Anti-Inflammatory Activity of a Demineralized Bone Matrix: An In Vitro Pilot Study

Demineralized bone matrix (DBM) is commonly used for the reconstruction of bone defects. Early graft consolidation involves a transient inflammatory process. It is, however, unclear whether DBM can modulate this process. To test this possibility, we prepared acid lysates of demineralized ground cortical (DGC) and moldable demineralized fibers (MDF). Murine RAW 264.7 and primary bone marrow macrophages were exposed to acid lysates of DGC and MFD prior to provoking an inflammatory response with lipopolysaccharide (LPS). Similarly, murine ST2 mesenchymal cells were exposed to DGC and MFD with and without interleukin 1β (IL1) and TNFα. We show here that acid lysates of DGC and MFD reduced the expression of IL1 and IL6 in RAW 264.7 macrophages, as determined by RT-PCR and, for IL6, by immunoassay. This response was confirmed with primary macrophages. Likewise, desalted acid lysates exert anti-inflammatory properties on RAW 264.7 cells and in ST2 cells, the forced expression of IL6, inducible nitric oxide synthase (iNOS) and chemokine ligand 5 (CCL5) was reduced. These in vitro findings suggest that DGC and MFD lower the inflammation-induced expression of inflammatory mediators in murine cell-based bioassays.

Antithrombotic Management in Adult Kidney Transplantation – A European survey study

In kidney transplantation (KTx), renal graft thrombosis (RGT) is one of the main reasons for early graft loss. Although evidence-based guidance on prevention of RGT is lacking, thromboprophylaxis is widely used. The aim of this survey was to obtain a European view of the different thromboprophylactic strategies applied in KTx. An online 22-question survey, addressed to KTx professionals, was distributed by e-mail and via platforms of the European Society for Organ Transplantation. Seventy-five responses (21 countries, 51 centers) were received: 75% had over 10 years’ clinical experience, 64% were surgeons, 29% nephrologists and 4% urologists. A written antithrombotic management protocol was available in 75% of centers. In 8 (16%) of centers respondents contradicted each other regarding the availability of a written protocol. Thromboprophylaxis is preferred by 78% of respondents, independent of existing antithrombotic management protocols. Ninety-two percent of respondents indicated that an anticipated bleeding risk is the main reason to discontinue chronic antithrombotic therapy preoperatively. Intraoperatively, 32% of respondents administer unfractionated heparin (400 – 10.000 international units with a median of 5000) in selected cases. Despite an overall preference for perioperative thromboprophylaxis in KTx, there is a high variation within Europe regarding type, timing and dosage, most likely due to the paucity of high-quality studies. Further research is warranted in order to develop better guidelines.

Designing Cardiovascular Implants Taking in View the Endothelial Basement Membrane

Insufficient endothelialization of cardiovascular grafts is a major hurdle in vascular surgery and regenerative medicine, bearing a risk for early graft thrombosis. Neither of the numerous strategies pursued to solve these problems were conclusive. Endothelialization is regulated by the endothelial basement membrane (EBM), a highly specialized part of the vascular extracellular matrix. Thus, a detailed understanding of the structure–function interrelations of the EBM components is fundamental for designing biomimetic materials aiming to mimic EBM functions. In this review, a detailed description of the structure and functions of the EBM are provided, including the luminal and abluminal interactions with adjacent cell types, such as vascular smooth muscle cells. Moreover, in vivo as well as in vitro strategies to build or renew EBM are summarized and critically discussed. The spectrum of methods includes vessel decellularization and implant biofunctionalization strategies as well as tissue engineering-based approaches and bioprinting. Finally, the limitations of these methods are highlighted, and future directions are suggested to help improve future design strategies for EBM-inspired materials in the cardiovascular field.

Intraoperative Assessment of Coronary Resistances: A New Quality Marker and Potential Tool to Predict Early Graft Failure after Coronary Artery Bypass Grafting?

Intraoperative assessment of graft patency is pivotal for successful coronary revascularization. In the present study we aimed to propose a new, easy to perform tool to assess anastomotic quality intraoperatively, and to investigate its potential reliability in predicting early graft failure. Intraoperative graft flowmetry of 63 consecutive patients undergoing CABG were prospectively collected. Transit time flowmetry and its derivatives were recorded. Coronary resistances were calculated according to Hagen–Poiseuille equation both during cardioplegic arrest and after withdrawal from cardiopulmonary bypass. Angiographic evidence of graft occlusion at follow-up was cross-checked with intraoperative recordings. After a mean follow-up of 10.4 ± 6.0 months, 22 grafts were studied, and occlusion was documented in five (22.7%). Occluded grafts showed lower flows and higher resistances recorded during aortic cross-clamping. Coronary resistances, recorded during aortic cross-clamping, greater than 2.0 mmHg/mL/min, showed a sensitivity of 80% and a specificity of 100% to predict graft failure. We propose the routine recording of coronary resistances during aortic cross-clamping as an additional tool to overcome the acknowledged limitation of TTF to predict graft occlusion at 1 year.

Advances in Hypothermic and Normothermic Perfusion in Kidney Transplantation

Hypothermic and normothermic machine perfusion in kidney transplantation are purported to exert a beneficial effect on post-transplant outcomes compared to the traditionally used method of static cold storage. Kidney perfusion techniques provide a window for organ reconditioning and quality assessment. However, how best to deliver these preservation methods or improve organ quality has not yet been conclusively defined. This review summarises the promising advances in machine perfusion science in recent years, which have the potential to further improve early graft function and prolong graft survival.

Reassessment of Relevance and Predictive Value of Parameters Indicating Early Graft Dysfunction in Liver Transplantation: AST Is a Weak, but Bilirubin and INR Strong Predictors of Mortality

Introduction: Early graft dysfunction (EAD) complicates liver transplantation (LT). The aim of this analysis was to discriminate between the weight of each variable as for its predictive value toward patient and graft survival.Methods: We reviewed all LT performed at the Medical University of Innsbruck between 2007 and 2018. EAD was recorded when one of the following criteria was present: (i) aspartate aminotransferase (AST) levels >2,000 IU/L within the first 7 days, (ii) bilirubin levels ≥10mg/dL or (iii) international normalized ratio (INR) ≥1.6 on postoperative day 7.Results: Of 616 LT, 30.7% developed EAD. Patient survival did not differ significantly (P = 0.092; log rank-test = 2.87), graft survival was significantly higher in non-EAD patients (P = 0.008; log rank-test = 7.13). Bilirubin and INR on postoperative day 7 were identified as strong mortality predictors (Bilirubin HR = 1.71 [1.34, 2.16]; INR HR = 2.69 [0.51, 14.31]), in contrast to AST (HR = 0.91 [0.75, 1.10]). Similar results were achieved for graft loss estimation. A comparison with the Model for Early Allograft Function (MEAF) and the Liver Graft Assessment Following Transplantation (L-GrAFT) score identified a superior discrimination potential but lower specificity.Conclusion: Contrarily to AST, bilirubin and INR have strong predictive capacity for patient and graft survival. This fits well with the understanding, that bile duct injury and deprivation of synthetic function rather than hepatocyte injury are key factors in LT.

Effect of Aprotinin on Liver Injury after Transplantation of Extended Criteria Donor Grafts in Humans: A Retrospective Propensity Score Matched Cohort Analysis

The number of patients awaiting liver transplantation still widely exceeds the number of donated organs available. Patients receiving extended criteria donor (ECD) organs are especially prone to an aggravated ischemia reperfusion syndrome during liver transplantation leading to massive hemodynamic stress and possible impairment in organ function. Previous studies have demonstrated aprotinin to ameliorate reperfusion injury and early graft survival. In this single center retrospective analysis of 84 propensity score matched patients out of 274 liver transplantation patients between 2010 and 2014 (OLT), we describe the association of aprotinin with postreperfusion syndrome (PRS), early allograft dysfunction (EAD: INR 1,6, AST/ALT > 2000 within 7–10 days) and recipient survival. The incidence of PRS (52.4% vs. 47.6%) and 30-day mortality did not differ (4.8 vs. 0%; p = 0.152) but patients treated with aprotinin suffered more often from EAD (64.3% vs. 40.5%, p = 0.029) compared to controls. Acceptable or poor (OR = 3.3, p = 0.035; OR = 9.5, p = 0.003) organ quality were independent predictors of EAD. Our data do not support the notion that aprotinin prevents nor attenuates PRS, EAD or mortality.

The Ensembles of Machine Learning Methods for Survival Predicting after Kidney Transplantation

Machine learning is used to develop predictive models to diagnose different diseases, particularly kidney transplant survival prediction. The paper used the collected dataset of patients’ individual parameters to predict the critical risk factors associated with early graft rejection. Our study shows the high pairwise correlation between a massive subset of the parameters listed in the dataset. Hence the proper feature selection is needed to increase the quality of a prediction model. Several methods are used for feature selection, and results are summarized using hard voting. Modeling the onset of critical events for the elements of a particular set is made based on the Kapplan-Meier method. Four novel ensembles of machine learning models are built on selected features for the classification task. Proposed stacking allows obtaining an accuracy, sensitivity, and specifity of more than 0.9. Further research will include the development of a two-stage predictor.