PatMatch: a program for finding patterns in peptide and nucleotide sequences

Here, we present PatMatch, an efficient, web-based pattern-matching program that enables searches for short nucleotide or peptide sequences such as cis-elements in nucleotide sequences or small domains and motifs in protein sequences. The program can be used to find matches to a user-specified sequence pattern that can be described using ambiguous sequence codes and a powerful and flexible pattern syntax based on regular expressions. A recent upgrade has improved performance and now supports both mismatches and wildcards in a single pattern. This enhancement has been achieved by replacing the previous searching algorithm, scan_for_matches [D'Souza et al. (1997), Trends in Genetics, 13, 497–498], with nondeterministic-reverse grep (NR-grep), a general pattern matching tool that allows for approximate string matching [Navarro (2001), Software Practice and Experience, 31, 1265–1312]. We have tailored NR-grep to be used for DNA and protein searches with PatMatch. The stand-alone version of the software can be adapted for use with any sequence dataset and is available for download at The Arabidopsis Information Resource (TAIR) at . The PatMatch server is available on the web at for searching Arabidopsis thaliana sequences

Association between serum resistin level and outcomes in kidney transplant recipients.

Resistin is an adipocytokine that is associated with inflammation, coronary artery disease, and other types of cardiovascular disease among patients with normal kidney function. However, little is known about the association of resistin with outcomes in kidney transplant recipients. We collected socio-demographic and clinical parameters, medical and transplant history, and laboratory data from 988 prevalent kidney transplant recipients enrolled in the Malnutrition-Inflammation in Transplant-Hungary Study (MINIT-HU study). Serum resistin levels were measured at baseline. Associations between serum resistin level and death with a functioning graft over a 6-year follow-up period were examined in unadjusted and adjusted models. The mean±SD age of the study population was 51 ± 13 years, among whom 57% were men and 21% were diabetics. Median serum resistin concentrations were significantly higher in patients who died with a functioning graft as compared to those who did not die during the follow-up period (median [IQR]: 22[15-26] vs. 19[14-22] ng/ml, respectively; P < 0.001). Higher serum resistin level was associated with higher mortality risk in both unadjusted and fully adjusted models: HRs (95% CI): 1.33(1.16-1.54) and 1.21(1.01-1.46), respectively. In prevalent kidney transplant recipients, serum resistin was an independent predictor of death with a functioning graft

S-matrix approach to quantum gases in the unitary limit II: the three-dimensional case

A new analytic treatment of three-dimensional homogeneous Bose and Fermi gases in the unitary limit of negative infinite scattering length is presented, based on the S-matrix approach to statistical mechanics we recently developed. The unitary limit occurs at a fixed point of the renormalization group with dynamical exponent z=2 where the S-matrix equals -1. For fermions we find T_c /T_F is approximately 0.1. For bosons we present evidence that the gas does not collapse, but rather has a critical point that is a strongly interacting form of Bose-Einstein condensation. This bosonic critical point occurs at n lambda^3 approximately 1.3 where n is the density and lambda the thermal wavelength, which is lower than the ideal gas value of 2.61.Comment: 26 pages, 16 figure

Novel Modifications of Parallel Jacobi Algorithms

We describe two main classes of one-sided trigonometric and hyperbolic Jacobi-type algorithms for computing eigenvalues and eigenvectors of Hermitian matrices. These types of algorithms exhibit significant advantages over many other eigenvalue algorithms. If the matrices permit, both types of algorithms compute the eigenvalues and eigenvectors with high relative accuracy. We present novel parallelization techniques for both trigonometric and hyperbolic classes of algorithms, as well as some new ideas on how pivoting in each cycle of the algorithm can improve the speed of the parallel one-sided algorithms. These parallelization approaches are applicable to both distributed-memory and shared-memory machines. The numerical testing performed indicates that the hyperbolic algorithms may be superior to the trigonometric ones, although, in theory, the latter seem more natural.Comment: Accepted for publication in Numerical Algorithm

There's no place like home: 35-year patient survival on home hemodialysis.

The vast majority of maintenance dialysis patients suffer from poor long-term survival rates and lower levels of health-related quality of life. However, home hemodialysis is a historically significant dialysis modality that has been associated with favorable outcomes as well as greater patient autonomy and control, yet only represents a small minority of the total dialysis performed in the United States. Some potential disadvantages of home hemodialysis include vascular access complications, infection-related hospitalizations, patient fatigue, and attrition. In addition, current barriers and challenges in expanding the utilization of this modality include limited patient and provider education and technical expertise. Here we report a 65-year old male with end-stage renal disease due to Alport's syndrome who has undergone 35 years of uninterrupted thrice-weekly home hemodialysis (ie, every Sunday, Tuesday, and Thursday evening, each session lasting 3 to 3¼ hours in length) using a conventional hemodialysis machine who has maintained a high functional status allowing him to work 6-8 hours per day. The patient has been able to liberalize his dietary and fluid intake while only requiring 3-4 liters of ultrafiltration per treatment, despite having absence of residual kidney function. Through this case of extraordinary longevity and outcomes after 35 years of dialysis and a review of the literature, we illustrate the history of home hemodialysis, its significant clinical and psychosocial advantages, as well as the barriers that hinder its widespread adaptation

Machine Learning to Identify Dialysis Patients at High Death Risk.

IntroductionGiven the high mortality rate within the first year of dialysis initiation, an accurate estimation of postdialysis mortality could help patients and clinicians in decision making about initiation of dialysis. We aimed to use machine learning (ML) by incorporating complex information from electronic health records to predict patients at risk for postdialysis short-term mortality.MethodsThis study was carried out on a contemporary cohort of 27,615 US veterans with incident end-stage renal disease (ESRD). We implemented a random forest method on 49 variables obtained before dialysis transition to predict outcomes of 30-, 90-, 180-, and 365-day all-cause mortality after dialysis initiation.ResultsThe mean (±SD) age of our cohort was 68.7 ± 11.2 years, 98.1% of patients were men, 29.4% were African American, and 71.4% were diabetic. The final random forest model provided C-statistics (95% confidence intervals) of 0.7185 (0.6994-0.7377), 0.7446 (0.7346-0.7546), 0.7504 (0.7425-0.7583), and 0.7488 (0.7421-0.7554) for predicting risk of death within the 4 different time windows. The models showed good internal validity and replicated well in patients with various demographic and clinical characteristics and provided similar or better performance compared with other ML algorithms. Results may not be generalizable to non-veterans. Use of predictors available in electronic medical records has limited the assessment of number of predictors.ConclusionWe implemented and ML-based method to accurately predict short-term postdialysis mortality in patients with incident ESRD. Our models could aid patients and clinicians in better decision making about the best course of action in patients approaching ESRD

Mean Corpuscular Volume and Mortality in Incident Hemodialysis Patients.

Background/aimsAnemia is common in patients with advanced chronic kidney disease (CKD). A proportion of patients present with macrocytic anemia, manifested by elevated mean corpuscular volume (MCV), which has been associated with worse outcomes in CKD patients. However, it is unknown whether elevated MCV is associated with higher mortality risk in incident hemodialysis (HD) patients.MethodsThis retrospective observational cohort study examined all-cause, cardiovascular, and infectious mortality associations with both baseline and time-varying MCV in 109,501 incident HD patients using Cox proportional hazards models with 3 levels of hierarchical multivariable adjustment. Odds ratios of high versus low baseline MCV were evaluated using logistic regression.ResultsThe mean age of patients was 65 ± 15 (standard deviation) years and the cohort was 44% female, 58% diabetic, and 31% African American. Higher MCV was associated with older age, female sex, non-Hispanic White race-ethnicity, alcohol consumption, and having a decreased albumin or protein intake. Patients with higher MCV levels (> 98 fL) had a higher all-cause, cardiovascular, and infectious mortality risk in both baseline and time varying models, and across all levels of adjustment. In the fully adjusted models, compared to a reference of MCV 92-< 94 fL, patients with a baseline MCV > 100+ fL had a 28% higher risk of all-cause mortality (hazard ratio [HR] 1.28, 95% CI 1.22-1.34), 27% higher risk of cardiovascular mortality (HR 1.27, 95% CI 1.18-1.36), and 18% higher risk of infectious mortality (HR 1.18, 95% CI 1.02-1.38). Associations of higher MCV with these adverse outcomes persisted across all examined subgroups of clinical characteristics.ConclusionsHigher MCV was associated with higher all-cause, cardiovascular, and infectious mortality in HD patients. Further investigation is necessary to understand the underlying nature of the observed association

The Look-back Time Evolution of Far-Ultraviolet Flux from the Brightest Cluster Elliptical Galaxies at z < 0.2

We present the GALEX UV photometry of the elliptical galaxies in Abell clusters at moderate redshifts (z < 0.2) for the study of the look-back time evolution of the UV upturn phenomenon. The brightest elliptical galaxies (M_r < -22) in 12 remote clusters are compared with the nearby giant elliptical galaxies of comparable optical luminosity in the Fornax and Virgo clusters. The sample galaxies presented here appear to be quiescent without signs of massive star formation or strong nuclear activity, and show smooth, extended profiles in their UV images indicating that the far-UV (FUV) light is mostly produced by hot stars in the underlying old stellar population. Compared to their counterparts in nearby clusters, the FUV flux of cluster giant elliptical galaxies at moderate redshifts fades rapidly with ~ 2 Gyrs of look-back time, and the observed pace in FUV - V color evolution agrees reasonably well with the prediction from the population synthesis models where the dominant FUV source is hot horizontal-branch stars and their progeny. A similar amount of color spread (~ 1 mag) in FUV - V exists among the brightest cluster elliptical galaxies at z ~ 0.1, as observed among the nearby giant elliptical galaxies of comparable optical luminosity.Comment: Accepted for publication in the Special GALEX ApJ Supplement, December 200