Expression of Winged Bean Basic Agglutinin in Spodoptera frugiperda Insect Cell Expression System

In this paper we report the successful expression of the winged bean basic agglutinin (WBA I) in insect cells infected with a recombinant baculovirus carrying the WBA I gene and its characterization in terms of its carbohydrate binding properties. The expressed protein appears to have a lower molecular weight than the native counterpart which is consistent with the lack of glycosylation of the former. Moreover, the expressed protein maintains its dimeric nature. Hence, a role for glycosylation in modulation of dimerization of WBA I is ruled out unlike Erythrina corallodendron (EcorL). Despite this the protein is active, with its sugar specificity unaltered.     

Optimizing methods for human testicular tissue cryopreservation and spermatogonial stem cell isolation

Cryopreservation of testicular tissue before cancer therapy for fertility preservation in prepubertal boys with cancer is of great interest in reproductive medicine. Isolation of spermatogonial stem cells (SSCs) from cryopreserved tissues would be a suitable cell source to re-establish spermatogenesis after cancer therapy. We herein establish optimized protocols for cryopreservation of human testicular tissue and isolation of SSCs from cryopreserved tissue. We developed a freezing protocol that provided high testicular cell viability and supported structural integrity and tubular epithelium coherence similar to fresh tissue. Then, we established a protocol that allowed efficient isolation of functional SSCs from cryopreserved tissues. Isolated cells were found on the testicular basement membrane after xenotransplantation. Our results demonstrated the preservation of testicular tissue structure and high cell viability with efficient isolation of SSCs after testicular cryopreservation, which is promising for future therapeutic applications in fertility preservation.     

Spatiotemporal Dynamics of Actomyosin Networks

Rhodamine–phalloidin-labeled actin filaments were visualized gliding over a skeletal heavy meromyosin (HMM)-coated surface. Experiments at low filament densities showed that when two filaments collided, their paths were affected in a manner that depended on collision angle. Some collisions resulted in complete alignment of the filament paths; in others, the filaments crossed over one another. Filament crossover or alignment was equally probable at ∼40° contact angle. Filaments often underwent significant bending during collision and analysis of filament shape indicated an energy requirement of ∼13 k_BT. Experiments were performed over a wide range of HMM surface density and actin filament bulk concentration. Actin filament gliding speed and path persistence plateaued above a critical HMM surface density, and at high (micromolar) actin filament concentrations, filament motion became dramatically aligned in a common direction. Spatiotemporal features of alignment behavior were determined by correlation analysis, supported by simulations. The thermal drift of individual filament tracks was suppressed as the population became more oriented. Spatial correlation analysis revealed that long-range alignment was due to incremental recruitment rather than fusion of locally ordered seed domains. The global alignment of filament movement, described by an “order parameter,” peaked at optimal actin concentrations and myosin surface densities, in contrast to previous predictions of a critical phase transition. Either hydrodynamic coupling or exchange of filaments between the surface bound and adjacent bulk phase layers might degrade order at high actin filament concentration, and high HMM surface densities might decrease alignment probability during collisions. Our results are compatible with generation of long-range order from mechanical interaction between individual actin filaments. Furthermore, we show that randomly oriented myosin motors align relatively short, submicrometer actin filaments into motile surface domains that extend over many tens of micrometers and these patterns persist for several minutes.     

Assessing the Necessity of the Standardized Infection Ratio for Reporting Central Line-Associated Bloodstream Infections

This brief article presents results that support the contention that risk adjustment via the standardized infection ratio (SIR) for the reporting of central line-associated bloodstream infections (CLABSIs) may be no more predictive than standard rate adjustments utilizing CLABSIs per central line days (i.e., CLABSI rates). Recent data posted on the U.S. Department of Health and Human Services’ Hospital Compare website showed that nearly 70% of 1721 reporting hospitals with at least 1000 central line days had five or fewer infections during 2011. These hospitals had 39.3% of the total central line days and a significantly lower SIR than poorer performing hospitals with six or more CLABSIs (p<0.0001). In addition, 19 hospitals are presented which had central line days between 9000 to over 22,000 that also had zero to three CLABSIs. Some of these hospitals were university referral centers and inner city facilities. There was great variation of CLABSI cases among US hospitals. Evidence is mounting that all hospitals should be able to achieve a near zero incidence of CLABSIs and that these infections may in fact be near ‘never events’, which begs whether risk adjustment with the SIR is needed and whether it adds more information than does rate adjustment using CLABSI rates.     

