Non-negative matrix factorization (NMF) has become one of the most powerful methods for clustering and feature selection. However, the performance of the traditional NMF method severely degrades when ...the data contain noises and outliers or the manifold structure of the data is not taken into account. In this article, a novel method called correntropy-based hypergraph regularized NMF (CHNMF) is proposed to solve the above problem. Specifically, we use the correntropy instead of the Euclidean norm in the loss term of CHNMF, which will improve the robustness of the algorithm. And the hypergraph regularization term is also applied to the objective function, which can explore the high-order geometric information in more sample points. Then, the half-quadratic (HQ) optimization technique is adopted to solve the complex optimization problem of CHNMF. Finally, extensive experimental results on multi-cancer integrated data indicate that the proposed CHNMF method is superior to other state-of-the-art methods for clustering and feature selection.
Background and aims
Although low-density lipoprotein cholesterol (LDL-C) has been considered as a risk factor of atherosclerotic cardiovascular disease, limited studies can be available to evaluate ...the association of LDL-C with risk of mortality in the general population. This study aimed to examine the association of LDL-C level with risk of mortality using a propensity-score weighting method in a Chinese population, based on the health examination data.
Methods
We performed a retrospective cohort study with 65,517 participants aged 40 years or older in Ningbo city, Zhejiang. LDL-C levels were categorized as five groups according to the Chinese dyslipidemia guidelines in adults. To minimize potential biases resulting from a complex array of covariates, we implemented a generalized boosted model to generate propensity-score weights on covariates. Then, we used Cox proportional hazard regression models with all-cause and cause-specific mortality as the dependent variables to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs).
Results
During the 439,186.5 person years of follow-up, 2403 deaths occurred. Compared with the median LDL-C group (100–130 mg/dL), subjects with extremely low LDL-C levels (group 1) had a higher risk of deaths from all-cause (HR = 2.53, 95% CI:1.80–3.53), CVD (HR = 1.84, 95% CI: 1.28–2.61), ischemic stroke (HR = 2.29, 95% CI:1.32–3.94), hemorrhagic stroke (HR = 3.49, 95% CI: 1.57–7.85), and cancer (HR = 2.12, 95% CI: 1.04–4.31) while the corresponding HRs in LDL-C group 2 were relatively lower than that in group 1.
Conclusions
Low LDL-C levels were associated with an increased risk of all-cause, CVD, ischemic stroke, hemorrhagic stroke, and cancer mortality in the Chinese population.
Abstract
Objective
Unprecedented rigorous public health measures were implemented during the coronavirus disease 2019 (COVID-19) epidemic, but it is still unclear how the intervention influenced ...hospital visits for different types of diseases. We aimed to evaluate the impact of the intervention on hospital visits in Yinzhou District, Ningbo, Zhejiang province, China.
Methods
We conducted an interrupted time-series analysis from 1 January 2017 to 6 September 2020 based on the Yinzhou Health Information System in Ningbo, Zhejiang province. The beginning of the intervention was on 23 January 2020, and thus, there were 160 weeks before the intervention and 32 weeks after the implementation of the intervention. Level changes between expected and observed hospital visits in the post-intervention period were estimated using quasi-Poisson regression models.
Results
Compared with the expected level, there was an estimated decrease of −22.60% (95% confidence interval (CI): −27.53%, −17.36%) in the observed total hospital visits following the intervention. Observed hospital visits for diseases of the respiratory system were found to be decreased dramatically (−62.25%; 95% CI: −65.62%, −58.60%). However, observed hospital visits for certain diseases were estimated to be increased, including diseases of the nervous system (+11.17%; 95% CI: +3.21%, +19.74%); diseases of pregnancy, childbirth and the puerperium (+27.01%; 95% CI: +17.89%, +36.85%); certain conditions originating in the perinatal period (+45.05%; 95% CI: +30.24%, +61.56%); and congenital malformation deformations and chromosomal abnormalities (+35.50%; 95% CI: +21.24%, +51.45%).
Conclusions
Our findings provided scientific evidence that cause-specific hospital visits evolve differently following the intervention during the COVID-19 epidemic.
Essential trace elements (ETEs) are essential nutrients for keeping the nervous system functioning. Associations between ETEs and cognitive function are still inconclusive and limited.
We aimed to ...investigate the individual and joint associations between ETEs and cognitive function among older adults.
A population (N = 2181) at an average age≥ 65 from Yiwu cohort in China was available for this study. Whole blood chromium (Cr), selenium (Se), manganese (Mn), and copper (Cu) concentrations were measured by inductively coupled plasma mass spectrometry (ICP-MS). Cognitive function was assessed using the Mini-Mental State Examination (MMSE), consisting of five specific cognitive domains: orientation, registry, attention and calculation, recall, and language and praxis. Linear regression, restricted cubic spline (RCS) analysis, and Bayesian kernel machine regression (BKMR) were used to analyze the individual and joint associations between ETEs and cognitive function.
The association between Cr and MMSE score presented an inverted-U shape (Q3 versus Q1: β = 0.774, 95 % CI: 0.297, 1.250; Q4 versus Q1: β = 0.481, 95 % CI: 0.006, 0.956); and Cr was especially associated with the registry, recall, and language and praxis. Per IQR (36.32 μg/L) increase of Se was positively associated with the MMSE score (β = 0.497, 95 % CI: 0.277, 0.717) and all five cognitive domains. The BKMR showed that the dose-response association between Se and cognitive function increased initially and then decreased with increasing Se concentration when fixed the other ETEs in median. ETEs mixture was positively associated with cognitive function, and Se (posterior inclusion probabilities, PIPs = 0.915) was the most important contributor within the ETEs mixture.
The nonlinear association between Cr and cognitive function suggested further exploration of an appropriate concentration range for ETEs. A positive association between mixed ETEs and cognitive function is a reminder that their joint association should be considered. Further prospective studies or intervention studies are warranted to validate our findings in the future.
Display omitted
•The association between Cr and cognitive function presented an inverted-U shape.•The joint association between ETEs mixture and cognitive function was positive.•Se was the most important contributor to cognitive function within the mixture.
In recent years, with the diversity and variability of cancer information, the multi-omics data have been applied in various fields. Many existing models of principal component analysis can only ...process single data, which makes limitations on cancer research. Therefore, in this paper, a new model called integrative principal component analysis (IPCA) is proposed to achieve the unification of multi-omics data. In addition, in order to preserve the high-order manifold structure between the data, an integrative hypergraph regularization principal component analysis (IHPCA) is further proposed by applying the hypergraph regularization constraint. The effectiveness of IHPCA method is tested on four multi-omics datasets. Experimental results show that the proposed method has better performance than other representative methods on sample clustering and common expression genes (co-expression genes) network analysis.
Ambient particulate matter is one of the main risk factors of chronic obstructive pulmonary disease (COPD) in developing countries. However, the studies were scant in China concerning the health ...effects of the fine particulate matter (PM
2.5
; particulate matter ≤ 2.5 μm in diameter) on hospital visits for COPD. We applied a generalized additive model (GAM) to calculate relative risks (RRs) with 95% confidence intervals (CIs) for the associations between hospital visits for COPD and an interquartile range (24.50 μg/m
3
) increment of ambient PM
2.5
concentrations in Yinzhou District between 2016 and 2018. The ambient PM
2.5
concentration was positively associated with hospital visits for COPD at a distributed lag of 0–7 days (RR = 1.073, 95% CI, 1.016, 1.133). In the stratified analysis, we found that the association between ambient PM
2.5
and COPD was stronger during the warm season (April to September) than that during the cold season (October to March), but we did not observe statistically significant differences in age groups (< 60 years and ≥ 60 years) or gender groups (male and female) related to the effects of PM
2.5
. The associations between ambient PM
2.5
and COPD became partially attenuated after the adjustment for gaseous pollutants in subgroups. Our findings could provide evidence that regulations for controlling both PM
2.5
and gaseous pollutants should be implemented to protect the overall population.
The purpose of this study is to describe the prevalence of overweight, general obesity, and abdominal obesity and examine their associations with socioeconomic status in a rural Chinese adult ...population.
This cross-sectional study was performed on 15,236 participants ≥ 35 years of age (6,313 men 41.4% and 8,923 women 58.6%). Each participant's weight, height, waist circumference (WC), and hipline circumference (HC) were measured, and demographic and socioeconomic data were collected using questionnaires.
