Relationship between the seed rain and the establishment of vegetation in two areas abandoned after peat harvesting

In this study the number and species composition of diaspores dispersing into two newly abandoned peat harvesting areas in Finland were investigated. In an area abandoned six years earlier a total of 2978 living seeds m⁻², representing 18 species, was captured by using water-filled traps during two summers. In a one-year-old succession area the total number of living seeds m⁻² was 2241, representing 16 plant species. The soil seed banks were found to be empty of viable seeds. In neither area there appeared to be any relation between number of dispersing seeds and of plant individuals of the same species in the pioneer vegetation. It is suggested that unfavourable conditions on the soil surface for seed germination and seedling growth of most dispersed species are majors factor in determining the structure of the established vegetation.     

Evaluation of different similarity indices as measures of succession in arthropod communities of the forest floor after clear-cutting

Summary Communities of spiders (Araneae) and beetles (Coleoptera) living in the soil and litter of clear-cut areas were compared with those of intact forest stands. Sixteen different indices of similarity were tested on three sets of material: spiders and beetles examined during one year in three clear-cut areas felled 3, 6 and 9 years earlier, and spiders in one clear-cut area examined during 7 successive years after felling. Other sources of evidence showed that succession in the spider community was divergent for at least 7 years after felling.The indices that seemed to express the changes best were: (1) Kendall's rank correlation test, (2) the Bray-Curtis measure, (3) Renkonen's percentage similarity, (4) the correlation coefficient r (2 to 4 after logarithmic transformation of data), (5) the Canberra metric, and (6) the diversity overlap (R ₀). The properties of the indices are discussed.     

Combined effects of thrombosis pathway gene variants predict cardiovascular events

The genetic background of complex diseases is proposed to consist of several low-penetrance risk loci. Addressing this complexity likely requires both large sample size and simultaneous analysis of different predisposing variants. We investigated the role of four thrombosis genes: coagulation factor V (F5), intercellular adhesion molecule 1 (ICAM1), protein C (PROC), and thrombomodulin (THBD) in cardiovascular diseases. Single allelic gene variants and their pair-wise combinations were analyzed in two independently sampled population cohorts from Finland. From among 14,140 FINRISK participants (FINRISK-92, n = 5,999 and FINRISK-97, n = 8,141), we selected for genotyping a sample of 2,222, including 528 incident cardiovascular disease (CVD) cases and random subcohorts totaling 786. To cover all known common haplotypes (>10%), 54 single nucleotide polymorphisms (SNPs) were genotyped. Classification-tree analysis identified 11 SNPs that were further analyzed in Cox's proportional hazard model as single variants and pair-wise combinations. Multiple testing was controlled by use of two independent cohorts and with false-discovery rate. Several CVD risk variants were identified: In women, the combination of F5 rs7542281 x THBD rs1042580, together with three single F5 SNPs, was associated with CVD events. Among men, PROC rs1041296, when combined with either ICAM1 rs5030341 or F5 rs2269648, was associated with total mortality. As a single variant, PROC rs1401296, together with the F5 Leiden mutation, was associated with ischemic stroke events. Our strategy to combine the classification-tree analysis with more traditional genetic models was successful in identifying SNPs-acting either in combination or as single variants--predisposing to CVD, and produced consistent results in two independent cohorts. These results suggest that variants in these four thrombosis genes contribute to arterial cardiovascular events at population level.     

A single bout of exercise with high mechanical loading induces the expression of Cyr61/CCN1 and CTGF/CCN2 in human skeletal muscle.

High mechanical loading was hypothesized to induce the expression of angiogenic and/or lymphangiogenic extracellular matrix (ECM) proteins in skeletal muscle. Eight men performed a strenuous exercise protocol, which consisted of 100 unilateral maximal drop jumps followed by submaximal jumping until exhaustion. Muscle biopsies were taken 30 min and 48 h postexercise from the vastus lateralis muscle and analyzed for the following parameters: mRNA and protein expression of ECM-associated CCN proteins [cysteine-rich angiogenic protein 61 (Cyr61)/CCN1, connective tissue growth factor (CTGF)/CCN2], and mRNA expression of vascular endothelial growth factors (VEGFs) and hypoxia-inducible factor-1alpha. The mRNA expression of Cyr61 and CTGF increased 30 min after the exercise (14- and 2.5-fold, respectively; P < 0.001). Cyr61 remained elevated 48 h postexercise (threefold; P < 0.05). The mRNA levels of VEGF-A, VEGF-B, VEGF-C, VEGF-D, or hypoxia-inducible factor-1alpha did not change significantly at either 30 min or 48 h postexercise; however, the variation between subjects increased markedly in VEGF-A and VEGF-B mRNA. Cyr61 protein levels were higher at both 30 min and 48 h after the exercise compared with the control (P < 0.05). Cyr61 and CTGF proteins were localized to muscle fibers and the surrounding ECM by immunohistochemistry. Fast fibers stained more intensively than slow fibers. In conclusion, mechanical loading induces rapid expression of CCN proteins in human skeletal muscle. This may be one of the early mechanisms involved in skeletal muscle remodeling after exercise, since Cyr61 and CTGF regulate the expression of genes involved in angiogenesis and ECM remodeling.     

