Micro-organisms growing on rapeseed during storage affect the profile of volatile compounds of virgin rapeseed oil.

BACKGROUND: Micro-organisms populate on rapeseed after harvest during storage depending on the growing conditions. The composition of the bacterial colonization is unknown, although its contribution to the profile of volatile aroma-active compounds determines the sensory quality of virgin cold-pressed rapeseed oil. RESULTS: From four rapeseed samples, 46 bacterial strains were isolated. By DNA-sequencing, the identification of four bacteria species and 17 bacteria genera was possible. In total, 22 strains were selected, based on their typical off-flavors resembling those of virgin sensory bad cold-pressed rapeseed oils. The cultivation of these strains on rapeseed meal agar and examination of volatile compounds by solid phase microextraction-gas chromatography-mass spectrometry allowed the identification of 29 different compounds, mainly degradation products of fatty acids such as alkanes, alkenes, aldehydes, ketones and alcohols and, in addition, sulfur-containing compounds, including one terpene and three pyrazines. From these compounds, 19 are described as aroma-active in the literature. CONCLUSION: Micro-organisms populating on rapeseed during storage may strongly influence the sensory quality of virgin rapeseed oil as a result of the development of volatile aroma-active metabolic products. It can be assumed that occurrence of off-flavor of virgin rapeseed oils on the market are the result of metabolic degradation products produced by micro-organisms populating on rapeseed during storage. © 2017 Society of Chemical Industry.

MeltDB 2.0-advances of the metabolomics software system.

MOTIVATION: The research area metabolomics achieved tremendous popularity and development in the last couple of years. Owing to its unique interdisciplinarity, it requires to combine knowledge from various scientific disciplines. Advances in the high-throughput technology and the consequently growing quality and quantity of data put new demands on applied analytical and computational methods. Exploration of finally generated and analyzed datasets furthermore relies on powerful tools for data mining and visualization. RESULTS: To cover and keep up with these requirements, we have created MeltDB 2.0, a next-generation web application addressing storage, sharing, standardization, integration and analysis of metabolomics experiments. New features improve both efficiency and effectivity of the entire processing pipeline of chromatographic raw data from pre-processing to the derivation of new biological knowledge. First, the generation of high-quality metabolic datasets has been vastly simplified. Second, the new statistics tool box allows to investigate these datasets according to a wide spectrum of scientific and explorative questions. AVAILABILITY: The system is publicly available at https://meltdb.cebitec.uni-bielefeld.de. A login is required but freely available.

Metabolite profiling on wheat grain to enable a distinction of samples from organic and conventional farming systems.

BACKGROUND: Identification of biomarkers capable of distinguishing organic and conventional products would be highly welcome to improve the strength of food quality assurance. Metabolite profiling was used for biomarker search in organic and conventional wheat grain (Triticum aestivum L.) of 11 different old and new bread wheat cultivars grown in the DOK system comparison trial. Metabolites were extracted using methanol and analysed by gas chromatography-mass spectrometry. RESULTS: Altogether 48 metabolites and 245 non-identified metabolites (TAGs) were detected in the cultivar Runal. Principal component analysis showed a sample clustering according to farming systems and significant differences in peak areas between the farming systems for 10 Runal metabolites. Results obtained from all 11 cultivars indicated a greater influence of the cultivar than the farming system on metabolite concentrations. Nevertheless, a t-test on data of all cultivars still detected 5 metabolites and 11 TAGs with significant differences between the farming systems. CONCLUSION: Based on individual cultivars, metabolite profiling showed promising results for the categorization of organic and conventional wheat. Further investigations are necessary with wheat from more growing seasons and locations before definite conclusions can be drawn concerning the feasibility to evolve a combined set of biomarkers for organically grown wheat using metabolite profiles.

The Effects of Complementary Therapies on Patient-Reported Outcomes: An Overview of Recent Systematic Reviews in Oncology.

Many patients with cancer make use of complementary medicine alongside conventional medicine, but clinicians in oncology often lack the knowledge to adequately advise patients on the evidence base for complementary therapies. This study aims to provide an overview of recently published systematic reviews that assess the effects of complementary therapies on patient-reported health outcomes in patients with cancer. Systematic reviews, including a meta-analysis of at least two randomized controlled trials, were identified from the PubMed, Embase, Cochrane Library, CINAHL and PsycINFO databases. The methodological quality was assessed with AMSTAR 2. One hundred systematic reviews were included. The results suggest that several complementary therapies can improve health outcomes reported by patients with cancer, such as acupuncture to relieve pain, music interventions to reduce anxiety and yoga to improve cancer-related fatigue. The side effects related to complementary therapy use are generally mild. The results remain inconclusive for some intervention-outcome combinations. Many of the included systematic reviews insufficiently assessed the causes and impact of bias in their interpretation of the results. This overview of systematic reviews can support clinicians in counselling their patients on this topic and provide directions for future research and clinical practice guidelines in the field of complementary medicine.

