Traditional and Emerging Lifestyle Risk Behaviors and All-Cause Mortality in Middle-Aged and Older Adults: Evidence from a Large Population-Based Australian Cohort

Background

Lifestyle risk behaviors are responsible for a large proportion of disease burden worldwide. Behavioral risk factors, such as smoking, poor diet, and physical inactivity, tend to cluster within populations and may have synergistic effects on health. As evidence continues to accumulate on emerging lifestyle risk factors, such as prolonged sitting and unhealthy sleep patterns, incorporating these new risk factors will provide clinically relevant information on combinations of lifestyle risk factors.

Methods and Findings

Using data from a large Australian cohort of middle-aged and older adults, this is the first study to our knowledge to examine a lifestyle risk index incorporating sedentary behavior and sleep in relation to all-cause mortality. Baseline data (February 2006– April 2009) were linked to mortality registration data until June 15, 2014. Smoking, high alcohol intake, poor diet, physical inactivity, prolonged sitting, and unhealthy (short/long) sleep duration were measured by questionnaires and summed into an index score. Cox proportional hazards analysis was used with the index score and each unique risk combination as exposure variables, adjusted for socio-demographic characteristics.During 6 y of follow-up of 231,048 participants for 1,409,591 person-years, 15,635 deaths were registered. Of all participants, 31.2%, 36.9%, 21.4%, and 10.6% reported 0, 1, 2, and 3+ risk factors, respectively. There was a strong relationship between the lifestyle risk index score and all-cause mortality. The index score had good predictive validity (c index = 0.763), and the partial population attributable risk was 31.3%. Out of all 96 possible risk combinations, the 30 most commonly occurring combinations accounted for more than 90% of the participants. Among those, combinations involving physical inactivity, prolonged sitting, and/or long sleep duration and combinations involving smoking and high alcohol intake had the strongest associations with all-cause mortality. Limitations of the study include self-reported and under-specified measures, dichotomized risk scores, lack of long-term patterns of lifestyle behaviors, and lack of cause-specific mortality data.

Conclusions

Adherence to healthy lifestyle behaviors could reduce the risk for death from all causes. Specific combinations of lifestyle risk behaviors may be more harmful than others, suggesting synergistic relationships among risk factors.     

Inhibition of <Emphasis Type="Italic">Candida</Emphasis> <Emphasis Type="Italic">albicans</Emphasis> Biofilm Formation by Antimycotics Released from Modified Polydimethyl Siloxane

Unlike various disinfectants, antifungals have not been commonly incorporated so far in medical devices, such as catheters or prostheses, to prevent biofilm formation by Candida spp. In the present study, five antimycotics were added to polydimethyl siloxane (PDMS) disks via admixture (nystatin) or impregnation (trimethylsilyl-nystatin (TMS-nystatin), miconazole, tea tree oil (TTO), zinc pyrithione). Nystatin-medicated PDMS disks exhibited a concentration-dependent inhibitory effect on biofilm formation in a microtiter plate (MTP) but not in a Modified Robbins Device (MRD). This observation, together with HPLC data and agar diffusion tests, indicates that a small fraction of free nystatin is released, which kills Candida albicans cells in the limited volume of a MTP well. In contrast, biofilm inhibition amounted to more than one log unit in the MRD on disks impregnated with miconazole, TTO, and zinc pyrithione. It is hypothesized that the reduction in biofilm formation by these compounds in a flow system occurs through a contact-dependent effect.     

Effects of time and rainfall on PCR success using DNA extracted from deer fecal pellets

