Therapeutic drug monitoring of vancomycin in the case of augmented renal clearance: a case report of a paediatric patient

Augmented renal clearance (ARC) is a condition in which renal circulation increases, causing drug levels in the blood to remain at subtherapeutic levels in severe trauma patients. Vancomycin, a hydrophilic anti-Gram-positive drug, has been shown in the literature to have its levels fall below the therapeutic range in the case of ARC. However, vancomycin dosing recommendations in the case of ARC are still lacking. Here, we identify an ARC case measured with urinary creatinine clearance in a severe trauma paediatric patient, causing vancomycin blood trough levels to drop. We could not be able to increase the vancomycin trough levels with intermittent dosing; hence, we administered vancomycin with continuous infusion, and this resulted in vancomycin blood trough levels remaining in the therapeutic range. No adverse effect was seen. Continuous infusion of vancomycin can be safely administered to paediatric patients in these cases

Optimizing Micropropagation and Rooting Protocols for Diverse Lavender Genotypes: A Synergistic Approach Integrating Machine Learning Techniques

This study comprehensively explored the micropropagation and rooting capabilities of four distinct lavender genotypes, utilizing culture media with and without 2 g/L of activated charcoal. A systematic examination of varying concentrations of BAP for micropropagation and IBA for rooting identified an optimal concentration of 1 mg/L for both BAP and IBA, resulting in excellent outcomes. Following robust root development, the acclimatization of plants to external conditions achieved a 100% survival rate across all genotypes. In addition to the conventional techniques employed, integrating machine learning (ML) methodologies holds promise for further enhancing the efficiency of lavender propagation protocols. Using cutting-edge computational tools, including MLP, RBF, XGBoost, and GP algorithms, our findings were rigorously examined and forecast using three performance measures (RMSE, R2, and MAE). Notably, the comparative evaluation of different machine learning models revealed distinct R2 rates for plant characteristics, with MLP, RBF, XGBoost, and GP demonstrating varying degrees of effectiveness. Future studies may leverage ML models, such as XGBoost, MLP, RBF, and GP, to fine-tune specific variables, including culture media composition and growth regulator treatments. The adaptability and ability of ML techniques to analyze complex biological processes can provide valuable insights into optimizing lavender micropropagation on a broader scale. This collaborative approach, combining traditional in vitro techniques with machine learning, validates the success of current micropropagation and rooting protocols and paves the way for continuous improvement. By embracing ML in lavender propagation studies, researchers can contribute to advancing sustainable and efficient plant propagation techniques, thereby fostering the preservation and exploitation of genetic resources for conservation and agriculture

Novel Benzotriazole-β-lactam Derivatives as Antimalarial Agents: Design, Synthesis, Biological Evaluation and Molecular Docking Studies

Many people around the world suffer from malaria, especially in tropical or subtropical regions. While malaria medications have shown success in treating malaria, there is still a problem with resistance to these drugs. Herein, we designed and synthesized some structurally novel benzotriazole-beta-lactams using 2-(1H-benzo[d][1,2,3]triazol-1-yl)acetic acid as a key intermediate. To synthesize the target molecules, the ketene-imine cycloaddition reaction was employed. First, The reaction of 1H-benzo[d][1,2,3]triazole with 2-bromoacetic acid in aqueous sodium hydroxide yielded 2-(1H-benzo[d][1,2,3]triazol-1-yl)acetic acid. Then, the treatment of 2-(1H-benzo[d][1,2,3]triazol-1-yl)acetic acid with tosyl chloride, triethyl amine, and Schiff base provided new beta-lactams in good to moderate yields.The formation of all cycloadducts was confirmed by elemental analysis, FT-IR, NMR and mass spectral data. Moreover, X-ray crystallography was used to determine the relative stereochemistry of 4a compound. The in vitro antimalarial activity test was conducted for each compound against P. falciparum K1. The IC50 values ranged from 5.56 to 25.65 mu M. A cytotoxicity profile of the compounds at 200 mu M final concentration revealed suitable selectivity of the compounds for malaria treatment. Furthermore, the docking study was carried out for each compound into the P. falciparum dihydrofolate reductase enzyme (PfDHFR) binding site to analyze their possible binding orientation in the active site. imag

Effect of economic policy uncertainty on CO2 with the discrimination of renewable and non renewable energy consumption

The link between policy-related economic uncertainty and the environment has a new and developing literature. In this study, the effects of economic policy uncertainty, energy consumption and economic growth on pollution in G7 countries are investigated by using methods of moments quantile regression over the perod of 1995–2018. According to the long run coefficient estimation results, in the model in which the fossil fuel energy consumption variable is used as an energy consumption indicator, economic policy uncertainty has a reducing effect on emissions at all quantile levels. Although this negative effect becomes more pronounced as the quantile level increases, it is statistically insignificant at the 0.90 quantile level. In the model that includes fossil fuel energy consumption, the coefficient of economic policy uncertainty variable is negative in all quantiles and is significant only at the 0.30 and 0.40 quantile levels. In addition, while a U-shaped relationship is detected between economic growth and emissions in these countries, the destroying effect of fossil fuel energy on environmental quality is confirmed in all quantiles. Thus, it should be a priority to support the developments in growth performance with environmental regulations, encourage energy-saving and energy-efficient practices as well as to establish the legal infrastructure

Various wave solutions to the nonlinear fractional Korteweg-de Vries Zakharov-Kuznetsov equation by a new approach to the two-variable expansion scheme

Solving nonlinear differential equations is crucial for the design, optimization, and characterization of engineering systems. However, investigating such equations poses significant challenges and requires the development of new mathematical and computational techniques. In this article, we extend the two-variable (G'/G,1/G) -expansion approach and establish scores of general analytical solutions, consisting of different functions and arbitrary parameters, to the time-fractional Korteweg-de Vries Zakharov-Kuznetsov (KdV-ZK) equation. The KdV-ZK equation provides a powerful model for modulating nonlinear waves in an assortment of physical systems, including plasma physics, atmospheric science, fluid dynamics, soliton theory, and optical fibers. The proposed technique allows extracting several novel solutions to the KdV-ZK equation, which is essential for gaining new insights into physical problems. In addition, the suggested extension shortens the calculation process and enhances computational efficiency. The obtained solitons have potential applications in several scientific and technological fields. The beta fractional derivative and the consistent wave variable are considered to restructure the stated fractional nonlinear equation. This study investigates the merits and demerits of the fractional-order derivative beta on the dynamics of the system through the representation of two-dimensional graphs, which vary according to different values of beta. The enhanced computational efficiency might assist the researchers in exploring a wider range of phenomena, facilitating further extensive investigations, and contributing to overall progress in the fields of science and engineering

Towards a standardized program of transitional care for adolescents with juvenile idiopathic arthritis for Turkey: a national survey study

Background: Juvenile idiopathic arthritis (JIA) is a prevalent childhood chronic arthritis, often persisting into adulthood. Effective transitional care becomes crucial as these patients transition from pediatric to adult healthcare systems. Despite the concept of transitional care being recognized, its real-world implementation remains inadequately explored. This study aims to evaluate the thoughts and practices of healthcare providers regarding transitional care for JIA patients. Methods: A cross-sectional survey was conducted among pediatric and adult rheumatologists in Turkey. Based on the American Academy of Pediatrics’ six core elements of transitional care, the survey included 86 questions. The respondents’ demographic data, attitudes towards transitional care, and practical implementation were assessed. Results: The survey included 48 rheumatologists, with 43.7% having a transition clinic. The main barriers to establishing transition programs were the absence of adult rheumatologists, lack of time, and financial constraints. Only 23.8% had a multidisciplinary team for transition care. Participants agreed on the importance of coordination and cooperation between pediatric and adult healthcare services. The timing of the transition process varied, with no consensus on when to initiate or complete it. Participants advocated for validated questionnaires adapted to local conditions to assess transition readiness. Conclusions: The study sheds light on the challenges and perspectives surrounding transitional care for JIA patients in Turkey. Despite recognized needs and intentions, practical implementation remains limited due to various barriers. Cultural factors and resource constraints affect the transition process. While acknowledging the existing shortcomings, the research serves as a ground for further efforts to improve transitional care and ensure better outcomes for JIA patients transitioning into adulthood