A framework for considering prior information in network-based approaches to omics data analysis

For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks (PKNs) in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of PKNs is amenable to the data type and the computational task they aim to accomplish. Here we present a five-level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network-based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.     

Impact of warm‐season grass management on feedstock production on marginal farmland in Central Illinois

The production of dedicated energy crops on marginally productive cropland is projected to play an important role in reaching the US Billion Ton goal. This study aimed to evaluate warm‐season grasses for biomass production potential under different harvest timings (summer [H1], after killing frost [H2], or alternating between two [H3]) and nitrogen (N) fertilizer rates (0, 56, and 112 kg N/ha) on a wet marginal land across multiple production years. Six feedstocks were evaluated including Miscanthus x giganteus, two switchgrass cultivars (Panicum virgatum L.), prairie cordgrass (Spartina pectinata Link), and two polycultures including a mixture of big bluestem (Andropogon gerardii Vitman), indiangrass (Sorghastrum nutans), and sideoats grama (Bouteloua curtipendula [Michx.] Torr.), and a mixture of big bluestem and prairie cordgrass. Across four production years, harvest timing and feedstock type played an important role in biomass production. Miscanthus x giganteus produced the greatest biomass (18.7 Mg/ha), followed by the switchgrass cultivar “Liberty” (14.7 Mg/ha). Harvest in H1 tended to increase yield irrespective of feedstock; the exception being M. x giganteus that had significantly lower biomass when harvested in H1 when compared to H2 and H3. The advantage H1 harvest had over H2 for all feedstocks declined over time, suggesting H2 or H3 would provide greater and more sustainable biomass production for the observed feedstocks. The N application rate played an important role mainly for M. x giganteus where 112 kg N/ha yielded more biomass than no N. Other feedstocks occasionally showed a slight, but statistically insignificant increase in biomass yield with increasing N rate. This study showed the potential of producing feedstocks for bioenergy on wet marginal land; however, more research on tissue and soil nutrient dynamics under different N rates and harvest regimes will be important in understanding stand longevity for feedstocks grown under these conditions.     

Study of Design Tunable Optical Sensor and Monochromatic Filter of the One-Dimensional Periodic Structure of TiO2/MgF2 with Defect Layer of Liquid Crystal (LC) Sandwiched with Two Silver Layers

In this paper, we have inspected the optical characteristics of one-dimensional periodic structure (1DPS) of TiO₂ and MgF₂ dielectric materials with defect layer of liquid crystal (LC) sandwiched with two silver layers, i.e., (TiO₂|MgF₂)³|Ag|LC|Ag|(TiO₂/MgF₂)³ using transfer matrix method (TMM). The optical tunable properties of considered periodic structures investigated at different incident angles and temperatures for TE and TM modes. Our study shows that absorption peak of 1DPS varies with incident angle and temperature. The defect layer (Ag-LC-Ag), sandwiched LC within two metallic (Ag) layers, exhibits the surface plasmon waves at the metal LC interfaces. The effect of surface plasmon waves can be better understand through the optical sensing property of such defect periodic structure. The detailed study concludes that such a type of one-dimensional periodic structure (1DPS) may be useful to design a tunable sensor and monochromatic filter.

     

Ethnic differentials in early childhood mortality in Nepal

This paper investigates the association of early childhood mortality (between birth and second birthday) with ethnicity in Nepal, based on data from the 1976 Nepal Fertility Survey, which was part of the World Fertility Survey. The approach is through a series of hazard models, which incorporate ethnicity, year of birth, mother's illiteracy, father's illiteracy, rural-urban residence, region, sex, maternal age, survival of previous birth, previous birth interval, and breast-feeding as covariates. Ethnic differentials in early childhood mortality are not explained by the other socioeconomic and demographic covariates, except for a modest effect of illiteracy, but the remaining covariates explain a great deal of variability in early childhood mortality itself. Analysis using an improved specification of breast-feeding as an age-varying covariate indicates, on average, that breast-feeding, relative to not breast-feeding, reduces age-specific mortality risks during the first 2 years of life by 76%, a very large effect.