Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level.

Awareness that disease susceptibility is not only dependent on genetic make up, but can be affected by lifestyle decisions, has brought more attention to the role of diet. However, food is often treated as a black box, or the focus is limited to few, well-studied compounds, such as polyphenols, lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently occurring phytochemical-disease pairs and we identified 20,654 phytochemicals from 16,102 plants associated to 1,592 human disease phenotypes. We selected colon cancer as a case study and analyzed our results in three directions; i) one stop legacy knowledge-shop for the effect of food on disease, ii) discovery of novel bioactive compounds with drug-like properties, and iii) discovery of novel health benefits from foods. This works represents a systematized approach to the association of food with health effect, and provides the phytochemical layer of information for nutritional systems biology research

NutriChem: a systems chemical biology resource to explore the medicinal value of plant-based foods

published_or_final_versio

Exploring mechanisms of diet-colon cancer associations through candidate molecular interaction networks

published_or_final_versio

Prevention of low back pain: effect, cost-effectiveness, and cost-utility of maintenance care - study protocol for a randomized clinical trial

BACKGROUND: Low back pain (LBP) is a prevalent condition and a socioeconomic problem in many countries. Due to its recurrent nature, the prevention of further episodes (secondary prevention), seems logical. Furthermore, when the condition is persistent, the minimization of symptoms and prevention of deterioration (tertiary prevention), is equally important. Research has largely focused on treatment methods for symptomatic episodes, and little is known about preventive treatment strategies. METHODS/DESIGN: This study protocol describes a randomized controlled clinical trial in a multicenter setting investigating the effect and cost-effectiveness of preventive manual care (chiropractic maintenance care) in a population of patients with recurrent or persistent LBP. Four hundred consecutive study subjects with recurrent or persistent LBP will be recruited from chiropractic clinics in Sweden. The primary outcome is the number of days with bothersome pain over 12 months. Secondary measures are self-rated health (EQ-5D), function (the Roland Morris Disability Questionnaire), psychological profile (the Multidimensional Pain Inventory), pain intensity (the Numeric Rating Scale), and work absence. The primary utility measure of the study is quality-adjusted life years and will be calculated using the EQ-5D questionnaire. Direct medical costs as well as indirect costs will be considered. Subjects are randomly allocated into two treatment arms: 1) Symptom-guided treatment (patient controlled), receiving care when patients feel a need. 2) Preventive treatment (clinician controlled), receiving care on a regular basis. Eligibility screening takes place in two phases: first, when assessing the primary inclusion/exclusion criteria, and then to only include fast responders, i.e., subjects who respond well to initial treatment. Data are collected at baseline and at follow-up as well as weekly, using SMS text messages. DISCUSSION: This study investigates a manual strategy (chiropractic maintenance care) for recurrent and persistent LBP and aims to answer questions regarding the effect and cost-effectiveness of this preventive approach. Strict inclusion criteria should ensure a suitable target group and the use of frequent data collection should provide an accurate outcome measurement. The study utilizes normal clinical procedures, which should aid the transferability of the results. TRIAL REGISTRATION: Clinical trials.gov; NCT01539863, February 22, 2012. The first patient was randomized into the study on April 13th 2012

Crystallization and preliminary X-ray diffraction analysis of eukaryotic α2-macroglobulin family members modified by methylamine, proteases and glycosidases

© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd. Summary: α2-Macroglobulin (α2M) has many functions in vertebrate physiology. To understand the basis of such functions, high-resolution structural models of its conformations and complexes with interacting partners are required. In an attempt to grow crystals that diffract to high or medium resolution, we isolated native human α2M (hα2M) and its counterpart from chicken egg white (ovostatin) from natural sources. We developed specific purification protocols, and modified the purified proteins either by deglycosylation or by conversion to their induced forms. Native proteins yielded macroscopically disordered crystals or crystals only diffracting to very low resolution (>20 Å), respectively. Optimization of native hα2M crystals by varying chemical conditions was unsuccessful, while dehydration of native ovostatin crystals improved diffraction only slightly (10 Å). Moreover, treatment with several glycosidases hindered crystallization. Both proteins formed spherulites that were unsuitable for X-ray analysis, owing to a reduction of protein stability or an increase in sample heterogeneity. In contrast, transforming the native proteins to their induced forms by reaction either with methylamine or with peptidases (thermolysin and chymotrypsin) rendered well-shaped crystals routinely diffracting below 7 Å in a reproducible manner.European, Spanish, and Catalan Agencies. Grant Number: FP7-HEALTH-2010-261460; Gums&Joints. Grant Number: FP7-PEOPLE-2011-ITN-290246; RAPID. Grant Number: FP7-HEALTH-2012-306029-2; TRIGGER. Grant Numbers: BFU2012-32862, CSD2006-00015; La Marató de TV3. Grant Numbers: 2009-100732, 2009SGR1036; ESRFPeer Reviewe

Analyzing repeated data collected by mobile phones and frequent text messages. An example of Low back pain measured weekly for 18 weeks

BACKGROUND: Repeated data collection is desirable when monitoring fluctuating conditions. Mobile phones can be used to gather such data from large groups of respondents by sending and receiving frequently repeated short questions and answers as text messages. The analysis of repeated data involves some challenges. Vital issues to consider are the within-subject correlation, the between measurement occasion correlation and the presence of missing values. The overall aim of this commentary is to describe different methods of analyzing repeated data. It is meant to give an overview for the clinical researcher in order for complex outcome measures to be interpreted in a clinically meaningful way. METHODS: A model data set was formed using data from two clinical studies, where patients with low back pain were followed with weekly text messages for 18 weeks. Different research questions and analytic approaches were illustrated and discussed, as well as the handling of missing data. In the applications the weekly outcome “number of days with pain” was analyzed in relation to the patients’ “previous duration of pain” (categorized as more or less than 30 days in the previous year). Research questions with appropriate analytical methods 1: How many days with pain do patients experience? This question was answered with data summaries. 2: What is the proportion of participants “recovered” at a specific time point? This question was answered using logistic regression analysis. 3: What is the time to recovery? This question was answered using survival analysis, illustrated in Kaplan-Meier curves, Proportional Hazard regression analyses and spline regression analyses. 4: How is the repeatedly measured data associated with baseline (predictor) variables? This question was answered using generalized Estimating Equations, Poisson regression and Mixed linear models analyses. 5: Are there subgroups of patients with similar courses of pain within the studied population? A visual approach and hierarchical cluster analyses revealed different subgroups using subsets of the model data. CONCLUSIONS: We have illustrated several ways of analysing repeated measures with both traditional analytic approaches using standard statistical packages, as well as recently developed statistical methods that will utilize all the vital features inherent in the data

Shift work and quality of sleep::Effect of working in designed dynamic light

PURPOSE: To examine the effect of designed dynamic light on staff’s quality of sleep with regard to sleep efficiency, level of melatonin in saliva, and subjective perceptions of quality of sleep. METHODS: An intervention group working in designed dynamic light was compared with a control group working in ordinary institutional light at two comparable intensive care units (ICUs). The study included examining (1) melatonin profiles obtained from saliva samples, (2) quality of sleep in terms of sleep efficiency, number of awakenings and subjective assessment of sleep through the use of sleep monitors and sleep diaries, and (3) subjective perceptions of well-being, health, and sleep quality using a questionnaire. Light conditions were measured at both locations. RESULTS: A total of 113 nurses (88 %) participated. There were no significant differences between the two groups regarding personal characteristics, and no significant differences in total sleep efficiency or melatonin level were found. The intervention group felt more rested (OR 2.03, p = 0.003) and assessed their condition on awakening as better than the control group (OR 2.35, p = 0.001). Intervention-ICU nurses received far more light both during day and evening shifts compared to the control-ICU. CONCLUSIONS: The study found no significant differences in monitored sleep efficiency and melatonin level. Nurses from the intervention-ICU subjectively assessed their sleep as more effective than participants from the control-ICU. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00420-015-1051-0) contains supplementary material, which is available to authorized users