Pharmakokinetik von Mycophenolatmofetil nach primärer orthotoper Herztransplantation – Entwicklung von Kurzalgorithmen zur therapeutischen Arzneimittelüberwachung–

Pharmacokinetics of mycophenolate mofetil (MMF) show large interindividual variability. Concentration-controlled dosing of MMF based on routine therapeutic drug monitoring, which requires area under the concentration-time curve (mycophenolic acid [MPA]-AUC0-12h) determinations, is uncommon. Dose adjustments are based on predose concentrations (C0h) or side effects. The aim of this study was to compare C0h with postdose concentrations (C0.5h-C12h) and to develop practical methods for estimation of MPA-AUCs on the basis of a limited sampling strategy (LSS) in heart transplant recipients under MMF and tacrolimus maintenance immunosuppression. Full MPA-AUC0-12h profiles were generated by high-performance liquid chromatography in 28 patients. Statistical analysis for MPA-AUC0-12h was performed by a case resampling bootstrap method. Bland and Altmann analysis was performed to test agreement between "predicted AUC" and "measured AUC." C1h provided the highest coefficient of determination (r2 = 0.57) among the concentrations determined during the 12-hour interval, which were correlated with AUC. All other MPA levels were better surrogates of the MPA-AUC0-12h when compared with C0h (r2 = 0.14). The best estimation of MPA-AUC0-12h was achieved with four sampling points with the algorithm AUC = 1.25*C1h + 5.29*C4h + 2.90*C8h + 3.61*C10h (r2 = 0.95). Since LSS with four time points appeared unpractical, the authors prefer models with three or two points. To optimize practicability, LSS with sample points within the first 2 hours were evaluated resulting in the algorithms: AUC = 1.09*C0.5h + 1.19*C1h + 3.60*C2h (r2 = 0.84) and AUC = 1.65*C0.5h + 4.74*C2h (r2 = 0.75) for three and two sample points, respectively. The results provide strong evidence for the use of either LSS or the use of time points other than C0h for therapeutic drug monitoring of MMF. Using the algorithms for the estimation of MPA-AUC0-12h based on LSS within the first 2 hours after MMF dosing may help to optimize treatment with MMF by individualization of dosing

(2Z)-N-(4-Meth­oxy­phen­yl)-2-(4-meth­oxy­phenyl­imino)-2H-1,4-benzoxazin-3-amine

In the crystal structure of the title compound, C22H19N3O3, inter­molecular C—H⋯O hydrogen bonds link the mol­ecules into a zigzag chain parallel to the face diagonal of the ac plane. The meth­oxy phenyl rings make a dihdral angle of 32.38 (7)° and form dihedral angles of 0.66 (8) and 24.17 (7)° with the fused benzooxazine ring system

STRESS DISTRIBUTION IN A CIRCULAR CYLINDRICAL SHELL WITH A CIRCULAR CUTOUT

Abstract not availabl

The Effect of Spiritual Marketing and Entrepreneurial Orientation on Determining Sustainable Competitive Advantage: A Case Study of Soliko Kale Company

In today's world, local, national and global competition forces companies to perform correct and competitive business methods. These methods are related to spiritual marketing and entrepreneurship. These two factors will enable the spiritual marketing of the company to address the needs, desires, and expectations of people based on ethical principles, and the entrepreneurial orientation of entrepreneurship will also create something new and different from the competitors as a result of these two methods, which will lead to the company's activity to increase. Finally, with the above explanations, the purpose of this research is to examine the effect of spiritual marketing and entrepreneurial orientation on determining sustainable competitive advantage (case study: Soliko Kale Company. The research method of this article is applied in terms of purpose, a descriptive survey in nature, and cross-sectional in terms of time. The statistical population of this research is the employees of Soliko Kale company. The number of personnel of this company is 125 people. The sample size was determined based on Cochran's formula of 94 people. The sampling method was chosen as simple random. The data collection tool, according to the standard questionnaire of Bambang et al. (2021), included 20 questions, the validity of the questionnaire by the supervisor and experts, management experts, and their reliability by calculating Cronbach's alpha coefficient for all conditions were confirmed to be greater than 0.7. In this research, 7 hypotheses were examined based on the conceptual model. Two types of descriptive statistics (using SPSS software) and inferential statistics (using PLS software) were used for data analysis. A structural equation test was used to check the model. The results of all hypotheses confirm the research model, and the results show that to create a sustainable competitive advantage in general marketing, it is necessary to implement spiritual marketing and promote entrepreneurial orientation. The innovation of this research study record is about the role and position of spiritual marketing in relation to marketing capabilities and sustainable competitive advantage along with entrepreneurial orientation variables

