Adaptive seamless clinical trials using early outcomes for treatment or subgroup selection: Methods,simulation model and their implementation in R

Adaptive seamless designs combine confirmatory testing, a domain of phase III trials, with features such as treatment or subgroup selection, typically associated with phase II trials. They promise to increase the efficiency of development programmes of new drugs, for example, in terms of sample size and/or development time. It is well acknowledged that adaptive designs are more involved from a logistical perspective and require more upfront planning, often in the form of extensive simulation studies, than conventional approaches. Here, we present a framework for adaptive treatment and subgroup selection using the same notation, which links the somewhat disparate literature on treatment selection on one side and on subgroup selection on the other. Furthermore, we introduce a flexible and efficient simulation model that serves both designs. As primary endpoints often take a long time to observe, interim analyses are frequently informed by early outcomes. Therefore, all methods presented accommodate interim analyses informed by either the primary outcome or an early outcome. The R package asd , previously developed to simulate designs with treatment selection, was extended to include subgroup selection (so-called adaptive enrichment designs). Here, we describe the functionality of the R package asd and use it to present some worked-up examples motivated by clinical trials in chronic obstructive pulmonary disease and oncology. The examples both illustrate various features of the R package and provide insights into the operating characteristics of adaptive seamless studies.     

Can soil seed banks contribute to the restoration of dune slacks under conservation management?

Questions: Does the soil seed bank resemble the former early successional stages of a dune slack system more than the established later successional vegetation? Does it have the potential to contribute to the conservation of a highly endangered habitat? Location: Dune slacks at Newborough Warren, UK. Methods: The composition of the soil seed bank in two depth layers was determined using the seedling emergence method between March 2004 and April 2005. Long-term monitoring data on the floristic composition of the established vegetation were obtained from the national conservation agency, and additional monitoring was undertaken in 2003. Floristic composition, seed weights, seed longevity of component species and Ellenberg indicator values were used to compare the seed bank and established vegetation. Results: The soil seed bank was diverse and contained typical dune slack species, species of early successional stages and species of conservation interest. A comparison between the composition of the seed bank and historical data on the composition of the established vegetation showed that the seed bank reflects earlier successional stages more closely than the current aboveground vegetation. This study increases the scarce information currently available on the seed bank ecology of several species, including two orchid species. Conclusions: The soil seed bank can be expected to contribute to vegetation change after disturbance. Stimulation of germination from the seed bank through management may contribute to the conservation of both characteristic and threatened species typical of dune slacks.     

Tri-locus sequence data reject a “Gondwanan origin hypothesis” for the African/South Pacific crab genus Hymenosoma

Crabs of the family Hymenosomatidae are common in coastal and shelf regions throughout much of the southern hemisphere. One of the genera in the family, Hymenosoma, is represented in Africa and the South Pacific (Australia and New Zealand). This distribution can be explained either by vicariance (presence of the genus on the Gondwanan supercontinent and divergence following its break-up) or more recent transoceanic dispersal from one region to the other. We tested these hypotheses by reconstructing phylogenetic relationships among the seven presently-accepted species in the genus, as well as examining their placement among other hymenosomatid crabs, using sequence data from two nuclear markers (Adenine Nucleotide Transporter [ANT] exon 2 and 18S rDNA) and three mitochondrial markers (COI, 12S and 16S rDNA). The five southern African representatives of the genus were recovered as a monophyletic lineage, and another southern African species, Neorhynchoplax bovis, was identified as their sister taxon. The two species of Hymenosoma from the South Pacific neither clustered with their African congeners, nor with each other, and should therefore both be placed into different genera. Molecular dating supports a post-Gondwanan origin of the Hymenosomatidae. While long-distance dispersal cannot be ruled out to explain the presence of the family Hymenosomatidae on the former Gondwanan land-masses and beyond, the evolutionary history of the African species of Hymenosoma indicates that a third means of speciation may be important in this group: gradual along-coast dispersal from tropical towards temperate regions, with range expansions into formerly inhospitable habitat during warm climatic phases, followed by adaptation and speciation during subsequent cooler phases.     

