Molecular heterogeneity of D-end products detected by anti-H-2.28 sera

Immunoprecipitation of NP-40 lysates of 125I-labeled lymph-node cells with different anti-H-2 sera and with anti-Qa-2 serum has shown that the BALB/cByA strain (H-2d, Qa-2-negative) expresses, besides H-2Ld, another molecule that is not detectable in the BALB/c-H-2dm2 strain. Electrophoresis in SDS polyacrylamide gels indicated that this molecule, provisionally designated Lq, has an apparent molecular weight of 41000 daltons, in contrast to approximately 49000 daltons for H-2Kd and H-2Ld, and 47000 daltons for H-2Dd molecules. The anti-Qa-2 serum precipitated from the Qa-2-positive strains BALB/cHeA but not from the Qa-2-negative strains BALB/cByA and BALB/c-H-2dm2 a protein that gave a very strong band corresponding to the molecular weight 41000 daltons in the gel electrophoresis. The biochemical characteristics of the Lq molecule are thus more similar to those of Qa-2 than of H-2 antigens.     

Detection of genetic variants affecting cattle behaviour and their impact on milk production: a genome‐wide association study

Behaviour traits of cattle have been reported to affect important production traits, such as meat quality and milk performance as well as reproduction and health. Genetic predisposition is, together with environmental stimuli, undoubtedly involved in the development of behaviour phenotypes. Underlying molecular mechanisms affecting behaviour in general and behaviour and productions traits in particular still have to be studied in detail. Therefore, we performed a genome‐wide association study in an F₂ Charolais × German Holstein cross‐breed population to identify genetic variants that affect behaviour‐related traits assessed in an open‐field and novel‐object test and analysed their putative impact on milk performance. Of 37 201 tested single nucleotide polymorphism (SNPs), four showed a genome‐wide and 37 a chromosome‐wide significant association with behaviour traits assessed in both tests. Nine of the SNPs that were associated with behaviour traits likewise showed a nominal significant association with milk performance traits. On chromosomes 14 and 29, six SNPs were identified to be associated with exploratory behaviour and inactivity during the novel‐object test as well as with milk yield traits. Least squares means for behaviour and milk performance traits for these SNPs revealed that genotypes associated with higher inactivity and less exploratory behaviour promote higher milk yields. Whether these results are due to molecular mechanisms simultaneously affecting behaviour and milk performance or due to a behaviour predisposition, which causes indirect effects on milk performance by influencing individual reactivity, needs further investigation.     

Losing the last feather: feather loss as an antipredator adaptation in birds

Birds often lose feathers during predation attempts, and thisability has evolved as a means of escape. Because predatorsare more likely to grab feathers on the rump and the back thanon the ventral side of an escaping bird, we predicted that theformer feathers would have evolved to be relatively looselyattached as an antipredator strategy in species that frequentlydie from predation. We estimated the force required to removefeathers from the rump, back, and breast by pulling featherswith a spring balance from a range of European bird speciesin an attempt to investigate ecological factors associated withease of feather loss during predation attempts. The force requiredto loosen a feather from the rump was less than that requiredto loosen a feather from back, which in turn was less than thatrequired to loosen a feather from the breast. The relative forceneeded to loosen rump feathers compared with feathers from theback and the breast was smaller for prey species preferred bythe most common predator of small passerine birds, the sparrowhawkAccipiter nisus. Likewise, the relative force was also smallerin species with a high frequency of complete tail loss amongfree-living birds, which we used as an index of the frequencyof failed predation attempts. The relative force required toremove feathers from the rump was smaller in species with ahigh frequency of fear screams, another measure of the relativeimportance of predation as a cause of death. Feather loss requiredparticularly little force among solitarily breeding bird speciesthat suffer the highest degree of predation. Antipredator defensein terms of force required to remove feathers from the rumpwas larger in species with a strong antiparasite defense interms of T-cell–mediated immune response. These findingsare consistent with the hypothesis that different defenses areantagonistic and that they are traded off against each other.     

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.     

Interactions Among Fuel Management,Species Composition,Bark Beetles,and Climate Change and the Potential Effects on Forests of the Lake Tahoe Basin

Climate-driven increases in wildfires, drought conditions, and insect outbreaks are critical threats to forest carbon stores. In particular, bark beetles are important disturbance agents although their long-term interactions with future climate change are poorly understood. Droughts and the associated moisture deficit contribute to the onset of bark beetle outbreaks although outbreak extent and severity is dependent upon the density of host trees, wildfire, and forest management. Our objective was to estimate the effects of climate change and bark beetle outbreaks on ecosystem carbon dynamics over the next century in a western US forest. Specifically, we hypothesized that (a) bark beetle outbreaks under climate change would reduce net ecosystem carbon balance (NECB) and increase uncertainty and (b) these effects could be ameliorated by fuels management. We also examined the specific tree species dynamics—competition and release—that determined NECB response to bark beetle outbreaks. Our study area was the Lake Tahoe Basin (LTB), CA and NV, USA, an area of diverse forest types encompassing steep elevation and climatic gradients and representative of mixed-conifer forests throughout the western United States. We simulated climate change, bark beetles, wildfire, and fuels management using a landscape-scale stochastic model of disturbance and succession. We simulated the period 2010–2100 using downscaled climate projections. Recurring droughts generated conditions conducive to large-scale outbreaks; the resulting large and sustained outbreaks significantly increased the probability of LTB forests becoming C sources over decadal time scales, with slower-than-anticipated landscape-scale recovery. Tree species composition was substantially altered with a reduction in functional redundancy and productivity. Results indicate heightened uncertainty due to the synergistic influences of climate change and interacting disturbances. Our results further indicate that current fuel management practices will not be effective at reducing landscape-scale outbreak mortality. Our results provide critical insights into the interaction of drivers (bark beetles, wildfire, fuel management) that increase the risk of C loss and shifting community composition if bark beetle outbreaks become more frequent.     

Does maternal condition or predation risk influence small mammal population dynamics?

There is strong debate over whether the intrinsic traits of individuals or the extrinsic environment exert the greater influence on small mammal population dynamics. We test the roles of maternal effects (an intrinsic factor) and predation risk (an extrinsic factor) in the population dynamics of wild strain house mice using a 2-factor enclosure experiment. Pre-release supplemental feeding with a high-fat diet created female treatment founders that were 6–10% heavier than controls, a condition that we predicted would be passed on as a maternal effect. Predation risk was enhanced using regular application of predator (red fox Vulpes vulpes ) scats. Founder populations of six females and six males released into eight, 15×15 m enclosures showed near exponential population growth over 17 weeks (maximum 3 generations). But there were no responses to either treatment in terms of survival, inherited body weights, fecundity or population size. We suggest that elevated maternal condition may have only minor and transient intergenerational effects with little long-term consequence. We also suggest that the general significance of predator scats as a cue to predation risk to alter prey behaviour may have been overestimated. Hence our results question the role of either factor in causing long-term responses that influence condition to affect population processes.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.