Key parameters controlling stiffness variability within trees: a multiscale experimental–numerical approach

Microstructural properties of wood vary considerably within a tree. Knowledge of these properties and a better understanding of their relationship to the macroscopic mechanical performance of wood are crucial to optimize the yield and economic value of forest stocks. This holds particularly for the end-use requirements in engineering applications. In this study the microstructure–stiffness relationships of Scots pine are examined with a focus on the effects of the microstructural variability on the elastic properties of wood at different length scales. For this purpose, we have augmented microstructural data acquired using SilviScan-3? (namely wood density, cell dimensions, earlywood and latewood proportion, microfibril angle) with local measurements of these quantities and of the chemical composition derived from wide-angle X-ray scattering, light microscopy, and thermogravimetric analysis, respectively. The stiffness properties were determined by means of ultrasonic tests at the clear wood scale and by means of nanoindentation at the cell wall scale. In addition, micro-mechanical modeling was applied to assess the causal relations between structural and mechanical properties and to complement the experimental investigations. Typical variability profiles of microstructural and mechanical properties are shown from pith to bark, across a single growth ring and from earlywood to latewood. The clear increase of the longitudinal stiffness as well as the rather constant transverse stiffness from pith to bark could be explained by the variation in microfibril angle and wood density over the entire radial distance. The dependence of local cell wall stiffness on the local microfibril angle was also demonstrated. However, the local properties did not necessarily follow the trends observed at the macroscopic scale and exhibited only a weak relationship with the macroscopic mechanical properties. While the relationship between silvicultural practice and wood microstructure remains to be modeled using statistical techniques, the influence of microstructural properties on the macroscopic mechanical behavior of wood can now be described by a physical model. The knowledge gained by these investigations and the availability of a new micromechanical model, which allows transferring these findings to non-tested material, will be valuable for wood quality assessment and optimization in timber engineering.     

Unraveling the Genetic Etiology of Adult Antisocial Behavior: A Genome-Wide Association Study

Crime poses a major burden for society. The heterogeneous nature of criminal behavior makes it difficult to unravel its causes. Relatively little research has been conducted on the genetic influences of criminal behavior. The few twin and adoption studies that have been undertaken suggest that about half of the variance in antisocial behavior can be explained by genetic factors. In order to identify the specific common genetic variants underlying this behavior, we conduct the first genome-wide association study (GWAS) on adult antisocial behavior. Our sample comprised a community sample of 4816 individuals who had completed a self-report questionnaire. No genetic polymorphisms reached genome-wide significance for association with adult antisocial behavior. In addition, none of the traditional candidate genes can be confirmed in our study. While not genome-wide significant, the gene with the strongest association (p-value = 8.7×10⁻⁵) was DYRK1A, a gene previously related to abnormal brain development and mental retardation. Future studies should use larger, more homogeneous samples to disentangle the etiology of antisocial behavior. Biosocial criminological research allows a more empirically grounded understanding of criminal behavior, which could ultimately inform and improve current treatment strategies.     

Provenance- and life-history stage-specific responses of the dwarf shrub Calluna vulgaris to elevated vapour pressure deficit

Climate change may alter microscale-effective ecosystem properties such as atmospheric water vapour pressure, but consequences for plant growth are insufficiently understood. Within a northwest German heathland an open-top chamber experiment was established to analyse the effects of elevated vapour pressure deficit (eVPD) on growth responses of Calluna vulgaris considering both plant origin (Atlantic (AP), sub-Atlantic (SAP), sub-Continental (SCP)) and life-history stage (1-year vs. 10-year old plants). We hypothesised that the plants’ sensitivity to eVPD decreases (i) from AP to SCP and (ii) with progressing life-history stage. Elevated VPD caused a provenance-specific decrease of shoot increment whilst aboveground biomass productivity remained unaffected. AP and SAP responded with increasing belowground biomass δ¹³C signatures to eVPD, whereas δ¹³C values decreased for SCP. Moreover, eVPD increased and decreased belowground biomass δ¹³C signatures of 1- and 10-year old plants, respectively. These responses to eVPD were related to differences in morphological-chemical traits and the plants’ trait plasticity in response to eVPD. SCP showed the highest aboveground tissue mass density and significantly increased tissue C:N ratios under eVPD. One-year old plants had a tenfold higher shoot:root ratio than 10-year old plants, making young plants more sensitive to eVPD. Our findings demonstrate that the atmospheric water status affects the morphology and physiology of Calluna independent of the soil water status. The results have implications for the conservation of heathlands under climate change: (i) SCP may constitute an appropriate ecotype for assisted migration-approaches, and (ii) management needs to weigh different options for heathland rejuvenation.

     

The aged hematopoietic system promotes hippocampal‐dependent cognitive decline

The aged systemic milieu promotes cellular and cognitive impairments in the hippocampus. Here, we report that aging of the hematopoietic system directly contributes to the pro‐aging effects of old blood on cognition. Using a heterochronic hematopoietic stem cell (HSC) transplantation model (in which the blood of young mice is reconstituted with old HSCs), we find that exposure to an old hematopoietic system inhibits hippocampal neurogenesis, decreases synaptic marker expression, and impairs cognition. We identify a number of factors elevated in the blood of young mice reconstituted with old HSCs, of which cyclophilin A (CyPA) acts as a pro‐aging factor. Increased systemic levels of CyPA impair cognition in young mice, while inhibition of CyPA in aged mice improves cognition. Together, these data identify age‐related changes in the hematopoietic system as drivers of hippocampal aging.     

