A simulation approach for power calculation in large cohort studies based on multistate models

Realistic power calculations for large cohort studies and nested case control studies are essential for successfully answering important and complex research questions in epidemiology and clinical medicine. For this, we provide a methodical framework for general realistic power calculations via simulations that we put into practice by means of an R‐based template. We consider staggered recruitment and individual hazard rates, competing risks, interaction effects, and the misclassification of covariates. The study cohort is assembled with respect to given age‐, gender‐, and community distributions. Nested case‐control analyses with a varying number of controls enable comparisons of power with a full cohort analysis. Time‐to‐event generation under competing risks, including delayed study‐entry times, is realized on the basis of a six‐state Markov model. Incidence rates, prevalence of risk factors and prefixed hazard ratios allow for the assignment of age‐dependent transition rates given in the form of Cox models. These provide the basis for a central simulation‐algorithm, which is used for the generation of sample paths of the underlying time‐inhomogeneous Markov processes. With the inclusion of frailty terms into the Cox models the Markov property is specifically biased. An “individual Markov process given frailty” creates some unobserved heterogeneity between individuals. Different left‐truncation‐ and right‐censoring patterns call for the use of Cox models for data analysis. p‐values are recorded over repeated simulation runs to allow for the desired power calculations. For illustration, we consider scenarios with a “testing” character as well as realistic scenarios. This enables the validation of a correct implementation of theoretical concepts and concrete sample size recommendations against an actual epidemiological background, here given with possible substudy designs within the German National Cohort.     

A review of malaria vaccine clinical projects based on the WHO rainbow table

Development and Phase 3 testing of the most advanced malaria vaccine, RTS,S/AS01, indicates that malaria vaccine R&D is moving into a new phase. Field trials of several research malaria vaccines have also confirmed that it is possible to impact the host-parasite relationship through vaccine-induced immune responses to multiple antigenic targets using different platforms. Other approaches have been appropriately tested but turned out to be disappointing after clinical evaluation. As the malaria community considers the potential role of a first-generation malaria vaccine in malaria control efforts, it is an apposite time to carefully document terminated and ongoing malaria vaccine research projects so that lessons learned can be applied to increase the chances of success for second-generation malaria vaccines over the next 10 years. The most comprehensive resource of malaria vaccine projects is a spreadsheet compiled by WHO thanks to the input from funding agencies, sponsors and investigators worldwide. This spreadsheet, available from WHO's website, is known as "the rainbow table". By summarizing the published and some unpublished information available for each project on the rainbow table, the most comprehensive review of malaria vaccine projects to be published in the last several years is provided below.     

Composition and stability of the vervet monkey milk microbiome

The human milk microbiome is vertically transmitted to offspring during the postnatal period and has emerged as a critical driver of infant immune and metabolic development. Despite this importance in humans, the milk microbiome of nonhuman primates remains largely unexplored. This dearth of comparative work precludes our ability to understand how species‐specific differences in the milk microbiome may differentially drive maternal effects and limits how translational models can be used to understand the role of vertically transmitted milk microbes in human development. Here, we present the first culture‐independent data on the milk microbiome of a nonhuman primate. We collected milk and matched fecal microbiome samples at early and late lactation from a cohort of captive lactating vervet monkeys (N = 15). We found that, similar to humans, the vervet monkey milk microbiome comprises a shared community of taxa that are universally present across individuals. However, unlike in humans, this shared community is dominated by the genera Lactobacillus, Bacteroides, and Prevotella. We also found that, in contrast to previous culture‐dependent studies in humans, the vervet milk microbiome exhibits greater alpha‐diversity than the gut microbiome across lactation. Finally, we did not find support for the translocation of microbes from the gut to the mammary gland within females (i.e., “entero‐mammary pathway”). Taken together, our results show that the vervet monkey milk microbiome is taxonomically diverse, distinct from the gut microbiome, and largely stable. These findings demonstrate that the milk microbiome is a unique substrate that may selectively favor the establishment and persistence of particular microbes across lactation and highlights the need for future experimental studies on the origin of microbes in milk.     

Chemo-enzymatic synthesis of the Galili epitope Gal(alpha)(1-->3)Galbeta(1-->4)GlcNAc on a homogeneously soluble PEG polymer by a multi-enzyme system.

The alpha-Gal trisaccharide Gal(alpha)(1-->3)Galbeta(1-->4)GlcNAc 11 was synthesized on a homogeneously soluble polymeric support (polyethylene glycol, PEG) by use of a multi-enzyme system consisting of beta-1,4-galactosyltransferase (EC 2.4.1.38), alpha-1,3-galactosyltransferase (EC 2.4.1.151), sucrose synthase (EC 2.4.1.13) and UDP-glucose-4-epimerase (EC 5.1.3.2). In addition workup was simplified by use of dia-ultrafiltration. Thus the advantages of classic chemistry/enzymology and solid-phase synthesis could be united in one. Subsequent hydrogenolytic cleavage afforded the free alpha-Gal trisaccharide.     

Trait plasticity alters the range of possible coexistence conditions in a competition–colonisation trade‐off

Most of the classical theory on species coexistence has been based on species‐level competitive trade‐offs. However, it is becoming apparent that plant species display high levels of trait plasticity. The implications of this plasticity are almost completely unknown for most coexistence theory. Here, we model a competition–colonisation trade‐off and incorporate trait plasticity to evaluate its effects on coexistence. Our simulations show that the classic competition–colonisation trade‐off is highly sensitive to environmental circumstances, and coexistence only occurs in narrow ranges of conditions. The inclusion of plasticity, which allows shifts in competitive hierarchies across the landscape, leads to coexistence across a much broader range of competitive and environmental conditions including disturbance levels, the magnitude of competitive differences between species, and landscape spatial patterning. Plasticity also increases the number of species that persist in simulations of multispecies assemblages. Plasticity may generally increase the robustness of coexistence mechanisms and be an important component of scaling coexistence theory to higher diversity communities.