Isolation and biochemical characterization of Plant Growth Promoting (PGP) bacteria colonizing the rhizosphere of Tef crop during the seedling stage

The use of novel PGPR as bio inoculant is an alternative sustainable agricultural practice to improve soil health, grain quality, increase crop productivity, and conserve biodiversity. The aim of this study is to isolate, and characterized PGP bacteria colonizing tef rhizosphere during the seedling stage. For this concern, 426 samples of tef (Eragrostis tef) rhizosphere soils and roots were collected from East Shewa zone, Oromia regional state. 200 morphologically different bacterial pure colonies were isolated and screened for their PGP traits and biocontrol properties. Among these 40.5% isolates were positive for phosphate solubilization. 36% were positive for IAA production, 4.5% were positive for ammonia production, 19 % were positive for (EXPS), 15.5% were positive for protease production, 12.5% were positive for HCN productions, 9.5 % were positive for cellulase production, 4% were positive for amylase production, 3.5% were positive for chitinase production. For abiotic stress tolerance test, all of the isolates were grown well at 20oc and 30oc and neutral pH, 27% isolates were grown well at 4oc, 25.5% grew at 40oc, 25.5% were grown well on pH-9 and pH-11, 23.5% were tolerated pH-5, 3.5% grew at 50oc and 60oc, 13.5% were grown well on 5% NaCl (w/v), 3.5% were grown well on 10 and 15% NaCl (w/v), which indicated these isolates can survive in some extreme conditions. Totally 15 bacterial species having PGP traits, biocontrol properties, and abiotic stress tolerance ability were identified using the Biolog bacterial identification system. Among these, the majority of the identified PGPR have utilized carbohydrate, carboxylic acid, and amino acid, which are the main components of plant root exudates. The above results indicated that thus PGPR can be used as biofertilizers as well as biocontrol agents to replace agrochemicals to improve crop productivity. Hence, these species can be further formulated and used for greenhouse and field applications

Physician agreement on the diagnosis of sepsis in the intensive care unit: estimation of concordance and analysis of underlying factors in a multicenter cohort

Abstract Background Differentiating sepsis from the systemic inflammatory response syndrome (SIRS) in critical care patients is challenging, especially before serious organ damage is evident, and with variable clinical presentations of patients and variable training and experience of attending physicians. Our objective was to describe and quantify physician agreement in diagnosing SIRS or sepsis in critical care patients as a function of available clinical information, infection site, and hospital setting. Methods We conducted a post hoc analysis of previously collected data from a prospective, observational trial (N = 249 subjects) in intensive care units at seven US hospitals, in which physicians at different stages of patient care were asked to make diagnostic calls of either SIRS, sepsis, or indeterminate, based on varying amounts of available clinical information (clinicaltrials.gov identifier: NCT02127502). The overall percent agreement and the free-marginal, inter-observer agreement statistic kappa (κ free) were used to quantify agreement between evaluators (attending physicians, site investigators, external expert panelists). Logistic regression and machine learning techniques were used to search for significant variables that could explain heterogeneity within the indeterminate and SIRS patient subgroups. Results Free-marginal kappa decreased between the initial impression of the attending physician and (1) the initial impression of the site investigator (κ free 0.68), (2) the consensus discharge diagnosis of the site investigators (κ free 0.62), and (3) the consensus diagnosis of the external expert panel (κ free 0.58). In contrast, agreement was greatest between the consensus discharge impression of site investigators and the consensus diagnosis of the external expert panel (κ free 0.79). When stratified by infection site, κ free for agreement between initial and later diagnoses had a mean value + 0.24 (range − 0.29 to + 0.39) for respiratory infections, compared to + 0.70 (range + 0.42 to + 0.88) for abdominal + urinary + other infections. Bioinformatics analysis failed to clearly resolve the indeterminate diagnoses and also failed to explain why 60% of SIRS patients were treated with antibiotics. Conclusions Considerable uncertainty surrounds the differential clinical diagnosis of sepsis vs. SIRS, especially before organ damage has become highly evident, and for patients presenting with respiratory clinical signs. Our findings underscore the need to provide physicians with accurate, timely diagnostic information in evaluating possible sepsis

Validation of a host response assay, SeptiCyte LAB, for discriminating sepsis from systemic inflammatory response syndrome in the ICU

Rationale: A molecular test to distinguish between sepsis and systemic inflammation of noninfectious etiology could potentially have clinical utility. Objectives: This study evaluated the diagnostic performance of a molecular host response assay (SeptiCyte LAB) designed to distinguish between sepsis and noninfectious systemic inflammation in critically ill adults. Methods: The study employed a prospective, observational, noninterventional design and recruited a heterogeneous cohort of adult critical care patients from seven sites in the United States (n = 249). An additional group of 198 patients, recruited in the largeMARS (Molecular Diagnosis and Risk Stratification of Sepsis) consortium trial in the Netherlands (www.clinicaltrials.gov identifier NCT01905033), was also tested and analyzed, making a grand total of 447 patients in our study. The performance of SeptiCyte LAB was compared with retrospective physician diagnosis by a panel of three experts. Measurements and Main Results: In receiver operating characteristic curve analysis, SeptiCyte LAB had an estimated area under the curve of 0.82-0.89 for discriminating sepsis from noninfectious systemic inflammation. The relative likelihood of sepsis versus noninfectious systemic inflammation was found to increase with increasing test score (range, 0-10). In a forward logistic regression analysis, the diagnostic performance of the assay was improved only marginally when used in combination with other clinical and laboratory variables, including procalcitonin. The performance of the assay was not significantly affected by demographic variables, including age, sex, or race/ethnicity. Conclusions: SeptiCyte LAB appears to be a promising diagnostic tool to complement physician assessment of infection likelihood in critically ill adult patients with systemic inflammation