National and international agricultural research and rural poverty: the case of rice research in India and China

The study attempts to measure the total benefits from rice varietal improvement research in China and India using variety adoption and performance data over the last two decades. It then uses genetic or pedigree information to partition the total benefits between these two countries and IRRI. Finally, the study uses reported elasticity of poverty reduction with respect to agricultural output growth to assess the effects of national and international research on poverty reduction in rural India and China. The results indicate that rice varietal improvement research has contributed tremendously to increase in rice production, accounting for 14-23 percent of total production value over the last two decades in both countries. Rice research has also helped reduce large numbers of rural poor. IRRI played a crucial role in these successes. In 1999, for every $1 million invested at IRRI, more than 800 and 15,000 rural poor were lifted above the poverty line in China and India, respectively. These poverty-reduction effects were even larger in the earlier years." Authors' AbstractRice Asia., Rice Research., Rice Varieties., Rice Yields., Poverty alleviation., genetically modified organisms,

Prophylaxis of heterotopic ossification – an updated review

Heterotopic ossification (HO) is defined as the process by which trabecular bone forms outside of the skeletal structure, occupying space in soft tissue where it does not normally exist. The current popular prophylactic treatment modalities include non-steroidal anti-inflammatory drugs (NSAIDs) and radiation therapy, although the literature remains inconclusive as to which is superior. Additionally, both treatments can lead to adverse effects to the patient. Recently there have been several studies attempting to identify new aspects of the etiology of heterotopic bone formation and introduce new prophylactic modalities with increased efficacy and fewer side effects. For this review, we selectively retrieved articles from Medline published from 1958–2008 on the prophylaxis of HO with the aim of assisting readers in quickly grasping the current status of research and clinical aspects of HO prophylaxis

New ternary blend strategy based on a vertically self-assembled passivation layer enabling efficient and photostable inverted organic solar cells

Herein, a new ternary strategy to fabricate efficient and photostable inverted organic photovoltaics (OPVs) is introduced by combining a bulk heterojunction (BHJ) blend and a fullerene self-assembled monolayer (C60 -SAM). Time-of-flight secondary-ion mass spectrometry - analysis reveals that the ternary blend is vertically phase separated with the C60 -SAM at the bottom and the BHJ on top. The average power conversion efficiency - of OPVs based on the ternary system is improved from 14.9% to 15.6% by C60 -SAM addition, mostly due to increased current density (Jsc ) and fill factor -. It is found that the C60 -SAM encourages the BHJ to make more face-on molecular orientation because grazing incidence wide-angle X-ray scattering - data show an increased face-on/edge-on orientation ratio in the ternary blend. Light-intensity dependent Jsc data and charge carrier lifetime analysis indicate suppressed bimolecular recombination and a longer charge carrier lifetime in the ternary system, resulting in the enhancement of OPV performance. Moreover, it is demonstrated that device photostability in the ternary blend is enhanced due to the vertically self-assembled C60 -SAM that successfully passivates the ZnO surface and protects BHJ layer from the UV-induced photocatalytic reactions of the ZnO. These results suggest a new perspective to improve both performance and photostability of OPVs using a facial ternary method

The Direct Synthesis of H ₂ O ₂ Using TS-1 Supported Catalysts

In this study we show that using gold palladium nanoparticles supported on a commercial titanium silicate (TS‐1) prepared using a wet co‐impregnation method it is possible to produce hydrogen peroxide from molecular H2 and O2 via the direct synthesis reaction. The effect of Au: Pd ratio and calcination temperature is evaluated as well as the role of platinum addition to the AuPd supported catalysts. The effect of platinum addition to gold‐palladium nanoparticles is observed to result in a significant improvement in catalytic activity and selectivity to hydrogen peroxide with detailed characterisation indicating this is a result of selectively tuning the ratio of palladium oxidation states

Black carbon-induced snow albedo reduction over the Tibetan Plateau: uncertainties from snow grain shape and aerosol–snow mixing state based on an updated SNICAR model