Phenotypic and molecular characterization of CTX-M extended-spectrum beta-lactamase-producing Escherichia coli isolates in Shiraz, Iran

AbstractINTRODUCTIONThe aim of this study was to detect the prevalence of the extended-spectrum beta-lactamase (ESBL)-encoding CTX-M gene in Escherichia coliisolates.METHODS:Phenotypic screening of 376 E. coli isolates for ESBL was conducted using disk diffusion. ESBL-producing isolates were tested using PCR and specific primers. The blaCTX-M cluster was identified using the RFLP method, and its genotype was sequenced.RESULTS:From 202 ESBL-producing E. coli , 185 (91.5%) possessed CTX-M genes. CTX-M-1 subtypes were found in 98% of the isolates. The blaCTX-M gene was identical to CTX-M-15.CONCLUSIONS:A high prevalence of CTX-M-1-producing E. coli apparently exists in Shiraz, Iran

Potential anti-icing applications of encapsulated phase change material–embedded coatings; a review

Icephobic surfaces are highly sought-after materials as there is a need to reduce the catastrophic outcomes of ice formation on outdoor surfaces. Existing anti-icing strategies, including superhydrophobic surfaces (SHPSs) and slippery liquid–infused porous surfaces (SLIPS), are often ineffective against frost formation or have a limited durability. As such, new approaches are required, and the incorporation of phase change materials (PCMs) into polymeric matrices offers a potential means of delaying ice formation and reducing ice adhesion on exposed surfaces. Homogeneously dispersed encapsulated PCMs (EPCMs) of uniform size inside a binder can release high amounts of latent heat and produce local shear stresses on surfaces—due to their volume change—during icing conditions, thereby reducing ice adhesion strength. Furthermore, surface protrusions produced by the EPCMs can also impart hydrophobicity or even superhydophobicity onto a surface to delay ice formation. This contribution reviews recent progress in the development of ECPM-based anti-icing surfaces. We also discuss the advantages and challenges of using PCM materials for anti-icing applications, summarize existing encapsulation methods, and outline the ECPM-based mechanisms that hinder ice formation and lower ice adhesion

Integration of experimental analysis and machine learning to predict drop behavior on superhydrophobic surfaces

The design of water-repellent surfaces is of great importance as water repellency of surfaces against impacting water drops is a promising approach for most of applications as anti-icing and self-cleaning. To comprehensively investigate drop interactions with hydrophobic and superhydrophobic surfaces, we conducted a large suite of experimental tests to evaluate the morphology of impacting drops on these surfaces as a function of drop properties (drop diameter, density, viscosity, and surface tension), kinematic parameters (velocity), and surface features (contact angle, contact angle hysteresis, and surface roughness). Following analyzing the experimental results, we utilized a novel approach in this field by applying a predictive approach based on machine learning to predict the behavior of impacting drops on hydrophobic and superhydrophobic surfaces. Our developed model, based on a random-forest approach, predicted drop behavior at up to 98% accuracy. Aiming at finding those conditions favorable for producing a bouncing behavior upon drop impact, we predicted the outcome of an impinging drop for a wide range of Weber numbers, i.e., impact velocities, and numerous hypothetical surfaces. Our results offer some design criteria for creating superhydrophobic surfaces that favor bouncing upon drop impact on these surfaces