Synergistic Effects of Serum Uric Acid and Cardiometabolic Risk Factors on Early Stage Atherosclerosis: The Cardiometabolic Risk in Chinese Study

Objective: To comprehensively examine the associations of serum uric acid (SUA) with central and peripheral arterial stiffness in Chinese adults, and particularly assess the interactions between SUA and other cardiometabolic risk factors. Methods: The study included 3,772 Chinese men and women with carotid radial pulse wave velocity (crPWV), carotid femoral PWV (cfPWV), carotid artery dorsalis pedis PWV (cdPWV) and SUA measured. Results: After adjustment for age, sex, and BMI, the levels of SUA were significantly associated with increasing trend of cfPWV, crPWV and cdPWV (P for trend <0.0001). Further adjustment for heart rate (HR), blood pressure (BP) and lipids attenuated the associations with crPWV and cdPWV to be non-significant (P = 0.1, P = 0.099 respectively), but the association between SUV and cfPWV remained significant (P = 0.004). We found significant interactions between SUA and HR or BP in relation to cfPWV (P for interaction = 0.03, 0.003 respectively). The associations between SUA and cfPWV were more evident among individuals with higher HR or normal BP than those with lower HR or hypertension. Conclusions: SUA was associated with elevated aortic arterial stiffness in Chinese adults, independent of conventional cardiovascular risk factors. BP and HR might modify the deleterious effects of SUA

QAGCF: Graph Collaborative Filtering for Q&A Recommendation

Question and answer (Q&A) platforms usually recommend question-answer pairs to meet users' knowledge acquisition needs, unlike traditional recommendations that recommend only one item. This makes user behaviors more complex, and presents two challenges for Q&A recommendation, including: the collaborative information entanglement, which means user feedback is influenced by either the question or the answer; and the semantic information entanglement, where questions are correlated with their corresponding answers, and correlations also exist among different question-answer pairs. Traditional recommendation methods treat the question-answer pair as a whole or only consider the answer as a single item, which overlooks the two challenges and cannot effectively model user interests. To address these challenges, we introduce Question & Answer Graph Collaborative Filtering (QAGCF), a graph neural network model that creates separate graphs for collaborative and semantic views to disentangle the information in question-answer pairs. The collaborative view disentangles questions and answers to individually model collaborative information, while the semantic view captures the semantic information both within and between question-answer pairs. These views are further merged into a global graph to integrate the collaborative and semantic information. Polynomial-based graph filters are used to address the high heterophily issues of the global graph. Additionally, contrastive learning is utilized to obtain robust embeddings during training. Extensive experiments on industrial and public datasets demonstrate that QAGCF consistently outperforms baselines and achieves state-of-the-art results

Genetically predicted asthma and the risk of abnormal spermatozoa

BackgroundSeveral previous animal and human studies have found a strong association between asthma and spermatozoa quality, but whether these associations are causal or due to bias remains to be elucidated.MethodsWe performed a two-sample Mendelian randomization (MR) analysis to assess the causal effect of genetically predicted asthma on the risk of abnormal spermatozoa. Asthma, childhood-onset asthma (COA), and adult-onset asthma (AOA) (sample sizes ranging from 327,670 to 408,442) were included as the exposures. Genetic information for abnormal spermatozoa was obtained from a genome-wide association study (GWAS) comprising 209,921 participants. In univariable MR (UVMR) analysis, the inverse variance weighted (IVW) method was conducted as the primary method, with the MR Egger and weighted median used as supplementary methods for causal inference. Sensitivity analyses, including the Cochran Q test, Egger intercept test, MR-PRESSO, and leave-one-out analysis, were performed to verify the robustness of the MR results. Multivariable MR (MVMR) was conducted to evaluate the direct causal effects of asthma on abnormal spermatozoa risk.ResultsUVMR detected causal associations between genetically predicted asthma and an increased risk of abnormal spermatozoa (OR: 1.270, 95% CI: 1.045–1.545, p = 0.017). Moreover, we found that AOA (OR: 1.46, 95% CI: 1.051, 2.018, p = 0.024) has positive causal effects on the risk of abnormal spermatozoa rather than COA (p = 0.558). Sensitivity analysis found little evidence of bias in the current study (p &gt; 0.05). MVMR further confirmed that asthma directly affected the risk of abnormal spermatozoa.ConclusionOur MR study suggested that genetically predicted asthma could be associated with an increased risk of abnormal spermatozoa, and similar results were obtained in AOA. Further studies are warranted to explain the underlying mechanisms of this association and may provide new avenues for prevention and treatment

Geographic Variability of Upper Urinary Tract Stone Constituents in Hebei Adults

BackgroundUrinary stones are a common and frequently-occurring disease of the urinary system, among which upper urinary tract stones are the most common, imposing a heavy burden on patients. The causes of upper urinary tract stones are complex, which are closely associated with gender, age, geographic condition, climate, diet, and so on. However, it is still unclear whether upper urinary stone constituents vary by geographical conditions.ObjectiveTo analyze the constituents of upper urinary tract stones among adults in different geographic regions of Hebei, providing evidence for clinical treatment and prevention of upper urinary tract stones.MethodsOutpatients and inpatients (n=1 192, ≥18 years old) with upper urinary calculis who were from three geographical regions (mountainous, plain and coastal) of Hebei were selected from the Second Hospital of Hebei Medical University in 2019. Upper urinary tract stones of the outpatients removed by extracorporeal shock wave lithotripsy, and those of the inpatients removed by surgery were collected for quantitative and qualitative constituent analyses by geographical region using infrared spectrometry.ResultsUpper urinary tract stones were more often found in those 30 to 70 years old, with a male to female ratio about 1.75∶1. Kidney stones and ureteral stones accounted for similar proportions (about 1.1∶1) , and the mixed stones were more common (61.5%) . Calcium-containing stones were the major type of upper urinary tract stones in participants from each geographic regions, with calcium oxalate monohydrate being the most. The prevalence of infectious stones showed no significant differences across participants from three regions (P&gt;0.05) . The prevalence of uric acid-containing stones in participants from plain was significantly different from that of participants from mountainous or coastal region (P&lt;0.05) .ConclusionCalcium-containing stones were the most common prevalent in upper urinary tract stones patients across three geographic regions of Hebei, and the prevalence of uric acid-containing stones in those from mountainous or coastal region was higher, which require the attention of urologists

Sex-Specific Prediction Models for Sleep Apnea From the Hispanic Community Health Study/Study of Latinos

OBJECTIVE: We developed and validated the first-ever sleep apnea (SA) risk calculator in a large population-based cohort of Hispanic/Latino subjects. METHODS: Cross-sectional data on adults from the Hispanic Community Health Study/Study of Latinos (2008-2011) were analyzed. Subjective and objective sleep measurements were obtained. Clinically significant SA was defined as an apnea-hypopnea index ≥ 15 events per hour. Using logistic regression, four prediction models were created: three sex-specific models (female-only, male-only, and a sex × covariate interaction model to allow differential predictor effects), and one overall model with sex included as a main effect only. Models underwent 10-fold cross-validation and were assessed by using the C statistic. SA and its predictive variables; a total of 17 variables were considered. RESULTS: A total of 12,158 participants had complete sleep data available; 7,363 (61%) were women. The population-weighted prevalence of SA (apnea-hypopnea index ≥ 15 events per hour) was 6.1% in female subjects and 13.5% in male subjects. Male-only (C statistic, 0.808) and female-only (C statistic, 0.836) prediction models had the same predictor variables (ie, age, BMI, self-reported snoring). The sex-interaction model (C statistic, 0.836) contained sex, age, age × sex, BMI, BMI × sex, and self-reported snoring. The final overall model (C statistic, 0.832) contained age, BMI, snoring, and sex. We developed two websites for our SA risk calculator: one in English (https://www.montefiore.org/sleepapneariskcalc.html) and another in Spanish (http://www.montefiore.org/sleepapneariskcalc-es.html). CONCLUSIONS: We created an internally validated, highly discriminating, well-calibrated, and parsimonious prediction model for SA. Contrary to the study hypothesis, the variables did not have different predictive magnitudes in male and female subjects

Alcohol Consumption and Metabolic Syndrome Among Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos

Background: The association between alcohol consumption and metabolic syndrome (MetS) among Hispanic/Latino populations has not been studied in great detail. Our study examined the relationship between alcohol consumption and MetS among U.S. Hispanics/Latinos and explored whether this relationship varied by age, body mass index, gender, and Hispanic/Latino backgrounds

Reconstruction of primary vertices at the ATLAS experiment in Run 1 proton–proton collisions at the LHC

This paper presents the method and performance of primary vertex reconstruction in proton–proton collision data recorded by the ATLAS experiment during Run 1 of the LHC. The studies presented focus on data taken during 2012 at a centre-of-mass energy of √s=8 TeV. The performance has been measured as a function of the number of interactions per bunch crossing over a wide range, from one to seventy. The measurement of the position and size of the luminous region and its use as a constraint to improve the primary vertex resolution are discussed. A longitudinal vertex position resolution of about 30μm is achieved for events with high multiplicity of reconstructed tracks. The transverse position resolution is better than 20μm and is dominated by the precision on the size of the luminous region. An analytical model is proposed to describe the primary vertex reconstruction efficiency as a function of the number of interactions per bunch crossing and of the longitudinal size of the luminous region. Agreement between the data and the predictions of this model is better than 3% up to seventy interactions per bunch crossing

Detecting prediabetes among Hispanics/Latinos from diverse heritage groups: Does the test matter? Findings from the Hispanic Community Health Study/Study of Latinos

The objectives of this analysis were to compare the ability of fasting plasma glucose (FPG), post oral load plasma glucose (2hPG), and hemoglobin A1c (HbA1c) to identify U.S. Hispanic/Latino individuals with prediabetes, and to assess its cardiovascular risk factor correlates

Differences in Hemoglobin A 1c Between Hispanics/Latinos and Non-Hispanic Whites: An Analysis of the Hispanic Community Health Study/Study of Latinos and the 2007–2012 National Health and Nutrition Examination Survey

To determine whether, after adjustment for glycemia and other selected covariates, hemoglobin A1c (HbA1c) differed among adults from six Hispanic/Latino heritage groups (Central American, Cuban, Dominican, Mexican, Puerto Rican, and South American) and between Hispanic/Latino and non-Hispanic white adults without self-reported diabetes