care technology is still limited or missing. Moreover, combining these methods is valuable when decision makers are interested in other patient relevant outcomes measures besides the technology’s clinical effectiveness, and that may not (adequately or explicitly) be captured in mainstream utility measures

Validation of precision-cut liver slices to study drug-induced cholestasis:A transcriptomics approach

Hepatotoxicity is one of the major reasons for withdrawal of drugs from the market. Therefore, there is a need to screen new drugs for hepatotoxicity in humans at an earlier stage. The aim of this study was to validate human precision-cut liver slices (PCLS) as an ex vivo model to predict drug-induced cholestasis and identify the possible mechanisms of cholestasis-induced toxicity using gene expression profiles. Five hepatotoxicants, which are known to induce cholestasis (alpha-naphthyl isothiocyanate, chlorpromazine, cyclosporine, ethinyl estradiol and methyl testosterone) were used at concentrations inducing low (<30 %) and medium (30-50 %) toxicity, based on ATP content. Human PCLS were incubated with the drugs in the presence of a non-toxic concentration (60 µM) of a bile acid mixture (portal vein concentration and composition) as model for bile acid-induced cholestasis. Regulated genes include bile acid transporters and cholesterol transporters. Pathway analysis revealed that hepatic cholestasis was among the top ten regulated pathways, and signaling pathways such as farnesoid X receptor- and liver X receptor-mediated responses, which are known to play a role in cholestasis, were significantly affected by all cholestatic compounds. Other significantly affected pathways include unfolded protein response and protein ubiquitination implicating the role of endoplasmic reticulum stress. This study shows that human PCLS incubated in the presence of a physiological bile acid mixture correctly reflect the pathways affected in drug-induced cholestasis in the human liver. In the future, this human PCLS model can be used to identify cholestatic adverse drug reactions of new chemical entities

Host microbiota dictates the proinflammatory impact of LPS in the murine liver

Gut microbiota can impact liver disease development via the gut-liver axis. Liver inflammation is a shared pathological event in various liver diseases and gut microbiota might influence this pathological process. In this study, we studied the influence of gut microbiota on the inflammatory response of the liver to lipopolysaccharide (LPS). The inflammatory response to LPS (1–10 μg/ml) of livers of specific-pathogen-free (SPF) or germ-free (GF) mice was evaluated ex vivo, using precision-cut liver slices (PCLS). LPS induced a more pronounced inflammatory response in GF PCLS than in SPF PCLS. Baseline TNF-α gene expression was significantly higher in GF slices as compared to SPF slices. LPS treatment induced TNF-α, IL-1β, IL-6 and iNOS expression in both SPF and GF PCLS, but the increase was more intense in GF slices. The anti-inflammatory markers SOCS3 and IRAK-M gene expression was significantly higher in GF PCLS than SPF PCLS at 24h with 1 µg/ml LPS treatment, and IL-10 was not differently expressed in GF PCLS than SPF PCLS. In addition, TLR-4 mRNA, but not protein, at basal level was higher in GF slices than in SPF slices. Taken together, this study shows that, in mice, the host microbiota attenuates the pro-inflammatory impact of LPS in the liver, indicating a positive role of the gut microbiota on the immune homeostasis of the liver

Empirical comparison of discrete choice experiment and best-worst scaling to estimate stakeholders' risk tolerance for hip replacement surgery

Objectives Empirical comparison of two preference elicitation methods, discrete choice experiment (DCE) and profile case best-worst scaling (BWS), regarding the estimation of the risk tolerance for hip replacement surgery (total hip arthroplasty and total hip resurfacing arthroplasty). Methods An online survey was constructed, following international guidelines, and consisted of socio-demographic questions and two randomised sections with 12 DCE and 8 BWS questions. The survey was sent to a general population who can be faced with choosing between THA and TRA (males between 45-65 years old) in the US. After an intensive literature search, the following attributes were selected: probability of a first and a second revision in seven years, pain relief, ability to perform moderate daily activities, and hospital stay. In addition, survey respondents rated the difficulty of each method and the time to complete each section was monitored. BWS and DCE data was analysed using conditional logit analysis. The maximum acceptable risk (MAR) for a revision was estimated for four different hypothetical hip replacement scenarios. Results The final data set consisted of 429 respondents. The MARs estimated for four hypothetical hip replacement scenarios differed between both methods, ranging from 0% to 19% difference for a first revision. BWS questions took significantly more time (401 s.) than DCE (228 s.) questions. And respondents found BWS more difficult to complete. Conclusions Both methods to elicit stakeholder preferences produce different results. Yet, both seem to be consistent in predicting risk tolerance if the benefits are changed. However, DCE seems to be more sensitive for a change in benefits and risks while the MAR estimates obtained through BWS have considerably lower uncertainty than DC