A preliminary investigation into the apparent abhesive effect of stearic acid on cured silicone elastomer

The effect of addition of small amounts of stearic acid on the adhesive properties of polydimethylsiloxane (PDMS) was investigated. Stearic acid reduced the peel strength of bonded aluminium samples with the joint weakening effect increasing with increased loadings. Surface analysis of the peeled surfaces was carried out using XPS, SSIMS and FTIR. This showed that stearic acid did not form a weak boundary layer at the metal-polymer interface as would traditionally be expected. Local Force Microscopy confirmed this, as the surface adhesion of the PDMS increased, rather than decreased, on addition of stearic acid

Pragmatic considerations for negative control outcome studies to guide non-randomized comparative analyses: A narrative review

Purpose: This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. Methods: We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. Results: Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. Conclusions: Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence

Global extent and drivers of mammal population declines in protected areas under illegal hunting pressure

Illegal hunting is a persistent problem in many protected areas, but an overview of the extent of this problem and its impact on wildlife is lacking. We reviewed 40 years (1980–2020) of global research to examine the spatial distribution of research and socio-ecological factors influencing population decline within protected areas under illegal hunting pressure. From 81 papers reporting 988 species/site combinations, 294 mammal species were reported to have been illegally hunted from 155 protected areas across 48 countries. Research in illegal hunting has increased substantially during the review period and showed biases towards strictly protected areas and the African continent. Population declines were most frequent in countries with a low human development index, particularly in strict protected areas and for species with a body mass over 100 kg. Our results provide evidence that illegal hunting is most likely to cause declines of large-bodied species in protected areas of resource-poor countries regardless of protected area conservation status. Given the growing pressures of illegal hunting, increased investments in people’s development and additional conservation efforts such as improving anti-poaching strategies and conservation resources in terms of improving funding and personnel directed at this problem are a growing priority

Prior distributions on symmetric groups

coset spaces, permutation group, ranked data, terminal sets,

Targeted Metabolic Profiling of the Tg197 Mouse Model Reveals Itaconic Acid as a Marker of Rheumatoid Arthritis

Rheumatoid arthritis is a progressive, highly debilitating disease where early diagnosis, enabling rapid clinical intervention, would provide obvious benefits to patients, healthcare systems, and society. Novel biomarkers that enable noninvasive early diagnosis of the onset and progression of the disease provide one route to achieving this goal. Here a metabolic profiling method has been applied to investigate disease development in the Tg197 arthritis mouse model. Hind limb extract profiling demonstrated clear differences in metabolic phenotypes between control (wild type) and Tg197 transgenic mice and highlighted raised concentrations of itaconic acid as a potential marker of the disease. These changes in itaconic acid concentrations were moderated or indeed reversed when the Tg197 mice were treated with the anti-hTNF biologic infliximab (10 mg/kg twice weekly for 6 weeks). Further in vitro studies on synovial fibroblasts obtained from healthy wild-type, arthritic Tg197, and infliximab-treated Tg197 transgenic mice confirmed the association of itaconic acid with rheumatoid arthritis and disease-moderating drug effects. Preliminary indications of the potential value of itaconic acid as a translational biomarker were obtained when studies on K4IM human fibroblasts treated with hTNF showed an increase in the concentrations of this metabolite. © 2016 American Chemical Society