Energy transduction in photosynthetic bacteria. VIII. Activation of the energy-transducing ATPase by inorganic phosphate

ATPase activity and ATP-induced energization of photosynthetic membranes from Rhodopseudomonas capsulata are stimulated by phosphate; the maximum stimulatory effect occurs at a concentration between 1 and 2 mM.The sensitivity of the ATPase to oligomycin increases in the presence of phosphate since all the P_i-stimulated activity is inhibited by this antibiotic. Aurovertin, which has no effect on ATPase in the absence of phosphate, inhibits completely the activity elicited by this anion.The addition of P_i induces a substantial increase in the V of ATPase activity without changing the affinity of the enzyme for ATP or ADP.Arsenate, at the same concentrations, produces effects very similar to those of phosphate. The stimulation by arsenate of the transfer of energy from ATP to the membrane suggests a non-hydrolytic role of this anion as a modifier of the ATPase activity.     

Can biochemical traits bridge the gap between genomics and plant performance? A study in rice under drought

The possibility of introducing metabolic/biochemical phenotyping to complement genomics-based predictions in breeding pipelines has been considered for years. Here we examine to what extent and under what environmental conditions metabolic/biochemical traits can effectively contribute to understanding and predicting plant performance. In this study, multivariable statistical models based on flag leaf central metabolism and oxidative stress status were used to predict grain yield (GY) performance for 271 indica rice (Oryza sativa) accessions grown in the field under well-watered and reproductive stage drought conditions. The resulting models displayed significantly higher predictability than multivariable models based on genomic data for the prediction of GY under drought (Q² = 0.54–0.56 versus 0.35) and for stress-induced GY loss (Q² = 0.59–0.64 versus 0.03–0.06). Models based on the combined datasets showed predictabilities similar to metabolic/biochemical-based models alone. In contrast to genetic markers, models with enzyme activities and metabolite values also quantitatively integrated the effect of physiological differences such as plant height on GY. The models highlighted antioxidant enzymes of the ascorbate–glutathione cycle and a lipid oxidation stress marker as important predictors of rice GY stability under drought at the reproductive stage, and these stress-related variables were more predictive than leaf central metabolites. These findings provide evidence that metabolic/biochemical traits can integrate dynamic cellular and physiological responses to the environment and can help bridge the gap between the genome and the phenome of crops as predictors of GY performance under drought.

Biochemical traits outperform the explanatory power of genetic markers when used as variables in models for predicting yield performance in rice under drought stress.     

A quantitative trait locus involved in maize yield is tightly associated to the r1 gene on the long arm of chromosome 10

We produced and studied for 3?years two synthetic populations of maize differing in their constitution only for the selected alleles present at the red color 1 (r1) locus (R-sc vs. r?Cr). r1 is a regulatory gene conferring anthocyanin pigmentation in different tissues: the R-sc allele confers pigmentation only in the aleurone seed layer, while the r?Cr allele confers pigmentation in several tissues such as root, silk and anther but the seed is colourless. The colourless population (r?Cr/r?Cr) was characterized by improved agronomic features, such as ear weight and plant height, compared with the R-sc/R-sc coloured population. This finding was confirmed by studying single F4 R/r families where the presence of the r?Cr allele conferred positive features, acting as a dominant trait. Quantitative trait locus (QTL) analysis performed using molecular markers on the long arm of chromosome 10 (bin 10.06), where the r1 gene maps, identified a QTL map position for plant height tightly associated to the r1 gene. Thus the r1 gene may represent a major QTL or it could be closely linked to another gene involved in the agronomic performance of the two populations studied.     

Is interest toward the environment really declining? The complexity of analysing trends using internet search data

Recent analyses of internet search volume hypothesized a decline of public interest toward themes related to environment, biodiversity conservation and fishery. These analyses were based on Google Trends, which is a measure of how frequently a term is searched in Google, in proportion to the total of searches performed. Google Trends is a measure of relative search, and this may make difficult assessing temporal trends. I evaluated whether relative declines in internet search volumes represent genuine decline in interest toward environmental-related themes, by comparing trends of terms representing various themes, including environment, computer science, other disciplines (astrophysics) and leisure. Similar values of relative decline were detected for environmental terms, for computer science terms, and for other scientific disciplines. Conversely, an increase was observed for leisure related terms. This suggests that interest toward the environment is not truly decreasing. The apparent decline of environmental and scientific terms is most likely caused by the increasing use of internet for aims unrelated to science and technology, such as leisure. Internet search tools are a powerful source of information, but users should be aware of the complexity of analysing their data: using unrelated terms as benchmark may help to identify genuine trends.     

Synthesis,semipreparative HPLC separation,biological evaluation,and 3D-QSAR of hydrazothiazole derivatives as human monoamine oxidase B inhibitors

The present study reports on synthesis in high yields (70–99%), HPLC enantioseparation, inhibitory activity against human monoamino oxidases, and molecular modeling including 3D-QSAR studies, of a large series of (4-aryl-thiazol-2-yl)hydrazones (1–45). Most of the synthesized compounds proved to be potent and selective inhibitors of hMAO-B isoform in the micromolar or nanomolar range, thus demonstrating that hydrazothiazole could be considered a good pharmacophore to design new hMAO-B inhibitors. Due to the presence in some derivatives of a chiral center, we also performed a semipreparative chromatographic enantioseparation of these compounds obtained by a stereoconservative pattern. The separated enantiomers were submitted to in vitro biological evaluation to point out the stereorecognition of the active site of the enzyme towards these structures. Finally, a 3D-QSAR study was carried out using Comparative Molecular Field Analysis (CoMFA), aiming to deduce rational guidelines for the further structural modification of these lead compounds.     

Adapting Stand‐Alone Renewable Energy Technologies for the Circular Economy through Eco‐Design and Recycling

Renewable energy (RE) technologies are looked upon favorably to provide for future energy demands and reduce greenhouse gas (GHG) emissions. However, the installation of these technologies requires large quantities of finite material resources. We apply life cycle assessment to 100 years of electricity generation from three stand‐alone RE technologies—solar photovoltaics, run‐of‐river hydro, and wind—to evaluate environmental burden profiles against baseline electricity generation from fossil fuels. We then devised scenarios to incorporate circular economy (CE) improvements targeting hotspots in systems’ life cycle, specifically (1) improved recycling rates for raw materials and (ii) the application of eco‐design. Hydro presented the lowest environmental burdens per kilowatt‐hour of electricity generation compared with other RE technologies, owing to its higher efficiency and longer life spans for main components. Distinct results were observed in the environmental performance of each system based on the consideration of improved recycling rates and eco‐design. CE measures produced similar modest savings in already low GHG emissions burdens for each technology, while eco‐design specifically had the potential to provide significant savings in abiotic resource depletion. Further research to explore the full potential of CE measures for RE technologies will curtail the resource intensity of RE technologies required to mitigate climate change.     

Oscillations in the prefrontal cortex: a gateway to memory and attention

We consider the potential role of oscillations in the prefrontal cortex (PFC) in mediating attention, working memory and memory consolidation. Activity in the theta, beta, and gamma bands is related to communication between PFC and different brain areas. While gamma/beta oscillations mediate bottom-up and top-down interactions between PFC and visual cortices, related to attention, theta rhythms are engaged by hippocampal/PFC interplay. These interactions are dynamic, depending on the nature and relevance of the information currently being processed. The profound modifications of the PFC neuronal network associated with changes in oscillatory coherence are controlled by neuromodulators such as dopamine, which thereby allow or prevent the formation of cell assemblies for information encoding and storage.     

Reverse engineering and analysis of genome-wide gene regulatory networks from gene expression profiles using high-performance computing

Regulation of gene expression is a carefully regulated phenomenon in the cell. “Reverse-engineering” algorithms try to reconstruct the regulatory interactions among genes from genome-scale measurements of gene expression profiles (microarrays). Mammalian cells express tens of thousands of genes; hence, hundreds of gene expression profiles are necessary in order to have acceptable statistical evidence of interactions between genes. As the number of profiles to be analyzed increases, so do computational costs and memory requirements. In this work, we designed and developed a parallel computing algorithm to reverse-engineer genome-scale gene regulatory networks from thousands of gene expression profiles. The algorithm is based on computing pairwise Mutual Information between each gene-pair. We successfully tested it to reverse engineer the Mus Musculus (mouse) gene regulatory network in liver from gene expression profiles collected from a public repository. A parallel hierarchical clustering algorithm was implemented to discover “communities” within the gene network. Network communities are enriched for genes involved in the same biological functions. The inferred network was used to identify two mitochondrial proteins.