DIANA—algorithmic improvements for analysis of data-independent acquisition MS data

Motivation: Data independent acquisition mass spectrometry has emerged as a reproducible and sensitive alternative in quantitative proteomics, where parsing the highly complex tandem mass spectra requires dedicated algorithms. Recently, targeted data extraction was proposed as a novel analysis strategy for this type of data, but it is important to further develop these concepts to provide quality-controlled, interference-adjusted and sensitive peptide quantification. Results: We here present the algorithm DIANA and the classifier PyProphet, which are based on new probabilistic sub-scores to classify the chromatographic peaks in targeted data-independent acquisition data analysis. The algorithm is capable of providing accurate quantitative values and increased recall at a controlled false discovery rate, in a complex gold standard dataset. Importantly, we further demonstrate increased confidence gained by the use of two complementary data-independent acquisition targeted analysis algorithms, as well as increased numbers of quantified peptide precursors in complex biological samples. Availability and implementation: DIANA is implemented in scala and python and available as open source (Apache 2.0 license) or pre-compiled binaries from http://quantitativeproteomics.org/diana. PyProphet can be installed from PyPi (https://pypi.python.org/pypi/pyprophet). Supplementary information: Supplementary data are available at Bioinformatics onlin

Friend or foe? The current epidemiologic evidence on selenium and human cancer risk.

Scientific opinion on the relationship between selenium and the risk of cancer has undergone radical change over the years, with selenium first viewed as a possible carcinogen in the 1940s then as a possible cancer preventive agent in the 1960s-2000s. More recently, randomized controlled trials have found no effect on cancer risk but suggest possible low-dose dermatologic and endocrine toxicity, and animal studies indicate both carcinogenic and cancer-preventive effects. A growing body of evidence from human and laboratory studies indicates dramatically different biological effects of the various inorganic and organic chemical forms of selenium, which may explain apparent inconsistencies across studies. These chemical form-specific effects also have important implications for exposure and health risk assessment. Overall, available epidemiologic evidence suggests no cancer preventive effect of increased selenium intake in healthy individuals and possible increased risk of other diseases and disorders

Development of a novel scheme for long-term body temperature monitoring: a review of benefits and applications