Predictors of plant phenology in a diverse high‐latitude alpine landscape: growth forms and topography

Question: Different plant growth forms may have distinctly different functioning in ecosystems. Association of phenological patterns with growth form will therefore help elucidate the role of phenology in an ecosystem. We ask whether growth forms of common vascular plants differ in terms of vegetative and flowering phenology, and if such phenological differences are consistent across environmental gradients caused by landscape‐scale topography. Location: A high‐latitude alpine landscape in Finnmark County, Norway (70°N). Methods: We assessed vegetative and flowering phenology repeatedly in five growth forms represented by 11 common vascular plant species across an altitudinal gradient and among differing slope aspects. Results: Species phenology clustered well according to growth form, and growth form strongly explained variation in both flowering and vegetative phenology. Altitude and aspect were poor predictors of phenological variation. Vegetative phenology of the growth forms, ranked from slowest to fastest, was in the order evergreen shrubs <sedges‐deciduous shrubs <grasses <forbs, while a reverse ranking was found for flowering phenology. Conclusion: Growth form‐specific phenological patterns are associated with fundamentally different abilities for resource acquisition and resource conservation. The weak effect of landscape‐scale topographic factors indicates that variation within growth forms is mainly influenced by local environmental factors not accounted for in this study. On the basis of these results, we argue that growth forms should be considered as predictors of phenology together with the customary use of topography and normalized difference vegetation index, especially when assessing the role of phenology in an ecosystem.     

Land use improves spatial predictions of mountain plant abundance but not presence‐absence

Question: Does a land‐use variable improve spatial predictions of plant species presence‐absence and abundance models at the regional scale in a mountain landscape? Location: Western Swiss Alps. Methods: Presence‐absence generalized linear models (GLM) and abundance ordinal logistic regression models (LRM) were fitted to data on 78 mountain plant species, with topo‐climatic and/or land‐use variables available at a 25‐m resolution. The additional contribution of land use when added to topo‐climatic models was evaluated by: (1) assessing the changes in model fit and (2) predictive power, (3) partitioning the deviance respectively explained by the topo‐climatic variables and the land‐use variable through variation partitioning, and (5) comparing spatial projections. Results: Land use significantly improved the fit of presence‐absence models but not their predictive power. In contrast, land use significantly improved both the fit and predictive power of abundance models. Variation partitioning also showed that the individual contribution of land use to the deviance explained by presence‐absence models was, on average, weak for both GLM and LRM (3.7% and 4.5%, respectively), but changes in spatial projections could nevertheless be important for some species. Conclusions: In this mountain area and at our regional scale, land use is important for predicting abundance, but not presence‐absence. The importance of adding land‐use information depends on the species considered. Even without a marked effect on model fit and predictive performance, adding land use can affect spatial projections of both presence‐absence and abundance models.     

Leaf manganese concentrations as a tool to assess belowground plant functioning in phosphorus-impoverished environments

Plant and Soil - Root-released carboxylates enhance the availability of manganese (Mn), which enters roots through transporters with low substrate specificity. Leaf Mn concentration ([Mn]) has been...     

Determining the appropriate pretreatment procedures and the utility of liver tissue for bulk stable isotope (δ13C and δ15N) studies in sharks

Stable-isotope analysis (SIA) provides a valuable tool to address complex questions pertaining to elasmobranch ecology. Liver, a metabolically active, high turnover tissue (~166 days for 95% turnover), has the potential to reveal novel insights into recent feeding/movement behaviours of this diverse group. To date, limited work has used this tissue, but ecological application of SIA in liver requires consideration of tissue preparation techniques given the potential for high concentrations of urea and lipid that could bias δ¹³C and δ¹⁵N values (i.e., result in artificially lower δ¹³C and δ¹⁵N values). Here we investigated the effectiveness of (a) deionized water washing (WW) for urea removal from liver tissue and (b) chloroform-methanol for extraction of lipids from this lipid rich tissue. We then (a) established C:N thresholds for deriving ecologically relevant liver isotopic values given complications of removing all lipid and (b) undertook a preliminary comparison of δ¹³C values between tissue pairs (muscle and liver) to test if observed isotopic differences correlated with known movement behaviour. Tests were conducted on four large shark species: the dusky (DUS, Carcharhinus obscurus), sand tiger (RAG, Carcharias taurus), scalloped hammerhead (SCA, Sphyrna lewini) and white shark (GRE, Carcharodon carcharias). There was no significant difference in δ¹⁵N values between lipid-extracted (LE) liver and lipid-extracted/water washed (WW) treatments, however, WW resulted in significant increases in %N, δ¹³C and %C. Following lipid extraction (repeated three times), some samples were still biased by lipids. Our species-specific “C:N thresholds” provide a method to derive ecologically viable isotope data given the complexities of this lipid rich tissue (C:N thresholds of 4.0, 3.6, 4.7 and 3.9 for DUS, RAG, SCA and GRE liver_LEWW tissue, respectively). The preliminary comparison of C:N threshold corrected liver and muscle δ¹³C values corresponded with movement/habitat behaviours for each shark; minor differences in δ¹³C values were observed for known regional movements of DUS and RAG (δ¹³C_Diffs = 0.24 ± 0.99‰ and 0.57 ± 0.38‰, respectively), while SCA and GRE showed greater differences (1.24 ± 0.63‰ and 1.08 ± 0.71‰, respectively) correlated to large-scale movements between temperate/tropical and pelagic/coastal environments. These data provide an approach for the successful application of liver δ¹³C and δ¹⁵N values to examine elasmobranch ecology.     

