A primary aim of microbial ecology is to determine patterns and drivers of community distribution, interaction, and assembly amidst complexity and uncertainty. Microbial community composition has been shown to change across gradients of environment, geographic distance, salinity, temperature, oxygen, nutrients, pH, day length, and biotic factors 1-6 . These patterns have been identified mostly by focusing on one sample type and region at a time, with insights extra polated across environments and geography to produce generalized principles. To assess how microbes are distributed across environments globally-or whether microbial community dynamics follow funda mental ecological 'laws' at a planetary scale-requires either a massive monolithic cross environment survey or a practical methodology for coordinating many independent surveys. New studies of microbial environments are rapidly accumulating; however, our ability to extract meaningful information from across datasets is outstripped by the rate of data generation. Previous meta analyses have suggested robust gen eral trends in community composition, including the importance of salinity 1 and animal association 2 . These findings, although derived from relatively small and uncontrolled sample sets, support the util ity of meta analysis to reveal basic patterns of microbial diversity and suggest that a scalable and accessible analytical framework is needed.The Earth Microbiome Project (EMP, http://www.earthmicrobiome. org) was founded in 2010 to sample the Earth's microbial communities at an unprecedented scale in order to advance our understanding of the organizing biogeographic principles that govern microbial commu nity structure 7,8 . We recognized that open and collaborative science, including scientific crowdsourcing and standardized methods 8 , would help to reduce technical variation among individual studies, which can overwhelm biological variation and make general trends difficult to detect 9 . Comprising around 100 studies, over half of which have yielded peer reviewed publications (Supplementary Table 1), the EMP has now dwarfed by 100 fold the sampling and sequencing depth of earlier meta analysis efforts 1,2 ; concurrently, powerful analysis tools have been developed, opening a new and larger window into the distri bution of microbial diversity on Earth. In establishing a scalable frame work to catalogue microbiota globally, we provide both a resource for the exploration of myriad questions and a starting point for the guided acquisition of new data to answer them. As an example of using this Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of r...

An activation-verification model for letter and word recognition yielded predictions of two-alternative forced-choice performance for 864 individual stimuli that were either words, orthographically regular nonwords, or orthographically irregular nonwords. The encoding algorithm (programmed in APL) uses empirically determined confusion matrices to activate units in both an alphabetum and a lexicon. In general, predicted performance is enhanced when decisions are based on lexical information, because activity in the lexicon tends to constrain the identity of test letters more than the activity in the alphabetum. Thus, the model predicts large advantages of words over irregular nonwords, and smaller advantages of words over regular nonwords. The predicted differences are close to those obtained in a number of experiments and clearly demonstrate that the effects of manipulating lexicality and orthography can be predicted on the basis of lexical constraint alone. Furthermore, within each class (word, regular nonword, irregular nonword) there are significant correlations between the simulated and obtained performance on individual items. Our activation-verification model is contrasted with McClelland and Rumelhart's (1981) interactive activation model.

Key Points PET false-negativity was seen in 11% of MM patients. PET false-negativity was associated with low hexokinase-2 expression.

The iliac crest is the sampling site for minimal residual disease (MRD) monitoring in Multiple Myeloma (MM). However, the disease distribution is often heterogeneous, and imaging can be used to complement MRD detection at a single site. We have investigated patients in complete remission (CR) during first-line or salvage therapy, for whom MRD flow-cytometry and the two imaging modalities positron-emission-tomography (PET) and diffusion-weighted magnetic resonance imaging (DW-MRI) were performed at the onset of CR. Residual focal lesions (FLs), detectable in 24% of first-line patients, were associated with short progression-free survival (PFS), with DW-MRI detecting disease in more patients. In some patients, FLs were only PET-positive, indicating that the two approaches are complementary. Combining MRD and imaging improved prediction of outcome, with double-negative and double-positive features defining groups with excellent and dismal PFS, respectively. FLs were a rare event (12%) in first-line MRD-negative CR patients. In contrast, patients achieving an MRD-negative CR during salvage therapy frequently had FLs (50%). Multi-region sequencing and imaging in an MRD-negative patient showed persistence of spatially separated clones. In conclusion, we show that DW-MRI is a promising tool for monitoring residual disease that complements PET and should be combined with MRD.

criteria associated with semantically related words in the observer's lexicon. The second issue concerns the level or levels of encoding affected by semantic context. For example, context could affect featural analysis, the analysis of letters, or the activation of word units. We begin by describing the general theoretical orientation that provides the framework for the investigation.