Body temperature is a health or disease marker that has been in clinical use for centuries. The threshold currently applied to define fever, with small variations, is 38 °C. However, current approaches do not provide a full picture of the thermoregulation process and its correlation with disease. This paper describes a new non-invasive body temperature device that improves the understanding of the pathophysiology of diseases by integrating a variety of temperature data from different body locations. This device enables to gain a deeper insight into fever, endogenous rhythms, subject activity and ambient temperature to provide anticipatory and more efficient treatments. Its clinical use would be a big step in the overcoming of the anachronistic febrile/afebrile dichotomy and walking towards a system medicine approach to certain diseases. This device has already been used in some clinical applications successfully. Other possible applications based on the device features and clinical requirements are also described in this paper.Cuesta Frau, D.; Varela Entrecanales, M.; Valor Pérez, R.; Vargas, B. (2015). Development of a novel scheme for long-term body temperature monitoring: a review of benefits and applications. Journal of Medical Systems. 39(4):1-7. doi:10.1007/s10916-015-0209-3S17394Gai, M., Merlo, I., Dellepiane, S., Cantaluppi, V., Leonardi, G., Fop, F., Guarena, C., Grassi, G., and Biancore, L., Glycemic pattern in diabetic patients on hemodialysis: Continuous Glucose Monitoring (CGM) analysis. Blood Purif. 38(1):68–73 , 2014.Kondziella, D., Friberg, C.K., Wellwood, I., Reiffurth, C., Fabricius, M., and Dreier, J.P.: Continuous EEG monitoring in aneurysmal subarachnoid hemorrhage: A systematic review. Neurocrit. Care (2014)Ciccone, A., Celani, M.G., Chiaramonte, R., Rossi, C., and Righetti, E., Continuous versus intermittent physiological monitoring for acute stroke. Cochrane Database Syst. Rev. 31, 2013.Kushimoto, S., Yamanouchi, S., Endo, T., Sato, T., Nomura, R., Fujita, M., Kudo, D., Omura, T., Miyagawa, N., and Sato, T., Body temperature abnormalities in non-neurological critically ill patients: A review of the literature. J. Intensive Care 2, 2014.Mc Callum, L., and Higgings, D., Measuring body temperature. Nursing Times 108:20–22, 2012.Varela, M., Ruiz-Esteban, R., Martinez-Nicolas, A., Cuervo-Arango, A., Barros, C., and Delgado, E.G., Catching the spike and tracking the flow: Holter-temperature monitoring in patients admitted in a general internal medicine ward. Int. J. Clin. Pract. 65(12):1283–1288, 2011.Lopes, F., Peres, D., Bross, A., Melot, C., and Vincent, J.L., Serial evaluation of the SOFA score to predict outcome in critically ill patients. J. Am. Med. Assoc. 286:1754–1758, 2001.Vincent, J.L., and Moreno, R., Clinical review: Scoring systems in the critically ill. Crit. Care, 14, 2010.Sund-Levander, M., and Grodzinsky, E., Time for a change to assess and evaluate body temperature in clinical practice. Int. J. Nurs. Pract. 15:241–249, 2009.Cuesta-Frau, D., Varela, M., Aboy, M., and Miro, P., Description of a portable wireless device for body temperature acquisition and analysis. Sensors 9(10):7648–7663, 2009.Varela, M., Cuesta-Frau, D., Madrid, J.A., Churruca, J., Miro-Matinez, P., Ruiz, R., and Marinez, C., Holter monitoring of central peripheral temperature: Possible uses and feasibility study in outpatient settings. J. Clin. Monit. Comput. 4(23):209–216, 2009.Jordan, J., Miro, P., Cuesta-Frau, D., Varela, M., and Vargas B.: Aplicacion de analisis multivariante para la deteccion de estados prefebriles en pacientes ingresados (in Spanish), XXXIV Congreso Nacional de Estadistica e Investigacion Operativa, Castellon (Spain) (2013)Richman, J., and Moorman, J.R., Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278(6):H2039–2049, 2000.Young, P., Saxena, M., Eastwood, G.M., Bellomo, R., and Beasley, R., Fever and fever management among intensive care patients with known or suspected infection: A multicentre prospective cohort study. Crit. Care Resusc. 13:97–102 , 2011.Drewry, A.M., Fuller, B.M., Bailey, T.C., and Hotchkiss, R.S., Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients: A case-control study. Crit. Care,17, 2013.Musher, D., Fainstein, V., Young, E., and Pruett, T., Fever patterns. Their lack of significance. Arch. Intern. Med. 139(11):1225–8, 1979.Varela, M., Calvo, M., Chana, M., Gomez-Mestre, I., Asensio, R., and Galdos, P., Clinical implications of temperature curve complexity in critically ill patients. Crit. Care Med. 33(12):2764–2771, 2005.Varela, M., Churruca, J., Gonzalez, A., Martin, A., Ode, J., and Galdos, P., Temperature curve complexity predicts survival in critically ill patients. Am. J. Respir. Crit. Care Med. 174(3):290–298, 2006.Cuesta-Frau, D., Varela, M., Miro, P., Galdos, P., Abasolo, D., Hornero, R., and Aboy, M., Predicting survival in critical patients by use of body temperature regularity measurement based on Approximate Entropy. Med. Biol. Eng. Computing 45:671–678, 2007.Mackiowak, P. Temperature regulation and the pathogenesis of fever, Principles and Practice of Infectious Diseases, pp. 765–778. New York: Churchill Livingston Elsevier, 2010.Cherbuin N., and Brinkman C., Cognition is cool: Can hemispheric activation be assessed by tympanic membrane thermometry? Brain Cogn. 54:228–231, 2004

Psychosocial correlates with depressive symptoms six years after a first episode of psychosis as compared with findings from a general population sample

BACKGROUND: Depression is frequently occurring during and after psychosis. The aim of this study was to analyze if the psychosocial characteristics associated with depression/depressive symptoms in the late phase of a first episode psychosis (FEP) population were different compared to persons from the general population. METHODS: A questionnaire was sent out to all individuals six years after their FEP and to a general population sample. Depressive symptoms were recorded using a self-rating scale, the Major Depression Inventory. RESULTS: Formerly FEP persons had a higher representation of depressive symptoms/depression, unemployment, financial problems and insufficient social network. Depressive symptoms/depression were found to be associated with psychosocial problems. An age and gender effect was found in the general population, but not in the FEP sample. When the psychosocial characteristics were taken into account there were no association between having had FEP and depressive symptoms. CONCLUSIONS: The association between having been a FEP patient and depressive symptoms/depression disappeared when negative social aspects were taken into account