Non-invasive wildlife research using DNA from feces has become increasingly popular. Recent studies have attempted to solve problems associated with recovering DNA from feces by investigating the influence of factors such as season, diet, collection method, preservation method, extraction protocol, and time. To our knowledge, studies of this nature have not addressed DNA degradation over time in wet environments, and have not been performed on fecal pellets of ungulates. Therefore, our objective was to determine the length of time a fecal pellet from a Sitka black-tailed deer (Odocoileus hemionus sitkensis) could remain in the field in a temperate rainforest environment before the DNA became too degraded for individual identification. Pellets were extracted from the rectum of recently killed deer and placed in an environment protected from rainfall and in an environment exposed to rainfall. Pellets from each treatment group were sampled at intervals of 2, 7, 14, 21, and 28 days after deer harvest. DNA was extracted from sampled pellets and individual samples were genotyped using microsatellite markers. Amplification failure and errors (dropout and false alleles) were recorded to determine extent of DNA degradation. Eighty percent of samples in the protected environment and 22% of samples in the exposed environment were successfully genotyped during the 28-day experiment. With no samples being successfully genotyped in the exposed environment after 7 days, our study showed that rainfall significantly increases degradation rates of DNA from ungulate pellets.     

Maintaining high anaerobic succinic acid productivity by product removal

During dual-phase fermentations using Escherichia coli engineered for succinic acid production, the productivity and viable cell concentration decrease as the concentration of succinic acid increases. The effects of succinic acid on the fermentation kinetics, yield, and cell viability were investigated by resuspending cells in fresh media after selected fermentation times. The cellular succinic acid productivity could be restored, but cell viability continuously decreased throughout the fermentations by up to 80% and subsequently the volumetric productivity was reduced. Omitting complex nutrients in the resuspension media had no significant effect on cellular succinate productivity and yield, although the viable cell concentration and thus the volumetric productivity was reduced by approximately 20%. By resuspending the cells, the amount of succinate produced during a 100-h fermentation was increased by more than 60%. The results demonstrate that by product removal succinic acid productivity can be maintained at high levels for extended periods of time.     

2‐D DIGE reveals changes in wheat xylanase inhibitor protein families due to Fusarium graminearum ΔTri5 infection and grain development

Wheat contains three different classes of proteinaceous xylanase inhibitors (XIs), i.e. Triticum aestivum xylanase inhibitors (TAXIs) xylanase‐inhibiting proteins (XIPs), and thaumatin‐like xylanase inhibitors (TLXIs) which are believed to act as a defensive barrier against phytopathogenic attack. In the absence of relevant data in wheat kernels, we here examined the response of the different members of the XI protein population to infection with a ΔTri5 mutant of Fusarium graminearum, the wild type of which is one of the most important wheat ear pathogens, in early developing wheat grain. Wheat ears were inoculated at anthesis, analyzed using 2‐D DIGE and multivariate analysis at 5, 15, and 25 days post anthesis (DPA), and compared with control samples. Distinct abundance patterns could be distinguished for different XI forms in response to infection with F. graminearum ΔTri5. Some (iso)forms were up‐regulated, whereas others were down‐regulated. This pathogen‐specific regulation of proteins was mostly visible at five DPA and levelled off in the samples situated further from the inoculation point. Furthermore, it was shown that most identified TAXI‐ and XIP‐type XI (iso)forms significantly increased in abundance from the milky (15 DPA) to the soft dough stages (25 DPA) on a per kernel basis, although the extent of increase differed greatly. Non‐glycosylated XIP forms increased more strongly than their glycosylated counterparts.     

Plasticity in response to phosphorus and light availability in four forest herbs

The differential ability of forest herbs to colonize secondary forests on former agricultural land is generally attributed to different rates of dispersal. After propagule arrival, however, establishing individuals still have to cope with abiotic soil legacies from former agricultural land use. We focused on the plastic responses of forest herbs to increased phosphorus availability, as phosphorus is commonly found to be persistently bioavailable in post-agricultural forest soils. In a pot experiment performed under field conditions, we applied three P levels to four forest herbs with contrasting colonization capacities: Anemone nemorosa, Primula elatior, Circaea lutetiana and Geum urbanum. To test interactions with light availability, half of the replicas were covered with shade cloths. After two growing seasons, we measured aboveground P uptake as well as vegetative and regenerative performance. We hypothesized that fast-colonizing species respond the most opportunistically to increased P availability, and that a low light availability can mask the effects of P on performance. All species showed a significant increase in P uptake in the aboveground biomass. The addition of P had a positive effect on the vegetative performances of two of the species, although this was unrelated to their colonization capacities. The regenerative performance was affected by light availability (not by P addition) and was related to the species’ phenology. Forest herbs can obviously benefit from the increased availability of P in post-agricultural forests, but not all species respond in the same way. Such differential patterns of plasticity may be important in community dynamics, as they affect the interactions among species.     

