A long road ahead

Background: Climate change may well be the “largest threat” to humankind. Changes to our climate system lead to a decrease in global health. The healthcare sector presents one of the largest carbon footprints across all industries. Since surgical departments have one of the largest carbon footprints within the healthcare sector, they represent an area with vast opportunities for improvement. To drive change, it is vital to create awareness of these issues and encourage engagement in changes among people working in the healthcare industry. Methods: We conducted an anonymous cross-sectional survey study to assess awareness among surgeons regarding the impact of healthcare systems on climate change. The questions were designed to investigate surgeons’ willingness to accept and promote changes to reduce carbon footprints. Participants included surgical professionals of all ages and levels of expertise. Results: A total of 210 participants completed the survey in full and were included in the evaluation. Sixty percent emphasized a lack of information and the need for personal education. Over 90 % expressed concern for the environment and a strong desire to gain new insights. Provided that clinical performance remains the same, more than 70 % are willing to embrace carbon-friendly alternatives. In this context, all participants accepted the additional time required for training and initially increased personal efforts to achieve equal performance. Conclusion: Limited awareness and information about carbon footprints were observed in surgical departments in German hospitals. Nevertheless, the vast majority of surgeons across all age groups are more than willing to acquire new insights and adapt to changes in order to reduce energy consumption and carbon dioxide production

Frequent Follow-Up of Delisted Liver Transplant Candidates Is Necessary: An Observational Study about Characteristics and Outcomes of Delisted Liver Transplant Candidates

This observational study focuses on the characteristics and survival of patients taken off of the liver transplant waiting list. Assessment of post-delisting survival and a frequent follow-up of patients after delisting are important keys to improve the survival rate of patients with liver failure after being delisted. Within this study, delisted liver transplant candidates were divided into the following groups: (1) "too good" (54%) or (2) "too sick" (22%) for transplantation, (3) adherence issues (12%) or (4) therapy goal changed (11%). The 5-year survival after delisting within these groups was 84%, 9%, 50%, and 68%, respectively. Less than 3% of the delisted patients had to be relisted again. The clinical expert decision of the multidisciplinary transplant team was sufficiently accurate to differentiate between patients requiring liver transplantation and those who were delisted after a stable recovery of liver function. The assessment of post-delisting survival may serve as a complementary metric to assess differences in center practices and to estimate cumulative post-delisting mortality risk

Proteins from Modern and Ancient Wheat Cultivars: Impact on Immune Cells of Healthy Individuals and Patients with NCGS

In non-celiac gluten sensitivity (NCGS), the elimination of wheat results in a clear symptom improvement, but gluten has still not been proven as (the sole) trigger. Due to the increase in the prevalence of gluten-related diseases, the breeding of high-performance wheat cultivars is discussed as a trigger. To analyze the immune stimulation and signal pathways, the immune cells of healthy subjects and patients with NCGS were stimulated with gliadins from wheat, and the expression and secretion of interleukin 1ß (IL1ß) and interleukin 6 (IL6) were studied. To determine the impact of wheat breeding, the monocyte cell line THP1 and human immune cells were stimulated with gliadin, glutenin, and albumin/globulin fractions of ancient and modern cereals, and expression of inflammatory molecules was checked. Immune cells of patients with NCGS showed an increased expression of IL1ß and IL6 after stimulation with gliadins compared to immune cells of healthy controls. Gliadins caused a strong activation of P-STAT3 in immune cells of healthy controls, and inhibitors of JAK and NFκB pathways considerably reduced this response. In addition to gliadins, we further showed that glutenins and albumin/globulins from all wheat cultivars from the last century, and especially from einkorn and spelt, also markedly induced the expression of inflammatory genes in THP1 and human immune cells. There was no correlation between enhanced immune stimulation and ancient or modern cultivars. This does not support the hypothesis that modern wheat breeding is responsible for the increase in gluten-related diseases. An altered immune situation is suggested in patients with NCGS

A Novel Deep Learning Model as a Donor-Recipient Matching Tool to Predict Survival after Liver Transplantation

Background: The digital era in the field of medicine is the new here and now. Artificial intelligence has entered many fields of medicine and is recently emerging in the field of organ transplantation. Solid organs remain a scarce resource. Being able to predict the outcome after liver transplantation promises to solve one of the long-standing problems within organ transplantation. What is the perfect donor recipient match? Within this work we developed and validated a novel deep-learning-based donor-recipient allocation system for liver transplantation. Method: In this study we used data collected from all liver transplant patients between 2004 and 2019 at the university transplantation centre in Munich. We aimed to design a transparent and interpretable deep learning framework to predict the outcome after liver transplantation. An individually designed neural network was developed to meet the unique requirements of transplantation data. The metrics used to determine the model quality and its level of performance are accuracy, cross-entropy loss, and F1 score as well as AUC score. Results: A total of 529 transplantations with a total of 1058 matching donor and recipient observations were added into the database. The combined prediction of all outcome parameters was 95.8% accurate (cross-entropy loss of 0.042). The prediction of death within the hospital was 94.3% accurate (cross-entropy loss of 0.057). The overall F1 score was 0.899 on average, whereas the overall AUC score was 0.940. Conclusion: With the achieved results, the network serves as a reliable tool to predict survival. It adds new insight into the potential of deep learning to assist medical decisions. Especially in the field of transplantation, an AUC Score of 94% is very valuable. This neuronal network is unique as it utilizes transparent and easily interpretable data to predict the outcome after liver transplantation. Further validation must be performed prior to utilization in a clinical context

