Freedom of choice to migrate: adaptation to climate change in Bangladesh

Adaptation is an essential part of climate change policy. In areas where impacts are likely to be severe, migration is considered to be an adaptation option. In Bangladesh coastal areas migration due to climate change is contingent on people’s freedom of choice at individual and household level. Following Amartya Sen’s capability approach, we argue that there should be a line drawn between migrations by free choice versus forced migration. Sen’s capability approach focuses on the importance of people’s freedom of choice to act, and the ability to achieve what they consider valuable in their life. In this paper, we use an extensive empirical work engaging 22 focus groups discussions (8–12 individuals in each group) and 14 Key Informants Interviews in South-West Bangladesh to elicit how freedom of choice changes with the economic class and social status of an individual. Using these data we apply Sen’s capability approach to understand the role of the freedom of choice when considering migration as an adaptation option. We argue that the capability approach is essential in revealing a thin border between migration as a (planned) adaptation option and forced migration

The timing of elective caesarean delivery between 2000 and 2009 in England

BACKGROUND: In 2004, the National Institute for Clinical Excellence (NICE) recommended that an elective caesarean section for an uncomplicated pregnancy should not be carried out before 39 completed weeks due to increased risk of respiratory morbidity in newborns. We describe the trends and variation across 63 English NHS trusts in the timing of elective caesarean section (CS) for low-risk singleton deliveries. METHODS: We identified elective CS deliveries between 1st April 2000 and 28th February 2009 in English NHS trusts using the Hospital Episode Statistics. We selected women with uncomplicated pregnancies who had an elective CS delivery after 34 completed weeks of gestation, and analysed the trends and the trust-level variation in the timing of elective CS. The impact of the NICE guidance on the monthly rate of elective CS deliveries performed after 39 weeks was estimated using an interrupted time-series design with autoregressive integrated moving average (ARIMA). RESULTS: There were 118,456 elective CS deliveries at the 63 NHS trusts. The overall proportion of elective CS deliveries done after 39 completed weeks steadily increased from 39% in 2000/01 to 63% in 2008/09. The proportions rose from 43% to 67% for women with breech presentation and from 35% to 62% for women with a previous CS. There was significant variation across NHS trusts in each year; in 2008/09, with the proportions of elective CS done after 39 weeks ranging from 28% to 89% (Inter-quartile range limits: 54% to 72%). We found a small but statistically significant increase in the proportion immediately after the publication of the NICE guidance, but its rate of growth rate declined slightly thereafter. CONCLUSIONS: NHS trusts in our study have responded to the new evidence on the benefits of delaying elective CS to after 39 weeks gestation. However, substantial differences between NHS trusts remain, which indicates there is room for further improvement. We suggest that maternity services and commissioners adopt the "timing of elective caesarean" as a quality indicator to support clinical practice

Systems-Level Modeling of Cancer-Fibroblast Interaction

Cancer cells interact with surrounding stromal fibroblasts during tumorigenesis, but the complex molecular rules that govern these interactions remain poorly understood thus hindering the development of therapeutic strategies to target cancer stroma. We have taken a mathematical approach to begin defining these rules by performing the first large-scale quantitative analysis of fibroblast effects on cancer cell proliferation across more than four hundred heterotypic cell line pairings. Systems-level modeling of this complex dataset using singular value decomposition revealed that normal tissue fibroblasts variably express at least two functionally distinct activities, one which reflects transcriptional programs associated with activated mesenchymal cells, that act either coordinately or at cross-purposes to modulate cancer cell proliferation. These findings suggest that quantitative approaches may prove useful for identifying organizational principles that govern complex heterotypic cell-cell interactions in cancer and other contexts

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer

An examination of the long-term business value of investments in information technology

In this paper, we examine the effects of investments in Information Technology (IT) on the long term business values of organizations. The regression discontinuity design is used in this research to examine eight hundred and ten IT investment announcements collected from the period 1982–2007. Our results found that press releases can affect the market value of a firm by possibly providing investors with a better idea of a firm’s current and future operations and strategy. On the other hand, these press releases also appear to attract more transient investors. The attraction of transient investors likely suggests the market believes the IT investing firm is serious about its potential for growth and expansion

Pharmacokinetic-Pharmacodynamic Modeling in Pediatric Drug Development, and the Importance of Standardized Scaling of Clearance.

Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies