Molasses growth medium for production of Rhizobium sp. based biofertilizer

378-383Rhizobium forms symbiotic relationship with leguminous crops and is recommended for use in various legumes. Rhizobium sp. fix atmospheric nitrogen and make it available to legumes through formation of root nodules. Rhizobium biofertilizer production is carried out mostly by using semi-synthetic microbiological medium which forms major expense of this activity. Successful commercial production of biofertilizer can be enhanced by use of natural substrates, as molasses, cheese whey, corn steep liquor, for bacterial biomass production. The present work centers around the use of sugarcane molasses as a source of fermentable sugars. It was supplemented with various organic/inorganic nitrogen sources, chemical compounds to increase biomass yield and to increase the shelf life of the product thus prepared. Compliance to Fertilizer Control Order specifications was demonstrated in wet lab analysis

Molasses growth medium for production of Rhizobium sp. based biofertilizer

Rhizobium forms symbiotic relationship with leguminous crops and is recommended for use in various legumes. Rhizobium sp. fix atmospheric nitrogen and make it available to legumes through formation of root nodules. Rhizobium biofertilizer production is carried out mostly by using semi-synthetic microbiological medium which forms major expense of this activity. Successful commercial production of biofertilizer can be enhanced by use of natural substrates, as molasses, cheese whey, corn steep liquor, for bacterial biomass production. The present work centers around the use of sugarcane molasses as a source of fermentable sugars. It was supplemented with various organic/inorganic nitrogen sources, chemical compounds to increase biomass yield and to increase the shelf life of the product thus prepared. Compliance to Fertilizer Control Order specifications was demonstrated in wet lab analysis

ProKinO: An Ontology for Integrative Analysis of Protein Kinases in Cancer

Protein kinases are a large and diverse family of enzymes that are genomically altered in many human cancers. Targeted cancer genome sequencing efforts have unveiled the mutational profiles of protein kinase genes from many different cancer types. While mutational data on protein kinases is currently catalogued in various databases, integration of mutation data with other forms of data on protein kinases such as sequence, structure, function and pathway is necessary to identify and characterize key cancer causing mutations. Integrative analysis of protein kinase data, however, is a challenge because of the disparate nature of protein kinase data sources and data formats., where the mutations are spread over 82 distinct kinases. We also provide examples of how ontology-based data analysis can be used to generate testable hypotheses regarding cancer mutations.

ICAR: endoscopic skull‐base surgery

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Germline selection shapes human mitochondrial DNA diversity.

Approximately 2.4% of the human mitochondrial DNA (mtDNA) genome exhibits common homoplasmic genetic variation. We analyzed 12,975 whole-genome sequences to show that 45.1% of individuals from 1526 mother-offspring pairs harbor a mixed population of mtDNA (heteroplasmy), but the propensity for maternal transmission differs across the mitochondrial genome. Over one generation, we observed selection both for and against variants in specific genomic regions; known variants were more likely to be transmitted than previously unknown variants. However, new heteroplasmies were more likely to match the nuclear genetic ancestry as opposed to the ancestry of the mitochondrial genome on which the mutations occurred, validating our findings in 40,325 individuals. Thus, human mtDNA at the population level is shaped by selective forces within the female germ line under nuclear genetic control, which ensures consistency between the two independent genetic lineages.NIHR, Wellcome Trust, MRC, Genomics Englan

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Improving nitrogen use efficiency using precision nitrogen management in wheat (Triticum aestivum L.)

Background: Excessive application of nitrogen (N) fertilizer in cereal crops not only decreases the N use efficiency but also accelerates greenhouse gas (GHG) emission. Aim: To improve N use efficiency in wheat (Triticum aestivum L.) using precision N management and coating seeds with arbuscular mycorrhizal fungi (AMF). Methods: Field experiment laid out in split-plot design was conducted to study the role of AMF consortia (four species) seed coating and different precision N management strategies in rationalizing fertilizer N use. Results: The AMF seed coating improved mycorrhization but did not improve N assimilation, grain yield, root weight, N uptake, chlorophyll value, normalized difference vegetative index, and physiological efficiency (PEN) of applied N fertilizer. The benefits of AMF seed coating in improving N assimilation were not visible even in no-N treatment. Precision N management using leaf color chart (LCC), chlorophyll meter (SPAD), and GreenSeeker optical sensor (GS) sustained wheat grain yield equivalent to the soil-test based N fertilizer recommendation with the average savings of 20% N fertilizer. Precision N management strategies improved mean recovery efficiency (REN) and partial factor productivity (PFPN) of applied N fertilizer, respectively by 26.0% and 26.4% over the soil-test based N management. Spectral properties measured with LCC, SPAD and GS showed good correlation (R2 > 0.71) with grain yield, depicting great potential of optical sensing tools in predicting grain yield and inferring need-based fertilizer N topdressings decisions in wheat. Conclusions: Precision N management provides a potential solution to improve N nutrition in wheat while reducing nitrous oxide (N2O) and total GHG emissions by 23.2 and 23.6%, respectively, in comparison to soil-test based N application