Cultivar and Year-to-Year Variation of Phytosterol Content in Rye (Secale cereale L.)

Intake of phytosterols (and -stanols) has been shown to decrease the level of low-density lipoprotein cholesterol and thus protect against development of cardiovascular diseases. Therefore, studies on the cultivar and year-to-year variation in phytosterol content in rye grains have been performed. The phytosterol content and composition of different rye cultivars, grown under identical conditions on the same field in three consecutive years, were analyzed. Both cultivar and year-to-year variation in sterol content were statistically significant (p < 0.0001). The total sterol content varied from 1007 ± 21 mg/kg in the highest yielding cultivar, Tsulpan 3, to 761 ± 10 mg/kg in the lowest yielding cultivar (Amando in the 1999 harvest). Because the meteorological conditions varied substantially between the different years, it was possible to deduce the impact of varying weather conditions on phytosterol content in the different cultivars. The studied cultivars had all the lowest phytosterol contents in the dry and warm harvest season of 1999. Although there were statistically significant cultivar and year-to-year variations in the sterol composition (p < 0.0001), these were only between 2 and 4% of the total sterol content

Materials characterisation and software tools as key enablers in Industry 5.0 and wider acceptance of new methods and products

Recently, the NMBP-35 Horizon 2020 projects -NanoMECommons, CHARISMA, and Easi-stress -organised a collaborative workshop to increase awareness of their contributions to the industry "commons" in terms of characterisation and digital transformation. They have established interoperability standards for knowledge management in characterisation and introduced new solutions for materials testing, aided by the standardisation of faster and more accurate assessment methods. The lessons learned from these projects and the discussions during the joint workshop emphasised the impact of recent developments and emerging needs in the field of characterisation. Specifically, the focus was on enhancing data quality through harmonisation and stand-ardisation, as well as making advanced technologies and instruments accessible to a broader community with the goal of fostering increased trust in new products and a more skilled society. Experts also highlighted how characterisation and the corresponding experimental data can drive future innovation agendas towards tech-nological breakthroughs. The focus of the discussion revolved around the characterisation and standardisation processes, along with the collection of modelling and characterisation tools, as well as protocols for data ex-change. The broader context of materials characterisation and modelling within the materials community was explored, drawing insights from the Materials 2030 Roadmap and the experiences gained from NMBP-35 pro-jects. This whitepaper has the objective of addressing common challenges encountered by the materials com-munity, illuminating emerging trends and evolving techniques, and presenting the industry's perspective on emerging requirements and past success stories. It accomplishes this by providing specific examples and high-lighting how these experiences can create fresh opportunities and strategies for newcomers entering the market. These advancements are anticipated to facilitate a more efficient transition from Industry 4.0 to 5.0 during the industrial revolution

Time to Recurrence and Survival in Serous Ovarian Tumors Predicted from Integrated Genomic Profiles

Serous ovarian cancer (SeOvCa) is an aggressive disease with differential and often inadequate therapeutic outcome after standard treatment. The Cancer Genome Atlas (TCGA) has provided rich molecular and genetic profiles from hundreds of primary surgical samples. These profiles confirm mutations of TP53 in ∼100% of patients and an extraordinarily complex profile of DNA copy number changes with considerable patient-to-patient diversity. This raises the joint challenge of exploiting all new available datasets and reducing their confounding complexity for the purpose of predicting clinical outcomes and identifying disease relevant pathway alterations. We therefore set out to use multi-data type genomic profiles (mRNA, DNA methylation, DNA copy-number alteration and microRNA) available from TCGA to identify prognostic signatures for the prediction of progression-free survival (PFS) and overall survival (OS). prediction algorithm and applied it to two datasets integrated from the four genomic data types. We (1) selected features through cross-validation; (2) generated a prognostic index for patient risk stratification; and (3) directly predicted continuous clinical outcome measures, that is, the time to recurrence and survival time. We used Kaplan-Meier p-values, hazard ratios (HR), and concordance probability estimates (CPE) to assess prediction performance, comparing separate and integrated datasets. Data integration resulted in the best PFS signature (withheld data: p-value = 0.008; HR = 2.83; CPE = 0.72).We provide a prediction tool that inputs genomic profiles of primary surgical samples and generates patient-specific predictions for the time to recurrence and survival, along with outcome risk predictions. Using integrated genomic profiles resulted in information gain for prediction of outcomes. Pathway analysis provided potential insights into functional changes affecting disease progression. The prognostic signatures, if prospectively validated, may be useful for interpreting therapeutic outcomes for clinical trials that aim to improve the therapy for SeOvCa patients

A Critical Review on the Structural Health Monitoring Methods of the Composite Wind Turbine Blades

With increasing turbine size, monitoring of blades becomes increasingly im-portant, in order to prevent catastrophic damages and unnecessary mainte-nance, minimize the downtime and labor cost and improving the safety is-sues and reliability. The present work provides a review and classification of various structural health monitoring (SHM) methods as strain measurement utilizing optical fiber sensors and Fiber Bragg Gratings (FBG’s), active/ pas-sive acoustic emission method, vibration‒based method, thermal imaging method and ultrasonic methods, based on the recent investigations and prom-ising novel techniques. Since accuracy, comprehensiveness and cost-effectiveness are the fundamental parameters in selecting the SHM method, a systematically summarized investigation encompassing methods capabilities/ limitations and sensors types, is needed. Furthermore, the damages which are included in the present work are fiber breakage, matrix cracking, delamina-tion, fiber debonding, crack opening at leading/ trailing edge and ice accre-tion. Taking into account the types of the sensors relevant to different SHM methods, the advantages/ capabilities and disadvantages/ limitations of repre-sented methods are nominated and analyzed