A blind benchmark of analysis tools to infer kinetic rate constants from single-molecule FRET trajectories

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We test them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models

Production of Nickel‐Rich Cathodes for Lithium‐Ion Batteries from Lab to Pilot Scale under Investigation of the Process Atmosphere

The selection of an appropriate cathode active material is important for operation performance and production of high-performance lithium-ion batteries. Promising candidates are nickel-rich layered oxides like LiNi$_x$Co$_y$Mn$_z$O$_2$ (NCM, x+y+z=1) with nickel contents of ‘x’ ≥ 0.8, characterized by high electrode potential and specific capacity. However, these materials are associated with capacity fading due to their high sensitivity to moisture. Herein, two different polycrystalline NCM materials with nickel contents of 0.81 ≤ ‘x’ ≤ 0.83 and protective surface coatings are processed in dry-room atmosphere (dew point of supply air T$_D$ ≈ −65 °C) at lab scale including the slurry preparation and coating procedure. In comparison, cathodes are produced in ambient atmosphere and both variants are tested in coin cells. Moreover, processing at pilot scale in ambient atmosphere is realized successfully by continuous coating and drying of the cathodes. Relevant electrode properties such as adhesion strength, specific electrical resistance, and pore-size distribution for the individual process steps are determined, as well as the moisture uptake during calendering. Furthermore, rate capability and cycling stability are investigated in pouch cells, wherein initial specific discharge capacities of up to 190 mAh g$^{−1}$ (with regard to the cathode material mass) are achieved at 0.2C

Regional transplant rates depend more on physician-dependent variables than on proximity to transplant center

Purpose The objective of this work was to uncover inequalities in access to liver transplantation in Bavaria, Germany. Methods For this purpose, the annual transplantation rate per 1 million inhabitants for the respective districts was determined from the aggregated postal codes of the place of residence of transplanted patients. The variables examined were proximity and travel time to the nearest transplant center, as well as the care category of the regional hospital. In addition, we assessed whether the head of gastroenterology at the regional hospital through which liver transplant candidates are referred was trained at a liver transplant center. Results We could not demonstrate a direct relationship between proximity or travel time to the nearest transplant center and access to liver transplantation. Multivariate regression analysis shows that liver transplant training ( p  < 0.0001) of the chief physician (gastroenterologist) of the regional hospital was the most decisive independent factor for access to liver transplantation within a district. Conclusion We show that the transplant training experience of the head of gastroenterology at a regional hospital is an independent factor for the regional transplantation rate. Therefore, it appears important to maintain some liver transplant expertise outside the transplant centers in order to properly identify and assign potential transplant candidates for transplantation.Open Access funding enabled and organized by Projekt DEAL.Universitätsklinik München (6933

Hypothermic Oxygenated Machine Perfusion (HOPE) Prior to Liver Transplantation Mitigates Post-Reperfusion Syndrome and Perioperative Electrolyte Shifts

(1) Background: Post-reperfusion syndrome (PRS) and electrolyte shifts (ES) represent considerable challenges during liver transplantation (LT) being associated with significant morbidity. We aimed to investigate the impact of hypothermic oxygenated machine perfusion (HOPE) on PRS and ES in LT. (2) Methods: In this retrospective study, we compared intraoperative parameters of 100 LTs, with 50 HOPE preconditioned liver grafts and 50 grafts stored in static cold storage (SCS). During reperfusion phase, prospectively registered serum parameters and vasopressor administration were analyzed. (3) Results: Twelve percent of patients developed PRS in the HOPE cohort vs. 42% in the SCS group (p = 0.0013). Total vasopressor demand in the first hour after reperfusion was lower after HOPE pretreatment, with reduced usage of norepinephrine (-26%;p = 0.122) and significant reduction of epinephrine consumption (-52%;p = 0.018). Serum potassium concentration dropped by a mean of 14.1% in transplantations after HOPE, compared to a slight decrease of 1% (p < 0.001) after SCS. The overall incidence of early allograft dysfunction (EAD) was reduced by 44% in the HOPE group (p = 0.04). (4) Conclusions: Pre-transplant graft preconditioning with HOPE results in higher hemodynamic stability during reperfusion and lower incidence of PRS and EAD. HOPE has the potential to mitigate ES by preventing hyperpotassemic complications that need to be addressed in LT with HOPE-pre-treated grafts

A novel approach towards skill-based search and services of Open Educational Resources

Ha, K.-H., Niemann, K., Schwertel, U., Holtkamp, P., Pirkkalainen, H., Börner, D. et al (2011). A novel approach towards skill-based search and services of Open Educational Resources. In E. Garcia-Barriocanal, A. Öztürk, & M. C. Okur (Eds.), Metadata and Semantics Research: 5th International Conference MTSR 2011 (pp. 312-323), Izmir, Turkey, October 12-14, 2011. Springer.Open educational resources (OER) have a high potential to address the growing need for training materials in management education and training. Today, a high number of OER in management are already available in a large number of repositories. However, users face barriers as they have to search repository by repository with different interfaces to retrieve the appropriate learning content. In addition, the use of search criteria related to skills, such as learning objectives and skill-levels is not generally supported. The European co-funded project OpenScout addresses these barriers by intelligently connecting leading European OER repositories and providing federated, skillbased search and retrieval web services. On top of this content federation the project supports users with easy-to-apply tools that will accelerate the (re-) use of open content