A comparison of background correction methods for two-colour microarrays

MOTIVATION: Microarray data must be background corrected to remove the effects of non-specific binding or spatial heterogeneity across the array, but this practice typically causes other problems such as negative corrected intensities and high variability of low intensity log-ratios. Different estimators of background, and various model-based processing methods, are compared in this study in search of the best option for differential expression analyses of small microarray experiments. RESULTS: Using data where some independent truth in gene expression is known, eight different background correction alternatives are compared, in terms of precision and bias of the resulting gene expression measures, and in terms of their ability to detect differentially expressed genes as judged by two popular algorithms, SAM and limma eBayes. A new background processing method (normexp) is introduced which is based on a convolution model. The model-based correction methods are shown to be markedly superior to the usual practice of subtracting local background estimates. Methods which stabilize the variances of the log-ratios along the intensity range perform the best. The normexp+offset method is found to give the lowest false discovery rate overall, followed by morph and vsn. Like vsn, normexp is applicable to most types of two-colour microarray data. AVAILABILITY: The background correction methods compared in this article are available in the R package limma (Smyth, 2005) from http://www.bioconductor.org. SUPPLEMENTARY INFORMATION: Supplementary data are available from http://bioinf.wehi.edu.au/resources/webReferences.html.     

Empirical array quality weights in the analysis of microarray data

Background  

Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results.     

Elevated carbon dioxide plus chronic warming causes dramatic increases in leaf angle in tomato,which correlates with reduced plant growth

Limited evidence indicates that moderate leaf hyponasty can be induced by high temperatures or unnaturally high CO₂. Here, we report that the combination of warming plus elevated CO₂ (eCO₂) induces severe leaf hyponasty in tomato (Solanum lycopersicum L.). To characterize this phenomenon, tomato plants were grown at two levels of CO₂ (400 vs. 700 ppm) and two temperature regimes (30 vs. 37°C) for 16–18 days. Leaf hyponasty increased dramatically with warming plus eCO₂ but increased only slightly with either factor alone and was slowly reversible upon transfer to control treatments. Increases in leaf angle were not correlated with leaf temperature, leaf water stress, or heat‐related damage to photosynthesis. However, steeper leaf angles were correlated with decreases in leaf area and biomass, which could be explained by decreased light interception and thus in situ photosynthesis, as leaves became more vertical. Petiole hyponasty and leaf‐blade cupping were also observed with warming + eCO₂ in marigold and soybean, respectively, which are compound‐leaved species like tomato, but no such hyponasty was observed in sunflower and okra, which have simple leaves. If severe leaf hyponasty is common under eCO₂ and warming, then this may have serious consequences for food production in the future.     

Terminal osteoblast differentiation, mediated by runx2 and p27KIP1, is disrupted in osteosarcoma

The molecular basis for the inverse relationship between differentiation and tumorigenesis is unknown. The function of runx2, a master regulator of osteoblast differentiation belonging to the runt family of tumor suppressor genes, is consistently disrupted in osteosarcoma cell lines. Ectopic expression of runx2 induces p27KIP1, thereby inhibiting the activity of S-phase cyclin complexes and leading to the dephosphorylation of the retinoblastoma tumor suppressor protein (pRb) and a G1 cell cycle arrest. Runx2 physically interacts with the hypophosphorylated form of pRb, a known coactivator of runx2, thereby completing a feed-forward loop in which progressive cell cycle exit promotes increased expression of the osteoblast phenotype. Loss of p27KIP1 perturbs transient and terminal cell cycle exit in osteoblasts. Consistent with the incompatibility of malignant transformation and permanent cell cycle exit, loss of p27KIP1 expression correlates with dedifferentiation in high-grade human osteosarcomas. Physiologic coupling of osteoblast differentiation to cell cycle withdrawal is mediated through runx2 and p27KIP1, and these processes are disrupted in osteosarcoma.     

Biosorption and Desorption of Lead(II) by Hydrilla verticillata

The potential of nonliving biomass of Hydrilla verticillata to adsorb Pb(II) from an aqueous solution containing very low concentrations of Pb(II) was determined in this study. Effects of shaking time, contact time, biosorbent dosage, pH of the medium, and initial Pb(II) concentration on metal-biosorbent interactions were studied through batch adsorption experiments. Maximum Pb(II) removal was obtained after 2 h of shaking. Adsorption capacity at the equilibrium increased with increasing initial Pb(II) concentration, whereas it decreased with increasing biosorbent dosage. The optimum pH of the biosorption was 4.0. Surface titrations showed that the surface of the biosorbent was positively charged at low pH and negatively charged at pH higher than 3.6. Fourier transform infrared (FT-IR) spectra of the biosorbent confirmed the involvement of hydroxyl and C?O of acylamide functional groups on the biosorbent surface in the Pb(II) binding process. Kinetic and equilibrium data showed that the adsorption process followed the pseudo-second-order kinetic model and both Langmuir and Freundlich isothermal models. The mean adsorption energy showed that the adsorption of Pb(II) was physical in nature. The monolayer adsorption capacity of Pb(II) was 125 mg g^?1. The desorption of Pb(II) from the biosorbent by selected desorbing solutions were HNO₃ > Na₂CO₃ > NaOH > NaNO₃.     