Modeling Lignin Polymerization. I. Simulation Model of Dehydrogenation Polymers

Lignin is a heteropolymer that is thought to form in the cell wall by combinatorial radical coupling of monolignols. Here, we present a simulation model of in vitro lignin polymerization, based on the combinatorial coupling theory, which allows us to predict the reaction conditions controlling the primary structure of lignin polymers. Our model predicts two controlling factors for the β-O-4 content of syringyl-guaiacyl lignins: the supply rate of monolignols and the relative amount of supplied sinapyl alcohol monomers. We have analyzed the in silico degradability of the resulting lignin polymers by cutting the resulting lignin polymers at β-O-4 bonds. These are cleaved in analytical methods used to study lignin composition, namely thioacidolysis and derivatization followed by reductive cleavage, under pulping conditions, and in some lignocellulosic biomass pretreatments.Lignins are aromatic polymers that are predominantly present in secondarily thickened cell walls. These polymers make the cell wall rigid and impervious, allowing transport of water and nutrients through the vascular system and protecting plants against microbial invasion. Lignins are heterogeneous polymers derived from phenylpropanoid monomers, mainly the hydroxycinnamyl alcohols coniferyl alcohol (G-monomer) and sinapyl alcohol (S-monomer) and minor amounts of p-coumaryl alcohol (H-monomer). These monolignols differ in their degree of aromatic methoxylation (-OCH₃ group; Fig. 1). The resulting units in the lignin polymer are the guaiacyl (G), syringyl (S), and p-hydroxyphenyl (H) units. They are linked by a variety of chemical bonds (Fig. 2) that have different chemical properties (Boerjan et al., 2003; Ralph et al., 2004; Vanholme et al., 2008).Open in a separate windowFigure 1.Chemical structures of three monolignols. A, H-monomer (p-coumaryl alcohol). B, G-monomer (coniferyl alcohol). C, S-monomer (sinapyl alcohol). G- and S-monomers are considered in our simulations. The G-monomer is methoxylated (-OCH₃ group) on position 3, and the S-monomer is methoxylated on positions 3 and 5.Open in a separate windowFigure 2.Chemical structures resulting from the possible bonding between two monomers (A) or a monomer and the bindable end of an oligomer (B). X and Y in the monomers denote the absence (for a G-unit) or presence (for an S-unit) of a methoxyl group at position 5 (see Fig. 1). The red line indicates the bonds generated by couplings of the B position and B, 4, or 5 position.Lignification is the process by which monomers and/or oligomers are polymerized via radical coupling reactions and typically occurs after the polysaccharides have been laid down in the cell wall. Lignin composition varies among cell types and can even be different in individual cell wall layers (Ruel et al., 2009). Lignin composition is also influenced by environmental conditions; for example, lignin in compression wood is enriched in H-units (Timell, 1986). Hence, both developmental and environmental parameters influence the composition and thus the structure of the lignin polymer (Boerjan et al., 2003; Ralph et al., 2004).Lignin is one of the main negative factors in the conversion of lignocellulosic plant biomass into pulp and bioethanol (Lynd et al., 1991; Hill et al., 2006). In these processes, lignin needs to be degraded by chemical or mechanical processes that are expensive and often environmentally polluting. Hence, major research efforts are devoted toward understanding lignin biosynthesis and structure. It has already been shown that reducing lignin content and modifying its composition in transgenic plants can result in dramatic improvements in pulping efficiency (Pilate et al., 2002; Baucher et al., 2003; Huntley et al., 2003; Leplé et al., 2007) and in the conversion of biomass into bioethanol (Stewart et al., 2006; Chen and Dixon, 2007; Custers, 2009). These altered biomass properties are related to the alterations in lignin composition and structure in terms of the frequencies of the lignin units and the bond types connecting them and possibly also their interaction with hemicelluloses (Ralph et al., 2004; Ralph, 2006).To study the parameters that influence lignin structure, lignin polymerization has been mimicked in vitro by experiments with dehydrogenation polymers (DHPs; Terashima et al., 1995). Indeed, lignification can be mimicked by oxidizing monolignols using