Genetic Markers Enhance Coronary Risk Prediction in Men: The MORGAM Prospective Cohorts

Background

More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design.

Methods

Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5–18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived.

Results

Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50–59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events.

Conclusions

Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.     

Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

Background

Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.

Methods and Findings

106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18–103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1–standard deviation increment, 95% CI 1.53–1.82, p = 5×10⁻³¹), albumin (HR 0.70, 95% CI 0.65–0.76, p = 2×10⁻¹⁸), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62–0.77, p = 3×10⁻¹²), and citrate (HR 1.33, 95% CI 1.21–1.45, p = 5×10⁻¹⁰). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).

Conclusions

Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention. Please see later in the article for the Editors'' Summary     

Endotoxemia is associated with an adverse metabolic profile

Our aim was to analyze whether endotoxemia, i.e. translocation of LPS to circulation, is reflected in the serum metabolic profile in a general population and in participants with cardiometabolic disorders. We investigated three Finnish cohorts separately and in a meta-analysis (n = 7178), namely population-based FINRISK97, FinnTwin16 consisting of young adult twins, and Parogene, a random cohort of cardiac patients. Endotoxemia was determined as serum LPS activity and metabolome by an NMR platform. Potential effects of body mass index (BMI), smoking, metabolic syndrome (MetS), and coronary heart disease (CHD) status were considered. Endotoxemia was directly associated with concentrations of VLDL, IDL, LDL, and small HDL lipoproteins, VLDL particle diameter, total fatty acids (FA), glycoprotein acetyls (GlycA), aromatic and branched-chain amino acids, and Glc, and inversely associated with concentration of large HDL, diameters of LDL and HDL, as well as unsaturation degree of FAs. Some of these disadvantageous associations were significantly stronger in smokers and subjects with high BMI, but did not differ between participants with different CHD status. In participants with MetS, however, the associations of endotoxemia with FA parameters and GlycA were particularly strong. The metabolic profile in endotoxemia appears highly adverse, involving several inflammatory characters and risk factors for cardiometabolic disorders.     

Cytological evidence for somatic diploidization in dikaryotic cells ofArmillariella mellea

Dikaryotic hyphae isolated from basidiocarps ofArmillariella mellea are unstable in aseptic culture and change into monokaryotic hypae. During monokaryotization the nuclei of a dikaryon fuse and fusion nucleus immediately divides resulting in two uninucleate cells, from which the monokaryotic mycelium originates. Similar fusion of two nuclei takes place in matings of compatible singlespore isolates. It is concluded that the resulting monokaryotic mycelium is diploid.     

Effects of 45-Hz magnetic fields on the functional state of the human brain

The influence of sinusoidal 45-Hz magnetic fields on the brain functions of 20 volunteers was investigated in a double-blind study using spectral analysis of EEG and measurements of Omega potentials and reaction time (RT). The field strength was 1,000 A/m (1.26 mT) and the duration of exposure was 1 h. Ten volunteers were exposed to a continuous field and ten received an intermittent exposure (1 s on/1 s off). Each person received one real and one sham exposure. One half of the volunteers got the real exposure first and the sham treatment after at least 24 h. For the rest, the sequence was inverse. The measurements of EEG, omega potentials and RT were performed before and after each exposure. Several statistically significant changes were observed, most of them after intermittent exposure. In the EEG, an increase of alpha (7.6–13.9 Hz) activity and a decrease of delta (1.5–3.9 Hz) activity were observed. β waves (14.2–20 Hz) increased in the frontal derivations as did the total power in occipital derivations. The mean and peak frequencies of EEG increased mainly in the frontal derivations. No direct effects on RT were seen. Learning to perform the RT test (decrease of RT in repeated trials), however, seemed to be affected by the exposure. The persons who received real exposure first learned more slowly than those who got sham exposure first. Further experiments are necessary to confirm the findings and for understanding the mechanisms of the effects. © 1993 Wiley-Liss. Inc.