We implement a set of new parameterizations into the widely used Snow, Ice, and Aerosol Radiative (SNICAR) model to account for effects of snow grain shape (spherical vs. nonspherical) and black carbon (BC)–snow mixing state (external vs. internal). We find that nonspherical snow grains lead to higher pure albedo but weaker BC-induced albedo reductions relative to spherical snow grains, while BC–snow internal mixing significantly enhances albedo reductions relative to external mixing. The combination of snow nonsphericity and internal mixing suggests an important interactive effect on BC-induced albedo reduction. Comparisons with observations of clean and BC-contaminated snow albedo show that model simulations accounting for both snow nonsphericity and BC–snow internal mixing perform better than those using the common assumption of spherical snow grains and external mixing. We further apply the updated SNICAR model with comprehensive in situ measurements of BC concentrations in the Tibetan Plateau snowpack to quantify the present-day (2000–2015) BC-induced snow albedo effects from a regional and seasonal perspective. The BC concentrations show distinct and substantial sub-regional and seasonal variations, with higher values in the non-monsoon season and low altitudes. As a result, the BC-induced regional mean snow albedo reductions and surface radiative effects vary by up to an order of magnitude across different sub-regions and seasons, with values of 0.7–30.7 and 1.4–58.4&thinsp;W&thinsp;m−2 for BC externally mixed with fresh and aged snow spheres, respectively. The BC radiative effects are further complicated by uncertainty in snow grain shape and BC–snow mixing state. BC–snow internal mixing enhances the mean albedo effects over the plateau by 30–60&thinsp;% relative to external mixing, while nonspherical snow grains decrease the mean albedo effects by up to 31&thinsp;% relative to spherical grains. Based on this study, extensive measurements and improved model characterization of snow grain shape and aerosol–snow mixing state are urgently needed in order to precisely evaluate BC–snow albedo effects.</p

Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions

Previous and present "academic" research aiming at atomic scale understanding is mainly concerned with the study of individual molecular processes possibly underlying materials science applications. Appealing properties of an individual process are then frequently discussed in terms of their direct importance for the envisioned material function, or reciprocally, the function of materials is somehow believed to be understandable by essentially one prominent elementary process only. What is often overlooked in this approach is that in macroscopic systems of technological relevance typically a large number of distinct atomic scale processes take place. Which of them are decisive for observable system properties and functions is then not only determined by the detailed individual properties of each process alone, but in many, if not most cases also the interplay of all processes, i.e. how they act together, plays a crucial role. For a "predictive materials science modeling with microscopic understanding", a description that treats the statistical interplay of a large number of microscopically well-described elementary processes must therefore be applied. Modern electronic structure theory methods such as DFT have become a standard tool for the accurate description of individual molecular processes. Here, we discuss the present status of emerging methodologies which attempt to achieve a (hopefully seamless) match of DFT with concepts from statistical mechanics or thermodynamics, in order to also address the interplay of the various molecular processes. The new quality of, and the novel insights that can be gained by, such techniques is illustrated by how they allow the description of crystal surfaces in contact with realistic gas-phase environments.Comment: 24 pages including 17 figures, related publications can be found at http://www.fhi-berlin.mpg.de/th/paper.htm

Quantifying risk factors and potential geographic extent of African swine fever across the world

African swine fever (ASF) has spread to many countries in Africa, Europe and Asia in the past decades. However, the potential geographic extent of ASF infection is unknown. Here we combined a modeling framework with the assembled contemporary records of ASF cases and multiple covariates to predict the risk distribution of ASF at a global scale. Local spatial variations in ASF risk derived from domestic pigs is influenced strongly by livestock factors, while the risk of having ASF in wild boars is mainly associated with natural habitat covariates. The risk maps show that ASF is to be ubiquitous in many areas, with a higher risk in areas in the northern hemisphere. Nearly half of the world’s domestic pigs (1.388 billion) are in the high-risk zones. Our results provide a better understanding of the potential distribution beyond the current geographical scope of the disease

