Integrated farming system for improving agricultural productivity

This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Development of a Full Mission Simulator for Pilot Training of Fighter Aircraft

With aircraft becoming more complex and avionics intensive and flight being almost autonomous based on waypoint navigation, software and displays becoming a significant component of the all glass cockpit of the modern day fighter aircraft, it is imperative that pilots are trained on missions using ground based full mission simulator (FMS) for routine flight as well as advanced missions. A flight simulator is as good as the real system only when it is able to mimic the physical system, both in terms of dynamics and layout so that the pilot gets the complete feel of the environment as encountered during actual sortie. The objective of this research paper is to provide a detailed insight into the various aspects of development of a FMS for pilot training with minimal maintenance operations for long hours of realistic flight training on ground. The approach followed by ADE in developing a FMS using a healthy mix of conventional flight simulation methodologies and novel approaches for various simulator sub-systems to tailor and meet the specific training needs, one presented. The FMS developed by ADE is presently being used by Indian Air Force for flight and mission critical training of squadron pilots

BioBuilder as a database development and functional annotation platform for proteins

BACKGROUND: The explosion in biological information creates the need for databases that are easy to develop, easy to maintain and can be easily manipulated by annotators who are most likely to be biologists. However, deployment of scalable and extensible databases is not an easy task and generally requires substantial expertise in database development. RESULTS: BioBuilder is a Zope-based software tool that was developed to facilitate intuitive creation of protein databases. Protein data can be entered and annotated through web forms along with the flexibility to add customized annotation features to protein entries. A built-in review system permits a global team of scientists to coordinate their annotation efforts. We have already used BioBuilder to develop Human Protein Reference Database , a comprehensive annotated repository of the human proteome. The data can be exported in the extensible markup language (XML) format, which is rapidly becoming as the standard format for data exchange. CONCLUSIONS: As the proteomic data for several organisms begins to accumulate, BioBuilder will prove to be an invaluable platform for functional annotation and development of customizable protein centric databases. BioBuilder is open source and is available under the terms of LGPL

miREE: miRNA recognition elements ensemble

Abstract Background Computational methods for microRNA target prediction are a fundamental step to understand the miRNA role in gene regulation, a key process in molecular biology. In this paper we present miREE, a novel microRNA target prediction tool. miREE is an ensemble of two parts entailing complementary but integrated roles in the prediction. The Ab-Initio module leverages upon a genetic algorithmic approach to generate a set of candidate sites on the basis of their microRNA-mRNA duplex stability properties. Then, a Support Vector Machine (SVM) learning module evaluates the impact of microRNA recognition elements on the target gene. As a result the prediction takes into account information regarding both miRNA-target structural stability and accessibility. Results The proposed method significantly improves the state-of-the-art prediction tools in terms of accuracy with a better balance between specificity and sensitivity, as demonstrated by the experiments conducted on several large datasets across different species. miREE achieves this result by tackling two of the main challenges of current prediction tools: (1) The reduced number of false positives for the Ab-Initio part thanks to the integration of a machine learning module (2) the specificity of the machine learning part, obtained through an innovative technique for rich and representative negative records generation. The validation was conducted on experimental datasets where the miRNA:mRNA interactions had been obtained through (1) direct validation where even the binding site is provided, or through (2) indirect validation, based on gene expression variations obtained from high-throughput experiments where the specific interaction is not validated in detail and consequently the specific binding site is not provided. Conclusions The coupling of two parts: a sensitive Ab-Initio module and a selective machine learning part capable of recognizing the false positives, leads to an improved balance between sensitivity and specificity. miREE obtains a reasonable trade-off between filtering false positives and identifying targets. miREE tool is available online at http://didattica-online.polito.it/eda/miREE/</p

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

The Small Molecule Inhibitor QLT0267 Radiosensitizes Squamous Cell Carcinoma Cells of the Head and Neck

BACKGROUND: The constant increase of cancer cell resistance to radio- and chemotherapy hampers improvement of patient survival and requires novel targeting approaches. Integrin-Linked Kinase (ILK) has been postulated as potent druggable cancer target. On the basis of our previous findings clearly showing that ILK transduces antisurvival signals in cells exposed to ionizing radiation, this study evaluated the impact of the small molecule inhibitor QLT0267, reported as putative ILK inhibitor, on the cellular radiation survival response of human head and neck squamous cell carcinoma cells (hHNSCC). METHODOLOGY/PRINCIPAL FINDINGS: Parental FaDu cells and FaDu cells stably transfected with a constitutively active ILK mutant (FaDu-IH) or empty vectors, UTSCC45 cells, ILK(floxed/floxed(fl/fl)) and ILK(-/-) mouse fibroblasts were used. Cells grew either two-dimensionally (2D) on or three-dimensionally (3D) in laminin-rich extracellular matrix. Cells were treated with QLT0267 alone or in combination with irradiation (X-rays, 0-6 Gy single dose). ILK knockdown was achieved by small interfering RNA transfection. ILK kinase activity, clonogenic survival, number of residual DNA double strand breaks (rDSB; gammaH2AX/53BP1 foci assay), cell cycle distribution, protein expression and phosphorylation (e.g. Akt, p44/42 mitogen-activated protein kinase (MAPK)) were measured. Data on ILK kinase activity and phosphorylation of Akt and p44/42 MAPK revealed a broad inhibitory spectrum of QLT0267 without specificity for ILK. QLT0267 significantly reduced basal cell survival and enhanced the radiosensitivity of FaDu and UTSCC45 cells in a time- and concentration-dependent manner. QLT0267 exerted differential, cell culture model-dependent effects with regard to radiogenic rDSB and accumulation of cells in the G2 cell cycle phase. Relative to corresponding controls, FaDu-IH and ILK(fl/fl) fibroblasts showed enhanced radiosensitivity, which failed to be antagonized by QLT0267. A knockdown of ILK revealed no change in clonogenic survival of the tested cell lines as compared to controls. CONCLUSIONS/SIGNIFICANCE: Our data clearly show that the small molecule inhibitor QLT0267 has potent cytotoxic and radiosensitizing capability in hHNSCC cells. However, QLT0267 is not specific for ILK. Further in vitro and in vivo studies are necessary to clarify the potential of QLT0267 as a targeted therapeutic in the clinic