Integrating human behavior and snake ecology with agent-based models to predict snakebite in high risk landscapes

Snakebite causes more than 1.8 million envenoming cases annually and is a major cause of death in the tropics especially for poor farmers. While both social and ecological factors influence the chance encounter between snakes and people, the spatio-temporal processes underlying snakebites remain poorly explored. Previous research has focused on statistical correlates between snakebites and ecological, sociological, or environmental factors, but the human and snake behavioral patterns that drive the spatio-temporal process have not yet been integrated into a single model. Here we use a bottom-up simulation approach using agent-based modelling (ABM) parameterized with datasets from Sri Lanka, a snakebite hotspot, to characterise the mechanisms of snakebite and identify risk factors. Spatio-temporal dynamics of snakebite risks are examined through the model incorporating six snake species and three farmer types (rice, tea, and rubber). We find that snakebites are mainly climatically driven, but the risks also depend on farmer types due to working schedules as well as species present in landscapes. Snake species are differentiated by both distribution and by habitat preference, and farmers are differentiated by working patterns that are climatically driven, and the combination of these factors leads to unique encounter rates for different landcover types as well as locations. Validation using epidemiological studies demonstrated that our model can explain observed patterns, including temporal patterns of snakebite incidence, and relative contribution of bites by each snake species. Our predictions can be used to generate hypotheses and inform future studies and decision makers. Additionally, our model is transferable to other locations with high snakebite burden as well.     

Evaluating spatiotemporal dynamics of snakebite in Sri Lanka: Monthly incidence mapping from a national representative survey sample

BackgroundSnakebite incidence shows both spatial and temporal variation. However, no study has evaluated spatiotemporal patterns of snakebites across a country or region in detail. We used a nationally representative population sample to evaluate spatiotemporal patterns of snakebite in Sri Lanka.MethodologyWe conducted a community-based cross-sectional survey representing all nine provinces of Sri Lanka. We interviewed 165 665 people (0.8% of the national population), and snakebite events reported by the respondents were recorded. Sri Lanka is an agricultural country; its central, southern and western parts receive rain mainly from Southwest monsoon (May to September) and northern and eastern parts receive rain mainly from Northeast monsoon (November to February). We developed spatiotemporal models using multivariate Poisson process modelling to explain monthly snakebite and envenoming incidences in the country. These models were developed at the provincial level to explain local spatiotemporal patterns.Principal findingsSnakebites and envenomings showed clear spatiotemporal patterns. Snakebite hotspots were found in North-Central, North-West, South-West and Eastern Sri Lanka. They exhibited biannual seasonal patterns except in South-Western inlands, which showed triannual seasonality. Envenoming hotspots were confined to North-Central, East and South-West parts of the country. Hotspots in North-Central regions showed triannual seasonal patterns and South-West regions had annual patterns. Hotspots remained persistent throughout the year in Eastern regions. The overall monthly snakebite and envenoming incidences in Sri Lanka were 39 (95%CI: 38–40) and 19 (95%CI: 13–30) per 100 000, respectively, translating into 110 000 (95%CI: 107 500–112 500) snakebites and 45 000 (95%CI: 32 000–73 000) envenomings in a calendar year.Conclusions/significanceThis study provides information on community-based monthly incidence of snakebites and envenomings over the whole country. Thus, it provides useful insights into healthcare decision-making, such as, prioritizing locations to establish specialized centres for snakebite management and allocating resources based on risk assessments which take into account both location and season.     

A mechanistic model of snakebite as a zoonosis: Envenoming incidence is driven by snake ecology,socioeconomics and its impacts on snakes

Snakebite is the only WHO-listed, not infectious neglected tropical disease (NTD), although its eco-epidemiology is similar to that of zoonotic infections: envenoming occurs after a vertebrate host contacts a human. Accordingly, snakebite risk represents the interaction between snake and human factors, but their quantification has been limited by data availability. Models of infectious disease transmission are instrumental for the mitigation of NTDs and zoonoses. Here, we represented snake-human interactions with disease transmission models to approximate geospatial estimates of snakebite incidence in Sri Lanka, a global hotspot. Snakebites and envenomings are described by the product of snake and human abundance, mirroring directly transmitted zoonoses. We found that human-snake contact rates vary according to land cover (surrogate of occupation and socioeconomic status), the impacts of humans and climate on snake abundance, and by snake species. Our findings show that modelling snakebite as zoonosis provides a mechanistic eco-epidemiological basis to understand snakebites, and the possible implications of global environmental and demographic change for the burden of snakebite.     

Elevated CO2 plus chronic warming reduce nitrogen uptake and levels or activities of nitrogen‐uptake and ‐assimilatory proteins in tomato roots

Atmospheric CO₂ enrichment is expected to often benefit plant growth, despite causing global warming and nitrogen (N) dilution in plants. Most plants primarily procure N as inorganic nitrate (NO₃^?) or ammonium (NH₄⁺), using membrane‐localized transport proteins in roots, which are key targets for improving N use. Although interactive effects of elevated CO₂, chronic warming and N form on N relations are expected, these have not been studied. In this study, tomato (Solanum lycopersicum) plants were grown at two levels of CO₂ (400 or 700 ppm) and two temperature regimes (30 or 37°C), with NO₃^? or NH₄⁺ as the N source. Elevated CO₂ plus chronic warming severely inhibited plant growth, regardless of N form, while individually they had smaller effects on growth. Although %N in roots was similar among all treatments, elevated CO₂ plus warming decreased (1) N‐uptake rate by roots, (2) total protein concentration in roots, indicating an inhibition of N assimilation and (3) shoot %N, indicating a potential inhibition of N translocation from roots to shoots. Under elevated CO₂ plus warming, reduced NO₃^?‐uptake rate per g root was correlated with a decrease in the concentration of NO₃^?‐uptake proteins per g root, reduced NH₄⁺ uptake was correlated with decreased activity of NH₄⁺‐uptake proteins and reduced N assimilation was correlated with decreased concentration of N‐assimilatory proteins. These results indicate that elevated CO₂ and chronic warming can act synergistically to decrease plant N uptake and assimilation; hence, future global warming may decrease both plant growth and food quality (%N).