Predicting the outcome of renal transplantation

ObjectiveRenal transplantation has dramatically improved the survival rate of hemodialysis patients. However, with a growing proportion of marginal organs and improved immunosuppression, it is necessary to verify that the established allocation system, mostly based on human leukocyte antigen matching, still meets today's needs. The authors turn to machine-learning techniques to predict, from donor-recipient data, the estimated glomerular filtration rate (eGFR) of the recipient 1 year after transplantation.DesignThe patient's eGFR was predicted using donor-recipient characteristics available at the time of transplantation. Donors' data were obtained from Eurotransplant's database, while recipients' details were retrieved from Charite Campus Virchow-Klinikum's database. A total of 707 renal transplantations from cadaveric donors were included.MeasurementsTwo separate datasets were created, taking features with <10% missing values for one and <50% missing values for the other. Four established regressors were run on both datasets, with and without feature selection.ResultsThe authors obtained a Pearson correlation coefficient between predicted and real eGFR (COR) of 0.48. The best model for the dataset was a Gaussian support vector machine with recursive feature elimination on the more inclusive dataset. All results are available at http://transplant.molgen.mpg.de/.LimitationsFor now, missing values in the data must be predicted and filled in. The performance is not as high as hoped, but the dataset seems to be the main cause.ConclusionsPredicting the outcome is possible with the dataset at hand (COR=0.48). Valuable features include age and creatinine levels of the donor, as well as sex and weight of the recipient

Three-dimensional simulation of cavitating flow in real journal bearing geometry

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu.Hydrodynamic journal bearings are commonly used in many technical applications because they provide low friction and minimal wear. In general, flow simulation during the engineering design process is carried out by means of the Reynolds equation. The Reynolds equation is a non-linear two-dimensional differential equation, which is based on the pressure and the gap between shaft and bushing in relation to bearing clearance, eccentricity, bushing deformation and load. However, due its two-dimensional nature it is inaccurate where the lubricant flow inside the bearing becomes three-dimensional e.g., in the vicinity of feed holes or grooves. The work on hand presents the numerical approach and the cavitation model based on the Rayleigh-Plesset equation. Moreover, a bearing flow experiment was designed and constructed with the goal to validate numerical results. Finally, the validated 3D simulation model is applied on a real bearing, which was subject to an experimental investigation targeting cavitation. The numerical results include images of complex three-dimensional flow structures, vortices and vapor distributions. In comparison of 2D and 3D simulation, the two-dimensional approach gives wrong information in 2 out of 6 critical regions pertaining cavitation failing in both, over- and under-prediction of cavitation. In summary, a new numerical model expands the scope for the numerical simulation of the lubricant flow in hydrodynamic journal bearings and improves the prediction of cavitation

Rain volume estimation over areas using satellite and radar data

The analysis of 18 convective clusters demonstrates that the extension of the Area-Time-Integral (ATI) technique to the use of satellite data is possible. The differences of the internal structures of the radar reflectivity features, and of the satellite features, give rise to differences in estimating rain volumes by delineating area; however, by focusing upon the area integrated over the lifetime of the storm, it is suggested that some of the errors produced by the differences in the cloud geometries as viewed by radar or satellite are minimized. The results are good and future developments should consider data from different climatic regions and should allow for implementation of the technique in a general circulation model

Evidence and modeling of turbulence bifurcation in L-mode confinement transitions on Alcator C-Mod

