Genetic Predisposition of Donors Affects the Allograft Outcome in Kidney Transplantation; Polymorphisms of Stromal-Derived Factor-1 and CXC Receptor 4

Genetic interaction between donor and recipient may dictate the impending responses after transplantation. In this study, we evaluated the role of the genetic predispositions of stromal-derived factor-1 (SDF1) [rs1801157 (G>A)] and CXC receptor 4 (CXCR4) [rs2228014 (C>T)] on renal allograft outcomes. A total of 335 pairs of recipients and donors were enrolled. Biopsy-proven acute rejection (BPAR) and long-term graft survival were traced. Despite similar allele frequencies between donors and recipients, minor allele of SDF1 rs1801157 (GA+AA) from donor, not from recipients, has a protective effect on the development of BPAR compared to wild type donor (GG) (P = 0.005). Adjustment for multiple covariates did not affect this result (odds ratio 0.39, 95% C.I 0.20–0.76, P = 0.006). CXCR4 rs2228014 polymorphisms from donor or recipient did not affect the incidence of acute rejection. SDF1 was differentially expressed in renal tubular epithelium with acute rejection according to genetic variations of donor rs1801157 showing higher expressions in the grafts from GG donors. Contrary to the development of BPAR, the presence of minor allele rs1801157 A, especially homozygocity, predisposed poor graft survival (P = 0.001). This association was significant after adjusting for several risk factors (hazard ratio 3.01; 95% C.I = 1.19–7.60; P = 0.020). The allelic variation of recipients, however, was not associated with graft loss. A donor-derived genetic polymorphism of SDF1 has influenced the graft outcome. Thus, the genetic predisposition of donor should be carefully considered in transplantation

Expression of dihydropyrimidine dehydrogenase (DPD) and hENT1 predicts survival in pancreatic cancer

Background: Dihydropyrimidine dehydrogenase (DPD) tumour expression may provide added value to human equilibrative nucleoside transporter-1 (hENT1) tumour expression in predicting survival following pyrimidine-based adjuvant chemotherapy. Methods: DPD and hENT1 immunohistochemistry and scoring was completed on tumour cores from 238 patients with pancreatic cancer in the ESPAC-3(v2) trial, randomised to either postoperative gemcitabine or 5-fluorouracil/folinic acid (5FU/FA). Results: DPD tumour expression was associated with reduced overall survival (hazard ratio, HR = 1.73 [95% confidence interval, CI = 1.21-2.49], p = 0.003). This was significant in the 5FU/FA arm (HR = 2.07 [95% CI = 1.22-3.53], p = 0.007), but not in the gemcitabine arm (HR = 1.47 [0.91-3.37], p = 0.119). High hENT1 tumour expression was associated with increased survival in gemcitabine treated (HR = 0.56 [0.38-0.82], p = 0.003) but not in 5FU/FA treated patients (HR = 1.19 [0.80-1.78], p = 0.390). In patients with low hENT1 tumour expression, high DPD tumour expression was associated with a worse median [95% CI] survival in the 5FU/FA arm (9.7 [5.3-30.4] vs 29.2 [19.5-41.9] months, p = 0.002) but not in the gemcitabine arm (14.0 [9.1-15.7] vs. 18.0 [7.6-15.3] months, p = 1.000). The interaction of treatment arm and DPD expression was not significant (p = 0.303), but the interaction of treatment arm and hENT1 expression was (p = 0.009). Conclusion: DPD tumour expression was a negative prognostic biomarker. Together with tumour expression of hENT1, DPD tumour expression defined patient subgroups that might benefit from either postoperative 5FU/FA or gemcitabine

Osteobiology, strain, and microgravity. Part II: studies at the tissue level.

Loading microgravity, and/or defective mechanical strain-forces have important effects on bone cells and bone quality and quantity. The complex mechanisms induced by strain and microgravity on bone cells have been reviewed in Part I of this paper. In Part II, we have considered the data on the alterations induced by unloading and microgravity on the skeleton and the mechanisms that are involved at the tissue level in animals and humans.Journal ArticleResearch Support, Non-U.S. Gov'tReviewinfo:eu-repo/semantics/publishe

Requirements and Design of the PROSPER Protocol for Implementation of Information Infrastructures Supporting Pandemic Response: A Nominal Group Study

Background: Advanced technical systems and analytic methods promise to provide policy makers with information to help them recognize the consequences of alternative courses of action during pandemics. Evaluations still show that response programs are insufficiently supported by information systems. This paper sets out to derive a protocol for implementation of integrated information infrastructures supporting regional and local pandemic response programs at the stage(s) when the outbreak no longer can be contained at its source. Methods: Nominal group methods for reaching consensus on complex problems were used to transform requirements data obtained from international experts into an implementation protocol. The analysis was performed in a cyclical process in which the experts first individually provided input to working documents and then discussed them in conferences calls. Argument-based representation in design patterns was used to define the protocol at technical, system, and pandemic evidence levels. Results: The Protocol for a Standardized information infrastructure for Pandemic and Emerging infectious disease Response (PROSPER) outlines the implementation of information infrastructure aligned with pandemic response programs. The protocol covers analyses of the community at risk, the response processes, and response impacts. For each of these, the protocol outlines the implementation of a supporting information infrastructure in hierarchical patterns ranging from technical components and system functions to pandemic evidence production. Conclusions: The PROSPER protocol provides guidelines for implementation of an information infrastructure for pandemic response programs both in settings where sophisticated health information systems already are used and in developing communities where there is limited access to financial and technical resources. The protocol is based on a generic health service model and its functions are adjusted for community-level analyses of outbreak detection and progress, and response program effectiveness. Scientifically grounded reporting principles need to be established for interpretation of information derived from outbreak detection algorithms and predictive modeling.Original Publication:Toomas Timpka, Henrik Eriksson, Elin A Gursky, Magnus Stromgren, Einar Holm, Joakim Ekberg, Olle Eriksson, Anders Grimvall, Lars Valter and James M Nyce, Requirements and Design of the PROSPER Protocol for Implementation of Information Infrastructures Supporting Pandemic Response: A Nominal Group Study, 2011, PLOS ONE, (6), 3, 0017941.http://dx.doi.org/10.1371/journal.pone.0017941Copyright: Public Library of Science (PLoS)http://www.plos.org