The mean body mass index (BMI) values were 23.31 ± 2.96 and 23.89 ± 3.23 kg m(-2) and the mean WC values were 79.13 ± 8.43 and 79.54 ± 8.27 cm for men and women, respectively. The age-standardized prevalence rates of overweight (BMI ≥ 24.0 kg m(-2)), general obesity (BMI ≥ 28.0 kg m(-2)), and abdominal obesity (WC ≥ 85 cm for men and ≥ 80 cm for women) were 32.0%, 6.7%, and 27.0% for men and 35.1%, 9.7%, and 48.3% for women, respectively. All gender differences were statistically significant (p < 0.001). In addition, the age-specific prevalence rates of general and abdominal obesity slowly decreased among men but sharply increased among women as age increased (p < 0.001). In subsequent logistic regression analysis, educational level was negatively associated with both general obesity and abdominal obesity among women but positively associated with abdominal obesity among men. No significant correlation was found between obesity and income.
These results suggest a high prevalence of obesity which might differ by gender and age, and an inverse association among women and a mixed association among men noted between education and obesity in our locality. Preventive and therapeutic programs are warranted to control this serious public health problem. The gender-specific characteristics of populations at high-risk of developing obesity should be taken into consideration when designing interventional programs.
Social Health Scale for the Elderly short version (SHSE-S) is a psychometrically sound instrument that comprehensively assesses the social health status of older adults in China. The aim of the ...present study was to establish continuous normative data of SHSE-S.
We conducted a multicenter cross-sectional study among 31 communities in eastern China. Older adults aged 60 years and above were invited to participate in the study. Each participant was interviewed in-person to finish a structured questionnaire. The SHES-S score was calculated and standardized for each participant. We split the sample into generation and validation datasets and compared the distribution of SHSE-S score between two datasets. Multivariable linear regression was used to assess the SHSE-S score and demographic variables. Regression-based norms were built using a four-step process.
A total of 6089 participants (51.2% females) aged 60 years old and above (mean age = 71.3, SD = 8.0) were enrolled as the normative sample. No significant difference was found between the distribution of SHSE-S standardized score in the generation (N = 2392) and validation (N = 3697) datasets. Multivariable linear regression showed that females, higher education levels were positive indicators while aging, living alone, divorced or never married, multimorbidity were negative factors. The regression-based norm which taking demographic factors into account was established and a user-friendly worksheet was also provided to facilitate the scoring and norming of the SHSE-S.
The population-based regression norm of SHSE-S can be a useful tool for assessing the social health status of the Chinese elderly population.
Non-negative matrix factorization (NMF) is a dimensionality reduction technique based on high-dimensional mapping. It can learn part-based representations effectively. In this paper, we propose a ...method called Dual Hyper-graph Regularized Supervised Non-negative Matrix Factorization (HSNMF). To encode the geometric information of the data, the hyper-graph is introduced into the model as a regularization term. The advantage of hyper-graph learning is to find higher order data relationship to enhance data relevance. This method constructs the data hyper-graph and the feature hyper-graph to find the data manifold and the feature manifold simultaneously. The application of hyper-graph theory in cancer datasets can effectively find pathogenic genes. The discrimination information is further introduced into the objective function to obtain more information about the data. Supervised learning with label information greatly improves the classification effect. Furthermore, the real datasets of cancer usually contain sparse noise, so the <inline-formula><tex-math notation="LaTeX">L_{2,1}</tex-math> <mml:math><mml:msub><mml:mi>L</mml:mi><mml:mrow><mml:mn>2</mml:mn><mml:mo>,</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msub></mml:math><inline-graphic xlink:href="wang-ieq1-2975173.gif"/> </inline-formula>-norm is applied to enhance the robustness of HSNMF algorithm. Experiments under The Cancer Genome Atlas (TCGA) datasets verify the feasibility of the HSNMF method.
Although the effect of air pollution on respiratory health has been identified, few studies can be available to evaluate the association of air pollution with hospital visits for children’s pneumonia ...in China. To explore whether high concentrations of air pollutants (including PM
2.5
, PM
10
, NO
2
, and SO
2
) are related to hospital visits for pneumonia in children, we conducted a population-based time-series study in Ningbo, China, from January 1st, 2014 to November 1st, 2015. We used a generalized additive Poisson regression model to calculate risk ratios and 95% confidence intervals for the associations of air pollutants and hospital visits for pneumonia in children and found that these four pollutants were associated with the increased hospital visits for pneumonia in children (1.3% for PM2.5, 1.0% for PM10, 2.9% for NO
2
, 5.0% for SO
2
per 10-μg/m
3
increase in PM2.5, PM10, NO
2
, and SO
2
, respectively). Stronger associations were observed in the cold seasons and among children under 5 years.
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