Characterization of Acetyl-CoA: Lyso-PAF Acetyltransferase of Human Mesangial Cells

Platelet activating factor (PAF) is a potent inflammatory mediator produced by various renal cells and it is implicated in renal pathology. The aim of this study is the characterization of remodeling lyso-PAF acetyltransferase, which is activated under inflammatory conditions, in human mesangial cell. Total membranes of mesangial cells were isolated and enzymatic activity and kinetic parameters were determined by trichloroacetic acid precipitation method. The effect of BSA, divalent cations, EDTA, and various chemicals on the activity of lyso-PAF acetyltransferase was also studied. Various detergents were also tested for the solubilization of the enzyme and only glycerol did not affect its activity. Partial purification of solubilized enzyme preparations of human kidney tissue and mesangial cells was performed on anion exchange column chromatography and native-PAGE electrophoresis and two active fractions were detected

Close correlation of cortisol with pain intensity and Aldrete score in immediate post anesthesia period

Background: Few studies have been made on postoperative pain, the patient’s stress and Aldrete scale score at the awakening period. In this study we investigated the correlation of the serum cortisol concentration between both pain scale score and Aldrete scale score at the early postoperative period. It is obvious that an Aldrete scale score less than 9, at the awakening, is possible to prolong the surgical patient’s staying in Post anesthesia care unit (PACU). Determining of this relation is important in clinical setting.Methods: Twenty five (25) - ASA physical status I, II - patients scheduled, to undergo a medium severity surgery, with gen­eral anesthesia were enrolled in this study. The patients received as pre–medication 100mg hydroxyzine (P.O) and 150 mg ranitidine (P.O). Anesthesia was induced with: ondasetron 4mg IV, fentanil 0.2mg IV, propofol 2mg.kg-1 IV, cis-atracurium 1mg.kg-1IV, midazolam 3mg IV. Anesthesia was maintained with sevoflurane, air, oxygen and remi­fentanil -as analgesic factor-. As postoperative analgesia morphine 0.1mg.kg-1IV, 30 min before the end of surgery was used. Blood samples were collected at the end of the surgery as well as after the awakening of the patients, and the concentration of serum cortisol was determined.Results: In the samples of the 25 patients, the mean (± SD) concentration of cortisol was 22.13 μg/dl (± 12.44). The patients Aldrete Scale mean score was 8.52 (± 1.15). The range of Aldrete score was 4 (6-10). Also, the mean pain score of patients was 2.88 (± 1.64), with range of pain score: 6 (0-6). Nine of the enrolled patients reached a score of 9 at the Aldrete scale and five reached a score of 10 at the Aldrete scale, at the awakening. Patients with Aldrete scale score less than 9, at the awakening, prolonged their staying in PACU from 60 to 165 minutes.Conclusion: There is clearly a positive correlation between the concentration of serum cortisol and Aldrete scale score, at the awakening stage of the surgical patient, but without any statistical significance.There is a statistically significant positive correlation between the concentration of serum cortisol and the pain scale score

Characterization of the De Novo Biosynthetic Enzyme of Platelet Activating Factor, DDT-Insensitive Cholinephosphotransferase, of Human Mesangial Cells

Platelet activating factor (PAF), a potent inflammatory mediator, is implicated in several proinflammatory/inflammatory diseases such as glomerulonephritis, glomerulosclerosis, atherosclerosis, cancer, allergy, and diabetes. PAF can be produced by several renal cells under appropriate stimuli and it is thought to be implicated in renal diseases. The aim of this study is the characterization of DTT-insensitive cholinephosphotransferase (PAF-CPT) of human mesangial cell (HMC), the main regulatory enzyme of PAF de novo biosynthetic pathway. Microsomal fractions of mesangial cells were isolated and enzymatic activity and kinetic parameters were determined by TLC and in vitro biological test in rabbit washed platelets. The effect of bovine serum albumin (BSA), dithiothreitol (DTT), divalent cations (Mg2+ and Ca2+), EDTA, and various chemicals on the activity of PAF-CPT of HMC was also studied. Moreover, preliminary in vitro tests have been performed with several anti-inflammatory factors such as drugs (simvastatin, IFNa, rupatadine, tinzaparin, and salicylic acid) and bioactive compounds of Mediterranean diet (resveratrol and lipids of olive oil, olive pomace, sea bass “Dicentrarchus labrax,” and gilthead sea bream “Sparus aurata”). The results indicated that the above compounds can influence PAF-CPT activity of HMC

Factors influencing the decision to start renal replacement therapy: results of a survey among European nephrologists

Background: Little is known about the criteria nephrologists use in the decision of when to start renal replacement therapy (RRT) in early referred adult patients. We evaluated opinions of European nephrologists on the decision for when to start RRT. Study Design: European web-based survey. Predictors: Patient presentations described as uncomplicated patients, patients with unfavorable clinical and unfavorable social conditions, or patients with specific clinical, social, and logistical factors. Setting & Participants: Nephrologists from 11 European countries. Outcomes & Measurements: We studied opinions of European nephrologists about the influence of clinical, social, and logistical factors on decision making regarding when to start RRT, reflecting practices in place in 2009. Questions included target levels of kidney function at the start of RRT and factors accelerating or postponing RRT initiation. Using linear regression, we studied determinants of target estimated glomerular filtration rate (eGFR) at the start of RRT. Results: We received 433 completed surveys. The median target eGFR selected to start RRT in uncomplicated patients was 10.0 (25th-75th percentile, 8.0-10.0) mL/min/1.73 m(2). Level of excretory kidney function was considered the most important factor in decision making regarding uncomplicated patients (selected by 54% of respondents); in patients with unfavorable clinical versus social conditions, this factor was selected by 24% versus 32%, respectively. Acute clinical factors such as life-threatening hyperkalemia refractory to medical therapy (100%) and uremic pericarditis (98%) elicited a preference for an immediate start, whereas patient preference (69%) and vascular dementia (66%) postponed the start. Higher target eGFRs were reported by respondents from high-versus low-RRT-incidence countries (10.4 [95% CI, 9.9-10.9] vs 9.1 mL/min/1.73 m(2)) and from for-profit versus not-for-profit centers (10.1 [95% CI, 9.5-10.7] vs 9.5 mL/min/1.73 m(2)). Limitations: We were unable to calculate the exact response rate and examined opinions rather than practice for 433 nephrologists. Conclusions: Only for uncomplicated patients did half the nephrologists consider excretory kidney function as the most important factor. Future studies should assess the weight of each factor affecting decision making. Am J Kidney Dis. 60(6): 940-948. (C) 2012 by the National Kidney Foundation, In