TMEM41B and VMP1 are scramblases and regulate the distribution of cholesterol and phosphatidylserine

TMEM41B and VMP1 are integral membrane proteins of the endoplasmic reticulum (ER) and regulate the formation of autophagosomes, lipid droplets (LDs), and lipoproteins. Recently, TMEM41B was identified as a crucial host factor for infection by all coronaviruses and flaviviruses. The molecular function of TMEM41B and VMP1, which belong to a large evolutionarily conserved family, remains elusive. Here, we show that TMEM41B and VMP1 are phospholipid scramblases whose deficiency impairs the normal cellular distribution of cholesterol and phosphatidylserine. Their mechanism of action on LD formation is likely to be different from that of seipin. Their role in maintaining cellular phosphatidylserine and cholesterol homeostasis may partially explain their requirement for viral infection. Our results suggest that the proper sorting and distribution of cellular lipids are essential for organelle biogenesis and viral infection.     

Triterpenoid saponins from a cytotoxic root extract of Sideroxylonfoetidissimum subsp. gaumeri

Evaluation of the cytotoxicity of an ethanolic root extract of Sideroxylonfoetidissimum subsp. gaumeri (Sapotaceae) revealed activity against the murine macrophage-like cell line RAW 264.7. Systematic bioassay-guided fractionation of this extract gave an active saponin-containing fraction from which four saponins were isolated. Use of 1D (¹H, ¹³C, DEPT135) and 2D (COSY, TOCSY, HSQC, and HMBC) NMR, mass spectrometry and sugar analysis gave their structures as 3-O-(β-d-glucopyranosyl-(1 → 6)-β-d-glucopyranosyl)-28-O-(α-l-rhamnopyranosyl-(1 → 3)[β-d-xylopyranosyl-(1 → 4)]-β-d-xylopyranosyl-(1 → 4)-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-16α-hydroxyprotobassic acid, 3-O-β-d-glucopyranosyl-28-O-(α-l-rhamnopyranosyl-(1 → 3)[β-d-xylopyranosyl-(1 → 4)]-β-d-xylopyranosyl-(1 → 4)-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-16α-hydroxyprotobassic acid, 3-O-(β-d-glucopyranosyl-(1 → 6)-β-d-glucopyranosyl)-28-O-(α-l-rhamnopyranosyl-(1 → 3)-β-d-xylopyranosyl-(1 → 4)[β-d-apiofuranosyl-(1 → 3)]-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-16α-hydroxyprotobassic acid, and the known compound, 3-O-β-d-glucopyranosyl-28-O-(α-l-rhamnopyranosyl-(1 → 3)[β-d-xylopyranosyl-(1 → 4)]-β-d-xylopyranosyl-(1 → 4)-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-protobassic acid. Two further saponins were obtained from the same fraction, but as a 5:4 mixture comprising 3-O-(β-d-glucopyranosyl)-28-O-(α-l-rhamnopyranosyl-(1 → 3)-β-d-xylopyranosyl-(1 → 4)[β-d-apiofuranosyl-(1 → 3)]-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-16α-hydroxyprotobassic acid and 3-O-(β-d-apiofuranosyl-(1 → 3)-β-d-glucopyranosyl)-28-O-(α-l-rhamnopyranosyl-(1 → 3)[β-d-xylopyranosyl-(1 → 4)]-β-d-xylopyranosyl-(1 → 4)-α-l-rhamnopyranosyl-(1 → 2)-α-l-arabinopyranosyl)-16α-hydroxyprotobassic acid, respectively. This showed greater cytotoxicity (IC₅₀ = 11.9 ± 1.5 μg/ml) towards RAW 264.7 cells than the original extract (IC₅₀ = 39.5 ± 4.1 μg/ml), and the saponin-containing fraction derived from it (IC₅₀ = 33.7 ± 6.2 μg/ml).