Soil Organic Carbon and Mineral Nitrogen Contents in Soils as Affected by Their pH, Texture and Fertilization

Soil organic carbon (SOC) and mineral nitrogen (Nmin), especially nitrates (NO3−) in agroecosystems have attracted much attention over the past few decades due to their crucial roles in soil fertility, crop productivity, environmental quality, and/or climate change mitigation and adaptation. The aim of the study was to evaluate the contents of organic carbon, ammonium, and nitrate in soils under differentiated pH, texture, and fertilization rates. A large-scale environmental study was conducted in Polish arable lands. The spatial distribution of the sampling points reflected agricultural production conditions, variability of soil properties, and representativeness of textures that are characteristic of Poland. Our results indicated that SOC content was significantly affected by the soil pH and texture as well as mineral and organic fertilization. The same factors, except organic amendments, significantly supported mineral nitrogen concentration in the present study. The most important factors controlling SOC in the study were ranked as follows: soil pH > pre-crop N fertilization > crop N fertilization > N applied with manure > soil texture. In the case of N-NH4 and N-NO3, mineral fertilization was the most critical variable. The carbon and nitrogen governance in agroecosystems should consider the ranks of factors controlling their contents

Neuron-specific enolase concentrations for the prediction of poor prognosis of comatose patients after out-of-hospital cardiac arrest: an observational cohort study

Background: Neuron-specific enolase (NSE) is a biomarker for neurological outcomes after cardiac arrest with the most evidence collected thus far; however, recommended prognostic cutoff values are lacking owing to the discrepancies in the published data.Aims: The aim of the study was to establish NSE cutoff values for prognostication in the environment of a cardiac intensive care unit following out-of-hospital cardiac arrest (OHCA).Methods: A consecutive series of 82 patients admitted after OHCA were enrolled. Blood samples for the measurement of NSE levels were collected at admission and after 1 hour, 3, 12, 24, 48, and 72 hours. Neurological outcomes were quantified using the cerebral performance category (CPC) index. Each patient was classified into either the good (CPC ≤2) or poor prognosis (CPC ≥3) group.Results: Median NSE concentrations were higher in the poor prognosis group, and the difference reached statistical significance at 48 and 74 hours (84.4 ng/ml vs 22.9 ng/ml at 48 hours and 152.1 ng/ml vs 18.7 ng/ml at 72 hours; P <0.001, respectively). Moreover, in the poor prognosis group, NSE increased significantly between 24 and 72 hours (P <0.001). NSE cutoffs for the prediction of poor prognosis after OHCA were 39.8 ng/ml, 78.7 ng/ml, and 46.2 ng/ml for 24, 48, and 72 hours, respectively. The areas under the curve were significant at each time point, with the highest values at 48 and 72 hours after admission (0.849 and 0.964, respectively).Conclusions: Elevated NSE concentrations with a rise in levels in serial measurements may be utilized in the prognostication algorithm after OHCA

Neuron-Specific Enolase and S100B: The Earliest Predictors of Poor Outcome in Cardiac Arrest

Background: Proper prognostication is critical in clinical decision-making following out-of-hospital cardiac arrest (OHCA). However, only a few prognostic tools with reliable accuracy are available within the first 24 h after admission. Aim: To test the value of neuron-specific enolase (NSE) and S100B protein measurements at admission as early biomarkers of poor prognosis after OHCA. Methods: We enrolled 82 consecutive patients with OHCA who were unconscious when admitted. NSE and S100B levels were measured at admission, and routine blood tests were performed. Death and poor neurological status at discharge were considered as poor clinical outcomes. We evaluated the optimal cut-off levels for NSE and S100B using logistic regression and receiver operating characteristic (ROC) analyses. Results: High concentrations of both biomarkers at admission were significantly associated with an increased risk of poor clinical outcome (NSE: odds ratio [OR] 1.042 per 1 ng/dL, [1.007–1.079; p = 0.004]; S100B: OR 1.046 per 50 pg/mL [1.004–1.090; p < 0.001]). The dual-marker approach with cut-off values of ≥27.6 ng/mL and ≥696 ng/mL for NSE and S100B, respectively, identified patients with poor clinical outcomes with 100% specificity. Conclusions: The NSE and S100B-based dual-marker approach allowed for early discrimination of patients with poor clinical outcomes with 100% specificity. The proposed algorithm may shorten the time required to establish a poor prognosis and limit the volume of futile procedures performed