Percutaneous aortic valve replacement: valvuloplasty studies in vitro

Objective: Valvuloplasty of the aortic valve is currently used in selected patients for severe calcified aortic valve disease, but clinical effectiveness is low and complication rate remains high. In this study, the total particle load after valvuloplasty and the embolization risk of calcific debris into the coronary arteries was analyzed in an in vitro model. Methods: Three highly calcified human aortic leaflets have been sutured into a porcine annulus (N=9). Both coronary arteries were separated and each was anastomized to a silicon line, which was drained off into a measuring beaker. Then valvuloplasty was performed (Thyshak II, 20mm, 1.5atm). After removal of the balloon, 100ml of sodium chloride solution irrigated the ascending aorta. After passing through the separated coronary arteries, the solution was filtered (filter size 0.45μm), dried, and the total amount of particles was analyzed microscopically. Results: Nine experiments were analyzed. After valvuloplasty, all hearts showed a median of 18 particles larger than 1mm in the coronary arteries (range 0-307). The amount of particles smaller than 1mm was 6574 (median, range 2207-14200). In five cases, coronary arteries were completely occluded by bulky particles. Conclusion: This study demonstrated a large amount of calcific particles after valvuloplasty with a consequently high risk for coronary embolic events in case of highly calcified aortic valves. In times of valvuloplasty rediscovering as part of transcatheter valve implantation, the risk of embolization should be taken into consideration and filtering techniques have to be develope

Accelerating Recovery from Exercise-Induced Muscle Injuries in Triathletes: Considerations for Olympic Distance Races

The triathlon is one of the fastest developing sports in the world due to expanding participation and media attention. The fundamental change in Olympic triathlon races from a single to a multistart event is highly demanding in terms of recovery from and prevention of exercise-induced muscle injures. In elite and competitive sports, ultrastructural muscle injuries, including delayed onset muscle soreness (DOMS), are responsible for impaired muscle performance capacities. Prevention and treatment of these conditions have become key in regaining muscular performance levels and to guarantee performance and economy of motion in swimming, cycling and running. The aim of this review is to provide an overview of the current findings on the pathophysiology, as well as treatment and prevention of, these conditions in compliance with clinical implications for elite triathletes. In the context of DOMS, the majority of recovery interventions have focused on different protocols of compression, cold or heat therapy, active regeneration, nutritional interventions, or sleep. The authors agree that there is a compelling need for further studies, including high-quality randomized trials, to completely evaluate the effectiveness of existing therapeutic approaches, particularly in triathletes. The given recommendations must be updated and adjusted, as further evidence emerges

CSF Metabolic and Proteomic Profiles in Patients Prodromal for Psychosis

BACKGROUND: The initial prodromal state of psychosis (IPS) is defined as an early disease stage prior to the onset of overt psychosis characterized by sub-threshold or more unspecific psychiatric symptoms. Little is known regarding the biochemical changes during this period. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the metabolic/proteomic profiles of cerebrospinal fluid (CSF) of first-onset drug naïve paranoid schizophrenia patients (n = 54) and individuals presenting with initial prodromal symptoms (n = 24), alongside healthy volunteers (n = 70) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy and surface enhanced laser desorption ionization (SELDI) mass spectrometry, respectively. Partial least square discriminant analysis (PLS-DA) showed that 36%/29% of IPS patients displayed proteomic/metabolic profiles characteristic of first-onset, drug naïve schizophrenia, i.e., changes in levels of glucose and lactate as well as changes in a VGF-derived peptide (VGF23-62) and transthyretin protein concentrations. However, only 29% (n = 7) of the investigated IPS patients (who to date have been followed up for up to three years) have so far received a diagnosis of schizophrenia. The presence of biochemical alterations in the IPS group did not correlate with the risk to develop schizophrenia. CONCLUSIONS/SIGNIFICANCE: Our results imply that schizophrenia-related biochemical disease processes can be traced in CSF of prodromal patients. However, the biochemical disturbances identified in IPS patients, at least when measured at a single time point, may not be sufficient to predict clinical outcome

Integrating Genome-Wide Genetic Variations and Monocyte Expression Data Reveals Trans-Regulated Gene Modules in Humans

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns—independent component analysis—to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease

Modeling of GERDA Phase II data

The GERmanium Detector Array (GERDA) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta ($0\nu\beta\beta$) decay of $^{76}$Ge. The technological challenge of GERDA is to operate in a "background-free" regime in the region of interest (ROI) after analysis cuts for the full 100$\,$kg$\cdot$yr target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition of events in the ROI around $Q_{\beta\beta}$ for the $0\nu\beta\beta$ search, to extract a precise measurement of the half-life of the double-beta decay mode with neutrinos ($2\nu\beta\beta$) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the background and achieve even better sensitivities. In this article the background decomposition prior to analysis cuts is presented for GERDA Phase II. The background model fit yields a flat spectrum in the ROI with a background index (BI) of $16.04^{+0.78}_{-0.85} \cdot 10^{-3}\,$cts/(kg$\cdot$keV$\cdot$yr) for the enriched BEGe data set and $14.68^{+0.47}_{-0.52} \cdot 10^{-3}\,$cts/(kg$\cdot$keV$\cdot$yr) for the enriched coaxial data set. These values are similar to the one of Gerda Phase I despite a much larger number of detectors and hence radioactive hardware components

Modeling of GERDA Phase II data

The GERmanium Detector Array (Gerda) experiment at the Gran Sasso underground laboratory (LNGS) of INFN is searching for neutrinoless double-beta (0νββ) decay of 76Ge. The technological challenge of Gerda is to operate in a “background-free” regime in the region of interest (ROI) after analysis cuts for the full 100 kg·yr target exposure of the experiment. A careful modeling and decomposition of the full-range energy spectrum is essential to predict the shape and composition of events in the ROI around Qββ for the 0νββ search, to extract a precise measurement of the half-life of the double-beta decay mode with neutrinos (2νββ) and in order to identify the location of residual impurities. The latter will permit future experiments to build strategies in order to further lower the background and achieve even better sensitivities. In this article the background decomposition prior to analysis cuts is presented for Gerda Phase II. The background model fit yields a flat spectrum in the ROI with a background index (BI) of 16.04+0.78−0.85⋅10−3 cts/(keV·kg·yr) for the enriched BEGe data set and 14.68+0.47−0.52⋅10−3 cts/(keV·kg·yr) for the enriched coaxial data set. These values are similar to the one of Phase I despite a much larger number of detectors and hence radioactive hardware components