Development of Chemometric Models Based on a LC-qToF-MS Approach to Verify the Geographic Origin of Virgin Olive Oil.

In the presented study a non-targeted approach using high-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (HPLC-ESI-qToF-MS) combined with chemometric techniques was used to build a statistical model to verify the geographic origin of virgin olive oils. The sample preparation by means of liquid/liquid extraction of polar compounds was optimized regarding the number of multiple extractions, application of ultrasonic treatment and temperature during concentration of the analytes. The presented workflow for data processing aimed to identify the most predictive features and was applied to a set of 95 olive oils from Spain, Italy, Portugal and Greece. Different strategies for data reduction and multivariate analysis were compared. Stepwise variable selection showed for both applied multivariate models-linear discriminant analysis (LDA) and logit regression (LR)-to be the most suitable variable selection strategy. The 10-fold cross validation of the LDA showed a classification rate of 83.1% for the test set. For the LR models the prediction accuracy of the test set was even higher with values of 90.4% (Portugal), 86.2% (Italy), 93.8% (Greece) and 88.3% (Spain). Moreover, the reduction of features allows an easier following up strategy for identification of the unknowns and defining marker substances.

A Randomized Study of Yoga for Fatigue and Quality of Life in Women with Breast Cancer Undergoing (Neo) Adjuvant Chemotherapy.

OBJECTIVES: To compare the effectiveness of yoga added to standard care (SC) versus SC only, in women with breast cancer during chemotherapy. DESIGN: A multicenter pragmatic, randomized controlled study. SETTINGS/LOCATION: Three hospitals in the Netherlands. SUBJECTS: Women with stage I-III breast cancer undergoing chemotherapy. INTERVENTIONS: Women were randomized either to a program based on Dru Yoga, once a week yoga sessions for 12 weeks (N = 47), or SC only (N = 36). OUTCOME MEASURES: Primary outcome fatigue (Multidimensional Fatigue Inventory [MFI]; general fatigue) and secondary outcomes fatigue (MFI, Fatigue Quality List [FQL]), quality of life (30-item Quality of Life Questionnaire-C of the European Organization for Research and Treatment of Cancer [EORTC-QLQ-C-30]) and psychological distress (Hospital Anxiety Depression Scale [HADS], Impact of Events Scale [IES]) were measured at baseline (T0), 3 months (T1), and 6 months (T2) and analyzed on observed cases. Other outcomes were adequate relief, reintegration to work, and adverse events. RESULTS: No significant differences were found in general fatigue at T1 (MFI: yoga; 14.6 ± 4.5 vs. SC; 14.2 ± 4.2, p = 0.987). Similar findings were observed for other fatigue (sub)scales of MFI and FQL and functional domains of EORTC. With respect to EORTCs symptom scales, women in the yoga group reported significantly less nausea and vomiting compared with SC at T2 (p = 0.004), but not at T1 (p = 0.807). Depressive symptoms were significantly lower with yoga at T1 (HADS: yoga; 4.7 ± 4.1 vs. SC; 5.1 ± 4.2, p = 0.031). More women in the yoga group experienced adequate relief compared with SC at T1 (yoga; 51% vs. SC; 19%) and had returned to work at T2 (yoga; 53% vs. SC; 23%). No adverse events were reported with yoga. CONCLUSIONS: A Dru-based yoga program failed to demonstrate a significant beneficial effect on fatigue. Possible favorable effects of the yoga program on nausea and vomiting and early return to work in breast cancer survivors warrant further research.

Metabolic Changes during Storage of Brassica napus Seeds under Moist Conditions and the Consequences for the Sensory Quality of the Resulting Virgin Oil.

Virgin rapeseed (Brassica napus) oil is a valuable niche product, if delivered with a high quality. In this study, the effects of moist storage of B. napus seeds for 1 to 4 days on the seed metabolome and the chemo-sensory properties of the produced oils were determined. The concentrations of several primary metabolites, including monosaccharides and amino acids, rapidly increased in the seeds, probably indicating the breakdown of storage compounds to support seed germination. Seed concentrations of indole glucosinolates increased with a slight time offset suggesting that amino acids may be used to modify secondary metabolism. The volatile profiles of the oils were pronouncedly influenced by moist seed storage, with the sensory quality of the oils decreasing. This study provides a direct time-resolved link between seed metabolism under moist conditions and the quality of the resulting oils, thereby emphasizing the crucial role of dry seed storage in ensuring high oil quality.

Learning to Classify Organic and Conventional Wheat - A Machine Learning Driven Approach Using the MeltDB 2.0 Metabolomics Analysis Platform.

We present results of our machine learning approach to the problem of classifying GC-MS data originating from wheat grains of different farming systems. The aim is to investigate the potential of learning algorithms to classify GC-MS data to be either from conventionally grown or from organically grown samples and considering different cultivars. The motivation of our work is rather obvious nowadays: increased demand for organic food in post-industrialized societies and the necessity to prove organic food authenticity. The background of our data set is given by up to 11 wheat cultivars that have been cultivated in both farming systems, organic and conventional, throughout 3 years. More than 300 GC-MS measurements were recorded and subsequently processed and analyzed in the MeltDB 2.0 metabolomics analysis platform, being briefly outlined in this paper. We further describe how unsupervised (t-SNE, PCA) and supervised (SVM) methods can be applied for sample visualization and classification. Our results clearly show that years have most and wheat cultivars have second-most influence on the metabolic composition of a sample. We can also show that for a given year and cultivar, organic and conventional cultivation can be distinguished by machine-learning algorithms.

Arthralgia during aromatase inhibitor treatment in early breast cancer patients: prevalence, impact, and recognition by healthcare providers.

BACKGROUND: Many breast cancer patients experience arthralgia symptoms during aromatase inhibitor (AI) treatment, which leads to poor compliance and a lower quality of life. OBJECTIVE: The research questions of this study were as follows: (1) What is the incidence of arthralgia during AI treatment in early breast cancer patients, (2) what is the impact of AI-associated arthralgia on hand function, daily activities, and AI adherence, and (3) does the healthcare provider recognize AI-associated arthralgia as relevant in clinical practice? METHODS: A total of 57 breast cancer patients of a University Breast Cancer Clinic participated in this study. Each patient completed a questionnaire, performed 2 function tests (goniometry of the wrist and a handgrip strength measurement), and consented to a review of the medical chart. RESULTS: Forty-two breast cancer patients (74%) reported symptoms of arthralgia. All patients with arthralgia symptoms experienced an impact on their daily activities, and 65% had a decrease in hand and finger function. Sixty-nine percent of all patients were fully adherent in their medicine treatment. In 26% of cases with arthralgia, the symptoms were not reported in the medical chart. CONCLUSION: Given the large number of patients with AI-associated arthralgia and its impact on daily life and functioning, it is of great importance to improve the recognition and care of arthralgia symptoms during AI treatment. IMPLICATIONS FOR PRACTICE: Oncology nurses could play an important role in assessment of modifiable risk factors, providing lifestyle advice and support in coping.

(18)F-FLT-PET for Response Evaluation of MEK Inhibitor Selumetinib (AZD6244, ARRY-142886) in Patients with Solid Tumors.

Selumetinib (AZD6244, ARRY-142886) is a potent, selective, uncompetitive inhibitor of MEK 1 / 2, part of the RAF/MEK/ERK protein kinase signal cascade, which is responsible for tumor. This pilot study was used to explore if (18)F-fluoro-l-thymidine (FLT), a thymidine analogue positron emission tomography (PET) tracer and a surrogate marker for proliferation, can be used as an early predictor of response for patients with solid cancers treated with Selumetinib. FLT-PET scans were performed in four patients at baseline and after 2 weeks of treatment with Selumetinib. FLT uptake in tumors was analyzed qualitatively and quantitatively by measuring standard uptake value (SUV) max in regions of interest (ROI). Results were compared to computed tomography (CT) scans (baseline and after 8 weeks), which were evaluated using the response evaluation criteria in solid tumors (RECIST) 1.0 criteria. One patient with melanoma showed both a qualitative and quantitative decrease in FLT uptake associated with a decrease in sum of longest diameter of 12% RECIST on CT evaluation. Another patient who had colorectal carcinoma (CRC) showed a significant increase in FLT uptake with initially stable, but eventually progressive disease on CT. The other two patients (one with melanoma and one with CRC) showed no significant changes in FLT uptake, whereas CT evaluation showed progressive disease. This is the first report describing changes in FLT-PET in patients receiving Selumetinib. In two patients, changes in FLT uptake as early as after 2 weeks of treatment were consistent with CT results after 8 weeks. Biomarkers to predict and evaluate treatment the outcome of targeted therapies are highly warranted. These initial results need further investigation.