Olive Plantation Mapping on a Sub-Tree Scale with Object-Based Image Analysis of Multispectral UAV Data; Operational Potential in Tree Stress Monitoring

The objective of this study was to develop a methodology for mapping olive plantations on a sub-tree scale. For this purpose, multispectral imagery of an almost 60-ha plantation in Greece was acquired with an Unmanned Aerial Vehicle. Objects smaller than the tree crown were produced with image segmentation. Three image features were indicated as optimum for discriminating olive trees from other objects in the plantation, in a rule-based classification algorithm. After limited manual corrections, the final output was validated by an overall accuracy of 93%. The overall processing chain can be considered as suitable for operational olive tree monitoring for potential stresses

Optimization of fertilization recommendation in Greek rice fields using precision agriculture

The objective of this research was to evaluate the correlation between rice yield and soil properties for improving fertilizer recommendations. This was achieved through the application of a new precision agriculture methodology on a large experimental setup of about 115 ha in Chalastra, Greece. The methodology uses multispectral satellite images acquired during the previous cropping season for the delineation of preliminary zones, inside of which representative soil samples are extracted and analyzed and fertilizer recommendations are formulated per zone. The spatial distribution of yield performances was recorded with a yield mapper mounted on the harvester. As a result of the zone-based applications in the 2017 cropping season, the grower realized 15% increase in yield compared to the mean of the previous decade’s yields, while the fertilizer inputs were reduced by 20%. Moreover, it was showed that the nitrogen added with the basal fertilization and soil magnesium were the major contributors of yield differences, whereas phosphorus and potassium needs were covered with the applied fertilization

Representation Learning with a Variational Autoencoder for Predicting Nitrogen Requirement in Rice

The scope of this research was to provide rice growers with optimal N-rate recommendations through precision agriculture applications. To achieve this goal, a prediction rice yield model was constructed, based on soil data, remote sensing data (optical and radar), climatic data, and farming practices. The dataset was collected from a rice crop surface of 89.2 ha cultivated continuously for a 5-year period and was analyzed with machine learning (ML) systems. A variational autoencoder (VAE) for reconstructing the input data of the prediction model was applied, resulting in MAE of 0.6 tn/ha, with an average yield for the study fields and period measured at 9.6 tn/ha. VAE learns the original input data representation and transforms them in a latent feature space, so that the anomalies and the discrepancies of the data are reduced. The reconstructed data by VAE provided a more sophisticated and detailed ML model, improving our knowledge about the various correlations between soil, N management parameters, and yield. Both optical and radar imagery and the climatic data were found to be of high importance for the model, as indicated by the application of XAI (explainable artificial intelligence) techniques. The new model was applied in the 2022 rice cultivation in the study fields, resulting in an average yield increase of 4.32% compared to the 5 previous years of experimentation

An Integrated Approach to Assessing the Soil Quality and Nutritional Status of Large and Long-Term Cultivated Rice Agro-Ecosystems

The aim of this study is to develop an integrated approach to soil quality and fertility assessment in high-yielding rice agro-ecosystems threatened due to overexploitation of soil resources by intensive agriculture. The proposed approach is implemented considering representative pilot fields allocated throughout a study area based on the assumption that soils of similar general properties present a similar nutritional status due to common long-term management practices. The analysis includes (a) object-based image analysis for land zonation, (b) hot-spot analysis for sampling scheme evaluation, (c) setting of critical thresholds in soil parameters for detecting nutrient deficiencies and soil quality problems, and (d) Redundancy Analysis, TITAN analysis, and multiple regression for identifying individual or combined effects of general soil properties (e.g., organic matter, soil texture, pH, salinity) or non-soil parameters (e.g., topographic parameters) on soil nutrients. The approach was applied using as a case study the large rice agro-ecosystem of Thessaloniki plain in Greece considering some site specificities (e.g., high rice yields, calcareous soils) when setting the critical thresholds in soil parameters. The results showed that (a) 62.5% of the pilot fields’ coverage has a simultaneous deficiency in Zn, Mn, and B, (b) organic matter (OM) was the most significant descriptor of nutrients’ variance, and its cold spots (clustered regions of low OM values) showed important overlapping with the cold spots of K, Mg, Zn, Mn, Cu, and B, (c) a higher rate of availability increase in P, K, Mg, Mn, Zn, Fe, Cu, and B was observed when the OM ranged between 2 and 3%, and (d) the multiple regression models that assess K and P concentrations based on general soil properties showed an adequate performance, allowing their use for general assessment of their soil concentrations in the fields of the whole agro-ecosystem