Quantification of Remimazolam Besylate (CNS7056B) and Its Metabolite (CNS7054X) by LC-MS/MS in Human Plasma Using Midazolam-d4 Maleate as Internal Standard.

A new assay was developed to measure the concentration of remimazolam besylate (CNS7056B) and its major carboxylic acid metabolite (CNS7054X) in human plasma. For this new assay method, midazolam-d4 maleate was used as an internal standard. After setting up a previously described assay method, using CNS7056-d4 and CNS7054-d4 as internal standards, analytical results of both methods were compared. For the new analytical method, ultra-high-performance liquid chromatography (UHPLC) with tandem mass spectrometry was applied. A purification method, using solid phase extraction, was developed and validated. The chromatographic separation of the analytes was achieved with a mobile phase gradient using a Water Acquity™ UHPLC-System. The Kinetex™ biphenyl 50 × 2.1 mm UHPLC column was used with a particle diameter of 1.7 µm (Phenomenex, Germany). A measuring range of 0.6-2,000 ng/mL for CNS7056B and of 6-20,000 ng/mL for CNS7054X could be achieved with this new assay. The lower limit of quantification was 0.6 ng/mL for CNS7056B and 6 ng/mL for CNS7054X. The assay was validated according to US Food and Drug Administration guidelines. The new method showed an accuracy of 96.9-110.4% and a precision of 2.1-6.7% for both analytes.

Interdisciplinary interactive blended learning concept in times of a pandemic - pain medicine "totally digital".

Introduction: Pain medicine is located in different sections of the medical curriculum. In the pandemic situation, an online teaching concept for Q14 which includes several disciplines had to be developed. The goal of the project was to create a fully digitized learning platform for the cross-sectional area Q14 that allows all participating disciplines to address the various learning goals without losing a practical component. Project description: First, the students' expectations regarding education in the field of pain medicine were recorded by means of a survey among medical students. Based on this, a teaching module in a blended learning format was developed, which consisted of two parts. Within a digital learning platform, students were first required to complete consecutive learning units using an interactive learning management system. This was followed by a presence phase (online ZOOM seminar) in which, under the guidance of teaching staff, the therapy suggestions of the individual case studies from the previous learning program were reflected. In the second part, the acquired knowledge was applied to a simulated patient. An evaluation of the online module was carried out through free-text answers and self-assessment of the completion time. The ZOOM seminar was evaluated on the basis of an assessment by the teachers. Results: The survey among students revealed a desire for practical training without "frontal teaching". The resulting project realized this aspect by teaching theory during an online module with case vignettes and interactive learning tasks. The subsequent online presence time during the ZOOM meeting enabled the students to repeat and deepen contents and to ask questions. 170 students completed the entire online program, of which evaluation data were available for 75 students. Self-assessment of completion time averaged at 4-6 hours. In the feedback, 90 aspects were addressed, including mainly comments on content (43%), praise (33%) and comments on technical problems (23%). According to the assessment of the presenters, the students were able to carry out the pain anamnesis survey in a structured manner. The submission of the therapy proposal, however, represents a particular hurdle. Conclusion: With the presented blended learning concept it is possible to address the different learning goals and the interdisciplinarity of Q14 sufficiently. After further processing and improvement of the project, a controlled and more extensive collection of evaluation data is required to further investigate the benefit of the platform for the students regarding achievement of defined learning goals.

Dynamic changes in the signal-averaged electrocardiogram are associated with the long-term outcomes after ablation of ischemic ventricular tachycardia.

PURPOSE: Signal-averaged ECG (SAECG) can detect inhomogeneous myocardial conduction in patients presenting with ventricular tachycardia (VT) after myocardial infarction. Radiofrequency ablation (RFCA) aims at elimination of the endocardial late potentials and non-inducibility of VT. Previously, we demonstrated that abnormal SAECG at baseline can return to normal after a successful VT ablation. The present research investigates the post-ablation changes in SAECG after RFCA of VT and their relation to the procedural long-term outcomes. METHODS: Thirty-three patients (31 male; age 68 ± 9 years; EF 36 ± 12%) with ischemic VT were prospectively enrolled to receive RFCA. One VT (range 1-7) per patient was ablated using substrate-guided RFCA and complete success was achieved in 28 (85%) cases. SAECG was performed before (t1), immediately after (t2), and at least 6 months (t3) after the RFCA. RESULTS: After RFCA, the amount of patients showing abnormal SAECG decreased from 82% initially (t1) to 57.6% post-interventionally (t2); P = 0.008; and remained unchanged thereafter in 57% (t3). Patients who experienced VT recurrence (VT+) during the follow-up period had broader averaged QRS (t2): (VT+) 150 ± 26 vs. (VT-) 129 ± 21 ms; P = 0.015, as well as longer LAS40 (t2): (VT+) 60 ± 26 vs. (VT-) 43 ± 18 ms; P = 0.03. Abnormal SAECG (t2) was a strong predictor for VT recurrence: HR 5.4; 95% CI 1.5-21. SAECG detected more late potentials in patients with inferior than in those with anterior scars: 95% vs. 58%; P = 0.016. CONCLUSIONS: RFCA of VT in the left ventricle can improve an abnormal SAECG in some patients after myocardial infarction. Normal SAECG after RFCA of VT is associated with a lower risk for VT recurrence and death.

Evolution and analysis of genetic networks for stable cellular growth and regeneration.

A computational model is presented that simulates stable growth of cellular structures that are in some cases capable of regeneration. In the model, cellular growth is governed by a gene regulatory network. By evolving the parameters and structure of the genetic network using a modified evolution strategy, a dynamically stable state can be achieved in the developmental process, where cell proliferation and cell apoptosis reach an equilibrium. The results of evolution with different setups in fitness evaluation during the development are compared with respect to their regeneration capability as well as their gene regulatory network structure. Network motifs responsible for stable growth and regeneration that emerged from the evolution are also analyzed. We expect that our findings can help to gain a better understanding of the process of growth and regeneration inspired by biological systems, in order to solve complex engineering problems, such as the design of self-healing materials.