Isolation and characterization of altered root growth behavior and salinity tolerant mutants in rice

Generation, screening and isolating mutants for any developmental and adaptive traits plays a major role in plant functional genomics research. Identification and exploitation of mutants possessing contrasting root growth behavior and salinity tolerance in rice will help us to identify key genes controlling these traits and in turn will be useful for manipulating abiotic stress tolerance through tilling and genetic engineering in rice. In this study, we have screened about 1500 mutants (M2 generation) generated by treating an upland drought tolerant genotype Nagina 22 with Ethyl Methane Sulfonate (EMS), for their root growth behavior and salinity tolerance under hydroponic conditions. Six independent mutant lines possessing significantly shorter roots and three mutant lines exhibiting greater degree of salinity tolerance than the wild type plants were identified. The identified mutant lines were advanced to M5 generation to allow the mutants to reach homozygosity, and the fixed mutants were confirmed for their phenotype. One mutant namely N22-C-241-5-6 was found to possess significantly shorter roots than wild type N22, and it was also noticed that the mutant was devoid of root cap. Among the three salinity tolerant mutant lines identified, N22-C-334-3 was found to possess a greater degree of tolerance upto 250 mM Nacl stress at germination stage. These identified mutant lines can be used for further physiological, biochemical and molecular biology experiments to identify candidate gene(s) controlling root growth behavior and salinity tolerance in rice.Keywords: Rice, mutation, EMS, altered rood growth and salinity tolerant mutantAfrican Journal of Biotechnology Vol. 12(40), pp. 5852-585

Identification of Host Genes Involved in Geminivirus Infection Using a Reverse Genetics Approach

Geminiviruses, like all viruses, rely on the host cell machinery to establish a successful infection, but the identity and function of these required host proteins remain largely unknown. Tomato yellow leaf curl Sardinia virus (TYLCSV), a monopartite geminivirus, is one of the causal agents of the devastating Tomato yellow leaf curl disease (TYLCD). The transgenic 2IRGFP N. benthamiana plants, used in combination with Virus Induced Gene Silencing (VIGS), entail an important potential as a tool in reverse genetics studies to identify host factors involved in TYLCSV infection. Using these transgenic plants, we have made an accurate description of the evolution of TYLCSV replication in the host in both space and time. Moreover, we have determined that TYLCSV and Tobacco rattle virus (TRV) do not dramatically influence each other when co-infected in N. benthamiana, what makes the use of TRV-induced gene silencing in combination with TYLCSV for reverse genetic studies feasible. Finally, we have tested the effect of silencing candidate host genes on TYLCSV infection, identifying eighteen genes potentially involved in this process, fifteen of which had never been implicated in geminiviral infections before. Seven of the analyzed genes have a potential anti-viral effect, whereas the expression of the other eleven is required for a full infection. Interestingly, almost half of the genes altering TYLCSV infection play a role in postranslational modifications. Therefore, our results provide new insights into the molecular mechanisms underlying geminivirus infections, and at the same time reveal the 2IRGFP/VIGS system as a powerful tool for functional reverse genetics studies

Diabetes mortality and trends before 25 years of age: an analysis of the Global Burden of Disease Study 2019

Background Diabetes, particularly type 1 diabetes, at younger ages can be a largely preventable cause of death with the correct health care and services. We aimed to evaluate diabetes mortality and trends at ages younger than 25 years globally using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We used estimates of GBD 2019 to calculate international diabetes mortality at ages younger than 25 years in 1990 and 2019. Data sources for causes of death were obtained from vital registration systems, verbal autopsies, and other surveillance systems for 1990–2019. We estimated death rates for each location using the GBD Cause of Death Ensemble model. We analysed the association of age-standardised death rates per 100 000 population with the Socio-demographic Index (SDI) and a measure of universal health coverage (UHC) and described the variability within SDI quintiles. We present estimates with their 95% uncertainty intervals. Findings In 2019, 16 300 (95% uncertainty interval 14 200 to 18 900) global deaths due to diabetes (type 1 and 2 combined) occurred in people younger than 25 years and 73·7% (68·3 to 77·4) were classified as due to type 1 diabetes. The age-standardised death rate was 0·50 (0·44 to 0·58) per 100 000 population, and 15 900 (97·5%) of these deaths occurred in low to high-middle SDI countries. The rate was 0·13 (0·12 to 0·14) per 100 000 population in the high SDI quintile, 0·60 (0·51 to 0·70) per 100 000 population in the low-middle SDI quintile, and 0·71 (0·60 to 0·86) per 100 000 population in the low SDI quintile. Within SDI quintiles, we observed large variability in rates across countries, in part explained by the extent of UHC (r2=0·62). From 1990 to 2019, age-standardised death rates decreased globally by 17·0% (−28·4 to −2·9) for all diabetes, and by 21·0% (–33·0 to −5·9) when considering only type 1 diabetes. However, the low SDI quintile had the lowest decline for both all diabetes (−13·6% [–28·4 to 3·4]) and for type 1 diabetes (−13·6% [–29·3 to 8·9]). Interpretation Decreasing diabetes mortality at ages younger than 25 years remains an important challenge, especially in low and low-middle SDI countries. Inadequate diagnosis and treatment of diabetes is likely to be major contributor to these early deaths, highlighting the urgent need to provide better access to insulin and basic diabetes education and care. This mortality metric, derived from readily available and frequently updated GBD data, can help to monitor preventable diabetes-related deaths over time globally, aligned with the UN's Sustainable Development Targets, and serve as an indicator of the adequacy of basic diabetes care for type 1 and type 2 diabetes across nations.publishedVersio

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

PROSPECTIVE OBSERVATIONAL STUDY ON ANTIBIOTIC-PRESCRIBING PATTERN AND MEDICATION ERRORS IN SURGICAL PROPHYLAXIS IN A SPECIALTY HOSPITAL

Objective: The objective was to study the antibiotic-prescribing patterns, identify the medication errors and impact of surgical antimicrobial prophylaxis (SAP) in preventing surgical site infection (SSI), and to understand the prescribers’ adherence to surgical prophylaxis guidelines. Methods: The study was conducted for a period of 6 months in all surgical departments of a specialty hospital. Data were collected from inpatients records. Australian guideline for SAP was used to assess the appropriateness in prescribing pattern. The sample size was calculated using Raosoft sample size calculator. Results: A prospective observational study was carried out among 178 patients. Of which, 100 were male and 78 were female. Four hundred and thirty-three antimicrobials were prescribed as pre- and post-operative surgical prophylaxis, among that 87% prescribed by brand name and 13% by generic. Seventy-one percent received single antimicrobial agent preoperatively, of which 99.5% prescribed as parenteral and 0.5% as oral formulation. Most often prescribed antibiotic was cefoperazone (28%) of cephalosporin group. Only 5.6% of cases had compliance with SAP guidelines. In this study, 11 patients affected with SSI due to inappropriate antibiotic selection and non-adherence to prophylactic antibiotic guidelines. Conclusion: The present study revealed that there is a poor compliance to SAP guidelines in terms of inappropriateness in antibiotic drug selection, dose, duration, and omission of drugs. Inappropriateness and non-compliance are mainly due to unavailability of clinical pharmacist to assist the physicians in the selection and administration of correct choice of prophylactic drug and unavailability of proper national or local guidelines. Hence, there is dire need to make local SAP guidelines to improve SAP-prescribing pattern