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1.
Toxins (Basel) ; 13(11)2021 Nov 13.
Artigo em Inglês | MEDLINE | ID: mdl-34822586

RESUMO

Ochratoxin A(OTA) is considered to be one of the most important contaminants of food and feed worldwide. The liver is one of key target organs for OTA to exert its toxic effects. Due to current lifestyle and diet, nonalcoholic fatty liver disease (NAFLD) has been the most common liver disease. To examine the potential effect of OTA on hepatic lipid metabolism and NAFLD, C57BL/6 male mice received 1 mg/kg OTA by gavage daily. Compared with controls, OTA increased lipid deposition and TG accumulation in mouse livers. In vitro OTA treatment also promoted lipid droplets accumulation in primary hepatocytes and HepG2 cells. Mechanistically, OTA prevented PPARγ degradation by reducing the interaction between PPARγ and its E3 ligase SIAH2, which led to activation of PPARγ signaling pathway. Furthermore, downregulation or inhibition of CD36, a known of PPARγ, alleviated OTA-induced lipid droplets deposition and TG accumulation. Therefore, OTA induces hepatic steatosis via PPARγ-CD36 axis, suggesting that OTA has an impact on liver lipid metabolism and may contribute to the development of metabolic diseases.

2.
Front Public Health ; 9: 687174, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34485217

RESUMO

Background: Although high genetic risk and unhealthful lifestyles are associated with a high risk of hypertension, but the combined relationship between lifestyle score and genetic factors on blood pressure remains limited, especially in resource-constrained areas. Aim: To explore the separate and joint effects between genetic and lifestyle factors on blood pressure and hypertension in rural areas. Methods: In 4,592 adults from rural China with a 3-year of follow-up, a genetic risk score (GRS) was established using 13 single nucleotide polymorphisms (SNPs) and the lifestyle score was calculated including factors diet, body mass index (BMI), smoking status, drinking status, and physical activity. The associations of genetic and lifestyle factors with blood pressure and hypertension were determined with generalized linear and logistic regression models, respectively. Results: The high-risk GRS was found to be associated with evaluated blood pressure and hypertension and the healthful lifestyle with diastolic blood pressure (DBP) level. Individuals with unhealthful lifestyles in the high GRS risk group had an odds ratio (OR) (95% CI) of 1.904 (1.006, 3.603) for hypertension than those with a healthful lifestyle in the low GRS risk group. Besides, the relative risk (RR), attributable risk (AR), and population attributable risk (PAR) for unhealthful lifestyle are 1.39, 5.87, 0.04%, respectively, and the prevented fraction for the population (PFP) for healthful lifestyle is 9.47%. Conclusion: These results propose a joint effect between genetic and lifestyle factors on blood pressure and hypertension. The findings provide support for adherence to a healthful lifestyle in hypertension precision prevention. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375.


Assuntos
Hipertensão , Adulto , Pressão Sanguínea/genética , China/epidemiologia , Estudos de Coortes , Humanos , Hipertensão/epidemiologia , Estilo de Vida
3.
Hypertens Res ; 44(11): 1483-1491, 2021 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-34480134

RESUMO

Current studies have shown the controversial effect of genetic risk scores (GRSs) in hypertension prediction. Machine learning methods are used extensively in the medical field but rarely in the mining of genetic information. This study aims to determine whether genetic information can improve the prediction of incident hypertension using machine learning approaches in a prospective study. The study recruited 4592 subjects without hypertension at baseline from a cohort study conducted in rural China. A polygenic risk score (PGGRS) was calculated using 13 SNPs. According to a ratio of 7:3, subjects were randomly allocated to the train and test datasets. Models with and without the PGGRS were established using the train dataset with Cox regression, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) methods. The discrimination and reclassification of models were estimated using the test dataset. The PGGRS showed a significant association with the risk of incident hypertension (HR (95% CI), 1.046 (1.004, 1.090), P = 0.031) irrespective of baseline blood pressure. Models that did not include the PGGRS achieved AUCs (95% CI) of 0.785 (0.763, 0.807), 0.790 (0.768, 0.811), 0.838 (0.817, 0.857), and 0.854 (0.835, 0.873) for the Cox, ANN, RF, and GBM methods, respectively. The addition of the PGGRS led to the improvement of the AUC by 0.001, 0.008, 0.023, and 0.017; IDI by 1.39%, 2.86%, 4.73%, and 4.68%; and NRI by 25.05%, 13.01%, 44.87%, and 22.94%, respectively. Incident hypertension risk was better predicted by the traditional+PGGRS model, especially when machine learning approaches were used, suggesting that genetic information may have the potential to identify new hypertension cases using machine learning methods in resource-limited areas. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375 .

