Long-range energy transport in photosystem II.

We simulate the long-range inter-complex electronic energy transfer in photosystem II-from the antenna complex, via a core complex, to the reaction center-using a non-Markovian (ZOFE) quantum master equation description that allows the electronic coherence involved in the energy transfer to be explicitly included at all length scales. This allows us to identify all locations where coherence is manifested and to further identify the pathways of the energy transfer in the full network of coupled chromophores using a description based on excitation probability currents. We investigate how the energy transfer depends on the initial excitation-localized, coherent initial excitation versus delocalized, incoherent initial excitation-and find that the overall energy transfer is remarkably robust with respect to such strong variations of the initial condition. To explore the importance of vibrationally enhanced transfer and to address the question of optimization in the system parameters, we systematically vary the strength of the coupling between the electronic and the vibrational degrees of freedom. We find that the natural parameters lie in a (broad) region that enables optimal transfer efficiency and that the overall long-range energy transfer on a ns time scale appears to be very robust with respect to variations in the vibronic coupling of up to an order of magnitude. Nevertheless, vibrationally enhanced transfer appears to be crucial to obtain a high transfer efficiency, with the latter falling sharply for couplings outside the optimal range. Comparison of our full quantum simulations to results obtained with a "classical" rate equation based on a modified-Redfield/generalized-Förster description previously used to simulate energy transfer dynamics in the entire photosystem II complex shows good agreement for the overall time scales of excitation energy transport

Mining gene expression data by interpreting principal components

BACKGROUND: There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis. RESULTS: We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset). We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.). Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation. CONCLUSION: We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It has proven especially valuable in instances where there are many diverse conditions (10's to hundreds of different tissues or cell types), a situation in which many clustering and ordering algorithms become problematic. This approach also shows promise in other topic domains such as multi-spectral imaging datasets

Tree-ring Isotopes Adjacent to Lake Superior Reveal Cold Winter Anomalies for the Great Lakes Region of North America

Tree-ring carbon isotope discrimination (Δ13C) and oxygen isotopes (δ18O) collected from white pine (Pinus strobus) trees adjacent to Lake Superior show potential to produce the first winter-specific paleoclimate reconstruction with inter-annual resolution for this region. Isotopic signatures from 1976 to 2015 were strongly linked to antecedent winter minimum temperatures (Tmin), Lake Superior peak ice cover, and regional to continental-scale atmospheric winter pressure variability including the North American Dipole. The immense thermal inertia of Lake Superior underlies the unique connection between winter conditions and tree-ring Δ13C and δ18O signals from the following growing season in trees located near the lake. By combining these signals, we demonstrate feasibility to reconstruct variability in Tmin, ice cover, and continental-scale atmospheric circulation patterns (r ≥ 0.65, P \u3c 0.001)

Systematic review of reviews of intervention components associated with increased effectiveness in dietary and physical activity interventions.

BACKGROUND: To develop more efficient programmes for promoting dietary and/or physical activity change (in order to prevent type 2 diabetes) it is critical to ensure that the intervention components and characteristics most strongly associated with effectiveness are included. The aim of this systematic review of reviews was to identify intervention components that are associated with increased change in diet and/or physical activity in individuals at risk of type 2 diabetes. METHODS: MEDLINE, EMBASE, CINAHL, PsycInfo, and the Cochrane Library were searched for systematic reviews of interventions targeting diet and/or physical activity in adults at risk of developing type 2 diabetes from 1998 to 2008. Two reviewers independently selected reviews and rated methodological quality. Individual analyses from reviews relating effectiveness to intervention components were extracted, graded for evidence quality and summarised. RESULTS: Of 3856 identified articles, 30 met the inclusion criteria and 129 analyses related intervention components to effectiveness. These included causal analyses (based on randomisation of participants to different intervention conditions) and associative analyses (e.g. meta-regression). Overall, interventions produced clinically meaningful weight loss (3-5 kg at 12 months; 2-3 kg at 36 months) and increased physical activity (30-60 mins/week of moderate activity at 12-18 months). Based on causal analyses, intervention effectiveness was increased by engaging social support, targeting both diet and physical activity, and using well-defined/established behaviour change techniques. Increased effectiveness was also associated with increased contact frequency and using a specific cluster of "self-regulatory" behaviour change techniques (e.g. goal-setting, self-monitoring). No clear relationships were found between effectiveness and intervention setting, delivery mode, study population or delivery provider. Evidence on long-term effectiveness suggested the need for greater consideration of behaviour maintenance strategies. CONCLUSIONS: This comprehensive review of reviews identifies specific components which are associated with increased effectiveness in interventions to promote change in diet and/or physical activity. To maximise the efficiency of programmes for diabetes prevention, practitioners and commissioning organisations should consider including these components.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Meat eating and nutritional quality of lambs sired by high and low muscle density rams

