Search Results (31)

Background: A gluten-free diet (GFD) has been shown to be nutritionally inadequate for those with wheat-related disorders. However, the differences in findings and the absence of quantitative analysis limits the interpretation of previous reviews. Objectives: We conducted a systematic review and meta-analysis to identify the risk of micronutrient deficiencies in patients with celiac disease (CeD) and non-celiac gluten or wheat sensitivity (NCWS). Methods: We searched the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, and Web of Science (Ovid) databases. The risk of bias was determined using the ROBINS-1, and the quality of evidence was assessed using the GRADE approach. Results We identified 7940 studies; 46 observational studies (11 cohort, 9 cross-sectional, and 26 case–control) were eligible for analysis. CeD patients had an increased risk of vitamin D and E deficiencies compared with the non-CeD controls. CeD on a GFD had a decreased risk of vitamin D, B12, E, calcium, and iron deficiencies compared with untreated CeD. NCWS had an increased risk of vitamin B12, folate, and iron deficiency compared to the controls. The overall quality of evidence was rated very low. Conclusions: The risk of various micronutrient deficiencies is increased in CeD but is decreased for some after a GFD. Adequately powered studies with a rigorous methodology are needed to inform the risk of nutrient deficiencies in patients with CeD and NCWS. Protocol registration: Prospero-CRD42022313508. Full article

Background: Cancer therapies predispose survivors to a high symptom burden. This study utilized mobile health (mHealth) technology to assess the feasibility of collecting daily symptoms from adult survivors of childhood cancer to evaluate symptom fluctuation and associations with future health-related quality-of-life (HRQOL). Methods: This prospective study used an mHealth platform to distribute a 20-item cancer-related symptom survey (5 consecutive days each month) and an HRQOL survey (the day after the symptom survey) over 3 consecutive months to participants from the Childhood Cancer Survivor Study. These surveys comprised a PROMIS-29 Profile and Neuro-QOL assessed HRQOL. Daily symptom burden was calculated by summing the severity (mild, moderate, or severe) of 20 symptoms. Univariate linear mixed-effects models were used to analyze total, person-to-person, day-to-day, and month-to-month variability for the burden of 20 individual symptoms. Multivariable linear regression was used to analyze the association between daily symptom burden in the first month and HRQOL in the third month, adjusted for covariates. Results: Out of the 60 survivors invited, 41 participated in this study (68% enrollment rate); 83% reported their symptoms ≥3 times and 95% reported HRQOL in each study week across 3 months. Variability of daily symptom burden differed from person-to-person (74%), day-to-day (18%), and month-to-month (8%). Higher first-month symptom burden was associated with poorer HRQOL related to anxiety (regression coefficient: 6.56; 95% CI: 4.10–9.02), depression (6.32; 95% CI: 3.18–9.47), fatigue (7.93; 95% CI: 5.11–10.80), sleep (6.07; 95% CI: 3.43–8.70), pain (5.16; 95% CI: 2.11–8.22), and cognitive function (–6.89; 95% CI: –10.00 to –3.79) in the third month. Conclusions: Daily assessment revealed fluctuations in symptomology, and higher symptom burden was associated with poorer HRQOL in the future. Utilizing mHealth technology for daily symptom assessment improves our understanding of symptom dynamics and sources of variability. Full article

Since the dawn of agriculture, crops have been genetically altered for desirable characteristics. This has included the selection of natural and induced mutants. Increasing the production of plant oils such as soybean (Glycine max) oil as a renewable resource for food and fuel is valuable. Successful breeding for higher oil levels in soybeans, however, usually results in reduced seed protein. A soybean fast neutron population was screened for oil content, and three high oil mutants with minimal reductions in protein levels were found. Three backcross F2 populations derived from these mutants exhibited segregation for seed oil content. DNA was pooled from the high-oil and normal-oil plants within each population and assessed by comparative genomic hybridization. A deletion encompassing 20 gene models on chromosome 14 was found to co-segregate with the high-oil trait in two of the three populations. Eighteen genes in the deleted region have known functions that appear unrelated to oil biosynthesis and accumulation pathways, while one of the unknown genes (Glyma.14G101900) may contribute to the regulation of lipid droplet formation. This high-oil trait can facilitate the breeding of high-oil soybeans without protein reduction, resulting in higher meal protein levels. Full article

A recent study showed the potential of the DA Perten 7200 NIR Spectrometer in detecting chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. However, this instrument is still lab-based and generally suited for point-of-sale testing. To provide a field-deployable version of this technique, an existing light emitting diode (LED)-based instrument that provides discrete NIR wavelength illumination and reflectance spectra over the range of 850–1550 nm was tested. Spectra were collected from rough, brown, and milled rice at different pesticide concentrations and analyzed for quantitative and qualitative measurement using partial least squares regression (PLS) and discriminant analysis (DA). Simulations for two LED-based instruments were also evaluated using corresponding segments of spectra from the DA7200 to represent LED illumination. For the simulation of the existing LED-based instrument (LEDPrototype1) fitted with 850, 910, 940, 970, 1070, 1200, 1300, 1450, and 1550 nm LED wavelengths, resulting R² ranged from 0.52 to 0.71, and the correct classification was 70.4% to 100%. The simulation of a second LED instrument (LEDPrototype2) fitted with 980, 1050, 1200, 1300, 1450, 1550, 1600, and 1650 nm LED wavelengths showed R² of 0.59 to 0.82 and correct classifications of 66% to 100%. These LED wavelengths were selected based on the significant wavelength regions from the PLS regression coefficients of DA7200 and the commercial availability of LED wavelengths. Results showed that it is possible to use a multi-spectral LED-based instrument to detect varying levels of chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. Full article

Wastewater-based epidemiology (WBE) has emerged as a key method for the continuous monitoring of COVID-19 prevalence including circulating SARS-CoV-2 lineages. WBE addresses the limitations of traditional clinical COVID-19 surveillance such as clinical test availability, fluctuating testing rates, and increased reliance on rapid antigen tests. Our study in Perth, Western Australia found a significant positive correlation between SARS-CoV-2 concentrations in wastewater and clinical PCR positivity rates (rs = 0.772; p < 0.001) over an 18-month period that included four successive COVID-19 waves. A strong positive correlation was apparent between the proportions of SARS-CoV-2 lineages in wastewater and clinical cases within the same region (rs = 0.728, p < 0.001), including earlier detection of Omicron and recombinant lineages in wastewater before clinical case confirmation. The successful integration of WBE with healthcare data underscores its critical role in enhancing public health decision-making and pandemic management. This approach not only demonstrates the value of WBE in current global health surveillance efforts but also highlights the potential of WBE to address future public health challenges, as a comprehensive disease monitoring and response approach. Full article

Theileria orientalis Ikeda genotype, a parasite causing a disease in cattle that leads to significant economic challenges in Asia, New Zealand, and Australia, has been identified in seven U.S. States since 2017. Two previously validated PCR tests for Theileria followed by DNA sequencing were performed to test blood samples collected from 219 cattle in Alabama, USA, during the period of 2022–2023. Bidirectional Sanger sequencing revealed that the MPSP gene sequences (639–660 bp) from two cattle in Lee and Mobile Counties of Alabama exhibited a 100% match with those of recognized T. orientalis Ikeda strains, and showed similarities ranging from 76% to 88% with ten other T. orientalis genotypes. A high copy number of T. orientalis Ikeda was detected in the blood of infected cattle (ALP-1: 1.7 × 10⁵ and 1.3 × 10⁶/mL whole blood, six months apart; ALP-2: 7.1 × 10⁶/mL whole blood). Although the confirmed competent vector for T. orientalis Ikeda, Haemaphysalis longicornis tick, has not yet been identified in Alabama, the persistent nature of T. orientalis Ikeda infection and the detection of a high pathogen burden in seemingly healthy cattle in this study suggest that other tick species, as well as shared needles and dehorning procedures, could facilitate pathogen transmission within the herd. Continued investigations are necessary for the surveillance of T. orientalis Ikeda and Haemaphysalis longicornis ticks in Alabama and other U.S. states, along with assessing the pathogenicity of T. orientalis Ikeda infections in cattle. Full article

Uniform grape maturity can be sought by producers to minimise underripe and/or overripe proportions of fruit and limit any undesirable effects on wine quality. Considering that grape heterogeneity is a multifaceted phenomenon, a composite index summarising overall grape heterogeneity was developed to benefit vineyard management and harvest date decisions. A grape heterogeneity index (GHI) was constructed by aggregating the sum of absolute residuals multiplied by the range of values from measurements of total soluble solids, pH, fresh weight, total tannins, absorbance at 520 nm (red colour), 3-isobutyl-2-methoxypyrazine, and malic acid. Management of grape heterogeneity was also studied, using Cabernet Sauvignon grapes grown under four viticultural regimes (normal/low crop load, full/deficit irrigation) during the 2019/2020 and 2020/2021 seasons. Comparisons of GHI scores showed grape variability decreased throughout ripening in both vintages, then significantly increased at the harvest time point in 2020, but plateaued on sample dates nearing the harvest date in 2021. Irrigation and crop load had no effect on grape heterogeneity by the time of harvest in both vintages. Larger vine yield, leaf area index, and pruning weight significantly increased GHI score early in ripening, but no significant relationship was found at the time of harvest. Differences in the Ravaz index, normalised difference vegetation index, and soil electrical conductivity did not significantly change the GHI score. Full article

In this study, a basic insect detection system consisting of a manual-focus camera, a Jetson Nano—a low-cost, low-power single-board computer, and a trained deep learning model was developed. The model was validated through a live visual feed. Detecting, classifying, and monitoring insect pests in a grain storage or food facility in real time is vital to making insect control decisions. The camera captures the image of the insect and passes it to a Jetson Nano for processing. The Jetson Nano runs a trained deep-learning model to detect the presence and species of insects. With three different lighting situations: white LED light, yellow LED light, and no lighting condition, the detection results are displayed on a monitor. Validating using F1 scores and comparing the accuracy based on light sources, the system was tested with a variety of stored grain insect pests and was able to detect and classify adult cigarette beetles and warehouse beetles with acceptable accuracy. The results demonstrate that the system is an effective and affordable automated solution to insect detection. Such an automated insect detection system can help reduce pest control costs and save producers time and energy while safeguarding the quality of stored products. Full article

Seeds play a critical role in ensuring food security for the earth’s 8 billion people. There is great biodiversity in plant seed content traits worldwide. Consequently, the development of robust, rapid, and high-throughput methods is required for seed quality evaluation and acceleration of crop improvement. There has been considerable progress in the past 20 years in various non-destructive methods to uncover and understand plant seed phenomics. This review highlights recent advances in non-destructive seed phenomics techniques, including Fourier Transform near infrared (FT-NIR), Dispersive-Diode Array (DA-NIR), Single-Kernel (SKNIR), Micro-Electromechanical Systems (MEMS-NIR) spectroscopy, Hyperspectral Imaging (HSI), and Micro-Computed Tomography Imaging (micro-CT). The potential applications of NIR spectroscopy are expected to continue to rise as more seed researchers, breeders, and growers successfully adopt it as a powerful non-destructive method for seed quality phenomics. It will also discuss the advantages and limitations that need to be solved for each technique and how each method could help breeders and industry with trait identification, measurement, classification, and screening or sorting of seed nutritive traits. Finally, this review will focus on the future outlook for promoting and accelerating crop improvement and sustainability. Full article

Design priorities for tall and supertall buildings have for some time shifted to achieving more energy efficiency to address the energy needs of the increasing global population. Engineers and architects aim to achieve energy conservation through active and passive approaches, pursuing technological innovations and adopting climate-responsive design. Because of the green movement currently dominating the building industry, tall buildings that need a massive amount of energy to build and operate, and the practical desire to switch from non-renewable to clean renewable energy resources, intense attention has been given to the energy efficiency of tall buildings in the recent past. Due to the vast array of energy-efficient design features, equipment, and applications available now, it is timely to examine the pros and cons of these issues. This review paper is an attempt to comprehensively present and deliberate these issues. It illustrates and discusses the concepts and applications through a few case studies from several continents worldwide. The review shows that the design of tall buildings focusing on energy conservation is an evolutionary process and there is a need for further research about how to face the associated challenges to improve energy efficiency by developing creative solutions and strategies, as well as applying additional innovative technologies. Full article

Generations of sensors have been developed for predicting food sensory profiles to circumvent the use of a human sensory panel, but a technology that can rapidly predict a suite of sensory attributes from one spectral measurement remains unavailable. Using spectra from grape extracts, this novel study aimed to address this challenge by exploring the use of a machine learning algorithm, extreme gradient boosting (XGBoost), to predict twenty-two wine sensory attribute scores from five sensory stimuli: aroma, colour, taste, flavour, and mouthfeel. Two datasets were obtained from absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) spectroscopy with different fusion methods: variable-level data fusion of absorbance and fluorescence spectral fingerprints, and feature-level data fusion of A-TEEM and CIELAB datasets. The results for externally validated models showed slightly better performance using only A-TEEM data, predicting five out of twenty-two wine sensory attributes with R² values above 0.7 and fifteen with R² values above 0.5. Considering the complex biotransformation involved in processing grapes to wine, the ability to predict sensory properties based on underlying chemical composition in this way suggests that the approach could be more broadly applicable to the agri-food sector and other transformed foodstuffs to predict a product’s sensory characteristics from raw material spectral attributes. Full article

Discontinuous fibre reinforced composites enable the manufacture of integrated structural components via the complex flow process of compression moulding. However, such processes can lead to the formation of detrimental weld-lines. Here, the meso-structure of carbon fibre sheet moulding compounds (C-SMC) was analysed using conventional non-destructive techniques and automated eddy current (EC) scanning, as well as destructive methods, in an attempt to identify defects such as weld-lines in this class of materials. Compression-moulded plaques with forced weld-lines in two different configurations (adjacent and opposing flow joints) were analysed, showing up to 80% strength reduction versus a defect-free plaque. The EC-determined local fibre orientation and elucidated local microstructure matched those obtained using conventional techniques, showing a dramatic fibre tow alignment parallel to the weld-lines. It was found that failure occurred in proximity to the “non-uniformity” defect regions identified by EC analyses, demonstrating the use of robot-guided EC for successful defect detection in C-SMC structures. Full article

Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research. Full article

Patients with cancer have been shown to have increased risk of COVID-19 severity. We previously built and validated the COVID-19 Risk in Oncology Evaluation Tool (CORONET) to predict the likely severity of COVID-19 in patients with active cancer who present to hospital. We assessed the differences in presentation and outcomes of patients with cancer and COVID-19, depending on the wave of the pandemic. We examined differences in features at presentation and outcomes in patients worldwide, depending on the waves of the pandemic: wave 1 D614G (n = 1430), wave 2 Alpha (n = 475), and wave 4 Omicron variant (n = 63, UK and Spain only). The performance of CORONET was evaluated on 258, 48, and 54 patients for each wave, respectively. We found that mortality rates were reduced in subsequent waves. The majority of patients were vaccinated in wave 4, and 94% were treated with steroids if they required oxygen. The stages of cancer and the median ages of patients significantly differed, but features associated with worse COVID-19 outcomes remained predictive and did not differ between waves. The CORONET tool performed well in all waves, with scores in an area under the curve (AUC) of >0.72. We concluded that patients with cancer who present to hospital with COVID-19 have similar features of severity, which remain discriminatory despite differences in variants and vaccination status. Survival improved following the first wave of the pandemic, which may be associated with vaccination and the increased steroid use in those patients requiring oxygen. The CORONET model demonstrated good performance, independent of the SARS-CoV-2 variants. Full article

The Dietary Guidelines for Americans recommends giving priority to nutrient-dense foods while decreasing energy-dense foods. Although both flax (Linum usitatissimum) and sorghum (Sorghum bicolor) are rich in various essential minerals, their ionomes have yet to be investigated. Furthermore, previous studies have shown that elevated CO₂ levels could reduce key nutrients in crops. In this study, we analyzed 102 flax and 108 sorghum varieties to investigate their ionomic variations (N, P, K, Ca, Mg, S, B, Zn, Mn, Fe, Cu, and Mo), elemental level interactions, and nutritional value. The results showed substantial genetic variations and elemental correlations in flax and sorghum. While a serving size of 28 g of flax delivers 37% daily value (DV) of Cu, 31% of Mn, 28% of Mg, and 19% of Zn, sorghum delivers 24% of Mn, 16% of Cu, 11% of Mg, and 10% of Zn of the recommended daily value (DV). We identified a set of promising flax and sorghum varieties with superior seed mineral composition that could complement breeding programs for improving the nutritional quality of flax and sorghum. Overall, we demonstrate additional minerals data and their corresponding health and food security benefits within flax and sorghum that could be considered by consumers and breeding programs to facilitate improving seed nutritional content and to help mitigate human malnutrition as well as the effects of rising CO₂ stress. Full article