© 2020 Author(s). Analysis and modeling of rotation reversal hysteresis experiments show that a single turbulent bifurcation is responsible for the Linear to Saturated Ohmic Confinement (LOC/SOC) transition and concomitant intrinsic rotation reversal on Alcator C-Mod. Plasmas on either side of the reversal exhibit different toroidal rotation profiles and therefore different turbulence characteristics despite the profiles of density and temperature, which are indistinguishable within measurement uncertainty. Elements of this bifurcation are also shown to persist for auxiliary heated L-modes. The deactivation of subdominant (in the linear growth rate and contribution to heat transport) ion temperature gradient and trapped electron mode instabilities is identified as the only possible change in turbulence within a reduced quasilinear transport model across the reversal, which is consistent with the measured profiles and inferred heat and particle fluxes. Experimental constraints on a possible change from strong to weak turbulence, outside the description of the quasilinear model, are also discussed. These results indicate an explanation for the LOC/SOC transition that provides a mechanism for the hysteresis through the dynamics of subdominant modes and changes in their relative populations and does not involve a change in the most linearly unstable ion-scale drift-wave instability

Protein kinase VRK-1 regulates cell invasion and EGL-17/FGF signaling in Caenorhabditis elegans

The vaccinia-related kinases (VRKs) are highly conserved throughout the animal kingdom and phosphorylate several chromatin proteins and transcription factors. In early Caenorhabditis elegans embryos, VRK-1 is required for proper nuclear envelope formation. In this work, we present the first investigation of the developmental role of VRKs by means of a novel C. elegans vrk-1 mutant allele. We found that VRK-1 is essential in hermaphrodites for formation of the vulva, uterus, and utse and for development and maintenance of the somatic gonad and thus the germ line. VRK-1 regulates anchor cell polarity and the timing of anchor cell invasion through the basement membranes separating vulval and somatic gonadal cells during the L3 larval stage. VRK-1 is also required for proper specification and proliferation of uterine cells and sex myoblasts. Expression of the fibroblast growth factor-like protein EGL-17 and its receptor EGL-15 is reduced in vrk-1 mutants, suggesting that VRK-1 might act at least partially through activation of FGF signaling. Expression of a translational VRK-1::GFP fusion protein in the ventral nerve cord and vulva precursor cells restores vulva and uterus formation, suggesting both cell autonomous and non-autonomous roles of VRK-1

Predictors and outcomes of crossover to surgery from physical therapy for meniscal tear and osteoarthritis a randomized trial comparing physical therapy and surgery

BACKGROUND: Arthroscopic partial meniscectomy (APM) combined with physical therapy (PT) have yielded pain relief similar to that provided by PT alone in randomized trials of subjects with a degenerative meniscal tear. However, many patients randomized to PT received APM before assessment of the primary outcome. We sought to identify factors associated with crossing over to APM and to compare pain relief between patients who had crossed over to APM and those who had been randomized to APM. METHODS: We used data from the MeTeOR (Meniscal Tear in Osteoarthritis Research) Trial of APM with PT versus PT alone in subjects ≥45 years old who had mild-to-moderate osteoarthritis and a degenerative meniscal tear. We assessed independent predictors of crossover to APM among those randomized to PT. We also compared pain relief at 6 months among those randomized to PT who crossed over to APM, those who did not cross over, and those originally randomized to APM. RESULTS: One hundred and sixty-four subjects were randomized to and received APM and 177 were randomized to PT, of whom 48 (27%) crossed over to receive APM in the first 140 days after randomization. In multivariate analyses, factors associated with a higher likelihood of crossing over to APM among those who had originally been randomized to PT included a baseline Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Pain Score of ≥40 (risk ratio [RR] = 1.99; 95% confidence interval [CI] = 1.00, 3.93) and symptom duration of <1 year (RR = 1.74; 95% CI = 0.98, 3.08). Eighty-one percent of subjects who crossed over to APM and 82% of those randomized to APM had an improvement of ≥10 points in their pain score at 6 months, as did 73% of those who were randomized to and received only PT. CONCLUSIONS: Subjects who crossed over to APM had presented with a shorter symptom duration and greater baseline pain than those who did not cross over from PT. Subjects who crossed over had rates of surgical success similar to those of the patients who had been randomized to surgery. Our findings also suggest that an initial course of rigorous PT prior to APM may not compromise surgical outcome. LEVEL OF EVIDENCE: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence