Recombination-deficient mutants of Salmonella typhimurium are avirulent and sensitive to the oxidative burst of macrophages

Mutations in the genes recA and recBC were constructed in the virulent Salmonella typhimurium strain 14028s. Both the recA and recBC mutants were attenuated in mice. The mutants were also sensitive to killing by macrophages in vitro. The recombination mutants were no longer macrophage sensitive in a variant line of J774 macrophage-like cells that fail to generate superoxide. This suggests that repair of DNA damage by Salmonella is necessary for full virulence in vivo and that the oxidative burst of phagocytes is one source of such DNA damage.     

Phenylalkyl ketones as potent reversible inhibitors of interleukin-1β converting enzyme

Phenylalkyl ketones are potent reversible inhibitors of interleukin-1β converting enzyme (ICE). The extended alkyl chain ketones AcTyrValAlaAspCO(CH₂)_nPh display increased potency over the simple aryl ketone. In particular, the tetrapeptide AcTyrValAlaAspCOPh has a K_i of 10μM while AcTyrValAlaAspCO(CH₂)₅Ph has a K_i of 18.5nM.     

Design considerations for two-stage enrichment clinical trials

When there is a predictive biomarker, enrichment can focus the clinical trial on a benefiting subpopulation. We describe a two-stage enrichment design, in which the first stage is designed to efficiently estimate a threshold and the second stage is a “phase III-like” trial on the enriched population. The goal of this paper is to explore design issues: sample size in Stages 1 and 2, and re-estimation of the Stage 2 sample size following Stage 1. By treating these as separate trials, we can gain insight into how the predictive nature of the biomarker specifically impacts the sample size. We also show that failure to adequately estimate the threshold can have disastrous consequences in the second stage. While any bivariate model could be used, we assume a continuous outcome and continuous biomarker, described by a bivariate normal model. The correlation coefficient between the outcome and biomarker is the key to understanding the behavior of the design, both for predictive and prognostic biomarkers. Through a series of simulations we illustrate the impact of model misspecification, consequences of poor threshold estimation, and requisite sample sizes that depend on the predictive nature of the biomarker. Such insight should be helpful in understanding and designing enrichment trials.     

Evaluating treatment effects in group sequential multivariate longitudinal studies with covariate adjustment

Jeffries et al. (2018) investigated testing for a treatment difference in the setting of a randomized clinical trial with a single outcome measured longitudinally over a series of common follow-up times while adjusting for covariates. That paper examined the null hypothesis of no difference at any follow-up time versus the alternative of a difference for at least one follow-up time. We extend those results here by considering multivariate outcome measurements, where each individual outcome is examined at common follow-up times. We consider the case where there is interest in first testing for a treatment difference in a global function of the outcomes (e.g., weighted average or sum) with subsequent interest in examining the individual outcomes, should the global function show a treatment difference. Testing is conducted for each follow-up time and may be performed in the setting of a group sequential trial. Testing procedures are developed to determine follow-up times for which a global treatment difference exists and which individual combinations of outcome and follow-up time show evidence of a difference while controlling for multiplicity in outcomes, follow-up, and interim analyses. These approaches are examined in a study evaluating the effects of tissue plasminogen activator on longitudinally obtained stroke severity measurements.     

Molecular Characterization and Mapping of Murine Genes Encoding Three Members of the Stefin Family of Cysteine Proteinase Inhibitors

Stefins or Type 1 cystatins belong to a large, evolutionarily conserved protein superfamily, the members of which inhibit the papain-like cysteine proteinases. We report here on the molecular cloning and chromosomal localization of three newly identified members of the murine stefin gene family. These genes, designated herein as mouse stefins 1, 2, and 3, were isolated on the basis of their relatively increased expression in moth-eaten viable compared to normal congenic mouse bone marrow cells. The open reading frames of the stefin cDNAs encode proteins of approximately 11.5 kDa that show between 50 and 92% identity to sequences of stefins isolated from various other species. Data from Southern analysis suggest that the murine stefin gene family encompasses at least 6 and possibly 10-20 members, all of which appear to be clustered in the genome. Analysis of interspecific backcross mice indicates that the genes encoding the three mouse stefins all map to mouse chromosome 16, a localization that is consistent with the recent assignment of the human stefin A gene to a region of conserved homology between human chromosome 3q and the proximal region of mouse chromosome 16.     

Flow rate and vertical position influence ingestion rates of colonial zebra mussels (Dreissena polymorpha)

1. Zebra mussels aggregate to form dense colonies where, depending on the flow rate, individuals in different vertical locations within the colony may experience restricted food availability. 2. Using ³²P‐labelled Chlamydomonas angulosa, we found ingestion rates of individual mussels located at the surface to exceed those in the bottom of a 6 cm thick colony by up to 75%. 3. Higher velocities (10 and 20 cm s^?1) increased algal delivery to the colony's middle layer (2–4 cm depth), subsequently increasing ingestion rates to equal those in the surface layer, while increasing ingestion only for the smallest mussels in the bottom (4–6 cm). 4. At all vertical locations within the colonies, smaller mussels showed higher ingestion rates per unit mass than larger mussels, particularly at higher flow rates.     

Mechanisms responsible for the positive diversity–productivity relationship in Minnesota grasslands

Species’ extinctions have spurred debate on whether interactions among few or among many species cause a positive diversity–productivity relationship in experimentally assembled grasslands. We addressed this question by quantifying the productivity of 14 species across an experimental diversity gradient in Minnesota. We found that interspecific interactions leading to coexistence and competitive displacement both determine which species overyield; i.e. are more productive at high diversity. Overyielding species were either superior N competitors (C4 grasses) or N fixers (legumes). Surprisingly, these species were not most productive in monoculture, thus, the ‘selection’ of productive species in diverse plots did not cause the positive diversity–productivity relationship. Both positive (with legumes) and negative interspecific interactions (with C4 grasses) determined whether individual species overyielded. Foliar pathogens did not cause overyielding, although other natural enemies may be responsible. Overyielding species are not displacing underyielding species over time, implying that other diversity‐promoting interactions also operate in this experiment.