4.
Oncogene ; 40(34): 5302-5313, 2021 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-34247189

RESUMO

The prognosis of hepatocellular carcinoma (HCC) remains unsatisfactory due to limited effective treatment options. In this work, we investigated the therapeutic efficacy of Terbinafine for HCC and the underlying mechanism. The influence of Terbinafine on cell growth, 3D spheroid formation, clonogenic survival, and protein synthesis was investigated in human HCC cell lines. Co-immunoprecipitation, immunofluorescence, and other techniques were employed to explore how Terbinafine exerts its anticancer effect. Subcutaneous tumorigenicity assay, orthotopic and patient-derived xenograft (PDX) HCC models were used to evaluate the anticancer effect of Terbinafine monotherapy and the combinatorial treatment with Terbinafine and sorafenib against HCC. The anticancer activity of Terbinafine was Squalene epoxidase (SQLE)-independent. Instead, Terbinafine robustly suppressed the proliferation of HCC cells by inhibiting mTORC1 signaling via activation of AMPK. Terbinafine alone or in combination with sorafenib delayed tumor progression and markedly prolonged the survival of tumor-bearing mice. The synergy between Terbinafine and sorafenib was due to concomitant inhibition of mTORC1 and induction of severe persistent DNA double-strand breaks (DSBs), which led to the delayed proliferation and accelerated cell death. Terbinafine showed promising anticancer efficacy in preclinical models of HCC and may serve as a potential therapeutic strategy for HCC.

5.
Micromachines (Basel) ; 12(7)2021 Jun 30.
Artigo em Inglês | MEDLINE | ID: mdl-34209411

RESUMO

Indoor localization is the basis for most Location-Based Services (LBS), including consumptions, health care, public security, and augmented reality. Sensory landmarks related to the indoor spatial structures (such as escalators, stairs, and corners) do not rely on active signal transmitting devices and have fixed positions, which can be used as the absolute positioning information to improve the performance of indoor localization effectively without extra cost. Specific motion patterns are presented when users pass these architectural structures, which can be captured by mobile built-in sensors, including accelerometers, gyroscopes, and magnetometers, to achieve the recognition of structure-related sensory landmarks. Therefore, the recognition of these landmarks can draw on the mature methods of Human Activity Recognition (HAR) with improvements. To this end, we improved a Long Short-Term Memory (LSTM) neural network to recognize different kinds of spatial structure-related sensory landmarks. Labels of structural sensory landmarks were proposed, and data processing methods (including interpolation, filter, and window length) were used and compared to achieve the highest recognition accuracy of 99.6%.

6.
Build Environ ; 201: 108009, 2021 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-34075270

RESUMO

In previous reports, the positive SARS-CoV-2 nucleic acid was detected in the fecal samples from confirmed pneumonia patients, suggesting a high probability of the fecal-oral transmission. To date, however, the role played by the drainage system of a high-rise building in the virus transmission is not clear and especially studies on the dynamics mechanism behind is scarce. From this point of view, the present work carries out a computational fluid dynamics (CFD) modeling to investigate the effects of the water seal effectiveness of the floor drain, the negative/positive pressures (P 1 , P 2 ) in the bathroom, temperature differential (ΔT), outside wind velocity (v), the piping fittings and the negative pressure at the cowl (P 3 ) on the transmission of the virus-laden aerosol particles in a drainage system of a typical 7-storeys residential building. The CFD models are first validated by the previous experiments in literature. Numerical results imply that the drainage system might play an essential role to the virus transmission. Then, results indicate that, the leakage risk of the aerosol particles via the floor drain with inefficient water-seal (UFD) mainly exists at the upper floors above the neutral pressure level (NPL). Besides, the negative and positive pressures at the bathroom can enhance and reduce the exposure risk of aerosol particles from the corresponding UFD, respectively. The ΔT increasing does not modify the location of the NPL. Moreover, the exposure risk of aerosol particles can be effectively avoided by the well water-sealed floor drains and/or the presence of a proper negative pressure at the cowl on the top floor. Finally, based on the CFD results, several protection suggestions on the drainage system and human activities are provided.

