John Tayu Lee

BRAF(V600E) is the most frequent oncogenic protein kinase mutation known. Furthermore, inhibitors targeting "active" protein kinases have demonstrated significant utility in the therapeutic repertoire against cancer. Therefore, we pursued the development of specific kinase inhibitors targeting B-Raf, and the V600E allele in particular. By using a structure-guided discovery approach, a potent and selective inhibitor of active B-Raf has been discovered. PLX4720, a 7-azaindole derivative that inhibits B-Raf(V600E) with an IC(50) of 13 nM, defines a class of kinase inhibitor with marked selectivity in both biochemical and cellular assays. PLX4720 preferentially inhibits the active B-Raf(V600E) kinase compared with a broad spectrum of other kinases, and potent cytotoxic effects are also exclusive to cells bearing the V600E allele. Consistent with the high degree of selectivity, ERK phosphorylation is potently inhibited by PLX4720 in B-Raf(V600E)-bearing tumor cell lines but not in cells lacking oncogenic B-Raf. In melanoma models, PLX4720 induces cell cycle arrest and apoptosis exclusively in B-Raf(V600E)-positive cells. In B-Raf(V600E)-dependent tumor xenograft models, orally dosed PLX4720 causes significant tumor growth delays, including tumor regressions, without evidence of toxicity. The work described here represents the entire discovery process, from initial identification through structural and biological studies in animal models to a promising therapeutic for testing in cancer patients bearing B-Raf(V600E)-driven tumors.

Abstract Shifts in the timing of spring phenology are a central feature of global change research. Long‐term observations of plant phenology have been used to track vegetation responses to climate variability but are often limited to particular species and locations and may not represent synoptic patterns. Satellite remote sensing is instead used for continental to global monitoring. Although numerous methods exist to extract phenological timing, in particular start‐of‐spring (SOS), from time series of reflectance data, a comprehensive intercomparison and interpretation of SOS methods has not been conducted. Here, we assess 10 SOS methods for North America between 1982 and 2006. The techniques include consistent inputs from the 8 km Global Inventory Modeling and Mapping Studies Advanced Very High Resolution Radiometer NDVIg dataset, independent data for snow cover, soil thaw, lake ice dynamics, spring streamflow timing, over 16 000 individual measurements of ground‐based phenology, and two temperature‐driven models of spring phenology. Compared with an ensemble of the 10 SOS methods, we found that individual methods differed in average day‐of‐year estimates by ±60 days and in standard deviation by ±20 days. The ability of the satellite methods to retrieve SOS estimates was highest in northern latitudes and lowest in arid, tropical, and Mediterranean ecoregions. The ordinal rank of SOS methods varied geographically, as did the relationships between SOS estimates and the cryospheric/hydrologic metrics. Compared with ground observations, SOS estimates were more related to the first leaf and first flowers expanding phenological stages. We found no evidence for time trends in spring arrival from ground‐ or model‐based data; using an ensemble estimate from two methods that were more closely related to ground observations than other methods, SOS trends could be detected for only 12% of North America and were divided between trends towards both earlier and later spring.

BACKGROUND: with ageing populations and increasing exposure to risk factors for chronic diseases, the prevalence of chronic disease multimorbidity is rising globally. There is little evidence on the determinants of multimorbidity and its impact on healthcare utilisation and health status in Europe. METHODS: we used cross-sectional data from the Survey of Health, Ageing and Retirement in Europe (SHARE) in 2011-12, which included nationally representative samples of persons aged 50 and older from 16 European nations. Negative binomial and logistic regression models were used to assess the association between number of chronic diseases and healthcare utilisation, self-perceived health, depression and reduction of functional capacity. RESULTS: overall, 37.3% of participants reported multimorbidity; the lowest prevalence was in Switzerland (24.7%), the highest in Hungary (51.0%). The likelihood of having multimorbidity increased substantially with age. Number of chronic conditions was associated with greater healthcare utilisation in both primary (regression coefficient for medical doctor visits = 0.29, 95% CI = 0.27-0.30) and secondary setting (adjusted odds ratio (AOR) for having any hospitalisation in the last year = 1.49, 95% CI = 1.42-1.55) in all countries analysed. Number of chronic diseases was associated with fair/poor health status (AOR 2.13, 95% CI = 2.03-2.24), being depressed (AOR 1.48, 95% CI = 1.42-1.54) and reduced functional capacity (AOR 2.12, 95% CI = 2.02-2.22). CONCLUSION: multimorbidity is associated with greater healthcare utilisation, worse self-reported health status, depression and reduced functional capacity in European countries. European health systems should prioritise improving the management of patients with multimorbidity to improve their health status and increase healthcare efficiency.