OBJECTIVE

Acute renal failure (ARF) frequently complicates lung transplantation. This study determined the prevalence, predictive factors, and consequences of ARF on long-term renal function and survival.

METHODS

One hundred and seventy-four lung transplantation recipients were divided into two groups based on the presence or absence of ARF defined as a 50% decrease in creatinine clearance from baseline (group I: 67 patients with ARF; group II: 107 patients without ARF). Multivariate analysis compared pre-operative, operative, and post-operative risk factors to assess predictive factors. Renal function over time was assessed by two-way repeated measures analysis of variance (ANOVA).

RESULTS

ARF developed in 67 (39%) of patients. Multivariate analysis identified aprotinin (OR 2.20 (1.11; 4.36), p = 0.02) and double lung transplantation (OR 2.61 (1.32; 5.15), p = 0.006) as risk factors for post-operative renal failure. At 5 years following transplant, creatinine clearance was similar between the two groups (group I CrCl: 73 ml s−1; group II CrCl: 53 ml s−1; p = 0.54). Survival at 5 years was the same in the two groups. Multivariate analysis associated age at the time of transplantation (HR 1.030 (1.004; 1.057), p = 0.02) and intensive care unit (ICU) length of stay (HR 1.029 (1.008; 1.051), p = 0.007) with decreased survival.

CONCLUSIONS

The use of aprotinin and double lung transplantation are associated with ARF following lung transplantation. Age at the time of transplantation and a longer intensive care stay predict decreased survival. ARF after lung transplantation is not predictive of late renal dysfunction or decreased long-term survival.

Valve interstitial cells populate aortic valve cusps and have been implicated in aortic valve calcification. Here we investigate a common in vitro model for aortic valve calcification by characterizing nodule formation in porcine aortic valve interstitial cells (PAVICs) cultured in osteogenic (OST) medium supplemented with transforming growth factor beta 1 (TGF-β1). Using a combination of materials science and biological techniques, we investigate the relevance of PAVICs nodules in modeling the mineralised material produced in calcified aortic valve disease. PAVICs were grown in OST medium supplemented with TGF-β1 (OST+TGF-β1) or basal (CTL) medium for up to 21 days. Murine calvarial osteoblasts (MOBs) were grown in OST medium for 28 days as a known mineralizing model for comparison. PAVICs grown in OST+TGF-β1 produced nodular structures staining positive for calcium content; however, micro-Raman spectroscopy allowed live, noninvasive imaging that showed an absence of mineralized material, which was readily identified in nodules formed by MOBs and has been identified in human valves. Gene expression analysis, immunostaining, and transmission electron microscopy imaging revealed that PAVICs grown in OST+TGF-β1 medium produced abundant extracellular matrix via the upregulation of the gene for Type I Collagen. PAVICs, nevertheless, did not appear to further transdifferentiate to osteoblasts. Our results demonstrate that ‘calcified’ nodules formed from PAVICs grown in OST+TGF-β1 medium do not mineralize after 21 days in culture, but rather they express a myofibroblast-like phenotype and produce a collagen-rich extracellular matrix. This study clarifies further the role of PAVICs as a model of calcification of the human aortic valve.

Cardiovascular diseases are complex pathologies that include alterations of various cell functions at the levels of intact tissue, single cells and subcellular signalling compartments. Conventional techniques to study these processes are extremely divergent and rely on a combination of individual methods, which usually provide spatially and temporally limited information on single parameters of interest. This review describes scanning ion conductance microscopy (SICM) as a novel versatile technique capable of simultaneously reporting various structural and functional parameters at nanometre resolution in living cardiovascular cells at the level of the whole tissue, single cells and at the subcellular level, to investigate the mechanisms of cardiovascular disease. SICM is a multimodal imaging technology that allows concurrent and dynamic analysis of membrane morphology and various functional parameters (cell volume, membrane potentials, cellular contraction, single ion-channel currents and some parameters of intracellular signalling) in intact living cardiovascular cells and tissues with nanometre resolution at different levels of organization (tissue, cellular and subcellular levels). Using this technique, we showed that at the tissue level, cell orientation in the inner and outer aortic arch distinguishes atheroprone and atheroprotected regions. At the cellular level, heart failure leads to a pronounced loss of T-tubules in cardiac myocytes accompanied by a reduction in Z-groove ratio. We also demonstrated the capability of SICM to measure the entire cell volume as an index of cellular hypertrophy. This method can be further combined with fluorescence to simultaneously measure cardiomyocyte contraction and intracellular calcium transients or to map subcellular localization of membrane receptors coupled to cyclic adenosine monophosphate production. The SICM pipette can be used for patch-clamp recordings of membrane potential and single channel currents. In conclusion, SICM provides a highly informative multimodal imaging platform for functional analysis of the mechanisms of cardiovascular diseases, which should facilitate identification of novel therapeutic strategies.