Identification of novel candidate target genes, including EPHB3, MASP1 and SST at 3q26.2–q29 in squamous cell carcinoma of the lung

<p>Abstract</p> <p>Background</p> <p>The underlying genetic alterations for squamous cell carcinoma (SCC) and adenocarcinoma (AC) carcinogenesis are largely unknown.</p> <p>Methods</p> <p>High-resolution array- CGH was performed to identify the differences in the patterns of genomic imbalances between SCC and AC of non-small cell lung cancer (NSCLC).</p> <p>Results</p> <p>On a genome-wide profile, SCCs showed higher frequency of gains than ACs (<it>p </it>= 0.067). More specifically, statistically significant differences were observed across the histologic subtypes for gains at 2q14.2, 3q26.2–q29, 12p13.2–p13.33, and 19p13.3, as well as losses at 3p26.2–p26.3, 16p13.11, and 17p11.2 in SCC, and gains at 7q22.1 and losses at 15q22.2–q25.2 occurred in AC (<it>P </it>< 0.05). The most striking difference between SCC and AC was gains at the 3q26.2–q29, occurring in 86% (19/22) of SCCs, but in only 21% (3/14) of ACs. Many significant genes at the 3q26.2–q29 regions previously linked to a specific histology, such as EVI1,<it>MDS1, PIK3CA </it>and <it>TP73L</it>, were observed in SCC (<it>P </it>< 0.05). In addition, we identified the following possible target genes (> 30% of patients) at 3q26.2–q29: <it>LOC389174 </it>(3q26.2),<it>KCNMB3 </it>(3q26.32),<it>EPHB3 </it>(3q27.1), <it>MASP1 </it>and <it>SST </it>(3q27.3), <it>LPP </it>and <it>FGF12 </it>(3q28), and <it>OPA1</it>,<it>KIAA022</it>,<it>LOC220729</it>, <it>LOC440996</it>,<it>LOC440997</it>, and <it>LOC440998 </it>(3q29), all of which were significantly targeted in SCC (<it>P </it>< 0.05). Among these same genes, high-level amplifications were detected for the gene, <it>EPHB3</it>, at 3q27.1, and <it>MASP1 </it>and <it>SST</it>, at 3q27.3 (18, 18, and 14%, respectively). Quantitative real time PCR demonstrated array CGH detected potential candidate genes that were over expressed in SCCs.</p> <p>Conclusion</p> <p>Using whole-genome array CGH, we have successfully identified significant differences and unique information of chromosomal signatures prevalent between the SCC and AC subtypes of NSCLC. The newly identified candidate target genes may prove to be highly attractive candidate molecular markers for the classification of NSCLC histologic subtypes, and could potentially contribute to the pathogenesis of the squamous cell carcinoma of the lung.</p

Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance

Using GeneReg to construct time delay gene regulatory networks

<p>Abstract</p> <p>Background</p> <p>Understanding gene expression and regulation is essential for understanding biological mechanisms. Because gene expression profiling has been widely used in basic biological research, especially in transcription regulation studies, we have developed GeneReg, an easy-to-use R package, to construct gene regulatory networks from time course gene expression profiling data; More importantly, this package can provide information about time delays between expression change in a regulator and that of its target genes.</p> <p>Findings</p> <p>The R package GeneReg is based on time delay linear regression, which can generate a model of the expression levels of regulators at a given time point against the expression levels of their target genes at a later time point. There are two parameters in the model, time delay and regulation coefficient. Time delay is the time lag during which expression change of the regulator is transmitted to change in target gene expression. Regulation coefficient expresses the regulation effect: a positive regulation coefficient indicates activation and negative indicates repression. GeneReg was implemented on a real Saccharomyces cerevisiae cell cycle dataset; more than thirty percent of the modeled regulations, based entirely on gene expression files, were found to be consistent with previous discoveries from known databases.</p> <p>Conclusions</p> <p>GeneReg is an easy-to-use, simple, fast R package for gene regulatory network construction from short time course gene expression data. It may be applied to study time-related biological processes such as cell cycle, cell differentiation, or causal inference.</p