Comprehensive expression profiling analysis to investigate salt and drought responding genes in wild barley (Hordeum spontaneum L.)

Drought and salinity are among the most affecting abiotic stress factors that limit the productivity in economically important plants. Understanding drought and salt tolerance mechanism is pivotal for developing drought and salt tolerant crop cultivars. Here, we monitored the changes in gene expression profiles of leaf and root tissues of two wild barley (Hordeum spontaneum L.) accessions after treatment with salt and drought stresses. We identified a total of 641 DEGs across 24 conditions (2 accessions, 2 stress conditions, 2 tissues and 3 time-points). Interestingly, there was a relatively little overlap between the leaf and the root stress responsive gene expression patterns, suggesting that different stress associated processes might be operating in these tissues during stress adaptation. In hierarchical clustering, the genes with distinct expression patterns were nearly half found in Cluster 1 and Cluster 9 and DEGs found in Cluster 9 were significantly enriched for metabolic processes and organic substance metabolic process. Gene ontology (GO) annotations of biological process of salt and drought analysis identified genes in categories including, catabolic processes, oxidation–reduction and organic substance metabolic process. Molecular function analyses significantly detected transcripts associated with oxidoreductase activity and nucleotide binding. Overall, our results revealed a number of candidate genes and plant processes associated with stress tolerance in wild barley. Determination of responsive genes will shed light on other barley studies aiming to elucidate molecular mechanism of drought or salt tolerance

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

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

KABUL EDİLDİSolving 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 ( ′ ⁄ , 1 ⁄ )-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&nbsp;investigates the merits and demerits of the fractional-order derivative β on the dynamics of the system through the representation of two-dimensional graphs, which vary according to different values of β. 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.</p

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