Terzyme: a tool for identification and analysis of the plant terpenome.

BACKGROUND: Terpenoid hydrocarbons represent the largest and most ancient group of phytochemicals, such that the entire chemical library of a plant is often referred to as its 'terpenome'. Besides having numerous pharmacological properties, terpenes contribute to the scent of the rose, the flavors of cinnamon and the yellow of sunflowers. Rapidly increasing -omics datasets provide an unprecedented opportunity for terpenome detection, paving the way for automated web resources dedicated to phytochemical predictions in genomic data. RESULTS: We have developed Terzyme, a predictive algorithm for identification, classification and assignment of broad substrate unit to terpene synthase (TPS) and prenyl transferase (PT) enzymes, known to generate the enormous structural and functional diversity of terpenoid compounds across the plant kingdom. Terzyme uses sequence information, plant taxonomy and machine learning methods for predicting TPSs and PTs in genome and proteome datasets. We demonstrate a significant enrichment of the currently identified terpenome by running Terzyme on more than 40 plants. CONCLUSIONS: Terzyme is the result of a rigorous analysis of evolutionary relationships between hundreds of characterized sequences of TPSs and PTs with known specificities, followed by analysis of genome-wide gene distribution patterns, ontology based clustering and optimization of various parameters for building accurate profile Hidden Markov Models. The predictive webserver and database is freely available at http://nipgr.res.in/terzyme.html and would serve as a useful tool for deciphering the species-specific phytochemical potential of plant genomes

Latest Expansions in Lipid Enhancement of Microalgae for Biodiesel Production: An Update

Research progress on sustainable and renewable biofuel has gained motion over the years, not just due to the rapid reduction of dwindling fossil fuel supplies but also due to environmental and potential energy security issues as well. Intense interest in microalgae (photosynthetic microbes) as a promising feedstock for third-generation biofuels has grown over recent years. Fuels derived from algae are now considered sustainable biofuels that are promising, renewable, and clean. Therefore, selecting the robust species of microalgae with substantial features for quality biodiesel production is the first step in the way of biofuel production. A contemporary investigation is more focused on several strategies and techniques to achieve higher biomass and triglycerides in microalgae. The improvement in lipid enhancement in microalgae species by genetic manipulation approaches, such as metabolic or genetic alteration, and the use of nanotechnology are the most recent ways of improving the production of biomass and lipids. Hence, the current review collects up-to-date approaches for microalgae lipid increase and biodiesel generation. The strategies for high biomass and high lipid yield are discussed. Additionally, various pretreatment procedures that may aid in lipid harvesting efficiency and improve lipid recovery rate are described

Daksha: On Alert for High Energy Transients

We present Daksha, a proposed high energy transients mission for the study of electromagnetic counterparts of gravitational wave sources, and gamma ray bursts. Daksha will comprise of two satellites in low earth equatorial orbits, on opposite sides of earth. Each satellite will carry three types of detectors to cover the entire sky in an energy range from 1 keV to >1 MeV. Any transients detected on-board will be announced publicly within minutes of discovery. All photon data will be downloaded in ground station passes to obtain source positions, spectra, and light curves. In addition, Daksha will address a wide range of science cases including monitoring X-ray pulsars, studies of magnetars, solar flares, searches for fast radio burst counterparts, routine monitoring of bright persistent high energy sources, terrestrial gamma-ray flashes, and probing primordial black hole abundances through lensing. In this paper, we discuss the technical capabilities of Daksha, while the detailed science case is discussed in a separate paper.Comment: 9 pages, 3 figures, 1 table. Additional information about the mission is available at https://www.dakshasat.in

Science with the Daksha High Energy Transients Mission

We present the science case for the proposed Daksha high energy transients mission. Daksha will comprise of two satellites covering the entire sky from 1~keV to $>1$~MeV. The primary objectives of the mission are to discover and characterize electromagnetic counterparts to gravitational wave source; and to study Gamma Ray Bursts (GRBs). Daksha is a versatile all-sky monitor that can address a wide variety of science cases. With its broadband spectral response, high sensitivity, and continuous all-sky coverage, it will discover fainter and rarer sources than any other existing or proposed mission. Daksha can make key strides in GRB research with polarization studies, prompt soft spectroscopy, and fine time-resolved spectral studies. Daksha will provide continuous monitoring of X-ray pulsars. It will detect magnetar outbursts and high energy counterparts to Fast Radio Bursts. Using Earth occultation to measure source fluxes, the two satellites together will obtain daily flux measurements of bright hard X-ray sources including active galactic nuclei, X-ray binaries, and slow transients like Novae. Correlation studies between the two satellites can be used to probe primordial black holes through lensing. Daksha will have a set of detectors continuously pointing towards the Sun, providing excellent hard X-ray monitoring data. Closer to home, the high sensitivity and time resolution of Daksha can be leveraged for the characterization of Terrestrial Gamma-ray Flashes.Comment: 19 pages, 7 figures. Submitted to ApJ. More details about the mission at https://www.dakshasat.in

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Quantification of the plant terpenome: predicted versus actual emission potentials

Plant essential oils are complex mixtures of volatile organic compounds, which play indispensable roles in communication, defense, and adaptive evolution. The complete chemical library produced by a plant is referred to as its terpenome. The potential biological information stored in essential oil composition data can provide an insight into the silent language of plants, as well as roles of terpene emissions in direct and indirect defense, and for playing a crucial role in adaptive evolution. In this work, we have attempted to measure the plant terpenome from a global perspective. One way of measuring the terpenome is to observe and record actual emissions in natural conditions, and this has been in practice for over a century through variously evolving methods of comprehensive GC–MS and HPLC. An alternative method is a knowledge-based prediction of the terpenome, and this method has gained popularity in recent years, with the advent of large-scale genome sequencing technologies. Over the past decade, our laboratory has been involved in compilation and investigation of the plant terpenome using both these methods and this has offered us the opportunity to compare and contrast data from actual and potential emissions, in order to better understand the terpenome and its roles in primary, secondary and adaptive metabolism. We have used emission data in conjunction with genomic data in order to understand how a plant creates the so-called final terpenome, specific to itself, and whether or not plants tap the complete potential for terpene biosynthesis at their disposal according to their genomes. For measuring actual emissions, we have used EssOilDB (the ESSential OIL DataBase), the largest contextual web resource for phytochemicals and for measuring the total plant potential for emissions, we have used TERZYME, an automated algorithm for identification and analysis of genes and proteins involved in isoprenoid biosynthesis. (PDF) Quantification of the plant terpenome: predicted versus actual emission potentials. Available from: https://www.researchgate.net/publication/310763919_Quantification_of_the_plant_terpenome_predicted_versus_actual_emission_potentials [accessed Jul 10 2018]

An Image-based Intelligent System for Data Extraction

Automation is the process of providing goods and services with fewer to no human interventions. The major advantage of automation is reduction in human error. The system proposes to extract data from images that are tilted at different angles and noisy. The system reduces human error by storing the data directly in the database. The proposed system will take image input from the user through a user interface. This interface is a web application. The input image is pre-processed and forwarded to a machine learning model. The machine learning model is trained and tested using a character data set and convolutional neural network. The model will detect the characters and will give the output as recognized text. This output will be automatically stored in the database and shared with the user through the same interface

Cloud computing, emerging computing technology of new age

Cloud computing is seen as an emerging technology highly utilized by different industries and businesses to optimize their processes conservation resources. Its popularity opens various loopholes and barriers, which are useful, especially when improving its overall performance. This study is conducted cloud computing further technological improvements suggested. This technology has been attractive developers and end-users because it provides both parties with an increased revenue opportunity. Entailed for and maintenance of physical hosting has been drastically eliminated from them for the end-user. Also true for the service providers since the increasing number integrating cloud computing to their systems increased revenue. However, the technology is facing challenges with security and privacy, workflow optimization, provisioning, cloud interoperability, data management, need or architecture modifications. These barriers inhibit cloud computing from achieving their maximum potential in terms of Service (QoS) and cost-effectiveness. Nevertheless, metrics monitored and measurements be done cloud computing's overall performance for of both the operation and economic aspects future studies is good & interesting