MTar: a computational microRNA target prediction architecture for human transcriptome

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.</p> <p>Results</p> <p>We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.</p> <p>Conclusion</p> <p>MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.</p

miR-125b Promotes Early Germ Layer Specification through Lin28/let-7d and Preferential Differentiation of Mesoderm in Human Embryonic Stem Cells

Unlike other essential organs, the heart does not undergo tissue repair following injury. Human embryonic stem cells (hESCs) grow indefinitely in culture while maintaining the ability to differentiate into many tissues of the body. As such, they provide a unique opportunity to explore the mechanisms that control human tissue development, as well as treat diseases characterized by tissue loss, including heart failure. MicroRNAs are small, non-coding RNAs that are known to play critical roles in the regulation of gene expression. We profiled the expression of microRNAs during hESC differentiation into myocardial precursors and cardiomyocytes (CMs), and determined clusters of human microRNAs that are specifically regulated during this process. We determined that miR-125b overexpression results in upregulation of the early cardiac transcription factors, GATA4 and Nkx2-5, and accelerated progression of hESC-derived myocardial precursors to an embryonic CM phenotype. We used an in silico approach to identify Lin28 as a target of miR-125b, and validated this interaction using miR-125b knockdown. Anti-miR-125b inhibitor experiments also showed that miR-125b controls the expression of miRNA let-7d, likely through the negative regulatory effects of Lin28 on let-7. We then determined that miR-125b overexpression inhibits the expression of Nanog and Oct4 and promotes the onset of Brachyury expression, suggesting that miR-125b controls the early events of human CM differentiation by inhibiting hESC pluripotency and promoting mesodermal differentiation. These studies identified miR-125b as an important regulator of hESC differentiation in general, and the development of hESC-derived mesoderm and cardiac muscle in particular. Manipulation of miR-125b-mediated pathways may provide a novel approach to directing the differentiation of hESC-derived CMs for cell therapy applications

Identification of a Novel TGFβ/PKA Signaling Transduceome in Mediating Control of Cell Survival and Metastasis in Colon Cancer

Understanding drivers for metastasis in human cancer is important for potential development of therapies to treat metastases. The role of loss of TGFβ tumor suppressor activities in the metastatic process is essentially unknown.Utilizing in vitro and in vivo techniques, we have shown that loss of TGFβ tumor suppressor signaling is necessary to allow the last step of the metastatic process - colonization of the metastatic site. This work demonstrates for the first time that TGFβ receptor reconstitution leads to decreased metastatic colonization. Moreover, we have identified a novel TGFβ/PKA tumor suppressor pathway that acts directly on a known cell survival mechanism that responds to stress with the survivin/XIAP dependent inhibition of caspases that effect apoptosis. The linkage between the TGFβ/PKA transduceome signaling and control of metastasis through induction of cell death was shown by TGFβ receptor restoration with reactivation of the TGFβ/PKA pathway in receptor deficient metastatic colon cancer cells leading to control of aberrant cell survival.This work impacts our understanding of the possible mechanisms that are critical to the growth and maintenance of metastases as well as understanding of a novel TGFβ function as a metastatic suppressor. These results raise the possibility that regeneration of attenuated TGFβ signaling would be an effective target in the treatment of metastasis. Our work indicates the clinical potential for developing anti-metastasis therapy based on inhibition of this very important aberrant cell survival mechanism by the multifaceted TGFβ/PKA transduceome induced pathway. Development of effective treatments for metastatic disease is a pressing need since metastases are the major cause of death in solid tumors

Identification of a Bacteria-produced Benzisoxazole with Antibiotic Activity against Multi-drug Resistant Acinetobacter baumannii

The emergence of multi-drug resistant pathogenic bacteria represents a serious and growing threat to national healthcare systems. Most pressing is an immediate need for the development of novel antibacterial agents to treat Gram-negative multi-drug resistant infections, including the opportunistic, hospital-derived pathogen, Acinetobacter baumannii. Herein we report a naturally occurring 1,2-benzisoxazole with minimum inhibitory concentrations as low as 6.25 μg ml−1 against clinical strains of multi-drug resistant A. baumannii and investigate its possible mechanisms of action. This molecule represents a new chemotype for antibacterial agents against A. baumannii and is easily accessed in two steps via de novo synthesis. In vitro testing of structural analogs suggest that the natural compound may already be optimized for activity against this pathogen. Our results demonstrate that supplementation of 4-hydroxybenzoate in minimal media was able to reverse 1,2-benzisoxazole’s antibacterial effects in A. baumannii. A search of metabolic pathways involving 4-hydroxybenzoate coupled with molecular modeling studies implicates two enzymes, chorismate pyruvate-lyase and 4-hydroxybenzoate octaprenyltransferase, as promising leads for the target of 3,6-dihydroxy-1,2-benzisoxazole