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Association between composite dietary antioxidant indices and anemia: NHANES 2003–2018
Background There is increasing acknowledgment of the potential role that diet rich in antioxidants may play in the prevention of anemia. As a significant indicator of antioxidant-rich diet, the relationship between the composite dietary antioxidant index (CDAI) and anemia has not been extensively studied. Therefore, this study aims to explore the association between CDAI and anemia. Methods Utilizing datas from the 2003–2018 National Health and Nutrition Examination Survey (NHANES) database. The CDAI was calculated using six dietary antioxidants, based on two 24-hour dietary recall interviews, serving as comprehensive measure of the intake of these antioxidants. Weighted multivariable logistic regression and restricted cubic spline (RCS) analysis was conducted to investigate the association between CDAI and anemia. Furthermore, subgroup analyses were performed to enhance datas reliability. Results A total of 33914 participants were included in the study, among which 3,416 (10.07%) were diagnosed with anemia. The unadjusted model showed negative association between CDAI and anemia (odds ratio [OR]: 0.94; 95% confidence interval [95%CI]: 0.93–0.96; P < 0.001). After adjusting for all covariates, with each increase in CDAI level linked to 3% lower risk of anemia (OR: 0.97; 95%CI: 0.95–0.98; P < 0.001). Moreover, when CDAI was categorized into quartiles, the observed trend persisted (P < 0.001). The RCS analysis revealed linear negative relationship between CDAI and anemia (P for nonlinearity = 0.619). Except for sex, smoking, diabetes and hypertension, no statistically significant interactions were found in any subgroup analysis (P < 0.05 for interaction). Conclusion Our findings suggest that CDAI levels are inversely related to the prevalence of anemia. Consequently, monitoring individuals with low CDAI scores may facilitate the timely identification of anemia and enhance clinical decision-making.
The revised colorectal cancer screening guideline and screening burden at community health centers
Local corner smoothing based on deep learning for CNC machine tools
Computational insights into spin-polarized density functional theory applied to actinide-based perovskites XBkO₃ (X = Sr, Ra, Pb)
A filter inspired by deep-sea glass sponges for oil cleanup under turbulent flow
Integrating electronic health records and GWAS summary statistics to predict the progression of autoimmune diseases from preclinical stages
Trade deregulation and fiscal revenue in selected Pacific Island countries
This paper examines the revenue implications of trade deregulation in a panel of Pacific Island countries from 2010 to 2021. First, we undertake a cross-country analysis of tax revenue, trade, and tax structure. Secondly, we empirically analyze the effect of trade deregulation on trade tax and overall government tax revenue. We find that as the countries have become more deregulated over the decade, the trade tax revenues and direct income tax revenues have declined whereas domestic indirect tax revenues have increased. The empirical estimation reveals the potential Laffer effect for trade tax revenues with respect to trade openness. The effect of regional trade agreements also shows some support for trade tax revenues. Further, the external public debt has a significant positive effect on aggregate tax revenues, while foreign aid has been significant in explaining the decline in both aggregate tax revenues as well as trade tax revenues in the selected Pacific Island countries.
Method for long-term room temperature storage of mouse freeze-dried sperm
DSIA U-Net: deep shallow interaction with attention mechanism UNet for remote sensing satellite images
AI-based visualization of loose connective tissue as a dissectable layer in gastrointestinal surgery
AbstractWe aimed to develop an AI model that recognizes and displays loose connective tissue as a dissectable layer in real-time during gastrointestinal surgery and to evaluate its performance, including feasibility for clinical application. Training data were created under the supervision of gastrointestinal surgeons. Test images and videos were randomly sampled and model performance was evaluated visually by 10 external gastrointestinal surgeons. The mean Dice coefficient of the 50 images was 0.46. The AI model could detect at least 75% of the loose connective tissue in 91.8% of the images (459/500 responses). False positives were found for 52.6% of the images, but most were not judged significant enough to affect surgical judgment. When comparing the surgeon’s annotation with the AI prediction image, 5 surgeons judged the AI image was closer to their own recognition. When viewing the AI video and raw video side-by-side, surgeons judged that in 99% of the AI videos, visualization was improved and stress levels were acceptable when viewing the AI prediction display. The AI model developed demonstrated performance at a level approaching that of a gastrointestinal surgeon. Such visualization of a safe dissectable layer may help to reduce intraoperative recognition errors and surgical complications.
Design principles for engineering bacteria to maximise chemical production from batch cultures
AbstractBacteria can be engineered to manufacture chemicals, but it is unclear how to optimally engineer a single cell to maximise production performance from batch cultures. Moreover, the performance of engineered production pathways is affected by competition for the host’s native resources. Here, using a ‘host-aware’ computational framework which captures competition for both metabolic and gene expression resources, we uncover design principles for engineering the expression of host and production enzymes at the cell level which maximise volumetric productivity and yield from batch cultures. However, this does not break the fundamental growth-synthesis trade-off which limits production performance. We show that engineering genetic circuits to switch cells to a high synthesis-low growth state after first growing to a large population can further improve performance. By analysing different circuit topologies, we show that highest performance is achieved by circuits that inhibit host metabolism to redirect it to product synthesis. Our results should facilitate construction of microbial cell factories with high and efficient production capabilities.
High-entropy alloys catalyzing polymeric transformation of water pollutants with remarkably improved electron utilization efficiency
AbstractHigh-entropy alloy nanoparticles (HEA-NPs) exhibit favorable properties in catalytic processes, as their multi-metallic sites ensure both high intrinsic activity and atomic efficiency. However, controlled synthesis of uniform multi-metallic ensembles at the atomic level remains challenging. This study successfully loads HEA-NPs onto a nitrogen-doped carbon carrier (HEAs) and pioneers the application in peroxymonosulfate (PMS) activation to drive Fenton-like oxidation. The HEAs-PMS system achieves ultrafast pollutant removal across a wide pH range with strong resistance to real-world water interferences. Furthermore, the nonradical HEAs-PMS system selectively transforms phenolics into high-molecular-weight products via a polymerization pathway. The unique non-mineralization regime remarkably reduces PMS consumption and achieves a high electron utilization efficiency of up to 213.4%. Further DFT calculations and experimental analysis reveal that Fe and Co in HEA-NPs act as the primary catalytic sites to complex with PMS for activation, while Ni, Cu, and Pd serve as charge mediators to facilitate electron transfer. The resulting PMS* complexes on HEAs possess a high redox potential, which drives spatially separated phenol oxidation on nitrogen-doped graphene support to form phenoxyl radicals, subsequently triggering the formation of high-molecule polymeric products via polymerization reactions. This study offers engineered HEAs catalysts for water treatment with low oxidant consumption and emissions.
Racial/ethnic differences in mental health treatment received among people with comorbid cardiometabolic and depressive symptomology: National Health and Nutrition Examination Survey, 2017 to March 2020 Pre-Pandemic
Background Individuals with chronic physical conditions and comorbid mental illness have increased probability of adverse health outcomes. As minority populations have limited access to both medical care and culturally appropriate mental health services, having a comorbid mental health condition can further impede their ability to manage chronic conditions and widen racial disparities in health outcomes. Further, racial/ethnic disparities in treatment patterns are likely to exacerbate disparities in adverse health outcomes. Objective To identify the racial/ethnic mental health treatment patterns among individuals with cardiometabolic and depressive symptomology co-occurrence. Methods This study utilized National Health and Nutrition Examination Survey data, 2017 to March 2020 Pre-Pandemic. The primary analysis was an adjusted linear logistic regression analysis of race/ethnicity, comorbidity status and mental health treatment type. Regression models were estimated to determine the likelihood of receiving counseling and medication therapy, and to determine if the likelihood is associated with race/ethnicity. Results Primary findings indicate that depressive symptomology only was the most common designation and fewer than half of persons received any mental health treatment. Across all racial/ethnic groups, receiving no mental health treatment was the most common designation. Sixty-one percent of Non-Hispanic White persons and more than three out of four Hispanic and Non-Hispanic Black persons with only depressive symptoms received no mental health treatment. Adjusted regression analyses revealed that participants with comorbid cardiometabolic and depressive symptomology have 28% lower odds of receiving combined mental health professional and medication therapy than participants with depressive symptomology only. Conclusions Simultaneously treating both mental illness and cardiometabolic symptoms properly is complicated, but there may be untapped synergies in treating both concurrently. Therefore, to achieve favorable health outcomes, policy should be implemented to optimize clinical treatment by addressing aspects of both conditions in an integrated approach and may need to be culturally tailored to be effective.
Assessing left main bifurcation anatomy and haemodynamics as a potential surrogate for disease risk in suspected coronary artery disease without stenosis
Experimental research on remote non-contact laser vibration measurement for tunnel lining cavities
Adaptability evaluation model and experiment of full section SBM in deep strata based on AHP-fuzzy theory
Boosting the durability of RuO2 via confinement effect for proton exchange membrane water electrolyzer
The hybrid lipoplex induces cytoskeletal rearrangement via autophagy/RhoA signaling pathway for enhanced anticancer gene therapy
AbstractDelivering plasmid DNA (pDNA) to solid tumors remains a significant challenge due to the requirement for multiple transport steps and the need to promote delivery efficiency. Herein, we present a virus-mimicking hybrid lipoplex, composed of an arginine-rich cationic lipid, hyaluronic acid derivatives coated gold nanoparticles, and pDNA. This system induces cytoskeletal rearrangements through “outside-in” mechanical and “inside-out” biochemical signaling, overcoming intra- and intercellular barriers to enhance pDNA delivery. By modulating autophagy, RhoA signaling, and cytoskeletal dynamics, we achieve a 20-fold increase in gene expression with high tissue specificity in solid tumors. Furthermore, the system is applied to co-deliver a p53 plasmid and an MDM2 inhibitor, demonstrating significant synergistic antitumor effects in hepatocellular and lung carcinomas.
Effects of the non-native Arapaima gigas on native fish species in Amazonian oxbow lakes (Bolivia)
The introduction of non-native fish species into new environments has raised global concerns due to potential ecological impacts on recipient ecosystems. A previous study focusing on the introduced fish species Arapaima gigas in Bolivian Amazon waters showed that its isotopic niche significantly overlapped with most co-occurring native fish species, suggesting potential competition. To evaluate this hypothesis, we extended here the investigation by comparing the trophic position and isotopic niche width of eleven abundant native fish species inhabiting both colonized and non-colonized floodplain lakes. We found lower trophic positions in colonized versus non-colonized lakes only for native piscivores, mostly driven by a shift towards increased dietary proportion of detritivorous fishes. Conversely, results showed that the isotopic niche width of most fish species analyzed (i.e. 10 over 11 species) did not significantly decrease in colonized compared to non-colonized lakes. Our overall results suggest potentially low competitive interactions between A. gigas and native fishes, with the notable exception of piscivorous species. We attribute our findings to the high abundance of available resources in Amazon oxbow lakes.