a peroxidase, such as horseradish peroxidase (HRP), and supplying its cofactor hydrogen peroxide, producing synthetic DHP lignins. Monolignol oxidation can also be achieved without enzymes (e.g. by using transition metal one-electron oxidants, such as copper acetate). Some of these biomimetic DHPs have been suggested to be better models for wood lignins than HRP-generated DHPs (Landucci, 2000).In DHP experiments, the monolignols are either added in bulk (Zulauf experiment) or dropwise (Zutropf experiment) to the reaction mixture, yielding lignin polymers with very different bond frequencies (Freudenberg, 1956). Zutropf experiments approach the in vivo formation of lignin, which depends on the slow introduction of monolignols into the wall matrix via diffusion to the site of incorporation (Hatfield and Vermerris, 2001). Because the exact reaction conditions are known, such in vitro experiments have provided insight into the lignification process in planta. In this way, numerous factors were shown to influence lignin structure, including the relative supply of the monolignols, the pH, the presence of polysaccharides, hydrogen peroxide concentrations, and cell wall matrix elements in general (Grabber et al., 2003; Vanholme et al., 2008).Computer simulations of lignin polymerization can help explain and predict lignin structure from low-level chemical kinetic factors, including subunit-coupling probabilities and monolignol synthesis rates. Such models are helpful in explaining the mechanism behind a range of controlling factors identified in the experimental work, including (1) the ratio of coniferyl versus sinapyl alcohol monolignols, (2) the monolignol supply rate, and (3) the abundance of alternative monomers present during lignin biosynthesis in mutants and transgenics. Thus, computer models will also help in suggesting new targets for controlled lignin biosynthesis.Here, we propose a simulation model of synthetic lignin polymerization that is based upon an emerging consensus from a variety of observations and derives from a series of previous models of lignin polymerization (Glasser and Glasser, 1974; Glasser et al., 1976; Jurasek, 1995; Roussel and Lim, 1995). Our model uses a symbolic grammar to describe a constructive dynamical system (Fontana, 1992) or a rule-based system (Feret et al., 2009) in which it is not necessary to define all possible products in advance. We assume that G- and S-monomers and newly formed oligomers couple in a well-mixed medium, depending on coupling rules and experimentally measured coupling probabilities. To develop the model, we have used information from DHP experiments rather than natural lignins, as they are formed in a well-mixed medium and their reaction conditions are well known (e.g. the influx rate of monomers). Using information from natural lignin would have further complicated our model, as the structures of natural lignin polymers are influenced by many factors, including the possible involvement of dirigent proteins (Davin and Lewis, 2005), steric hindrance by polysaccharides, spatiotemporal regulation, and modifications during isolation procedures (Boerjan et al., 2003; Ralph et al., 2004).Using our simulation models, we study how putative controlling factors of lignin primary structure, including the influx rate of monomers and the relative amount of S-monomers, affect in silico lignin synthesis, and we compare our predictions with in vitro experiments. To predict the degradability of lignins formed in our simulations, we apply an in silico thioacidolysis, which cleaves the polymers at their β-O-4 positions. This simulates the molecular action of two of the most used methods to analyze lignin composition, thioacidolysis (Lapierre, 1993; Baucher et al., 2003) and derivatization followed by reductive cleavage (Lu and Ralph, 1997). The G+S-monomer yield is often taken as a reflection of the fraction of units bound by β-O-4 bonds. Cleavage of β-O-4 bonds is also the most important reaction in kraft pulping of wood (Baucher et al., 2003). The model predicts from first principles (1) that DHP lignins formed under Zutropf conditions have a higher β-O-4 content than those formed under Zulauf conditions, (2) that DHP lignins formed with high S content have a higher β-O-4 content than those formed with high G content, and (3) that a higher β-O-4 content does not necessarily reduce the average length of lignin fragments generated during in silico thioacidolysis.