Association of oxidative balance score with hyperuricemia and gout: NHANES 2009-2018

IntroductionOxidative stress plays a crucial role in the development and progression of hyperuricemia/gout. This study aims to explore the relationship between the Oxidative Balance Score (OBS) and hyperuricemia/gout.MethodsThe study utilized complete data from adult participants in the National Health and Nutrition Examination Survey (NHANES) spanning from 2009 to 2018. OBS, composed of scores for 20 dietary and lifestyle factors, served as the exposure variable. Multivariable linear regression model was applied to evaluate the association between OBS and uric acid (UA). Multivariable logistic regression, subgroup analyses, and restricted cubic spline (RCS) regression were conducted to explore the relationship between OBS and hyperuricemia/gout.ResultsA total of 18,998 participants were included. In the fully adjusted model, compared to the lowest quartile, the highest quartiles of OBS, dietary OBS, and lifestyle OBS were negatively correlated with UA (β=-0.31 (-0.36,-0.25), β=-0.18 (-0.24,-0.12), and β=-0.64 (-0.69,-0.59), respectively) and hyperuricemia (OR=0.63 (0.55,0.71), OR=0.76 (0.67,0.86), OR=0.37 (0.33,0.42), respectively). Moreover, the highest quartiles of OBS and lifestyle OBS exhibited a negative correlation with gout (OR=0.72(0.58,0.91), OR=0.54 (0.43,0.67), respectively). Subgroup analyses revealed differences in the negative association between OBS and hyperuricemia concerning hypertension (p for interaction =0.002) and diabetes (p for interaction= 0.004), while gender-related disparities were observed in the negative association between OBS and gout (p for interaction =0.008). RCS analysis demonstrated a linear negative association between hyperuricemia and OBS (p for non-linearity >0.05), while gout exhibited a non-linear negative association (p for non-linearity<0.05).ConclusionThe study found that a higher OBS was associated with a decreased risk of developing hyperuricemia/gout, underscoring its potential in the prevention and management of these conditions

Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth of sequencing promises unprecedented data on natural sequence diversity. Protein language modeling at the scale of evolution is a logical step toward predictive and generative artificial intelligence for biology. To this end, we use unsupervised learning to train a deep contextual language model on 86 billion amino acids across 250 million protein sequences spanning evolutionary diversity. The resulting model contains information about biological properties in its representations. The representations are learned from sequence data alone. The learned representation space has a multiscale organization reflecting structure from the level of biochemical properties of amino acids to remote homology of proteins. Information about secondary and tertiary structure is encoded in the representations and can be identified by linear projections. Representation learning produces features that generalize across a range of applications, enabling state-of-the-art supervised prediction of mutational effect and secondary structure and improving state-of-the-art features for long-range contact prediction

Genetic Types and Ecological Potential of Selenium-Enriched Land in the Northern Margin of the Qinghai—Xizang Plateau

The study of the genesis type of selenium (Se)-enriched land found in the Qinghai—Xizang Plateau can provide a scientific basis for the construction of the research, development and utilization system of Se resources on the Qinghai—Xizang Plateau and has practical significance for improving the risk of low Se intake on the Qinghai—Xizang Plateau. On the basis of summarizing the characteristics and genesis types of the main natural Se-enriched lands in China, the distribution characteristics of Se and related elements are analyzed through the coordinated monitoring of soil and rock, and the conclusion is that there are three types of Se-enriched lands in the northern margin of the Qinghai—Xizang Plateau, namely, arid saline lake sedimentary type, sulfide mineralization type and organic matter adsorption type. (1) In the sedimentary Se-enriched land of the arid saline lake, the Se content ranges from 0.30 to 1.16mg/kg, and the contents of heavy metals are below the risk control screening values. Spatially, Se overlaps and co-enriches with beneficial elements such as Sr, Mg, Fe, Ca, and Mo. Se is derived from the red mudstone weathering of the Xining Group, which has the advantages of stable Se source sedimentation, moderate total amount of Se, low heavy metals, and composite of a variety of beneficial elements. It is a type of Se with greater ecological potential in the northern margin of the Qinghai—Xizang Plateau and even the entire northwest region. (2) In sulfide mineralized Se-enriched land, Se content ranges from 0.30 to 2.22mg/kg; Ni, Cd, Cr and As exceed screening values in 0.2%−2.4% of the samples; As exceeds control values in 0.1% of the samples. The land has high natural heavy metal backgrounds, posing ecological risks and limitations of high-altitude and cold climate, which can be used to develop the forest-based economy and wild Chinese herbal medicine industry under monitoring. (3) In the organic matter adsorption type Se-enriched land, Se content ranges from 0.30 to 0.59mg/kg, and Ni, Cd, Cr and As do not exceed the standard. Se has the dual effects of increasing forage nutrition and resisting heavy metal absorption, so the maximum ecological effect of Se can be regulated by further exploring the equilibrium conditions of organic matter in the process of adsorption-release of Se

Diagnostic value of multiple projection angle X-ray and CT 3D reconstruction for long-term unreduced posterior hip dislocation

BackgroundLong-term unreduced posterior hip dislocation is a rare and diagnostically challenging condition, with imaging findings often indistinguishable from those of other end-stage hip diseases. It remains a great challenge to determine whether certain imaging characteristics can improve the clinical diagnosis rate of long-term unreduced posterior hip dislocation.MethodsWe retrospectively reviewed 24 patients from 2010 to 2022. The diagnostic values of multiple projection angle X-ray and CT 3D reconstruction for long-term unreduced posterior hip dislocation were evaluated.ResultsFor aureole sign, 45.83% of patients (sensitivity = 45.83%, specificity = 81.52%, accuracy = 78.67%, Youden's index = 0.274, positive predictive value (PPV) = 17.74%, negative predictive value (NPV) = 94.54%, intraobserver consistency = 0.930, and interobserver consistency = 0.903) were diagnosed correctly. For obturator oblique radiograph of the pelvis, 58.33% of patients (sensitivity = 58.33%, specificity = 82.25%, accuracy = 80.33%, Youden's index = 0.406, PPV = 22.22%, NPV = 95.78%, intraobserver consistency = 0.923, and interobserver consistency = 0.900) were diagnosed correctly. For rhombus sign, 70.83% of patients (sensitivity = 70.83%, specificity = 90.94%, accuracy = 89.33%, Youden's index = 0.618, PPV = 40.48%, NPV = 97.29%, intraobserver consistency = 0.943, and interobserver consistency = 0.900) were diagnosed correctly. For CT 3D reconstruction, axial CT (sensitivity = 70.83%), coronal multiplanar reconstruction (sensitivity = 58.33%), and sagittal multiplanar reconstruction (sensitivity = 54.17%), all had high diagnostic values.ConclusionsThe signs, projection angle X-ray, and CT 3D reconstruction identified in this study are valuable in improving the diagnosis for long-term unreduced posterior hip dislocation