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The World Cancer Research Fund and American Institute for Cancer Research (WCRF/AICR) advise cancer survivors to follow their lifestyle recommendations for cancer prevention. Adhering to these recommendations may have beneficial effects on patient-reported outcomes after a cancer diagnosis, but evidence is scarce. We aimed to assess associations of the individual dietary WCRF/AICR recommendations regarding fruit and vegetables, fibre, fast foods, red and processed meat, sugar-sweetened drinks and alcohol consumption with patient-reported outcomes in colorectal cancer (CRC) survivors. Cross-sectional data of 150 stage I–III CRC survivors, 2–10 years post-diagnosis, were used. Dietary intake was measured by 7-d dietary records. Validated questionnaires were used to measure health-related quality of life (HRQoL), fatigue and neuropathy. Confounder-adjusted linear regression models were used to analyse associations of each WCRF/AICR dietary recommendation with patient-reported outcomes. Higher vegetable intake (per 50 g) was associated with better global QoL (β 2·6; 95 % CI 0·6, 4·7), better physical functioning (3·3; 1·2, 5·5) and lower levels of fatigue (−4·5; −7·6, −1·4). Higher fruit and vegetables intake (per 100 g) was associated with better physical functioning (3·2; 0·8, 5·5) and higher intake of energy-dense food (per 100 kJ/100 g) with worse physical functioning (−4·2; −7·1, −1·2). No associations of dietary recommendations with neuropathy were found. These findings suggest that adhering to specific dietary WCRF/AICR recommendations is associated with better HRQoL and less fatigue in CRC survivors. Although the recommendations regarding healthy dietary habits may be beneficial for the well-being of CRC survivors, longitudinal research is warranted to gain insight into the direction of associations.
The Eating Assessment in Toddlers FFQ (EAT FFQ) has been shown to have good reliability and comparative validity for ranking nutrient intakes in young children. With the addition of food items (n 4), we aimed to re-assess the validity of the EAT FFQ and estimate calibration factors in a sub-sample of children (n 97) participating in the Growing Up Milk – Lite (GUMLi) randomised control trial (2015–2017). Participants completed the ninety-nine-item GUMLi EAT FFQ and record-assisted 24-h recalls (24HR) on two occasions. Energy and nutrient intakes were assessed at months 9 and 12 post-randomisation and calibration factors calculated to determine predicted estimates from the GUMLi EAT FFQ. Validity was assessed using Pearson correlation coefficients, weighted kappa (κ) and exact quartile categorisation. Calibration was calculated using linear regression models on 24HR, adjusted for sex and treatment group. Nutrient intakes were significantly correlated between the GUMLi EAT FFQ and 24HR at both time points. Energy-adjusted, de-attenuated Pearson correlations ranged from 0·3 (fibre) to 0·8 (Fe) at 9 months and from 0·3 (Ca) to 0·7 (Fe) at 12 months. Weighted κ for the quartiles ranged from 0·2 (Zn) to 0·6 (Fe) at 9 months and from 0·1 (total fat) to 0·5 (Fe) at 12 months. Exact agreement ranged from 30 to 74 %. Calibration factors predicted up to 56 % of the variation in the 24HR at 9 months and 44 % at 12 months. The GUMLi EAT FFQ remained a useful tool for ranking nutrient intakes with similar estimated validity compared with other FFQ used in children under 2 years.
Dark-field x-ray microscopy is intended for the acquisition of three -dimensional (3D) movies of the nanostructure (grains, domains, and dislocations) and the associated local strain within bulk materials. It is analogous to dark-field electron microscopy in that an objective lens magnifies diffracting features of the sample. The use of high-energy synchrotron x-rays, however, means that these microstructural features can be large and deeply embedded. The spatial and angular resolution is on the order of 100 nm and 0.001°, respectively, and full maps can be recorded in seconds to minutes. Four applications of the technique are presented—domain switching in ferroelectrics, processing of metals, microstructural characterization of biominerals, and visualization of dislocations. The ability to directly characterize complex, multiscale phenomena in situ—and in 3D—is a key step toward formulating and validating multiscale models that account for the entire heterogeneity of materials.
Three-dimensional (3D) tomographic imaging of the structural, chemical, and physical properties of a material provides key knowledge that links the structure of a material to both its processing and structure that is central to studies across a broad spectrum of materials. For many decades, tomography using x-rays or electrons has proven to be an essential 3D characterization tool. In recent years, advances in technology have significantly pushed the envelope of these techniques in many respects, enabling new imaging capabilities at the nanometer and atomic scale. This article highlights several such developments in nanoscale x-ray and electron tomography. The five articles that appear in this issue of MRS Bulletin discuss research frontiers that include multimodal x-ray tomography at the nanoscale, x-ray spectroscopic tomography, dark-field x-ray microscopy, electron nanotomography for functional nanomaterials, and atomistic imaging by electron tomography. These articles give a holistic view of the status of these techniques and promising future directions, as well highlighting their applications for scientific problems.
At the forefront of developments in synchrotron x-ray microscopy, nanoscale-resolution high-dimensional spectrotomography under controlled sample environments has been demonstrated. Such cutting-edge experimental capability has been broadly applied to scientific studies in the field of energy materials science, where the dynamically evolving structural and chemical defects play a vital role in the functionality. In this article, we review novel developments of this technique from both experimental and data/information mining perspectives. Using studies on lithium-ion battery electrode materials as examples, we highlight the rich information in the high-dimensional and high-resolution x-ray tomographic data, which can be used to interpret the complicated thermal-electro-chemo-mechanical interplay that occurs under the operating conditions and collectively determines battery performance. We also discuss the frontier challenges in this field and our perspectives of the future directions in the context of projected major developments in the landscape of large-scale x-ray facilities across the globe.
Perovskite solar cells are at the edge of commercial success. Device efficiency records are being broken at a regular pace, while stability and optimization are progressing rapidly. The first commercial products could reach the market within a year. MRS Bulletin presents coverage of the most recent impactful advances in the burgeoning field of perovskite research.
Atomic electron tomography (AET) has become a powerful tool for atomic-scale structural characterization in three and four dimensions. It provides the ability to correlate structures and properties of materials at the single-atom level. With recent advances in data acquisition methods, iterative three-dimensional (3D) reconstruction algorithms, and post-processing methods, AET can now determine 3D atomic coordinates and chemical species with sub-Angstrom precision, and reveal their atomic-scale time evolution during dynamical processes. Here, we review the recent experimental and algorithmic developments of AET and highlight several groundbreaking experiments, which include pinpointing the 3D atom positions and chemical order/disorder in technologically relevant materials and capturing how atoms rearrange during early nucleation at four-dimensional atomic resolution.