The impact of different fertiliser management options and cultivars on nitrogen use efficiency and yield for rice cropping in the Indo-Gangetic Plain: two seasons of methane, nitrous oxide and ammonia emissions

This study presents detailed crop and gas flux data from two years of rice production at the experimental farm of the ICAR-Indian Agricultural Research Institute, New Delhi, India. In comparing 4 nitrogen (N) fertiliser regimes across 4 rice cultivars (CRD 310, IR-64, MTU 1010, P-44), we have added to growing evidence of the environmental costs of rice production in the region. The study shows that rice cultivar can impact yields of both grain, and total biomass produced in given circumstances, with the CRD 310 cultivar showing consistently high nitrogen use efficiency (NUE) for total biomass compared with other tested varieties, but not necessarily with the highest grain yield, which was P-44 in this experiment. While NUE of the rice did vary depending on experimental treatments (ranging from 41% to 73%), 73%), this did not translate directly into the reduction of emissions of ammonia (NH3) and nitrous oxide (N2O). Emissions were relatively similar across the different rice cultivars regardless of NUE. Conversely, agronomic practices that reduced total N losses were associated with higher yield. In terms of fertiliser application, the outstanding impact was of the very high methane (CH4) emissions as a result of incorporating farmyard manure (FYM) into rice paddies, which dominated the overall effect on global warming potential. While the use of nitrification and urease inhibiting substances decreased N2O emissions overall, NH3 emissions were relatively unaffected (or slightly higher). Overall, the greatest reduction in greenhouse gas (GHG) emissions came from reducing irrigation water added to the fields, resulting in higher N2O, but significantly less CH4 emissions, reducing net GHG emission compared with continuous flooding. Overall, genetic differences generated more variation in yield and NUE than agronomic management (excluding controls), whereas agronomy generated larger differences than genetics concerning gaseous losses. This study suggests that a mixed approach needs to be applied when attempting to reduce pollution and global warming potential from rice production and potential pollution swapping and synergies need to be considered. Finding the right balance of rice cultivar, irrigation technique and fertiliser type could significantly reduce emissions, while getting it wrong can result in considerably poorer yields and higher pollution

DMA, a Bisbenzimidazole, Offers Radioprotection by Promoting NFκB Transactivation through NIK/IKK in Human Glioma Cells

BACKGROUND: Ionizing radiation (IR) exposure often occurs for human beings through occupational, medical, environmental, accidental and/or other sources. Thus, the role of radioprotector is essential to overcome the complex series of overlapping responses to radiation induced DNA damage. METHODS AND RESULTS: Treatment of human glioma U87 cells with DMA (5- {4-methylpiperazin-1-yl}-2-[2'-(3, 4-dimethoxyphenyl)-5'-benzimidazolyl] in the presence or absence of radiation uncovered differential regulation of an array of genes and proteins using microarray and 2D PAGE techniques. Pathway construction followed by relative quantitation of gene expression of the identified proteins and their interacting partners led to the identification of MAP3K14 (NFκB inducing kinase, NIK) as the candidate gene affected in response to DMA. Subsequently, over expression and knock down of NIK suggested that DMA affects NFκB inducing kinase mediated phosphorylation of IKKα and IKKβ both alone and in the presence of ionizing radiation (IR). The TNF-α induced NFκB dependent luciferase reporter assay demonstrated 1.65, 2.26 and 3.62 fold increase in NFκB activation at 10, 25 and 50 µM DMA concentrations respectively, compared to control cells. This activation was further increased by 5.8 fold in drug + radiation (50 µM +8.5 Gy) treated cells in comparison to control. We observed 51% radioprotection in control siRNA transfected cells that attenuated to 15% in siRNA NIK treated U87 cells, irradiated in presence of DMA at 24 h. CONCLUSIONS: Our studies show that NIK/IKK mediated NFκB activation is more intensified in cells over expressing NIK and treated with DMA, alone or in combination with ionizing radiation, indicating that DMA promotes NIK mediated NFκB signaling. This subsequently leads to the radioprotective effect exhibited by DMA

Nuclear S100A7 Is Associated with Poor Prognosis in Head and Neck Cancer

Tissue proteomic analysis of head and neck squamous cell carcinoma (HNSCC) and normal oral mucosa using iTRAQ (isobaric tag for relative and absolute quantitation) labeling and liquid chromatography-mass spectrometry, led to the identification of a panel of biomarkers including S100A7. In the multi-step process of head and neck tumorigenesis, the presence of dysplastic areas in the epithelium is proposed to be associated with a likely progression to cancer; however there are no established biomarkers to predict their potential of malignant transformation. This study aimed to determine the clinical significance of S100A7 overexpression in HNSCC.Immunohistochemical analysis of S100A7 expression in HNSCC (100 cases), oral lesions (166 cases) and 100 histologically normal tissues was carried out and correlated with clinicopathological parameters and disease prognosis over 7 years for HNSCC patients. Overexpression of S100A7 protein was significant in oral lesions (squamous cell hyperplasia/dysplasia) and sustained in HNSCC in comparison with oral normal mucosa (p(trend)<0.001). Significant increase in nuclear S100A7 was observed in HNSCC as compared to dysplastic lesions (p = 0.005) and associated with well differentiated squamous cell carcinoma (p = 0.031). Notably, nuclear accumulation of S100A7 also emerged as an independent predictor of reduced disease free survival (p = 0.006, Hazard ratio (HR = 7.6), 95% CI = 1.3-5.1) in multivariate analysis underscoring its relevance as a poor prognosticator of HNSCC patients.Our study demonstrated nuclear accumulation of S100A7 may serve as predictor of poor prognosis in HNSCC patients. Further, increased nuclear accumulation of S100A7 in HNSCC as compared to dysplastic lesions warrants a large-scale longitudinal study of patients with dysplasia to evaluate its potential as a determinant of increased risk of transformation of oral premalignant lesions

