On meta-analytic assessment of surrogate outcomes

We discuss the strengths and weaknesses of the meta-analytic approach to estimating the effect of a new treatment on a true clinical outcome measure, T, from the effect of treatment on a surrogate response, S. The meta-analytic approach (see Daniels and Hughes (1997) 16, 1965-1982) uses data from a series of previous studies of interventions similar to the new treatment. The data are used to estimate relationships between summary measures of treatment effects on T and S that can be used to infer the magnitude of the effect of the new treatment on T from its effects on S. We extend the class of models to cover a broad range of applications in which the parameters define features of the marginal distribution of (T, S). We present a new bootstrap procedure to allow for the variability in estimating the distribution that governs the between-study variation. Ignoring this variability can lead to confidence intervals that are much too narrow. The meta-analytic approach relies on quite different data and assumptions than procedures that depend, for example, on the conditional independence, at the individual level, of treatment and T, given S (see Prentice (1989) 8, 431-440). Meta-analytic calculations in this paper can be used to determine whether a new study, based only on S, will yield estimates of the treatment effect on T that are precise enough to be useful. Compared to direct measurement on T, the meta-analytic approach has a number of limitations, including likely serious loss of precision and difficulties in defining the class of previous studies to be used to predict the effects on T for a new intervention.     

Gravity independence of seed-to-seed cycling in Brassica rapa

 Growth of higher plants in the microgravity environment of orbital platforms has been problematic. Plants typically developed more slowly in space and often failed at the reproductive phase. Short-duration experiments on the Space Shuttle showed that early stages in the reproductive process could occur normally in microgravity, so we sought a long-duration opportunity to test gravity's role throughout the complete life cycle. During a 122-d opportunity on the Mir space station, full life cycles were completed in microgravity with Brassica rapa L. in a series of three experiments in the Svet greenhouse. Plant material was preserved in space by chemical fixation, freezing, and drying, and then compared to material preserved in the same way during a high-fidelity ground control. At sampling times 13 d after planting, plants on Mir were the same size and had the same number of flower buds as ground control plants. Following hand-pollination of the flowers by the astronaut, siliques formed. In microgravity, siliques ripened basipetally and contained smaller seeds with less than 20% of the cotyledon cells found in the seeds harvested from the ground control. Cytochemical localization of storage reserves in the mature embryos showed that starch was retained in the spaceflight material, whereas protein and lipid were the primary storage reserves in the ground control seeds. While these successful seed-to-seed cycles show that gravity is not absolutely required for any step in the plant life cycle, seed quality in Brassica is compromised by development in microgravity. Received: 3 August 1999 / Accepted: 27 August 1999     

Systems‐wide analysis of BCR signalosomes and downstream phosphorylation and ubiquitylation

B‐cell receptor (BCR) signaling is essential for the development and function of B cells; however, the spectrum of proteins involved in BCR signaling is not fully known. Here we used quantitative mass spectrometry‐based proteomics to monitor the dynamics of BCR signaling complexes (signalosomes) and to investigate the dynamics of downstream phosphorylation and ubiquitylation signaling. We identify most of the previously known components of BCR signaling, as well as many proteins that have not yet been implicated in this system. BCR activation leads to rapid tyrosine phosphorylation and ubiquitylation of the receptor‐proximal signaling components, many of which are co‐regulated by both the modifications. We illustrate the power of multilayered proteomic analyses for discovering novel BCR signaling components by demonstrating that BCR‐induced phosphorylation of RAB7A at S72 prevents its association with effector proteins and with endo‐lysosomal compartments. In addition, we show that BCL10 is modified by LUBAC‐mediated linear ubiquitylation, and demonstrate an important function of LUBAC in BCR‐induced NF‐κB signaling. Our results offer a global and integrated view of BCR signaling, and the provided datasets can serve as a valuable resource for further understanding BCR signaling networks.     

Water use and yield of bioenergy poplar in future climates: modelling the interactive effects of elevated atmospheric CO2 and climate on productivity and water use

Vegetation exerts large control on global biogeochemical cycles through the processes of photosynthesis and transpiration that exchange CO₂ and water between the land and the atmosphere. Increasing atmospheric CO₂ concentrations exert direct effects on vegetation through enhanced photosynthesis and reduced stomatal conductance, and indirect effects through changes in climatic variables that drive these processes. How these direct and indirect CO₂ impacts interact with each other to affect plant productivity and water use has not been explicitly analysed and remains unclear, yet is important to fully understand the response of the global carbon cycle to future climate change. Here, we use a set of factorial modelling experiments to quantify the direct and indirect impacts of atmospheric CO₂ and their interaction on yield and water use in bioenergy short rotation coppice poplar, in addition to quantifying the impact of other environmental drivers such as soil type. We use the JULES land‐surface model forced with a ten‐member ensemble of projected climate change for 2100 with atmospheric CO₂ concentrations representative of the A1B emissions scenario. We show that the simulated response of plant productivity to future climate change was nonadditive in JULES, however this nonadditivity was not apparent for plant transpiration. The responses of both growth and transpiration under all experimental scenarios were highly variable between sites, highlighting the complexity of interactions between direct physiological CO₂ effects and indirect climate effects. As a result, no general pattern explaining the response of bioenergy poplar water use and yield to future climate change could be discerned across sites. This study suggests attempts to infer future climate change impacts on the land biosphere from studies that force with either the direct or indirect CO₂ effects in isolation from each other may lead to incorrect conclusions in terms of both the direction and magnitude of plant response to future climate change.