Intramuscular fat (IMF) content affects eating and nutritional quality of lamb meat. Muscle density measured by computer tomography is an in vivo proxy measure of IMF content that affects eating and nutritional quality of lamb meat. Lambs sired by high muscle density (HMD) or low muscle density (LMD) rams, selected for slaughter on commercial criteria were measured for meat quality and nutritional traits. A restricted maximum likelihood model was used to compare lamb traits. Additionally, regression analysis of sire estimated breeding value (EBV) for muscle density was performed for each meat quality trait. Muscle density EBV had a negative regression with IMF content (P < 0.001). For each unit increase in muscle density EBV, there was a significant decrease in loin (− 1.69 mg/100 g fresh weight) and topside IMF (− 0.03 mg/100 g fresh weight). Muscle density EBV had a negative regression with grouped saturated and monounsaturated fatty acids concentration (and monounsaturated proportion P < 0.001). Muscle density EBV had a negative regression with loin sensory traits tenderness, juiciness and overall liking and many novel tenderness sensory traits measured (P < 0.05). Selecting for LMD EBV increased IMF content and favourable meat eating quality traits. In contrast, sire muscle density EBV had a positive regression with loin polyunsaturated:saturated fat ratio and grouped polyunsaturated proportion traits (including total polyunsaturated proportion, total omega-6 (n-6) and total omega-3 (n-3) fatty acids (P < 0.001). This is explained by the fact that as sire muscle density EBV increases, polyunsaturated fatty acid proportion increases and the proportion of saturated and monounsaturated fatty acid content decreases. Muscle density EBV had a positive regression with shear force and the novel toughness sensory traits (P < 0.05). Selection for HMD EBV's increased shear force and toughness traits, which is unfavourable for the consumer. Low muscle density sired meat had higher meat colour traits chroma/saturation (+ 0.64, SD 2.30, P = 0.012), redness (+ 0.52, SD 1.91, P = 0.012) and yellowness (+ 0.31, SD 1.49, P = 0.08) compared to HMD sired meat. Selection for LMD could be used within a breeding programme to increase IMF content and enhance both meat colour and improve eating quality parameters

Short-Term Exercise Training Does Not Stimulate Skeletal Muscle ATP Synthesis in Relatives of Humans With Type 2 Diabetes

OBJECTIVE-We tested the hypothesis that short-term exercise training improves hereditary insulin resistance by stimulating ATP synthesis and investigated associations With gene polymorphisms. RESEARCH DESIGN AND METHODS-We studied 24 nono-bese first-degree relatives of type 2 diabetic patients and 12 control subjects at rest, and 48 h after three bouts of exercise. In addition to measurements of oxygen uptake and insulin sensitivity (oral glucose tolerance test), ectopic lipids and mitochondrial ATP synthesis were assessed using H-1 and P-31 magnetic resonance spectroscopy, respectively. They were genotyped for polymorphisms in genes regulating mitochondrial function, PPARGC1A (rs8192678) and NDUFB6 (rs540467). RESULTS-Relatives had slightly lower (P = 0.012) insulin sensitivity than control subjects. In control subjects, ATP synthase flux rose by 18% (P = 0.0001), being 23% higher (P = 0.002) than that in relatives after exercise training. Relatives responding to exercise training with increased ATP synthesis (+19%, P = 0.009) showed improved insulin sensitivity (P = 0.009) compared with those whose insulin sensitivity did not improve. A polymorphism in the NDUFB6 gene from respiratory chain complex I related to ATP synthesis (P = 0.02) and insulin Sensitivity response to exercise training (P = 0.05). ATP synthase flux correlated with O-2 uptake and insulin sensitivity. CONCLUSIONS-The ability of short-term exercise to stimulate ATP production distinguished individuals with improved insulin sensitivity from those whose insulin sensitivity did not improve. lit addition, the NDUFB6 gene polymorphism appeared to modulate this adaptation. This finding suggests that genes involved in mitochondrial function contribute to the response of ATP synthesis to exercise training. Diabetes 58:1333-1341, 200