Associations between plasma metal mixture exposure and risk of hypertension: A cross-sectional study among adults in Shenzhen, China

BackgroundMetal exposure affects human health. Current studies mainly focus on the individual health effect of metal exposure on hypertension (HTN), and the results remain controversial. Moreover, the studies assessing overall effect of metal mixtures on hypertension risk are limited.MethodsA cross-sectional study was conducted by recruiting 1,546 Chinese adults who attended routine medical check-ups at the Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen. The plasma levels of 13 metals were measured using inductively coupled plasma mass spectrometry. Multivariate logistic regression model, restricted cubic spline (RCS) model and the Bayesian Kernel Machine Regression (BKMR) model were applied to explore the single and combined effect of metals on the risk of HTN.ResultsA total of 642 (41.5%) participants were diagnosed with HTN. In the logistic regression model, the adjusted odds ratios (ORs) were 0.71 (0.52, 0.97) for cobalt, 1.40 (1.04, 1.89) for calcium, 0.66 (0.48, 0.90), and 0.60 (0.43, 0.83) for aluminum in the second and third quartile, respectively. The RCS analysis showed a V-shaped or an inverse V-shaped dose-response relationship between metals (aluminum or calcium, respectively) and the risk of HTN (P for non-linearity was 0.017 or 0.009, respectively). However, no combined effect was found between metal mixture and the risk of hypertension.ConclusionsPlasma levels of cobalt, aluminum and calcium were found to be associated with the risk of HTN. Further studies are needed to confirm our findings and their potential mechanisms with prospective studies and experimental study designs

The Relationship Between Facial Expression and Cognitive Function in Patients With Depression

Objective: Considerable evidence has shown that facial expression recognition ability and cognitive function are impaired in patients with depression. We aimed to investigate the relationship between facial expression recognition and cognitive function in patients with depression.Methods: A total of 51 participants (i.e., 31 patients with depression and 20 healthy control subjects) underwent facial expression recognition tests, measuring anger, fear, disgust, sadness, happiness, and surprise. The Chinese version of the MATRICS Consensus Cognitive Battery (MCCB), which assesses seven cognitive domains, was used.Results: When compared with a control group, there were differences in the recognition of the expressions of sadness (p = 0.036), happiness (p = 0.041), and disgust (p = 0.030) in a depression group. In terms of cognitive function, the scores of patients with depression in the Trail Making Test (TMT; p < 0.001), symbol coding (p < 0.001), spatial span (p < 0.001), mazes (p = 0.007), the Brief Visuospatial Memory Test (BVMT; p = 0.001), category fluency (p = 0.029), and continuous performance test (p = 0.001) were lower than those of the control group, and the difference was statistically significant. The accuracy of sadness and disgust expression recognition in patients with depression was significantly positively correlated with cognitive function scores. The deficits in sadness expression recognition were significantly correlated with the TMT (p = 0.001, r = 0.561), symbol coding (p = 0.001, r = 0.596), maze (p = 0.015, r = 0.439), and the BVMT (p = 0.044, r = 0.370). The deficits in disgust expression recognition were significantly correlated with impairments in the TMT (p = 0.005, r = 0.501) and symbol coding (p = 0.001, r = 0.560).Conclusion: Since cognitive function is impaired in patients with depression, the ability to recognize negative facial expressions declines, which is mainly reflected in processing speed, reasoning, problem-solving, and memory

A competing-risk-based score for predicting twenty-year risk of incident diabetes: the Beijing Longitudinal Study of Ageing study

Few risk tools have been proposed to quantify the long-term risk of diabetes among middle-aged and elderly individuals in China. The present study aimed to develop a risk tool to estimate the 20-year risk of developing diabetes while incorporating competing risks. A three-stage stratification random-clustering sampling procedure was conducted to ensure the representativeness of the Beijing elderly. We prospectively followed 1857 community residents aged 55 years and above who were free of diabetes at baseline examination. Sub-distribution hazards models were used to adjust for the competing risks of non-diabetes death. The cumulative incidence function of twenty-year diabetes event rates was 11.60% after adjusting for the competing risks of non-diabetes death. Age, body mass index, fasting plasma glucose, health status, and physical activity were selected to form the score. The area under the ROC curve (AUC) was 0.76 (95% Confidence Interval: 0.72–0.80), and the optimism-corrected AUC was 0.78 (95% Confidence Interval: 0.69–0.87) after internal validation by bootstrapping. The calibration plot showed that the actual diabetes risk was similar to the predicted risk. The cut-off value of the risk score was 19 points, marking mark the difference between low-risk and high-risk patients, which exhibited a sensitivity of 0.74 and specificity of 0.65

Global research trends in benign paroxysmal positional vertigo: a bibliometric analysis

BackgroundBenign paroxysmal positional vertigo is the most common disease in which vertigo is the main clinical manifestation, and it has become a global medical problem, affecting a wide range of areas and seriously affecting the quality of human life.ObjectiveThis article presents an analysis of the current characteristics of BPPV-related research and summarizes the current hot topics and trends, with the goal of inspiring future research into the prevention and treatment of BPPV, thereby improving the differential diagnosis and prevention of peripheral vertigo.MethodsA bibliometric approach was used to collect 1,219 eligible studies on BPPV from four databases—PubMed, Embase, Scopus, and Web of Science—published between 1974 and 2022. The characteristics and status of the accumulated scientific output were processed using R and VOSviewer so that we could visualize any trends or hotspots.ResultsThe results showed a significant increase in the annual number of publications, with an average annual growth rate of 21.58%. A possible reason for the especially pronounced peak in 2021 was an increase in the prevalence of BPPV as a result of COVID-19. The new coronavirus became a focus of research in 2021. A total of 3,876 authors (of whom 1,097 were first authors) published articles in 307 different journals; 15.7% of the articles were published in Acta Oto-Larygologica, Otology and Neurotology, and Frontiers in Neurology. Acta Oto-Laryngologica was well ahead of the other journals in terms of growth rate and number of articles published. American scholars generated the largest number of articles overall, and the USA was involved in the greatest number of international collaborations, followed by Italy and China. The themes of the research centered around three topics, namely the treatment of BPPV, its influencing factors, and diagnosis.ConclusionsThere has been a major increase in BPPV-related research over the last 50 years, leading to an increase in related articles and rapid development of the field. Key directions for future research include the improvement of individualized treatment for residual symptoms after initial treatment of BPPV among the elderly; effective control of comorbidities such as osteoporosis; and secondary inner ear disease, such as Ménière's disease

Group event recognition in ice hockey

With the success of deep learning in computer vision community, most approaches for group activity recognition in sports started relying on Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). However, how to model the interactions among players and the interactions between players and the scene remains a challenging problem. In order to better model these interactions, we propose two models. Our first model combines features of all players in a scene through an attention mechanism. The aggregated feature is then concatenated with the feature of the frame and passed through an RNN to generate the final prediction. In our second model, we designed a spatial grid feature and a temporal grid feature calculated from appearance features and motion features of all players in a scene, as well as their locations. We then apply CNNs to the spatial grid feature, the temporal grid feature, target frame of the scene (the frame at which the event happens), and the stack of optical flow containing the target frame separately. Results from the four streams are fused through score fusion to make the final prediction. Inputs to our models are: the target frame image, a stack of optical flow images, bounding boxes of players and coordinates of players calculated from homography matrix of the frame. We evaluated the two models on an Ice Hockey dataset, and results show that both models produced promising results. We also provide a possible solution for event detection in a more general setting.Science, Faculty ofComputer Science, Department ofGraduat

Familial cluster of COVID-19 infection from an asymptomatic

Since December 2019, the first case of a novel coronavirus (COVID-19) infection pneumonia was detected in Wuhan, and the outbreak has been spreading rapidly in the world. As of February 18, 2020, a total of 73,332 cases of confirmed COVID-19 infection have been detected in the world as reported by the WHO [1, 2]. Given that the asymptomatic persons are potential sources of COVID-19 infection [3], we report a familial cluster case of five patients infected with COVID-19 from an asymptomatic confirmed case in Beijing. We obtained the data of patients, which included demographic, epidemiological, and clinical features; chest radiography; laboratory test; and outcomes. Laboratory confirmation of COVID-19 was detected in the first hospital admission and verified by the Beijing Center for Disease Control and Prevention (CDC). An asymptomatic case was defined as a laboratory-confirmed COVID-19 infection case who was afebrile and well. We enrolled the family that had five patients in total with COVID-19 infection who were transferred by the Beijing Emergency Medical Service (EMS) from January 24 to 27, 2020, to the designated hospitals for special treatment. Clinical outcomes were followed up to February 29, 2020

Development in Preparation and Application of Graphene Functionalization

Graphene has attracted wide interest of academic and industrial circles due to its superior physical and chemical properties. The functionalization of graphene helps improve its dispersion, and adjusts its performances according to specific needs, thus enables wide applications of graphene, and becomes a hot spot of graphene related researches. This review introduced the recent advances of graphene functionalization, presents covalent and non-covalent methods of functional modification, and described applications of the modified graphene in composite materials, energy storing, optical electronics, chemical catalyzing, pollution processing, biology material and sensors. We concluded the characteristics of functionalized graphene that most of reactive groups can show their own practical properties very actively when being connected to the graphene surface. There will be two main research orientations in functionalized graphene field: one is quantifying, which is to determine and control the quantity of introduced functional species; the other is positioning that is to select the modification sites precisely and to design their fine chemical structures

Real-time brightfield, darkfield, and phase contrast imaging in a light-emitting diode array microscope.

We demonstrate a single-camera imaging system that can simultaneously acquire brightfield, darkfield, and phase contrast images in real time. Our method uses computational illumination via a programmable light-emitting diode (LED) array at the source plane, providing flexible patterning of illumination angles. Brightfield, darkfield, and differential phase contrast images are obtained by changing the LED patterns, without any moving parts. Previous work with LED array illumination was only valid for static samples because the hardware speed was not fast enough to meet real-time acquisition and processing requirements. Here, we time multiplex patterns for each of the three contrast modes in order to image dynamic biological processes in all three contrast modes simultaneously. We demonstrate multicontrast operation at the maximum frame rate of our camera (50 Hz with 2160 × 2560 pixels)