Recently, the molecule nicotinamide adenine dinucleotide (NAD) has attracted attention as it is involved in various important regulatory mechanisms, immune signaling, aging and regenerative processes. In this regard, it occupies key positions in many redox reactions of the body due to its role as a redox couple (NAD as an oxidized species and NADH as a reduced species). Consequently, NAD homeostasis (the maintenance of NAD in cells) is considered essential. The scientific consensus for many years was that the oxidized species resides exclusively in the intracellular milieu (iNAD). However, recent findings indicate that NAD also exists extracellularly (eNAD) and it is present in virtually all body fluids (from lymph to saliva to blood plasma). Based on these findings, precursors of NAD have recently been approved by the FDA and are commercially available. Measurement of eNAD in blood plasma is problematic due to its low concentration in the nanomolar range. However, quantifying eNAD plasma levels but also eNAD concentrations in cells is necessary to monitor the intake of NAD or its precursors and to adjust their dosage precisely.
The primary objective of this project is to validate, bioanalyze,and to document the assay for eNAD according to the ICH-M10 guidance document endorsed by the U. S. Food and Drug Administration (FDA). Adherence to the principles presented in this guideline should improve the quality and consistency of bioanalytical data, thereby supporting assay development and market approval. In addition, the assay will also be established for the measurement of intracellular NAD (iNAD), and validation of iNAD quantification will also be performed according to the guideline.
In the second part of the project, a clinical study will be conducted to determine whether the intake of nicotinamide riboside (precursor of NAD) leads to a change in eNAD and iNAD. Thus, the basis for an indication-dependent bioanalysis of the measurement of NAD will be developed to monitor the intake of NAD and its precursor or to adjust the dosage specifically on the basis of the quantification.
The Digital Clinician Scientist Program (DCSP) was jointly initiated by the German Research Foundation (DFG), the BIH, and the faculty of Charité - Universitätsmedizin Berlin in early 2019. The DCSP is an extension of the successful BIH Charité Clinician Scientist Program, which has set standards in the medical research landscape throughout Germany. The structured career path enables researching physicians to build the foundation for a successful career as a clinician scientist by providing protected time for research activities and non-clinical training during their residency. The DCSP is intended for clinically active physicians who are already actively shaping the digital transformation process of healthcare with their innovative research projects during their residency training. The main applicant of the continuation application is Prof. Dr. Igor M. Sauer, Director of the BIH Charité Digital Clinician Scientist Program, Deputy Clinic Director of the Department of Surgery, and Head of the Experimental Surgery at Charité. Since the start of the program in 2019, 24 physicians have benefited from funding, thus a broad spectrum of digital topics is already being addressed in various clinics at the Charité. The DFG originally funded the program for three years with more than three million euros. With the approved extension, the funding program now has a further 1.3 million euros available over a period of two years.
For in vitro cancer research, mini-tumours are grown in a gel-like cultivation structure that serves the three-dimensional growth of the mini-tumours. This gel-like cultivation substance is obtained from mouse tumours, an unnatural cultivation environment for human mini-tumours. The aim of the project "Development of human-based hydrogels as a substitute for mouse-derived Matrigel for cancer research" by Björn Papke from the Institute of Pathology and Karl Hillebrandt is to produce a cultivation structure without animal additives. For this purpose, a cultivation structure, also gel-like, is to be produced from tissue obtained from patients during surgical procedures, which better corresponds to the natural environment of the human mini-tumours.
Pancreatic surgery is associated with a high risk for postoperative complications and death of patients. Complications occur in a variable interval after the procedure. Often, a patient has already left the ICU and is not properly monitored anymore when the complication occurs. Risk stratification models can assist in identifying patients at risk in order to keep these patients in ICU for longer. This, in turn, helps to identify complications earlier and increase survival rates. We trained multiple machine learning models on pre-, intra- and short term postoperative data from patients who underwent pancreatic resection at the Department of Surgery, Campus Charité Mitte | Campus Virchow-Klinikum, Charité - Universitätsmedizin Berlin. The presented models achieve an area under the precision-recall curve (AUPRC) of up to 0.51 for predicting patient death and 0.53 for predicting a specific major complication. Overall, we found that a classical logistic regression model performs best for the investigated classification tasks. As more patient data becomes available throughout the perioperative stay, the performance of the risk stratification model improves and should therefore repeatedly be computed.
Authors are Bjarne Pfitzner, Jonas Chromik, Rachel Brabender, Eric Fischer, Alexander Kromer, Axel Winter, Simon Moosburner, Igor M. Sauer, Thomas Malinka, Johann Pratschke, Bert Arnrich, and Max M. Maurer.
Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:2211-2214. doi: 10.1109/EMBC46164.2021.9630897.