The Competitive Effects of Drug Withdrawals

In September 1997, the anti-obesity drugs Pondimin and Redux, ingredients in the popular drug combination fen-phen, were withdrawn from the market for causing potentially fatal side effects. That event provides an opportunity for studying how consumers respond to drug withdrawals. In theory, remaining drugs in the therapeutic class could enjoy competitive benefits, or suffer negative spillovers, from the withdrawal of a competing drug. Our findings suggest that, while the withdrawal of a rival drug may impose negative spillovers in the form of higher patient quit rates, on the whole non-withdrawn drugs in the same therapeutic class enjoy competitive benefits in the form of higher utilization.

Factor Substitution and Unobserved Factor Quality in Nursing Homes

This paper studies factor substitution in one important sector: the nursing home industry. Specifically, we measure the extent to which nursing homes substitute materials for labor when labor becomes relatively more expensive. From a policy perspective, factor substitution in this market is important because materials-intensive methods of care are associated with greater risks of morbidity and mortality among nursing home residents. Studying longitudinal data from 1991-1998 on nearly every nursing home in the United States, we use the method of instrumental variables (IV) to address the potential endogeneity of nursing home wages. The results from the IV models are consistent with the theory of factor substitution: higher nursing home wages are associated with lower staffing, greater use of materials (specifically, physical restraints), and a higher proportion of residents with pressure ulcers. A comparison of OLS and IV results suggests that empirical studies of factor substitution should take into account unobserved heterogeneity in factor quality.

Outcomes in a Program that Offers Financial Rewards for Weight Loss

Obesity rates in the U.S. have doubled since 1980. Given the medical, social, and financial costs of obesity, a large percentage of Americans are attempting to lose weight at any given time but the vast majority of weight loss attempts fail. Researchers continue to search for safe and effective methods of weight loss, and this paper examines one promising method - offering financial rewards for weight loss. This paper studies data on 2,407 employees in 17 worksites who participated in a year-long worksite health promotion program that offered financial rewards for weight loss. The intervention varied by employer, in some cases offering steady quarterly rewards for weight loss and in other cases requiring participants to post a bond that would be refunded at year's end conditional on achieving certain weight loss goals. Still others received no financial incentives at all and serve as a control group. We examine the basic patterns of enrollment, attrition, and weight loss in these three groups. Weight loss is modest. After one year, it averages 1.4 pounds for those paid steady quarterly rewards and 3.6 pounds for those who posted a refundable bond, under the assumption that dropouts experienced no weight loss. Year-end attrition is as high as 76.4%, far higher than that for interventions designed and implemented by researchers.

The Correlation of Ultrasonic Measurements with Toughness Changes During the Environmental Degradation of Adhesive Joints

Several factors have held back the more widespread use of adhesives. These principally are the detrimental effect of moisture on bond strength and also the lack of a suitable non-destructive testing technique for detecting strength loss due to environmental attack. It is the latter problem that this work attempts to answer. The focus of this work has been to look at the bonding of aluminium to aluminium using epoxy based adhesives, as would be used in the aerospace industry. Bonding of aluminium has been performed in the aerospace industry for many years, and there has been much work done to improve the durability of this type of joint. It has been seen that the improvement in corrosion resistance that can be achieved by treating aluminium prior to bonding has a significant effect on the durability of the bond produced. This is not surprising when it is often seen that a joint which has been exposed to a hot-wet environment will fail along the interface between the aluminium and epoxy, as opposed to through the adhesive when the joint has remained dry [1]. Therefore it is this interface region that is to be examined when searching for environmental attack. The most common form of pretreatment that is used when environmental attack is a concern is anodisation of the surface to be bonded. Anodising produces a thin oxide layer on the aluminium surface, typically 1 –3 μm thick. Joints that have been anodised are considerably more durable than joints that are not anodised, but they will still exhibit interfacial failure after exposure to hot-wet environments [1]. The problem for NDT techniques is that the oxide layer which we need to inspect is orders of magnitude smaller than the bounding layers; the aluminium being 1–5mm, and the adhesive being 0.1–0.5mm thick, as shown in Figure 1. Ultrasonics has appeared to be the most promising technique for inspecting for degradation of adhesive joints, and it is this technique on which we have concentrated our efforts [2–4]

The Ultrasonic Detection of Environmental Degradation in Adhesive Joints

There are many benefits to be gained when using adhesives compared with the use of more traditional joining techniques. Amongst these advantages can be listed the ability to join dissimilar materials, the uniform distribution of load over the area of the joint avoiding stress concentrations, the improvement in aesthetics and, potentially, a lower-weight for the component or structure. However several factors have retarded the more widespread use of adhesives. These principally are (i) the detrimental effect of moisture on the joint strength and (ii) the lack of a suitable non-destructive testing technique for detecting strength loss due to environmental attack. It is the latter problem that the present work addresses. The focus of this work has been to examine the bonding of aluminium alloy to aluminium alloy, using an epoxy-based adhesive

Towards Compound Identification of Synthetic Opioids in Non-targeted Screening Using Machine Learning Techniques.

The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a promising avenue to putatively identify a compound before confirmation against a standard. In this study, machine learning approaches were used to develop class prediction and retention time prediction models. The developed class prediction model used a Naïve Bayes architecture to classify opioids as belonging to either the fentanyl analogues, AH series or U series, with an accuracy of 89.5%. The model was most accurate for the fentanyl analogues, most likely due to their greater number in the training data. This classification model can provide guidance to an analyst when determining a suspected structure. A retention time prediction model was also trained for a wide array of synthetic opioids. This model utilised Gaussian Process Regression to predict the retention time of analytes based on multiple generated molecular features with 79.7% of the samples predicted within ± 0.1 min of their experimental retention time. Once the suspected structure of an unknown compound is determined, molecular features can be generated and input for the prediction model to compare with experimental retention time. The incorporation of machine learning prediction models into a compound identification workflow can assist putative identifications with greater confidence and ultimately save time and money in the purchase and/or production of superfluous certified reference materials

Collision-induced dissociation studies of synthetic opioids for non-targeted analysis

© 2019 Klingberg, Cawley, Shimmon and Fu. The continual introduction of a large number of new psychoactive substances, along with the large turnover of these substances, necessitates the development of non-targeted detection strategies to keep pace with the ever-changing drug market. The production of certified reference materials often lags behind the introduction of new substances to the market, therefore these detection strategies need to be able to function without relying on reference materials or library spectra. Synthetic opioids have recently emerged as a drug class of particular concern due to the health issues caused by their incredibly high potency. A common method which has been used for non-targeted analysis in the past involves the identification of common product ions formed as a result of the fragmentation of the parent molecule. These common fragments can then potentially be used as markers to indicate the presence of a particular class of compounds within a sample. In this study, standards of a number of different synthetic opioids, including 14 fentanyl derivatives, 7 AH series opioids, 4U series opioids, 4W series opioids and MT-45, were subjected to collision-induced dissociation studies to determine how the compounds fragment. The spectra obtained from these studies included a number of diagnostic fragments common to the different opioid classes that, when used in combination, show potential for use as class predictors. By using simple data processing techniques, such as extracted ion chromatograms, these diagnostic product ions identified can be applied to a non-targeted screening workflow