Overexpression of Prothymosin Alpha Predicts Poor Disease Outcome in Head and Neck Cancer

In our recent study, tissue proteomic analysis of oral pre-malignant lesions (OPLs) and normal oral mucosa led to the identification of a panel of biomarkers, including prothymosin alpha (PTMA), to distinguish OPLs from histologically normal oral tissues. This study aimed to determine the clinical significance of PTMA overexpression in oral squamous cell hyperplasia, dysplasia and head and neck squamous cell carcinoma (HNSCC).Immunohistochemistry of PTMA protein was performed in HNSCCs (n = 100), squamous cell hyperplasia (n = 116), dysplasia (n = 50) and histologically normal oral tissues (n = 100). Statistical analysis was carried out to determine the association of PTMA overexpression with clinicopathological parameters and disease prognosis over 7 years for HNSCC patients.<0.001). Chi-square analysis showed significant association of nuclear PTMA with advanced tumor stages (III+IV). Kaplan Meier survival analysis indicated reduced disease free survival (DFS) in HNSCC patients (p<0.001; median survival 11 months). Notably, Cox-multivariate analysis revealed nuclear PTMA as an independent predictor of poor prognosis of HNSCC patients (p<0.001, Hazard's ratio, HR = 5.2, 95% CI = 2.3–11.8) in comparison with the histological grade, T-stage, nodal status and tumor stage.Nuclear PTMA may serve as prognostic marker in HNSCC to determine the subset of patients that are likely to show recurrence of the disease

Non-methane volatile organic compounds emitted from domestic fuels in Delhi: Emission factors and total city-wide emissions

In controlled laboratory conditions, 62 samples of domestic fuels collected from 56 grids of Delhi were burnt to quantify the emissions of 23 non-methane volatile organic compounds (NMVOCs), i.e., alkanes (11), alkenes (6), alkynes (1) and aromatic compounds (5). The domestic fuels used for residential activities were comprised of 20 unique types of fuel woods, 3 species of crop residue, dung cakes and coal. These fuels are primarily used for cooking and water/space heating during winters. The current study reports the total emission budget of NMVOCs from domestic burning over Delhi. Furthermore, this study also compares the differences in EFs of NMVOCs which are calculated for different burning cycles and sample collection methods. The EFs of NMVOCs calculated from the samples collected during the flaming stage using canisters were analysed for 23 NMVOCs and then compared with same species emitted from complete burning cycle. In addition to this, 10 consumption and emission hotspot grids were also identified in Delhi; based on the ground survey and laboratory simulated results. The total annual usage of domestic fuels for the year 2019 was found to be 0.415 Mt/yr (million tonnes) in Delhi. 12.01 Gg/yr of annual NMVOC emissions was calculated from domestic fuel burning in which the emissions from dung cake and fuel wood dominated with 6.6 Gg/yr and 5.4 Gg/yr, respectively. The EFs of NMVOCs calculated using canister and online collection method differ significantly from each other. The flaming stage presented enhanced emissions compared to the complete burning cycle by ~7 times which suggests that the method of data analysis and the period of sample collection play a pivotal role in the preparation of an emission inventory and estimating the budget

The IASLC Lung Cancer Staging Project: A Renewed Call to Participation

Over the past two decades, the International Association for the Study of Lung Cancer (IASLC) Staging Project has been a steady source of evidence-based recommendations for the TNM classification for lung cancer published by the Union for International Cancer Control and the American Joint Committee on Cancer. The Staging and Prognostic Factors Committee of the IASLC is now issuing a call for participation in the next phase of the project, which is designed to inform the ninth edition of the TNM classification for lung cancer. Following the case recruitment model for the eighth edition database, volunteer site participants are asked to submit data on patients whose lung cancer was diagnosed between January 1, 2011, and December 31, 2019, to the project by means of a secure, electronic data capture system provided by Cancer Research And Biostatistics in Seattle, Washington. Alternatively, participants may transfer existing data sets. The continued success of the IASLC Staging Project in achieving its objectives will depend on the extent of international participation, the degree to which cases are entered directly into the electronic data capture system, and how closely externally submitted cases conform to the data elements for the project

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe