Proteins identification of wheat-rye translocation lines by MALDI-TOF-TOF mass spectrometry and ESI-QTOF/MS

OBJECTIVE: To examine the relationship between Timed Up and Go (TUG) performance, verbal executive function (EF) performance, and quality-of-life (QOL) measures in Parkinson's disease (PD). DESIGN: Cross-sectional. SETTING: Sixteen movement disorder centers from across the United States. PARTICIPANTS: Patients with PD (N=1964). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: TUG test, immediate and delayed 5-word recall, verbal fluency, PD QOL Questionnaire. RESULTS: TUG performance and verbal EF performance were significantly associated with, and predictors of, QOL measures, having the greatest association and predictability with the mobility domain of the QOL measures. CONCLUSIONS: The TUG test and verbal EF tests have QOL correlates, making the combined evaluation of mobility, cognitive, and QOL decline a potential examination tool to evaluate the sequelae of PD

Long-term annual primary production in the Ulleung Basin as a biological hot spot in the East/Japan Sea

Although the Ulleung Basin is an important biological hot spot in East/Japan Sea (hereafter the East Sea), very limited knowledge for seasonal and annual variations in the primary productivity exists. In this study, a recent decadal trend of primary production in the Ulleung Basin was analyzed based on MODIS-derived monthly primary production for a better annual production budget. Based on the MODIS-derived primary production, the mean daily primary productivity was 766.8 mg C m-2 d-1 (SD=+/- 196.7 mg C m-2 d-1) and the annual primary productivity was 280.2 g C m-2 yr-1 (SD=+/- 14.9 g C m-2 yr-1) in the Ulleung Basin during the study period. The monthly contributions of primary production were not largely variable among different months, and a relatively small interannual production variability was also observed in the Ulleung Basin, which indicates that the Ulleung Basin is a sustaining biologically productive region called as hot spot in the East Sea. However, a significant recent decline in the annual primary production was observed in the Ulleung Basin after 2006. Although no strong possibilities were found in this study, the current warming sea surface temperature and a negative phase PDO index were suggested for the recent declining primary production. For a better understanding of subsequent effects on marine ecosystems, more intensive interdisciplinary field studies will be required in the Ulleung Basin

Hepatocellular Carcinoma: Texture Analysis of Preoperative Computed Tomography Images Can Provide Markers of Tumor Grade and Disease-Free Survival

OBJECTIVE: To investigate the usefulness of computed tomography (CT) texture analysis (CTTA) in estimating histologic tumor grade and in predicting disease-free survival (DFS) after surgical resection in patients with hepatocellular carcinoma (HCC). MATERIALS AND METHODS: Eighty-one patients with a single HCC who had undergone quadriphasic liver CT followed by surgical resection were enrolled. Texture analysis of tumors on preoperative CT images was performed using commercially available software. The mean, mean of positive pixels (MPP), entropy, kurtosis, skewness, and standard deviation (SD) of the pixel distribution histogram were derived with and without filtration. The texture features were then compared between groups classified according to histologic grade. Kaplan-Meier and Cox proportional hazards analyses were performed to determine the relationship between texture features and DFS. RESULTS: SD and MPP quantified from fine to coarse textures on arterial-phase CT images showed significant positive associations with the histologic grade of HCC (p < 0.05). Kaplan-Meier analysis identified most CT texture features across the different filters from fine to coarse texture scales as significant univariate markers of DFS. Cox proportional hazards analysis identified skewness on arterial-phase images (fine texture scale, spatial scaling factor [SSF] 2.0, p < 0.001; medium texture scale, SSF 3.0, p < 0.001), tumor size (p = 0.001), microscopic vascular invasion (p = 0.034), rim arterial enhancement (p = 0.024), and peritumoral parenchymal enhancement (p = 0.010) as independent predictors of DFS. CONCLUSION: CTTA was demonstrated to provide texture features significantly correlated with higher tumor grade as well as predictive markers of DFS after surgical resection of HCCs in addition to other valuable imaging and clinico-pathologic parameters

Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories

Hydrogen bonds (H-bonds) play a key role in both the formation and stabilization of protein structures. H-bonds involving atoms from residues that are close to each other in the main-chain sequence stabilize secondary structure elements. H-bonds between atoms from distant residues stabilize a protein’s tertiary structure. However, H-bonds greatly vary in stability. They form and break while a protein deforms. For instance, the transition of a protein from a nonfunctional to a functional state may require some H-bonds to break and others to form. The intrinsic strength of an individual H-bond has been studied from an energetic viewpoint, but energy alone may not be a very good predictor. Other local interactions may reinforce (or weaken) an H-bond. This paper describes inductive learning methods to train a protein-independent probabilistic model of H-bond stability from molecular dynamics (MD) simulation trajectories. The training data describes H-bond occurrences at successive times along these trajectories by the values of attributes called predictors. A trained model is constructed in the form of a regression tree in which each non-leaf node is a Boolean test (split) on a predictor. Each occurrence of an H-bond maps to a path in this tree from the root to a leaf node. Its predicted stability is associated with the leaf node. Experimental results demonstrate that such models can predict H-bond stability quite well. In particular, their performance is roughly 20 % better than that of models based on H-bond energy alone. In addition, they can accurately identify a large fraction of the least stable H-bonds in a give

Defective Fluid Secretion from Submucosal Glands of Nasal Turbinates from CFTR-/- and CFTRΔF508/ΔF508 Pigs

Cystic fibrosis (CF), caused by reduced CFTR function, includes severe sinonasal disease which may predispose to lung disease. Newly developed CF pigs provide models to study the onset of CF pathophysiology. We asked if glands from pig nasal turbinates have secretory responses similar to those of tracheal glands and if CF nasal glands show reduced fluid secretion.Unexpectedly, we found that nasal glands differed from tracheal glands in five ways, being smaller, more numerous (density per airway surface area), more sensitive to carbachol, more sensitive to forskolin, and nonresponsive to Substance P (a potent agonist for pig tracheal glands). Nasal gland fluid secretion from newborn piglets (12 CF and 12 controls) in response to agonists was measured using digital imaging of mucus bubbles formed under oil. Secretion rates were significantly reduced in all conditions tested. Fluid secretory rates (Controls vs. CF, in pl/min/gland) were as follows: 3 µM forskolin: 9.2±2.2 vs. 0.6±0.3; 1 µM carbachol: 143.5±35.5 vs. 52.2±10.3; 3 µM forskolin + 0.1 µM carbachol: 25.8±5.8 vs. CF 4.5±0.9. We also compared CF(ΔF508/ΔF508) with CFTR(-/-) piglets and found significantly greater forskolin-stimulated secretion rates in the ΔF508 vs. the null piglets (1.4±0.8, n = 4 vs. 0.2±0.1, n = 7). An unexpected age effect was also discovered: the ratio of secretion to 3 µM forskolin vs. 1 µM carbachol was ∼4 times greater in adult than in neonatal nasal glands.These findings reveal differences between nasal and tracheal glands, show defective fluid secretion in nasal glands of CF pigs, reveal some spared function in the ΔF508 vs. null piglets, and show unexpected age-dependent differences. Reduced nasal gland fluid secretion may predispose to sinonasal and lung infections

Efficacy of Lactic Acid Bacteria (LAB) supplement in management of constipation among nursing home residents

<p>Abstract</p> <p>Background</p> <p>Constipation is a significant problem in the elderly, specifically nursing home and/or extended-care facility residents are reported to suffer from constipation. Lactic acid bacteria (LAB) are beneficial probiotic organisms that contribute to improved nutrition, microbial balance, and immuno-enhancement of the intestinal tract, as well as diarrhea and constipation effect. The objective of this study was to investigate the efficacy of this LAB supplement in the management of nursing home residents.</p> <p>Methods</p> <p>Nineteen subjects (8M, 11F; mean age 77.1 ± 10.1) suffering with chronic constipation were assigned to receive LAB (3.0 × 10¹¹CFU/g) twice (to be taken 30 minutes after breakfast and dinner) a day for 2 weeks in November 2008. Subjects draw up a questionnaire on defecation habits (frequency of defecation, amount and state of stool), and we collected fecal samples from the subjects both before entering and after ending the trial, to investigate LAB levels and inhibition of harmful enzyme activities. Results were tested with SAS and Student's t-test.</p> <p>Results</p> <p>Analysis of questionnaire showed that there was an increase in the frequency of defecation and amount of stool excreted in defecation habit after LAB treatment, but there were no significant changes. And it also affects the intestinal environment, through significantly increase (<it>p </it>< 0.05) fecal LAB levels. In addition, tryptophanase and urease among harmful enzyme activities of intestinal microflora were significantly decreased (<it>p </it>< 0.05) after LAB treatment.</p> <p>Conclusion</p> <p>LAB, when added to the standard treatment regimen for nursing home residents with chronic constipation, increased defecation habit such as frequency of defecation, amount and state of stool. So, it may be used as functional probiotics to improve human health by helping to prevent constipation.</p

Statistical design of personalized medicine interventions: The Clarification of Optimal Anticoagulation through Genetics (COAG) trial

