Gender Research Methodologies for Agricultural Research in India: Summary and Recommendations of a Workshop 27-28 May 1996

ICRISAT is concerned about the implications of technological changes in agriculture for the welfare of women. A 2-day informal workshop on methodologies for gender research was held on 27 and 28 May, 1996, at ICRISAT Asia Center. The primary objectives of the workshop were to refine the Institute's gender research methodologies and to initiate the development of a strategy for mainstreaming gender analysis in technology development at ICRISAT. Specifically, the workshop was intended to identify gender-related differences in preferences for varieties and technologies that may constrain technology adoption; identify a set of key indicators to measure the intrahousehold distribution of welfare gains from the adoption of given technologies; and identify simple, accurate, and quick methods for data collection. The workshop was attended by participants from research and training institutions and nongovernmental organizations in addition to ICRISAT scientists. This document contains a synthesis of discussions that took place, and the summaries of presentations made by participants. Specific recommendations on developing a strategy for mainstreaming gender are included in the synthesis

Comparative study of scoring systems in ICU and emergency department in predicting mortality of critically ill

Background: Scoring systems can be used to define critically ill patients, estimate their prognosis, help in clinical decision making, and guide the allocation of resources and to estimate the quality of care.  It remains unclear whether the additional data needed to compute ICU scores improves mortality prediction for critically ill patients compared to the simpler ED scores.Methods: We have done a prospective observational study of consecutively admitted 400 critically ill patients to ICU directly from Emergency Department in Dr PSIMS and RF over a period of 2 years. Clinical and laboratory data conforming to the modified early warning score (MEWS), rapid emergency medicine score (REMS), acute physiology and chronic health evaluation (APACHE II), and simplified acute physiology score (SAPS II) were recorded for all patients. A comparison was made between ED scoring systems MEWS, REMS and ICU scoring systems APACHE II, SAPSII. The outcome was recorded in two categories: survived and non-survived with a primary end point of 30-day mortality. Discrimination was evaluated using receiver operating characteristic (ROC) curves.Results: The ICU scores outperformed the ED scores with more area under curve values. The predicted mortality percentage of ICU based scoring systems is high compared to emergency scores (predicted mortality % of SAPS II-63%, APACHE II-33.3%, MEWS-18.5%, REMS-14.8%).Conclusions: ICU scores showed more predictive accuracy than ED scores in prognosticating the outcomes in critically ill patients. This difference is seemed more due to complexity of ICU scores

Introduction to Khovanov Homologies. I. Unreduced Jones superpolynomial

An elementary introduction to Khovanov construction of superpolynomials. Despite its technical complexity, this method remains the only source of a definition of superpolynomials from the first principles and therefore is important for development and testing of alternative approaches. In this first part of the review series we concentrate on the most transparent and unambiguous part of the story: the unreduced Jones superpolynomials in the fundamental representation and consider the 2-strand braids as the main example. Already for the 5_1 knot the unreduced superpolynomial contains more items than the ordinary Jones.Comment: 33 page

Torus knots and mirror symmetry

We propose a spectral curve describing torus knots and links in the B-model. In particular, the application of the topological recursion to this curve generates all their colored HOMFLY invariants. The curve is obtained by exploiting the full Sl(2, Z) symmetry of the spectral curve of the resolved conifold, and should be regarded as the mirror of the topological D-brane associated to torus knots in the large N Gopakumar-Vafa duality. Moreover, we derive the curve as the large N limit of the matrix model computing torus knot invariants.Comment: 30 pages + appendix, 3 figure

Evolutionary Sequence Modeling for Discovery of Peptide Hormones

There are currently a large number of “orphan” G-protein-coupled receptors (GPCRs) whose endogenous ligands (peptide hormones) are unknown. Identification of these peptide hormones is a difficult and important problem. We describe a computational framework that models spatial structure along the genomic sequence simultaneously with the temporal evolutionary path structure across species and show how such models can be used to discover new functional molecules, in particular peptide hormones, via cross-genomic sequence comparisons. The computational framework incorporates a priori high-level knowledge of structural and evolutionary constraints into a hierarchical grammar of evolutionary probabilistic models. This computational method was used for identifying novel prohormones and the processed peptide sites by producing sequence alignments across many species at the functional-element level. Experimental results with an initial implementation of the algorithm were used to identify potential prohormones by comparing the human and non-human proteins in the Swiss-Prot database of known annotated proteins. In this proof of concept, we identified 45 out of 54 prohormones with only 44 false positives. The comparison of known and hypothetical human and mouse proteins resulted in the identification of a novel putative prohormone with at least four potential neuropeptides. Finally, in order to validate the computational methodology, we present the basic molecular biological characterization of the novel putative peptide hormone, including its identification and regional localization in the brain. This species comparison, HMM-based computational approach succeeded in identifying a previously undiscovered neuropeptide from whole genome protein sequences. This novel putative peptide hormone is found in discreet brain regions as well as other organs. The success of this approach will have a great impact on our understanding of GPCRs and associated pathways and help to identify new targets for drug development

S-duality as a beta-deformed Fourier transform

An attempt is made to formulate Gaiotto's S-duality relations in an explicit quantitative form. Formally the problem is that of evaluation of the Racah coefficients for the Virasoro algebra, and we approach it with the help of the matrix model representation of the AGT-related conformal blocks and Nekrasov functions. In the Seiberg-Witten limit, this S-duality reduces to the Legendre transformation. In the simplest case, its lifting to the level of Nekrasov functions is just the Fourier transform, while corrections are related to the beta-deformation. We calculate them with the help of the matrix model approach and observe that they vanish for beta=1. Explicit evaluation of the same corrections from the U_q(sl(2)) infinite-dimensional representation formulas due to B.Ponsot and J.Teshner remains an open problem.Comment: 21 page

Scalable rule-based modelling of allosteric proteins and biochemical networks

Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology

Dandy Walker Syndrome: A Case Report

Dandy walker syndrome is a rare congenital malformation that involves the cerebellum and fourth ventricle. It is characterized by agenesis or hypoplasia of cerebellar vermis, cystic dilatation of the fourth ventricle and enlargement of the posterior fossa. Dandy Walker Malformation is a condition which can be effectively diagnosed by imaging modalities, especially in antenatal period with a proper antenatal checkup and sonograph