Inhibition of Cdc42 activity extends lifespan and decreases circulating inflammatory cytokines in aged female C57BL/6 mice

Cdc42 is a small RhoGTPase regulating multiple functions in eukaryotic cells. The activity of Cdc42 is significantly elevated in several tissues of aged mice, while the Cdc42 gain‐of‐activity mouse model presents with a premature aging‐like phenotype and with decreased lifespan. These data suggest a causal connection between elevated activity of Cdc42, aging, and reduced lifespan. Here, we demonstrate that systemic treatment of aged (75‐week‐old) female C57BL/6 mice with a Cdc42 activity‐specific inhibitor (CASIN) for 4 consecutive days significantly extends average and maximum lifespan. Moreover, aged CASIN‐treated animals displayed a youthful level of the aging‐associated cytokines IL‐1β, IL‐1α, and INFγ in serum and a significantly younger epigenetic clock as based on DNA methylation levels in blood cells. Overall, our data show that systemic administration of CASIN to reduce Cdc42 activity in aged mice extends murine lifespan.     

Compositional turnover and variation in Eemian pollen sequences in Europe

Vegetation History and Archaeobotany - The Eemian interglacial represents a natural experiment on how past vegetation with negligible human impact responded to amplified temperature changes...     

The mechanism of Single strand binding protein–RecG binding: Implications for SSB interactome function

The Escherichia coli single‐strand DNA binding protein (SSB) is essential to viability where it functions to regulate SSB interactome function. Here it binds to single‐stranded DNA and to target proteins that comprise the interactome. The region of SSB that links these two essential protein functions is the intrinsically disordered linker. Key to linker function is the presence of three, conserved PXXP motifs that mediate binding to oligosaccharide‐oligonucleotide binding folds (OB‐fold) present in SSB and its interactome partners. Not surprisingly, partner OB‐fold deletions eliminate SSB binding. Furthermore, single point mutations in either the PXXP motifs or, in the RecG OB‐fold, obliterate SSB binding. The data also demonstrate that, and in contrast to the view currently held in the field, the C‐terminal acidic tip of SSB is not required for interactome partner binding. Instead, we propose the tip has two roles. First, and consistent with the proposal of Dixon, to regulate the structure of the C‐terminal domain in a biologically active conformation that prevents linkers from binding to SSB OB‐folds until this interaction is required. Second, as a secondary binding domain. Finally, as OB‐folds are present in SSB and many of its partners, we present the SSB interactome as the first family of OB‐fold genome guardians identified in prokaryotes.     

Genetic variation in an ephemeral mudflat species: The role of the soil seed bank and dispersal in river and secondary anthropogenic habitats

Many ephemeral mudflat species, which rely on a soil seed bank to build up the next generation, are endangered in their natural habitat due to the widespread regulation of rivers. The aim of the present study was to elucidate the role of the soil seed bank and dispersal for the maintenance of genetic diversity in populations of near‐natural river habitats and anthropogenic habitats created by traditional fish farming practices using Cyperus fuscus as a model. Using microsatellite markers, we found no difference in genetic diversity levels between soil seed bank and above‐ground population and only moderate differentiation between the two fractions. One possible interpretation is the difference in short‐term selection during germination under specific conditions (glasshouse versus field) resulting in an ecological filtering of genotypes out of the reservoir in the soil. River populations harbored significantly more genetic diversity than populations from the anthropogenic pond types. We suggest that altered levels and patterns of dispersal together with stronger selection pressures and historical bottlenecks in anthropogenic habitats are responsible for the observed reduction in genetic diversity. Dispersal is also supposed to largely prohibit genetic structure across Europe, although there is a gradient in private allelic richness from southern Europe (high values) to northern, especially north‐western, Europe (low values), which probably relates to postglacial expansion out of southern and/or eastern refugia.     

Analysis of chemometric models applied to Raman spectroscopy for monitoring key metabolites of cell culture

The Food and Drug Administration (FDA) initiative of Process Analytical Technology (PAT) encourages the monitoring of biopharmaceutical manufacturing processes by innovative solutions. Raman spectroscopy and the chemometric modeling tool partial least squares (PLS) have been applied to this aim for monitoring cell culture process variables. This study compares the chemometric modeling methods of Support Vector Machine radial (SVMr), Random Forests (RF), and Cubist to the commonly used linear PLS model for predicting cell culture components—glucose, lactate, and ammonia. This research is performed to assess whether the use of PLS as standard practice is justified for chemometric modeling of Raman spectroscopy and cell culture data. Model development data from five small-scale bioreactors (2 × 1 L and 3 × 5 L) using two Chinese hamster ovary (CHO) cell lines were used to predict against a manufacturing scale bioreactor (2,000 L). Analysis demonstrated that Cubist predictive models were better for average performance over PLS, SVMr, and RF for glucose, lactate, and ammonia. The root mean square error of prediction (RMSEP) of Cubist modeling was acceptable for the process concentration ranges of glucose (1.437 mM), lactate (2.0 mM), and ammonia (0.819 mM). Interpretation of variable importance (VI) results theorizes the potential advantages of Cubist modeling in avoiding interference of Raman spectral peaks. Predictors/Raman wavenumbers (cm⁻¹) of interest for individual variables are X1139–X1141 for glucose, X846–X849 for lactate, and X2941–X2943 for ammonia. These results demonstrate that other beneficial chemometric models are available for use in monitoring cell culture with Raman spectroscopy.