<p>Abstract</p> <p>Background</p> <p>There is currently much interest in pharmacogenetics: determining variation in genes that regulate drug effects, with a particular emphasis on improving drug safety and efficacy. The ability to determine such variation motivates the application of personalized drug therapies that utilize a patient's genetic makeup to determine a safe and effective drug at the correct dose. To ascertain whether a genotype-guided drug therapy improves patient care, a personalized medicine intervention may be evaluated within the framework of a randomized controlled trial. The statistical design of this type of personalized medicine intervention requires special considerations: the distribution of relevant allelic variants in the study population; and whether the pharmacogenetic intervention is equally effective across subpopulations defined by allelic variants.</p> <p>Methods</p> <p>The statistical design of the Clarification of Optimal Anticoagulation through Genetics (COAG) trial serves as an illustrative example of a personalized medicine intervention that uses each subject's genotype information. The COAG trial is a multicenter, double blind, randomized clinical trial that will compare two approaches to initiation of warfarin therapy: genotype-guided dosing, the initiation of warfarin therapy based on algorithms using clinical information and genotypes for polymorphisms in <it>CYP2C9 </it>and <it>VKORC1</it>; and clinical-guided dosing, the initiation of warfarin therapy based on algorithms using only clinical information.</p> <p>Results</p> <p>We determine an absolute minimum detectable difference of 5.49% based on an assumed 60% population prevalence of zero or multiple genetic variants in either <it>CYP2C9 </it>or <it>VKORC1 </it>and an assumed 15% relative effectiveness of genotype-guided warfarin initiation for those with zero or multiple genetic variants. Thus we calculate a sample size of 1238 to achieve a power level of 80% for the primary outcome. We show that reasonable departures from these assumptions may decrease statistical power to 65%.</p> <p>Conclusions</p> <p>In a personalized medicine intervention, the minimum detectable difference used in sample size calculations is not a known quantity, but rather an unknown quantity that depends on the genetic makeup of the subjects enrolled. Given the possible sensitivity of sample size and power calculations to these key assumptions, we recommend that they be monitored during the conduct of a personalized medicine intervention.</p> <p>Trial Registration</p> <p>clinicaltrials.gov: NCT00839657</p

Monitoring of Optimal Cerebral Perfusion Pressure in Traumatic Brain Injured Patients Using a Multi-Window Weighting Algorithm.

Methods to identify an autoregulation guided "optimal" cerebral perfusion pressure (CPPopt) for traumatic brain injury patients (TBI) have been reported through several studies. An important drawback of existing methodology is that CPPopt can be calculated only in ∼50-60% of the monitoring time. In this study, we hypothesized that the CPPopt yield and the continuity can be improved significantly through application of a multi-window and weighting calculation algorithm, without adversely affecting preservation of its prognostic value. Data of 526 severe TBI patients admitted between 2003 and 2015 were studied. The multi-window CPPopt calculation was based on automated curve fitting in pressure reactivity index (PRx)-CPP plots using data from 36 increasing length time windows (2-8 h). The resulting matrix of CPPopts was then averaged in a weighted manner. The yield, continuity, and stability of CPPopt were studied. The difference between patients' actual CPP and CPPopt (ΔCPP) was calculated and the association with outcome was analyzed. Overall, the multi-window method demonstrated more continuous and stable presentation of CPPopt in this cohort. The new method resulted in a mean (±SE) CPPopt yield of 94% ± 2.1%, as opposed to the previous single-window-based CPPopt yield of 51% ± 0.94%. The stability of CPPopt across the whole monitoring period was significantly improved by using the new algorithm (p < 0.001). The relationship between ΔCPP according to the multi-window algorithm and outcome was similar to that for CPPopt calculated on the basis of a single window. In conclusion, this study validates the use of a new multi-window and weighting algorithm for significant improvement of CPPopt yield in TBI patients. This methodological improvement is essential for its clinical application in future CPPopt trials

Cause-specific mortality time series analysis: a general method to detect and correct for abrupt data production changes

<p>Abstract</p> <p>Background</p> <p>Monitoring the time course of mortality by cause is a key public health issue. However, several mortality data production changes may affect cause-specific time trends, thus altering the interpretation. This paper proposes a statistical method that detects abrupt changes ("jumps") and estimates correction factors that may be used for further analysis.</p> <p>Methods</p> <p>The method was applied to a subset of the AMIEHS (Avoidable Mortality in the European Union, toward better Indicators for the Effectiveness of Health Systems) project mortality database and considered for six European countries and 13 selected causes of deaths. For each country and cause of death, an automated jump detection method called Polydect was applied to the log mortality rate time series. The plausibility of a data production change associated with each detected jump was evaluated through literature search or feedback obtained from the national data producers.</p> <p>For each plausible jump position, the statistical significance of the between-age and between-gender jump amplitude heterogeneity was evaluated by means of a generalized additive regression model, and correction factors were deduced from the results.</p> <p>Results</p> <p>Forty-nine jumps were detected by the Polydect method from 1970 to 2005. Most of the detected jumps were found to be plausible. The age- and gender-specific amplitudes of the jumps were estimated when they were statistically heterogeneous, and they showed greater by-age heterogeneity than by-gender heterogeneity.</p> <p>Conclusion</p> <p>The method presented in this paper was successfully applied to a large set of causes of death and countries. The method appears to be an alternative to bridge coding methods when the latter are not systematically implemented because they are time- and resource-consuming.</p