Naturally p-hydroxybenzoylated lignins in palms

The industrial production of palm oil concurrently generates a substantial amount of empty fruit bunch (EFB) fibers that could be used as a feedstock in a lignocellulose-based biorefinery. Lignin byproducts generated by this process may offer opportunities for the isolation of value-added products, such as p-hydroxybenzoate (pBz), to help offset operating costs. Analysis of the EFB lignin by nuclear magnetic resonance (NMR) spectroscopy clearly revealed the presence of bound acetate and pBz, with saponification revealing that 1.1 wt% of the EFB was pBz; with a lignin content of 22.7 %, 4.8 % of the lignin is pBz that can be obtained as a pure component for use as a chemical feedstock. Analysis of EFB lignin by NMR and derivatization followed by reductive cleavage (DFRC) showed that pBz selectively acylates the γ-hydroxyl group of S units. This selectivity suggests that pBz, analogously with acetate in kenaf, p-coumarate in grasses, and ferulate in a transgenic poplar augmented with a feruloyl-CoA monolignol transferase (FMT), is incorporated into the growing lignin chain via its γ-p-hydroxybenzoylated monolignol conjugate. Involvement of such conjugates in palm lignification is proven by the observation of novel p-hydroxybenzoylated non-resinol β–β-coupled units in the lignins. Together, the data implicate the existence of p-hydroxybenzoyl-CoA:monolignol transferases that are involved in lignification in the various willows (Salix spp.), poplars and aspen (Populus spp., family Salicaceae), and palms (family Arecaceae) that have p-hydroxybenzoylated lignins. Even without enhancing the levels by breeding or genetic engineering, current palm oil EFB ‘wastes’ should be able to generate a sizeable stream of p-hydroxybenzoic acid that offers opportunities for the development of value-added products derived from the oil palm industry

Comprehensive genomic profiles of small cell lung cancer

We have sequenced the genomes of 110 small cell lung cancers (SCLC), one of the deadliest human cancers. In nearly all the tumours analysed we found bi-allelic inactivation of TP53 and RB1, sometimes by complex genomic rearrangements. Two tumours with wild-type RB1 had evidence of chromothripsis leading to overexpression of cyclin D1 (encoded by the CCND1 gene), revealing an alternative mechanism of Rb1 deregulation. Thus, loss of the tumour suppressors TP53 and RB1 is obligatory in SCLC. We discovered somatic genomic rearrangements of TP73 that create an oncogenic version of this gene, TP73Dex2/3. In rare cases, SCLC tumours exhibited kinase gene mutations, providing a possible therapeutic opportunity for individual patients. Finally, we observed inactivating mutations in NOTCH family genes in 25% of human SCLC. Accordingly, activation of Notch signalling in a pre-clinical SCLC mouse model strikingly reduced the number of tumours and extended the survival of the mutant mice. Furthermore, neuroendocrine gene expression was abrogated by Notch activity in SCLC cells. This first comprehensive study of somatic genome alterations in SCLC uncovers several key biological processes and identifies candidate therapeutic targets in this highly lethal form of cancer

Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (, , ) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

Asset Class Impacts on the 30-Year Efficient Frontier

We investigate the long-term (30-year) efficient frontier weights in five common asset class indexes by adding classes one-by-one to the stock-bond frontier. Our results show that bonds are the most effective diversifier for stocks, real estate is helpful only at higher risk levels, and international stocks and commodities add little diversification benefits over the longer time horizon. Overall, our results highlight the difficulties using modern portfolio theory to quantify asset class allocations

Evolutionary Computation Applied to Melody Generation

One of the major goals in the field of computer generated music is capturing the intangible human perception which determines whether or not a melody is good. Human perception of music is extremely difficult to encode in a computer because doing so requires modeling human experiences which combine to form an individual\u27s perception. Modeling perception is even more difficult when one considers that every person on earth has a unique vantage point. A solution employed by many researchers in the field is selecting one genre of music and building models from good selections in that style of music. The principal goal of this research is to determine whether a tree based music model can be used in an evolutionary algorithm fitness function to rate computer generated melodies. Well-known examples of church hymnody were employed in the construction of our music model. The results presented show that tree based music models are effective music critics when combined with application specific genetic operators

SNDL-MOEA: Stored Non-Domination Level MOEA

There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving Multi-Objective Optimization (MOO) problems; two of the best are NSGA-II and epsilon-MOEA. However, they lack an archive population sorted into levels of non-domination, making them unsuitable for construction problems where some type of backtracking to earlier intermediate solutions is required. In this paper we introduce our Stored Non-Domination Level (SNDL) MOEA for solving such construction problems. SNDL-MOEA combines some of the best features of NSGA-II and epsilon-MOEA with the ability to store and recall intermediate solutions necessary for construction problems. We present results for applying SNDL-MOEA to the Tight Single Change Covering Design (TSCCD) construction problem, demonstrating its applicability. Furthermore, we show with a detailed performance comparison between SNDL-MOEA, NSGA-II, and epsilon-MOEA on two standard test series that SNDL-MOEA is capable of outperforming NSGA-II and is competitive with epsilon-MOEA