Spatiotemporal Dynamics of Actomyosin Networks

Rhodamine–phalloidin-labeled actin filaments were visualized gliding over a skeletal heavy meromyosin (HMM)-coated surface. Experiments at low filament densities showed that when two filaments collided, their paths were affected in a manner that depended on collision angle. Some collisions resulted in complete alignment of the filament paths; in others, the filaments crossed over one another. Filament crossover or alignment was equally probable at ∼40° contact angle. Filaments often underwent significant bending during collision and analysis of filament shape indicated an energy requirement of ∼13 k_BT. Experiments were performed over a wide range of HMM surface density and actin filament bulk concentration. Actin filament gliding speed and path persistence plateaued above a critical HMM surface density, and at high (micromolar) actin filament concentrations, filament motion became dramatically aligned in a common direction. Spatiotemporal features of alignment behavior were determined by correlation analysis, supported by simulations. The thermal drift of individual filament tracks was suppressed as the population became more oriented. Spatial correlation analysis revealed that long-range alignment was due to incremental recruitment rather than fusion of locally ordered seed domains. The global alignment of filament movement, described by an “order parameter,” peaked at optimal actin concentrations and myosin surface densities, in contrast to previous predictions of a critical phase transition. Either hydrodynamic coupling or exchange of filaments between the surface bound and adjacent bulk phase layers might degrade order at high actin filament concentration, and high HMM surface densities might decrease alignment probability during collisions. Our results are compatible with generation of long-range order from mechanical interaction between individual actin filaments. Furthermore, we show that randomly oriented myosin motors align relatively short, submicrometer actin filaments into motile surface domains that extend over many tens of micrometers and these patterns persist for several minutes.     

Motor Performance Assessment in Parkinson’s Disease: Association between Objective In-Clinic,Objective In-Home,and Subjective/Semi-Objective Measures

Advances in wearable technology allow for the objective assessment of motor performance in both in-home and in-clinic environments and were used to explore motor impairments in Parkinson’s disease (PD). The aims of this study were to: 1) assess differences between in-clinic and in-home gait speed, and sit-to-stand and stand-to-sit duration in PD patients (in comparison with healthy controls); and 2) determine the objective physical activity measures, including gait, postural balance, instrumented Timed-up-and-go (iTUG), and in-home spontaneous physical activity (SPA), with the highest correlation with subjective/semi-objective measures, including health survey, fall history (fallers vs. non-fallers), fear of falling, pain, Unified Parkinson''s Disease Rating Scale, and PD stage (Hoehn and Yahr). Objective assessments of motor performance were made by measuring physical activities in the same sample of PD patients (n = 15, Age: 71.2±6.3 years) and age-matched healthy controls (n = 35, Age: 71.9±3.8 years). The association between in-clinic and in-home parameters, and between objective parameters and subjective/semi-objective evaluations in the PD group was assessed using linear regression-analysis of variance models and reported as Pearson correlations (R). Both in-home SPA and in-clinic assessments demonstrated strong discriminatory power in detecting impaired motor function in PD. However, mean effect size (0.94±0.37) for in-home measures was smaller compared to in-clinic assessments (1.30±0.34) for parameters that were significantly different between PD and healthy groups. No significant correlation was observed between identical in-clinic and in-home parameters in the PD group (R = 0.10–0.25; p>0.40), while the healthy showed stronger correlation in gait speed, sit-to-stand duration, and stand-to-sit duration (R = 0.36–0.56; p<0.03). This suggests a better correlation between supervised and unsupervised motor function assessments in healthy controls compared to PD group. In the PD group, parameters related to velocity and range-of-motion of lower extremity within gait assessment (R = 0.58–0.84), and turning duration and velocity within iTUG test (R = 0.62–0.77) demonstrated strong correlations with PD stage (p<0.01).     

Exploratory analysis of high-throughput metabolomic data

In order to make sense of the sheer volume of metabolomic data that can be generated using current technology, robust data analysis tools are essential. We propose the use of the growing self-organizing map (GSOM) algorithm and by doing so demonstrate that a deeper analysis of metabolomics data is possible in comparison to the widely used batch-learning self-organizing map, hierarchical cluster analysis and partitioning around medoids algorithms on simulated and real-world time-course metabolomic datasets. We then applied GSOM to a recently published dataset representing metabolome response patterns of three wheat cultivars subject to a field simulated cyclic drought stress. This novel and information rich analysis provided by the proposed GSOM framework can be easily extended to other high-throughput metabolomics studies.