7.
J Med Chem ; 64(14): 10312-10332, 2021 07 22.
Artigo em Inglês | MEDLINE | ID: mdl-34184879

RESUMO

Inhibitors of leucine-rich repeat kinase 2 (LRRK2) and mutants, such as G2019S, have potential utility in Parkinson's disease treatment. Fragment hit-derived pyrrolo[2,3-d]pyrimidines underwent optimization using X-ray structures of LRRK2 kinase domain surrogates, based on checkpoint kinase 1 (CHK1) and a CHK1 10-point mutant. (2R)-2-Methylpyrrolidin-1-yl derivative 18 (LRRK2 G2019S cKi 0.7 nM, LE 0.66) was identified, with increased potency consistent with an X-ray structure of 18/CHK1 10-pt. mutant showing the 2-methyl substituent proximal to Ala147 (Ala2016 in LRRK2). Further structure-guided elaboration of 18 gave the 2-[(1,3-dimethyl-1H-pyrazol-4-yl)amino] derivative 32. Optimization of 32 afforded diastereomeric oxolan-3-yl derivatives 44 and 45, which demonstrated a favorable in vitro PK profile, although they displayed species disconnects in the in vivo PK profile, and a propensity for P-gp- and/or BCRP-mediated efflux in a mouse model. Compounds 44 and 45 demonstrated high potency and exquisite selectivity for LRRK2 and utility as chemical probes for the study of LRRK2 inhibition.


Assuntos
Quinase 1 do Ponto de Checagem/química , Desenho de Fármacos , Serina-Treonina Proteína Quinase-2 com Repetições Ricas em Leucina/antagonistas & inibidores , Inibidores de Proteínas Quinases/farmacologia , Pirimidinas/farmacologia , Pirróis/farmacologia , Quinase 1 do Ponto de Checagem/metabolismo , Cristalografia por Raios X , Relação Dose-Resposta a Droga , Células HEK293 , Humanos , Serina-Treonina Proteína Quinase-2 com Repetições Ricas em Leucina/metabolismo , Modelos Moleculares , Estrutura Molecular , Inibidores de Proteínas Quinases/síntese química , Inibidores de Proteínas Quinases/química , Pirimidinas/síntese química , Pirimidinas/química , Pirróis/síntese química , Pirróis/química , Relação Estrutura-Atividade
8.
IEEE J Biomed Health Inform ; 25(10): 4005-4016, 2021 10.
Artigo em Inglês | MEDLINE | ID: mdl-33939617

RESUMO

Diabetes mellitus is one of the major public health problems in the world due to its high prevalence and medical costs. The prevention effort necessitates reliable risk assessment models which can effectively identify high-risk individuals and enable healthcare practitioners to initiate appropriate preventive interventions. However, diabetes risk assessment models based on data analysis face multiple challenges, such as class imbalance and low identification rate. To cope with these challenges, this paper proposed an analytical framework based on data-driven approaches using large population data from the Henan Rural Cohort Study. A joint bagging-boosting model (JBM) was developed and validated. For the convenience of large-scale population screening, our study excluded laboratory variables and collinearity variables using the maximum likelihood ratio method to obtain accessibility variables. Then, we explored the effects of different methods for dealing with the unbalanced nature of the available data, including over-sampling and under-sampling methods. Finally, to improve the overall model performance, a joint model which combined the bagging and boosting algorithms with the stacking algorithm was constructed. The model we built demonstrated good discrimination, with an area under the curve (AUC) value of 0.885, and acceptable calibration (Brier score = 0.072). Compared with the benchmark model, the proposed framework improved the AUC value of the overall model performance by 13.5%, and the recall increased from 0.744 to 0.847. The proposed model contributes to the personalized management of diabetes, especially in medical resource-poor settings.


Assuntos
Diabetes Mellitus Tipo 2 , População Rural , China/epidemiologia , Estudos de Coortes , Diabetes Mellitus Tipo 2/diagnóstico , Diabetes Mellitus Tipo 2/epidemiologia , Humanos , Medição de Risco
9.
Nat Commun ; 12(1): 3059, 2021 05 24.
Artigo em Inglês | MEDLINE | ID: mdl-34031390

RESUMO

Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent chronic liver disease in the world, however, no drug treatment has been approved for this disease. Thus, it is urgent to find effective therapeutic targets for clinical intervention. In this study, we find that liver-specific knockout of PPDPF (PPDPF-LKO) leads to spontaneous fatty liver formation in a mouse model at 32 weeks of age on chow diets, which is enhanced by HFD. Mechanistic study reveals that PPDPF negatively regulates mTORC1-S6K-SREBP1 signaling. PPDPF interferes with the interaction between Raptor and CUL4B-DDB1, an E3 ligase complex, which prevents ubiquitination and activation of Raptor. Accordingly, liver-specific PPDPF overexpression effectively inhibits HFD-induced mTOR signaling activation and hepatic steatosis in mice. These results suggest that PPDPF is a regulator of mTORC1 signaling in lipid metabolism, and may be a potential therapeutic candidate for NAFLD.


Assuntos
Fígado Gorduroso/metabolismo , Peptídeos e Proteínas de Sinalização Intracelular/genética , Peptídeos e Proteínas de Sinalização Intracelular/metabolismo , Fígado/metabolismo , Transdução de Sinais/fisiologia , Serina-Treonina Quinases TOR/metabolismo , Animais , Proteínas Culina/metabolismo , Proteínas de Ligação a DNA/metabolismo , Células HEK293 , Células Hep G2 , Humanos , Metabolismo dos Lipídeos , Fígado/patologia , Masculino , Camundongos , Camundongos Knockout , Hepatopatia Gordurosa não Alcoólica/metabolismo
10.
Front Public Health ; 9: 606711, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33681127

RESUMO

Background: Previous studies have constructed prediction models for type 2 diabetes mellitus (T2DM), but machine learning was rarely used and few focused on genetic prediction. This study aimed to establish an effective T2DM prediction tool and to further explore the potential of genetic risk scores (GRS) via various classifiers among rural adults. Methods: In this prospective study, the GRS for a total of 5,712 participants from the Henan Rural Cohort Study was calculated. Cox proportional hazards (CPH) regression was used to analyze the associations between GRS and T2DM. CPH, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) were used to establish prediction models, respectively. The area under the receiver operating characteristic curve (AUC) and net reclassification index (NRI) were used to assess the discrimination ability of the models. The decision curve was plotted to determine the clinical-utility for prediction models. Results: Compared with the individuals in the lowest quintile of the GRS, the HR (95% CI) was 2.06 (1.40 to 3.03) for those with the highest quintile of GRS (P trend < 0.05). Based on conventional predictors, the AUCs of the prediction model were 0.815, 0.816, 0.843, and 0.851 via CPH, ANN, RF, and GBM, respectively. Changes with the integration of GRS for CPH, ANN, RF, and GBM were 0.001, 0.002, 0.018, and 0.033, respectively. The reclassifications were significantly improved for all classifiers when adding GRS (NRI: 41.2% for CPH; 41.0% for ANN; 46.4% for ANN; 45.1% for GBM). Decision curve analysis indicated the clinical benefits of model combined GRS. Conclusion: The prediction model combined with GRS may provide incremental predictions of performance beyond conventional factors for T2DM, which demonstrated the potential clinical use of genetic markers to screen vulnerable populations. Clinical Trial Registration: The Henan Rural Cohort Study is registered in the Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699). http://www.chictr.org.cn/showproj.aspx?proj=11375.


Assuntos
Diabetes Mellitus Tipo 2 , Adulto , Estudos de Coortes , Diabetes Mellitus Tipo 2/epidemiologia , Humanos , Aprendizado de Máquina , Estudos Prospectivos , Medição de Risco , Fatores de Risco
11.
Nanoscale ; 13(8): 4496-4504, 2021 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-33599650

RESUMO

Photocatalytic overall water splitting to simultaneously obtain abundant hydrogen and oxygen is still the mountain that stands in the way for the practical applications of hydrogen energy, in which composite semiconductor photocatalysts are critical for providing both electrons and holes to promote the following redox reaction. However, the interface between different components forms a deplete layer to hinder the charge transfer to a large extent. In order to enhance the charger transfer from an interface to the surface and promote the spatial separation of electron-hole pairs, a built-in electric field induced by a p-n heterojunction emerges as the best choice. As a touchstone, a p-n heterojunction of TiO2/BiOBr with a strong built-in electric field has been constructed, which presents a wide spectrum response owing to its interleaved band gaps after composition. The built-in electric field greatly enhances the separation and transportation of photogenerated carriers, resulting in fluorescence quenching due to the carrier recombination. The sample also displayed exceptional photoelectron responses: its photocurrent density (43.3 µA cm-2) was over 10 times that of TiO2 (3.5 µA cm-2) or BiOBr (4.2 µA cm-2). In addition, the sample with a molar ratio of 3 : 1 between TiO2 and BiOBr showed the best photocatalytic overall water splitting performance under visible light (λ > 420 nm): the hydrogen and oxygen production rate were 472.7 µmol gcat.-1 h-1 and 95.7 µmol gcat.-1 h-1, respectively, which are the highest values under visible light without other cocatalysts to have been reported in literature for the photocatalyst.

12.
Lipids Health Dis ; 20(1): 11, 2021 Feb 12.
Artigo em Inglês | MEDLINE | ID: mdl-33579296

RESUMO

BACKGROUND: Few studies have developed risk models for dyslipidaemia, especially for rural populations. Furthermore, the performance of genetic factors in predicting dyslipidaemia has not been explored. The purpose of this study is to develop and evaluate prediction models with and without genetic factors for dyslipidaemia in rural populations. METHODS: A total of 3596 individuals from the Henan Rural Cohort Study were included in this study. According to the ratio of 7:3, all individuals were divided into a training set and a testing set. The conventional models and conventional+GRS (genetic risk score) models were developed with Cox regression, artificial neural network (ANN), random forest (RF), and gradient boosting machine (GBM) classifiers in the training set. The area under the receiver operating characteristic curve (AUC), net reclassification index (NRI), and integrated discrimination index (IDI) were used to assess the discrimination ability of the models, and the calibration curve was used to show calibration ability in the testing set. RESULTS: Compared to the lowest quartile of GRS, the hazard ratio (HR) (95% confidence interval (CI)) of individuals in the highest quartile of GRS was 1.23(1.07, 1.41) in the total population. Age, family history of diabetes, physical activity, body mass index (BMI), triglycerides (TGs), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were used to develop the conventional models, and the AUCs of the Cox, ANN, RF, and GBM classifiers were 0.702(0.673, 0.729), 0.736(0.708, 0.762), 0.787 (0.762, 0.811), and 0.816(0.792, 0.839), respectively. After adding GRS, the AUCs increased by 0.005, 0.018, 0.023, and 0.015 with the Cox, ANN, RF, and GBM classifiers, respectively. The corresponding NRI and IDI were 25.6, 7.8, 14.1, and 18.1% and 2.3, 1.0, 2.5, and 1.8%, respectively. CONCLUSION: Genetic factors could improve the predictive ability of the dyslipidaemia risk model, suggesting that genetic information could be provided as a potential predictor to screen for clinical dyslipidaemia. TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at the Chinese Clinical Trial Register. (Trial registration: ChiCTR-OOC-15006699 . Registered 6 July 2015 - Retrospectively registered).


Assuntos
Dislipidemias/genética , Predisposição Genética para Doença , Modelos Biológicos , Calibragem , Estudos de Coortes , Humanos , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Curva ROC , Fatores de Risco
13.
Arthritis Res Ther ; 23(1): 7, 2021 01 06.
Artigo em Inglês | MEDLINE | ID: mdl-33407821

RESUMO

BACKGROUND: There are few studies on the hyperuricemia (HUA) and moderate to vigorous intensity physical activity (PA) and also hardly regarding sitting time (ST). The purpose of this study was to examine the independent and interactive association of PA and ST with HUA. METHODS: A cross-sectional analysis was performed on 38,855 participants (aged 18-79) enrolled from the Henan Rural Cohort Study at baseline (2015 to 2017). PA and ST levels were assessed by using the International Physical Activity Questionnaire (IPAQ). HUA was defined as a serum uric acid level of > 7.0 mg/dL for males and > 6.0 mg/dL for females. Multivariable logistic regression and linear regression models were applied to examine the independent association between PA or ST and HUA and serum uric acid level. Interaction plots were used to visualize the interaction effects of PA and ST on HUA. RESULTS: PA level was inversely related with serum uric acid level (ß - 0.15, 95% confidence interval (CI) - 0.22, - 0.07), but ST was positively related with uric acid level (ß 2.12, 95% CI 1.90, 2.34). Metabolic equivalent (MET-hour/day) was associated with decreased prevalence of HUA (odds ratio (OR) 0.97, 95% CI 0.96, 0.99), while per hour increased for ST was associated with increased HUA (OR 1.05, 95% CI 1.04, 1.06). The interaction of PA and ST was significant (P < 0.001). CONCLUSION: Exposure to higher ST was independently related to increased prevalence of HUA, while vigorous PA with a decreased HUA prevalence. Meanwhile, higher daily ST might attenuate the protective effect of PA on HUA. TRIAL REGISTRATION: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699 ).


Assuntos
Hiperuricemia , Estudos de Coortes , Estudos Transversais , Exercício Físico , Feminino , Humanos , Hiperuricemia/epidemiologia , Masculino , Prevalência , Fatores de Risco , Ácido Úrico
14.
Environ Res ; 191: 110116, 2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-32846171

RESUMO

BACKGROUND: Prolonged sleep latency is associated with far-reaching public health consequences. Although evidence about the effect of air pollution on sleep problem has been shown, the effect on sleep latency remained unknown. The study aimed to analyze the association between long-term exposure to air pollution and prolonged sleep latency in rural China. METHODS: In all, 27935 participants were included in the study from Henan Rural Cohort Study. A satellite-based spatiotemporal model was used to evaluate the 3-year average concentration of air pollutants at the home address of participants before the baseline survey. Air pollutants included NO2 (nitrogen dioxide), PM1 (particulate matter with aerodynamic diameters ≤1 µm), PM2.5 (particulate matter with aerodynamic diameters ≤ 2.5 µm), and PM10 (particulate matter with aerodynamic diametes ≤ 10 µm). A logistic regression model was conducted to assess the odds ratio (OR) and 95% confidence interval (95% CI) between air pollutants and prolonged sleep latency. RESULTS: There were 5825 (20.85%) participants with prolonged sleep latency. The average concentration of NO2, PM1, PM2.5, and PM10 were 38.22 (2.54) µg/m3, 56.29 (1.75) µg/m3, 72.30 (1.87) µg/m3, and 130.01 (4.58) µg/m3. The odds ratio (95%CI) of prolonged sleep latency with an IQR increase of NO2, PM1, PM2.5, and PM10 were 1.59 (1.33-1.90), 1.23 (1.13-1.33), 1.28 (1.13-1.45) and 1.43 (1.22-1.67). The stratified analysis showed the effect of air pollutants was stronger among those with stroke. CONCLUSION: Long-term exposure to NO2, PM1, PM2.5 and PM10 were associated with prolonged sleep latency. The adverse impact of air pollution should be considered when treating sleep problems.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluentes Atmosféricos/toxicidade , Poluição do Ar/efeitos adversos , Poluição do Ar/análise , China/epidemiologia , Estudos de Coortes , Exposição Ambiental/efeitos adversos , Exposição Ambiental/análise , Humanos , Dióxido de Nitrogênio/análise , Dióxido de Nitrogênio/toxicidade , Material Particulado/análise , Material Particulado/toxicidade , Latência do Sono
15.
BMC Public Health ; 20(1): 1297, 2020 Aug 27.
Artigo em Inglês | MEDLINE | ID: mdl-32854672

RESUMO

BACKGROUND: The epidemiological evidence on the association of sleep quality on anxiety symptoms has been inconclusive. This study aimed to explore the association between sleep quality and anxiety symptoms in rural Chinese population and investigate whether age, lifestyles, and chronic diseases modified this association. METHODS: A total of 27,911 participants aged 18-79 years from the Henan Rural Cohort Study were included in the study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) scale. Poor sleep quality was defined as PSQI ≥6. Anxiety symptoms were evaluated with the two-item generalized anxiety disorder scale (GAD-2). Individual with score ≥ 3 was viewed as having anxiety symptoms. Logistic regression and restricted cubic spline were conducted to examine the association of sleep quality with anxiety symptoms. RESULTS: Altogether, 6087 (21.80%) participants were poor sleepers and 1557 (5.58%) had anxiety symptoms. The odds of anxiety were increased with increment of PSQI score after fitting restricted cubic splines. The poor sleep quality was associated with a higher possibility of anxiety symptoms [odd ratio (OR): 4.60, 95% confidence interval (CI): 3.70-5.72] in men, and (OR: 3.56, 95% CI: 3.10-4.09) in women for multivariable analysis. Further, stratified analyses showed that the effect of sleep quality on anxiety symptoms could be modified by age, marital status, smoking status, drinking status, hypertension, and type 2 diabetes mellitus. CONCLUSIONS: A dose-response association between PSQI score and anxiety symptoms was found. In addition, the relationship between poor sleep quality and greater anxiety symptoms was observed in this rural population, especially in participants aged ≥60 years and those with unhealthy habits or had a chronic disease. TRIAL REGISTRATION: The trial was prospectively registered on July 6, 2015 and available online at ClinicalTrials.gov ID: ChiCTR-OOC-15006699 .


Assuntos
Ansiedade/epidemiologia , Distúrbios do Início e da Manutenção do Sono/epidemiologia , Sono , Adolescente , Adulto , Distribuição por Idade , Idoso , China/epidemiologia , Doença Crônica/epidemiologia , Estudos de Coortes , Feminino , Humanos , Estilo de Vida , Masculino , Pessoa de Meia-Idade , Razão de Chances , Questionário de Saúde do Paciente , População Rural , Adulto Jovem
16.
Front Public Health ; 8: 70, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32266195

RESUMO

Background: Obesity is an important risk factor for hypertension. Previous studies have explored the association between body fat percentage (BFP) and hypertension, but evidence on the consistency of the association remains uncertain and limited. The aim of this study was to explore the relationship between BFP and hypertension in a Chinese rural population. Methods: The present cross-sectional study including 38,913 eligible individuals was conducted in rural areas of Henan province. BFP was measured by bioelectrical impedance methods using Omron body fat and weight measurement device. Logistic regression models and restricted cubic spline regression models were performed to investigate the relationship between BFP and hypertension. Receiver operating characteristic (ROC) analyses were used to compare the discriminating power of adiposity indices. Results: The age-standard prevalence of hypertension was 23.74 and 17.87% in males and females, respectively. Compared with the first quartile of BFP, the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension in the highest BFP quartile were 3.30 (95% CI: 2.85, 3.83) in males and 2.66 (95% CI: 2.36, 2.99) in females, and the adjusted ORs increased along with increasing BFP levels. The areas under ROC and 95% CIs of BFP were 0.673 (0.665, 0.682) in males and 0.696 (0.689, 0.703) in females, respectively. Conclusions: BFP was significantly positively associated with the prevalence of hypertension in both males and females in the Chinese rural population. Controlling of body fat should be emphasized in rural areas of China. Clinical Trial Registration: Registration number: ChiCTR-OOC-15006699. http://www.chictr.org.cn/showproj.aspx?proj=11375.


Assuntos
Hipertensão , População Rural , Tecido Adiposo , China/epidemiologia , Estudos de Coortes , Estudos Transversais , Feminino , Humanos , Hipertensão/epidemiologia , Masculino
17.
BMC Public Health ; 20(1): 285, 2020 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-32131791

RESUMO

BACKGROUND: Adiposity plays a crucial role in the risk of osteoporosis. However, the impact of body fat distribution on the skeleton is contentious. The study was designed to explore the association of various adiposity indices with estimated bone mineral density (BMD) and the risk of osteoporosis based on body mass index (BMI), body fat percentage (BFP), waist circumference (WC), waist to hip ratio (WHR), waist to height ratio (WHtR), and visceral fat index (VFI). METHODS: A total of 8475 subjects derived from the Henan Rural Cohort Study were analyzed. The estimated BMD of study participants were measured by calcaneal quantitative ultrasound (QUS). Linear regression and binary logistic regression were performed to estimate the association of adiposity and the outcomes. RESULTS: The mean age of the study participants was 55.23 ± 11.09 years and 59.61% were women. The crude and age-standardized prevalence of high osteoporosis risk was 16.24 and 11.82%. Per unit increment in adiposity indices was associated with 0.005-0.021 g/cm2 increase in estimated BMD. The adjusted odds ratios (95% confidence interval) for high osteoporosis risk in per 1 SD increase of WC, WHR, WHtR, BMI, BFP, and VFI were 0.820 (0.748, 0.898), 0.872 (0.811, 0.938), 0.825 (0.765, 0.891), 0.798 (0.726, 0.878), 0.882 (0.800, 0.972), and 0.807 (0.732, 0.889), respectively. Stratified analyses indicated greater effects on individuals aged 55 years or older. CONCLUSIONS: The adiposity indices have an inverse association with the risk of osteoporosis among Chinese rural population, especially in the elderly.


Assuntos
Adiposidade , Osteoporose/epidemiologia , População Rural/estatística & dados numéricos , Adulto , Idoso , China/epidemiologia , Estudos de Coortes , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Risco
18.
Sci Rep ; 10(1): 4406, 2020 03 10.
Artigo em Inglês | MEDLINE | ID: mdl-32157171

RESUMO

With the development of data mining, machine learning offers opportunities to improve discrimination by analyzing complex interactions among massive variables. To test the ability of machine learning algorithms for predicting risk of type 2 diabetes mellitus (T2DM) in a rural Chinese population, we focus on a total of 36,652 eligible participants from the Henan Rural Cohort Study. Risk assessment models for T2DM were developed using six machine learning algorithms, including logistic regression (LR), classification and regression tree (CART), artificial neural networks (ANN), support vector machine (SVM), random forest (RF) and gradient boosting machine (GBM). The model performance was measured in an area under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value and area under precision recall curve. The importance of variables was identified based on each classifier and the shapley additive explanations approach. Using all available variables, all models for predicting risk of T2DM demonstrated strong predictive performance, with AUCs ranging between 0.811 and 0.872 using laboratory data and from 0.767 to 0.817 without laboratory data. Among them, the GBM model performed best (AUC: 0.872 with laboratory data and 0.817 without laboratory data). Performance of models plateaued when introduced 30 variables to each model except CART model. Among the top-10 variables across all methods were sweet flavor, urine glucose, age, heart rate, creatinine, waist circumference, uric acid, pulse pressure, insulin, and hypertension. New important risk factors (urinary indicators, sweet flavor) were not found in previous risk prediction methods, but determined by machine learning in our study. Through the results, machine learning methods showed competence in predicting risk of T2DM, leading to greater insights on disease risk factors with no priori assumption of causality.


Assuntos
Diabetes Mellitus Tipo 2/epidemiologia , População Rural/estatística & dados numéricos , Adulto , Idoso , China/epidemiologia , Estudos de Coortes , Feminino , Humanos , Modelos Logísticos , Aprendizado de Máquina , Masculino , Pessoa de Meia-Idade , Redes Neurais de Computação , Curva ROC , Medição de Risco
19.
J Diabetes Complications ; 34(5): 107558, 2020 05.
Artigo em Inglês | MEDLINE | ID: mdl-32075751

RESUMO

AIMS: We aimed to evaluate the associations of mineralocorticoids with type 2 diabetes mellitus (T2DM) and glucose homeostasis among rural Chinese adults. METHODS: A total of 2713 participants were selected from the Henan Rural Cohort study. Serum mineralocorticoids were measured by liquid chromatography-tandem mass spectrometry. Logistic regression and restricted cubic splines were employed to evaluate the associations of mineralocorticoids with pre-diabetes and T2DM. Linear regression was implemented to assess the associations of aldosterone and 11-deoxycorticosterone with different markers of glucose homeostasis by different diabetes status. RESULTS: Elevated aldosterone and 11-deoxycorticosterone were associated with an increased prevalence of pre-diabetes and T2DM (P < 0.05), with a nonlinear dose-response trend, but the association between 11-deoxycorticosterone and T2DM was no statistical significance after adjustment. A 100% increase in ln-aldosterone was associated with a 0.029 mg/dl higher fasting plasma glucose (FPG) and a 1.2% higher HOMA2-IR among those with normal glucose tolerance (NGT), and related to a 0.034 mg/dl lower FPG, a 1.1% higher HbA1c and a 1.3% higher HOMA2-ß among individuals with pre-diabetes. A 100% increment in ln-11-deoxycorticosterone was associated with a 16% increase in HbA1c and a 5.6% decrease in HOMA2-ß in participants with T2DM. CONCLUSIONS: Higher aldosterone and 11-deoxycorticosterone are associated with T2DM risk and glucose homeostasis disorder among different diabetes status.


Assuntos
Aldosterona/sangue , Desoxicorticosterona/sangue , Diabetes Mellitus Tipo 2/epidemiologia , Glucose/metabolismo , Estado Pré-Diabético/epidemiologia , Idoso , Aldosterona/metabolismo , Biomarcadores/sangue , Biomarcadores/metabolismo , Glicemia/metabolismo , Estudos de Casos e Controles , China/epidemiologia , Desoxicorticosterona/metabolismo , Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/metabolismo , Diabetes Mellitus Tipo 2/fisiopatologia , Feminino , Glucose/análise , Homeostase , Humanos , Resistência à Insulina , Masculino , Pessoa de Meia-Idade , Mineralocorticoides/sangue , Mineralocorticoides/metabolismo , Estado Pré-Diabético/sangue , Estado Pré-Diabético/metabolismo , Estado Pré-Diabético/fisiopatologia , Prevalência , Fatores de Risco , População Rural/estatística & dados numéricos
20.
Proc Natl Acad Sci U S A ; 117(9): 4770-4780, 2020 03 03.
Artigo em Inglês | MEDLINE | ID: mdl-32071245

RESUMO

Recurrence and metastasis remain the major obstacles to successful treatment of hepatocellular carcinoma (HCC). Chromatin remodeling factor ARID2 is commonly mutated in HCC, indicating its important role in cancer development. However, its role in HCC metastasis is largely elusive. In this study, we find that ARID2 expression is significantly decreased in metastatic HCC tissues, showing negative correlation with pathological grade, organ metastasis and positive association with survival of HCC patients. ARID2 inhibits migration and invasion of HCC cells in vitro and metastasis in vivo. Moreover, ARID2 knockout promotes pulmonary metastasis in different HCC mouse models. Mechanistic study reveals that ARID2 represses epithelial-mesenchymal transition (EMT) of HCC cells by recruiting DNMT1 to Snail promoter, which increases promoter methylation and inhibits Snail transcription. In addition, we discover that ARID2 mutants with disrupted C2H2 domain lose the metastasis suppressor function, exhibiting a positive association with HCC metastasis and poor prognosis. In conclusion, our study reveals the metastasis suppressor role as well as the underlying mechanism of ARID2 in HCC and provides a potential therapeutic target for ARID2-deficient HCC.


Assuntos
Carcinoma Hepatocelular/tratamento farmacológico , Carcinoma Hepatocelular/metabolismo , Montagem e Desmontagem da Cromatina/fisiologia , DNA (Citosina-5-)-Metiltransferase 1/metabolismo , Neoplasias Hepáticas/tratamento farmacológico , Metástase Neoplásica/tratamento farmacológico , Fatores de Transcrição/metabolismo , Animais , Dedos de Zinco CYS2-HIS2 , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/patologia , Linhagem Celular Tumoral , Movimento Celular/efeitos dos fármacos , Modelos Animais de Doenças , Transição Epitelial-Mesenquimal , Regulação Neoplásica da Expressão Gênica , Humanos , Neoplasias Hepáticas/genética , Neoplasias Hepáticas/patologia , Neoplasias Pulmonares/tratamento farmacológico , Neoplasias Pulmonares/patologia , Camundongos , Camundongos Knockout , Mutação , Metástase Neoplásica/patologia , Fatores de Transcrição/antagonistas & inibidores , Fatores de Transcrição/genética
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