Comprehensive phenotypic analysis and quantitative trait locus identification for grain mineral concentration, content, and yield in maize (Zea mays L.)

Biofortification by enhanced mineral density in maize grain through genetic improvement is one of the efficient ways to solve global mineral malnutrition, in which one key step is to detect the corresponding Quantitative Trait Loci (QTL). In this work, a maize recombinant inbred population (RIL) was grown to maturity in four field environments with two locations × two years. Phenotypic data of mineral nutrition concentration, content and yield were determined for grain copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), magnesium (Mg), potassium (K) and phosphorus (P). Analysis of variance (ANOVA) showed significant effects of genotype, location and year for all investigated traits. Location showed the highest effect for all mineral yields, and Zn and Cu content and concentration, while year had the strongest impact for Mn, K, and P content and concentration. Heritabilities (h2) of different traits varied with higher h2 (72-85%) for mineral concentration and content and lower (48-63%) for nutrient yields. Correlation coefficient analysis revealed significant positive correlations for grain concentration between several minerals. P had the closest correlations to other elements, while Cu had the lowest. When environments were analyzed individually, a total of 28, 25, and 12 QTL were identified for nutrient concentration, content and yield, respectively. Among these QTL, 8 QTL were consistent within traits across different environments. These stable QTL may be most promising for controlling mineral accumulation in maize grain. Co-localization of QTL for different traits was found for 12 chromosome regions, suggesting that common processes might contribute seed nutrient accumulatio

Effects of Elsholtzia splendens and Cirsium japonicum on premenstrual syndrome

Premenstrual syndrome is a common chronic disorder in most women of reproductive age. The main symptoms are depression, anxiety, tension, feeling out of control, and mastalgia. In premenstrual syndrome, the effects of aromatic edible Elsholtzia splendens and Cirsium japonicum were investigated for over 3 months in 30 women participants in their twenties. In the Elsholtzia splendens capsule treated group, scores of depression and anxiety were significantly lower than those in the Cirsium japonicum capsule treated group. Moreover, instability of the premenstrual assessment form was significantly decreased in the Elsholtzia splendens capsule treated group. Our results suggest that Elsholtzia splendens could be an effective plant material in relieving symptoms of premenstrual syndrome

Comprehensive phenotypic analysis and quantitative trait locus identification for grain mineral concentration, content, and yield in maize (Zea mays L.)

Biofortification by enhanced mineral density in maize grain through genetic improvement is one of the efficient ways to solve global mineral malnutrition, in which one key step is to detect the corresponding Quantitative Trait Loci (QTL). In this work, a maize recombinant inbred population (RIL) was grown to maturity in four field environments with two locations × two years. Phenotypic data of mineral nutrition concentration, content and yield were determined for grain copper (Cu), iron (Fe), manganese (Mn), zinc (Zn), magnesium (Mg), potassium (K) and phosphorus (P). Analysis of variance (ANOVA) showed significant effects of genotype, location and year for all investigated traits. Location showed the highest effect for all mineral yields, and Zn and Cu content and concentration, while year had the strongest impact for Mn, K, and P content and concentration. Heritabilities (h2) of different traits varied with higher h2 (72-85%) for mineral concentration and content and lower (48-63%) for nutrient yields. Correlation coefficient analysis revealed significant positive correlations for grain concentration between several minerals. P had the closest correlations to other elements, while Cu had the lowest. When environments were analyzed individually, a total of 28, 25, and 12 QTL were identified for nutrient concentration, content and yield, respectively. Among these QTL, 8 QTL were consistent within traits across different environments. These stable QTL may be most promising for controlling mineral accumulation in maize grain. Co-localization of QTL for different traits was found for 12 chromosome regions, suggesting that common processes might contribute seed nutrient accumulationThis is a post-peer-review, pre-copyedit version of an article published in Theoretical and Applied Genetics. The final authenticated version is available online at: https://doi.org/10.1007/s00122-015-2546-5.</p

A Computational Framework for the Topological Analysis and Targeted Disruption of Signal Transduction Networks

In this article, optimization-based frameworks are introduced for elucidating the input-output structure of signaling networks and for pinpointing targeted disruptions leading to the silencing of undesirable outputs in therapeutic interventions. The frameworks are demonstrated on a large-scale reconstruction of a signaling network composed of nine signaling pathways implicated in prostate cancer. The Min-Input framework is used to exhaustively identify all input-output connections implied by the signaling network structure. Results reveal that there exist two distinct types of outputs in the signaling network that either can be elicited by many different input combinations or are highly specific requiring dedicated inputs. The Min-Interference framework is next used to precisely pinpoint key disruptions that negate undesirable outputs while leaving unaffected necessary ones. In addition to identifying disruptions of terminal steps, we also identify complex disruption combinations in upstream pathways that indirectly negate the targeted output by propagating their action through the signaling cascades. By comparing the obtained disruption targets with lists of drug molecules we find that many of these targets can be acted upon by existing drug compounds, whereas the remaining ones point at so-far unexplored targets. Overall the proposed computational frameworks can help elucidate input/output relationships of signaling networks and help to guide the systematic design of interference strategies

Infectious Agents and Neurodegeneration

A growing body of epidemiologic and experimental data point to chronic bacterial and viral infections as possible risk factors for neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. Infections of the central nervous system, especially those characterized by a chronic progressive course, may produce multiple damage in infected and neighbouring cells. The activation of inflammatory processes and host immune responses cause chronic damage resulting in alterations of neuronal function and viability, but different pathogens can also directly trigger neurotoxic pathways. Indeed, viral and microbial agents have been reported to produce molecular hallmarks of neurodegeneration, such as the production and deposit of misfolded protein aggregates, oxidative stress, deficient autophagic processes, synaptopathies and neuronal death. These effects may act in synergy with other recognized risk factors, such as aging, concomitant metabolic diseases and the host's specific genetic signature. This review will focus on the contribution given to neurodegeneration by herpes simplex type-1, human immunodeficiency and influenza viruses, and by Chlamydia pneumoniae