Changes in cognitive domains during three years in patients with Alzheimer's disease treated with donepezil

<p>Abstract</p> <p>Background</p> <p>The objective was to identify separate cognitive domains in the standard assessment tools (MMSE, ADAS-Cog) and analyze the process of decline within domains during three years in Alzheimer's disease (AD) patients with donepezil treatment.</p> <p>Method</p> <p>AD patients (n = 421) were recruited from a clinical multi-centre study program in Sweden. Patients were assessed every six months during three years. All patients received donepezil starting directly after study entry. After dropouts, 158 patients remained for analyses over three years. Data for the other patients were analysed until they dropped out (4 groups based on length in study).</p> <p>Results</p> <p>Factor analyses of all items suggested that there were three intercorrelated factors: a General, a Memory and a Spatial factor for which we constructed corresponding domains. Overall there was a cognitive improvement at six months followed by a linear drop over time for the three domains. Some group and domain differences were identified. Patients who remained longer in the study had better initial performance and a slower deterioration rate. The early dropouts showed no improvement at six months and many dropped out due to side effects. The other groups displayed a performance improvement at six months that was less pronounced in the Memory domain. Before dropping out, deterioration accelerated, particularly in the Spatial domain.</p> <p>Conclusion</p> <p>The course of illness in the three domains was heterogeneous among the patients. We were not able to identify any clinically relevant correlates of this heterogeneity. As an aid we constructed three algorithms corresponding to the cognitive domains, which can be used to characterize patients initially, identify rapid decliners and follow the course of the disease.</p

A case–control study of selenium in nails and prostate cancer risk in British men

In view of the experimental evidence suggesting that the micronutrient selenium reduces prostate cancer risk, we investigated the association between the selenium level in fingernails, a measure of long-term selenium intake, and prostate cancer risk in a case-control study among 656 British men, conducted in 1989-1992. Nail clippings were taken at the time of recruitment and selenium concentration, measured using neutron activation techniques, was successfully assayed for 300 case-control pairs and varied six-fold among the controls (0.59 p.p.m.; interquartile range, 0.50-0.71 p.p.m.). Nail selenium concentration was not significantly associated with prostate cancer risk: men in the highest quartile of nail selenium had a slightly increased risk compared with men in the lowest quartile (OR 1.24, 95 CI, 0.73-2.10); for advanced prostate cancer, men in the highest quartile had a slightly reduced risk compared with men in the lowest quartile (OR 0.78, 95% CI, 0.27-2.25). These results suggest that selenium is not strongly associated with prostate cancer risk in British men

Allomorphy as a mechanism of post-translational control of enzyme activity

Enzyme regulation is vital for metabolic adaptability in living systems. Fine control of enzyme activity is often delivered through post-translational mechanisms, such as allostery or allokairy. β-phosphoglucomutase (βPGM) from Lactococcus lactis is a phosphoryl transfer enzyme required for complete catabolism of trehalose and maltose, through the isomerisation of β-glucose 1-phosphate to glucose 6-phosphate via β-glucose 1,6-bisphosphate. Surprisingly for a gatekeeper of glycolysis, no fine control mechanism of βPGM has yet been reported. Herein, we describe allomorphy, a post-translational control mechanism of enzyme activity. In βPGM, isomerisation of the K145-P146 peptide bond results in the population of two conformers that have different activities owing to repositioning of the K145 sidechain. In vivo phosphorylating agents, such as fructose 1,6-bisphosphate, generate phosphorylated forms of both conformers, leading to a lag phase in activity until the more active phosphorylated conformer dominates. In contrast, the reaction intermediate β-glucose 1,6-bisphosphate, whose concentration depends on the β-glucose 1-phosphate concentration, couples the conformational switch and the phosphorylation step, resulting in the rapid generation of the more active phosphorylated conformer. In enabling different behaviours for different allomorphic activators, allomorphy allows an organism to maximise its responsiveness to environmental changes while minimising the diversion of valuable metabolites

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology