Causal relationship between linoleic acid and type 2 diabetes and glycemic traits: a bidirectional Mendelian randomization study.

Objective: To investigate the causal relationships between linoleic acid and type 2 diabetes, and between linoleic acid and glycemic traits in European populations. Methods: This study employed a two-sample Mendelian randomization approach to infer causality between linoleic acid and type 2 diabetes, as well as between linoleic acid and glycemic traits, leveraging genetic variations. Data were sourced from genome-wide association study summary datasets. Random-effects inverse-variance weighted, weighted median, and MR-Egger methods were used for the two-sample Mendelian randomization analyses. Results were presented as odds ratios with a 95% confidence interval. Multiple sensitivity analyses were conducted to assess result robustness. Results: MR findings indicated a correlation between linoleic acid levels and the risk of type 2 diabetes, fasting blood glucose, and glycated hemoglobin (HbA1c), but not with fasting insulin. Specifically: type 2 diabetes (OR: 0.811, 95% CI: 0.688-0.956, P=0.013<0.05),fasting blood glucose (ß_IVW): -0.056, 95% CI: (-0.091,-0.021), P=0.002< 0.0125), glycated hemoglobin (ß_IVW: -0.032, 95% CI: (-0.048,-0.015), P=0.0002< 0.0125) and Fasting insulin (ß_IVW: -0.024, 95% CI: (-0.056,-0.008), P=0.136 >0.05).Reverse MR analyses showed a correlation between type 2 diabetes and reduced levels of linoleic acid (ß_IVW: -0.033, 95% CI: (-0.059,-0.006), P=0.014<0.05). Multiple sensitivity analyses also detected study heterogeneity but found no evidence of horizontal pleiotropy. Conclusion: High levels linoleic acid can reduce the risk of type 2 diabetes, fasting blood glucose, and glycated hemoglobin, but has no significant relation with fasting insulin. Type 2 diabetes can lower linoleic acid levels; however, no significant causal relationship was observed between the three glycemic traits and reduced levels of linoleic acid.

Factors associated with overdiagnosis of benign pulmonary nodules as malignancy: a retrospective cohort study.

OBJECTIVE: To establish a preoperative model for the differential diagnosis of benign and malignant pulmonary nodules (PNs), and to evaluate the related factors of overdiagnosis of benign PNs at the time of imaging assessments. MATERIALS AND METHODS: In this retrospective study, 357 patients (median age, 52 years; interquartile range, 46-59 years) with 407 PNs were included, who underwent surgical histopathologic evaluation between January 2020 and December 2020. Patients were divided into a training set (n = 285) and a validation set (n = 122) to develop a preoperative model to identify benign PNs. CT scan features were reviewed by two chest radiologists, and imaging findings were categorized. The overdiagnosis rate of benign PNs was calculated, and bivariate and multivariable logistic regression analyses were used to evaluate factors associated with benign PNs that were over-diagnosed as malignant PNs. RESULTS: The preoperative model identified features such as the absence of part-solid and non-solid nodules, absence of spiculation, absence of vascular convergence, larger lesion size, and CYFRA21-1 positivity as features for identifying benign PNs on imaging, with a high area under the receiver operating characteristic curve of 0.88 in the validation set. The overdiagnosis rate of benign PNs was found to be 50%. Independent risk factors for overdiagnosis included diagnosis as non-solid nodules, pleural retraction, vascular convergence, and larger lesion size at imaging. CONCLUSION: We developed a preoperative model for identifying benign and malignant PNs and evaluating factors that led to the overdiagnosis of benign PNs. This preoperative model and result may help clinicians and imaging physicians reduce unnecessary surgery.

Integrating microbial community properties, biomass and necromass to predict cropland soil organic carbon.

Manipulating microorganisms to increase soil organic carbon (SOC) in croplands remains a challenge. Soil microbes are important drivers of SOC sequestration, especially via their necromass accumulation. However, microbial parameters are rarely used to predict cropland SOC stocks, possibly due to uncertainties regarding the relationships between microbial carbon pools, community properties and SOC. Herein we evaluated the microbial community properties (diversity and network complexity), microbial carbon pools (biomass and necromass carbon) and SOC in 468 cropland soils across northeast China. We found that not only microbial necromass carbon but also microbial community properties (diversity and network complexity) and biomass carbon were correlated with SOC. Microbial biomass carbon and diversity played more important role in predicting SOC for maize, while microbial network complexity was more important for rice. Models to predict SOC performed better when the microbial community and microbial carbon pools were included simultaneously. Taken together our results suggest that microbial carbon pools and community properties influence SOC accumulation in croplands, and management practices that improve these microbial parameters may increase cropland SOC levels.

Preserved Ratio Impaired Spirometry and Risks of Macrovascular, Microvascular Complications and Mortality Among Individuals With Type 2 Diabetes.

BACKGROUND: The prospective associations of preserved ratio impaired spirometry (PRISm) with new-onset macrovascular and microvascular complications and mortality among individuals with type 2 diabetes (T2D) and whether PRISm enhances the prediction ability of an established office-based risk score remain to be elucidated. RESEARCH QUESTION: Can PRISm be used as a predictor of poor prognosis in individuals with T2D? STUDY DESIGN AND METHODS: We included 20,047 study participants with T2D and complete data on spirometry at recruitment from the UK Biobank cohort. Multivariable Cox proportional hazards models were used to assess the associations of baseline PRISm (FEV1 to FVC ratio, ≥ 0.70; FEV1, < 80% predicted) with subsequent risks of incident stroke (any type), ischemic stroke, myocardial infarction, unstable angina, coronary heart disease, diabetic retinopathy, diabetic kidney disease, all-cause mortality, cardiovascular mortality, and respiratory mortality. RESULTS: For this cohort analysis, 4,521 patients (22.55% of participants with T2D) showed comorbid PRISm at baseline. Over a median follow-up of 11.52 to 11.87 years, patients with T2D with PRISm at baseline showed higher risks than those with normal spirometry findings of various T2D complications developing and mortality; the adjusted hazard ratios for PRISm were 1.413 (95% CI, 1.187-1.681) for stroke (any type), 1.382 (95% CI, 1.129-1.690) for ischemic stroke, 1.253 (95% CI, 1.045-1.503) for myocardial infarction, 1.206 (95% CI, 1.086-1.339) for coronary heart disease, 1.311 (95% CI, 1.141-1.506) for diabetic retinopathy, 1.384 (95% CI, 1.190-1.610) for diabetic kidney disease, 1.337 (95% CI, 1.213-1.474) for all-cause mortality, 1.597 (95% CI, 1.296-1.967) for cardiovascular mortality, and 1.559 (95% CI, 1.189-2.044) for respiratory mortality, respectively. The addition of PRISm significantly improved the reclassification ability, based on the net reclassification index, of an office-based risk score by 15.53% (95% CI, 10.14%-19.63%) to 33.60% (95% CI, 20.90%-45.79%). INTERPRETATION: Individuals with T2D with comorbid PRISm, accounting for a considerable proportion of the population with T2D, showed significantly increased risks of adverse macrovascular and microvascular complications and mortality.

Handgrip strength is associated with risks of new-onset stroke and heart disease: results from 3 prospective cohorts.

BACKGROUND: Stroke and heart disease are two major contributors to the global disease burden. We aimed to evaluate and compare the roles of different handgrip strength (HGS) expressions in predicting stroke and heart disease in three nationally representative cohorts. METHODS: This longitudinal study used data from the Health and Retirement Study (HRS), the Survey of Health, Ageing, and Retirement in Europe (SHARE), and the China Health and Retirement Longitudinal Study (CHARLS). The Cox proportional hazard model was applied to analyze the relationship between HGS and stroke and heart disease, and Harrell's C index was used to assess the predictive abilities of different HGS expressions. RESULTS: A total of 4,407 participants suffered from stroke and 9,509 from heart disease during follow-up. Compared with the highest quartile, participants in the lowest quartile of dominant HGS, absolute HGS and relative HGS possessed a significantly higher risk of new-onset stroke in Europe, America, and China (all P < 0.05). After adding HGS to office-based risk factors, there were minimal or no differences in the increases of Harrell's C indexes among three HGS expressions. In contrast, the modest association between HGS and heart disease was only seen in SHARE and HRS, but not in CHARLS. CONCLUSION: Our findings support that HGS can be used as an independent predictor of stroke in middle-aged and older European, American and Chinese populations, and the predictive ability of HGS may not depend on how it is expressed. The relationship between HGS and heart disease calls for further validation.

Preserved Ratio Impaired Spirometry, Metabolomics, and the Risk of Type 2 Diabetes.

CONTEXT: Whether baseline preserved ratio impaired spirometry (PRISm) is associated with the risk of developing type 2 diabetes (T2D) and if this association could be mediated by circulating metabolites remains to be elucidated. OBJECTIVE: To measure the prospective association of PRISm with T2D and potential metabolic mediators thereof. METHODS: This study used data from the UK Biobank and included 72 683 individuals without diabetes at baseline. PRISm was defined as the predicted forced expiratory volume in 1 second (FEV1) <80% and the FEV1/forced vital capacity ratio ≥0.70. Cox proportional hazards modeling was performed to assess the longitudinal relation between baseline PRISm and incident T2D. Mediation analysis was used to explore the mediation effects of circulating metabolites in the path from PRISm to T2D. RESULTS: During a median follow-up of 12.06 years, 2513 participants developed T2D. Individuals who had PRISm (N = 8394) were 47% (95% CI, 33%-63%) more likely to develop T2D compared with those who had normal spirometry (N = 64 289). A total of 121 metabolites showed statistically significant mediation effects in the path from PRISm to T2D (false discovery rate <0.05). Glycoprotein acetyls, cholesteryl esters in large high-density lipoprotein (HDL), degree of unsaturation, cholesterol in large HDL, and cholesteryl esters in very large HDL were the top 5 metabolic markers, with mediation proportions (95% CI) being 11.91% (8.76%-16.58%), 11.04% (7.34%-15.55%), 10.36% (7.34%-14.71%), 9.87% (6.78%-14.09%), and 9.51% (6.33%-14.05%), respectively. A total of 11 principal components that explained 95% variance of the metabolic signatures accounted for 25.47% (20.83%-32.19%) of the relation between PRISm and T2D. CONCLUSIONS: Our study revealed the association of PRISm with T2D risk and the potential roles of circulating metabolites in mediating this association.

Cyclodextrin Metal-Organic Framework as a Broad-Spectrum Potential Delivery Vehicle for the Gasotransmitters.

The important role of gasotransmitters in physiology and pathophysiology suggest employing gasotransmitters for biomedical treatment. Unfortunately, the difficulty in storage and controlled delivery of these gaseous molecules hindered the development of effective gasotransmitters-based therapies. The design of a safe, facile, and wide-scale method to delivery multiple gasotransmitters is a great challenge. Herein, we use an ultrasonic assisted preparation γ-cyclodextrin metal organic framework (γ-CD-MOF) as a broad-spectrum delivery vehicle for various gasotransmitters, such as SO2, NO, and H2S. The release rate of gasotransmitters could be tuned by modifying the γ-CD-MOF with different Pluronics. The biological relevance of the exogenous gasotransmitters produced by this method is evidenced by the DNA cleavage ability and the anti-inflammatory effects. Furthermore, the γ-CD-MOF composed of food-grade γ-CD and nontoxic metal salts shows good biocompatibility and particle size (180 nm). Therefore, γ-CD-MOF is expected to be an excellent tool for the study of co-delivery and cooperative therapy of gasotransmitters.

Efficient Fabrication of Carbon Nanotube-Based Stretchable Electrodes for Flexible Electronic Devices.

Stretchable electrodes are highly demanded in various wearable and flexible electronic devices, whereas the efficient fabrication approach is still a challenge. In this work, an efficient shrinking method to fabricate carbon nanotube (CNT)-based stretchable electrodes is proposed. The electrode is a layer of anisotropic CNT wrinkling film coated on a latex balloon substrate (CNT@latex), whose resistivity remains stable after 25 000 stretching cycles of 0 to 50% tensile strain, and can survive up to 500% tensile train. The highly conductive electrode can be used as the current collector of a stretchable Zinc-ion battery, maintaining an output voltage of 1.3 V during the stretching process of 0 to 100%. The applications of the electrode in flexible triboelectric nanogenerators and Joule heating devices are also demonstrated, further indicating their good prospects in the field of stretchable electronic devices.

Role of depression in the development of cardiometabolic multimorbidity: Findings from the UK Biobank study.

BACKGROUND: Depression has been acknowledged as a risk factor for cardiometabolic diseases, but its role in the development of cardiometabolic multimorbidity (CM) remains unclear. We aimed to prospectively investigate how depression affected the development of CM based on the UK Biobank study. METHODS: We included 459,747 participants with none or one prior cardiometabolic disease. Depression was assessed by the clinical diagnosis and Patient Health Questionnaire (PHQ-2). CM was defined as the coexistence of two or more conditions of type 2 diabetes, stroke, and coronary heart disease (CHD). Multistate models were used to examine the role of depression in the transitions from baseline to single cardiometabolic diseases and subsequently to CM. RESULTS: During a median follow-up of 12.07 years, we documented 3413 incident CM cases among initially disease-free participants and 7461 cases among participants with one prior cardiometabolic disease, respectively. The hazard of developing CM associated with depression was higher among disease-free individuals than that among individuals with one cardiometabolic disease (HR, 95 % CI: 1.68, 1.54-1.83 vs 1.28, 1.20-1.35). Moreover, depression was significantly associated with all transitions from baseline to diabetes (HR, 95 % CI: 1.43, 1.37-1.50), stroke (1.28, 1.20-1.38), and CHD (1.35, 1.31-1.40). After the onset of these cardiometabolic diseases, the HR values (95 % CIs) of progression to CM were 1.26 (1.09-1.46) for diabetes, 1.43 (1.16-1.76) for stroke, and 1.23 (1.08-1.40) for CHD. CONCLUSIONS: Depression was an independent risk factor for CM, and adversely influenced the whole progression from disease-free status to CM.

Hierarchical Wrinkles for Tunable Strain Sensing Based on Programmable, Anisotropic, and Patterned Graphene Hybrids.

Flexible, stretchable, wearable, and stable electronic materials are widely studied, owing to their applications in wearable devices and the Internet of Things. Because of the demands for both strain-insensitive resistors and high gauge factor (GF) strain-sensitive materials, anisotropic strain sensitivity has been an important aspect of electronic materials. In addition, the materials should have adjustable strain sensitivities. In this work, such properties are demonstrated in reduced graphene oxide (RGO) with hierarchical oriented wrinkle microstructures, generated using the two-step shrinkage of a rubber substrate. The GF values range from 0.15 to 28.32 at 100% strain. For device demonstrations, macrostructure patterns are designed to prepare patterned wrinkling graphene at rubber substrate (PWG@R). Serpentiform curves can be used for the constant-value resistor, combined with the first-grade wrinkles. Strip lines can increase the strain-sensing property, along with the second-grade wrinkles. The patterned sensor exhibits improved GF values range from 0.05 to 49.5. The assembled sensor shows an excellent stability (>99% retention after 600 cycles) with a high GF (49.5). It can monitor the vital signs of the throat and wrist and sense large motions of fingers. Thus, PWG@R-based strain sensors have great potential in various health or motion monitoring fields.

Associations of handgrip strength with morbidity and all-cause mortality of cardiometabolic multimorbidity.

BACKGROUND: Cardiometabolic multimorbidity (CM) is an increasing public health and clinical concern. However, predictors for the development and prognosis of CM are poorly understood. The aims of this study were to investigate the relation between handgrip strength (HGS) and the risk of CM and to examine the association of HGS with all-cause mortality risk among patients with CM. METHODS: This prospective cohort study involved 493,774 participants from the UK Biobank. CM was defined as the simultaneous occurrence of two or more of the following conditions: type 2 diabetes, stroke, and coronary heart disease (CHD). Cox proportional hazards models were performed to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs). RESULTS: During a median follow-up of 12.1 years, 4701 incident CM cases were documented among participants with none cardiometabolic disease at baseline. Compared with the fourth quartile (Q4), the multivariable adjusted HR (95% CI) value of Q1 of HGS for developing CM was 1.46 (1.34-1.60). In participants with one cardiometabolic disease at baseline, participants in Q1 of HGS also possessed higher risk of CM than those in Q4, with HRs (95% CIs) being 1.35 (1.23-1.49) in patients with type 2 diabetes, 1.23 (1.04-1.46) in patients with stroke, and 1.23 (1.11-1.36) in patients with CHD. For participants with CM at recruitment, HGS was also associated with the risk of all-cause mortality (Q1 vs. Q4 HR: 1.57, 95% CI: 1.36-1.80). CONCLUSIONS: Our study provided novel evidence that HGS could be an independent predictor of morbidity and all-cause mortality of CM.

Role of Pulmonary Function in Predicting New-Onset Cardiometabolic Diseases and Cardiometabolic Multimorbidity.

BACKGROUND: Although pulmonary function has been studied in relationship to individual cardiometabolic diseases, uncertainty persists about the difference in risk magnitudes of pulmonary function for these diseases and its association with cardiometabolic multimorbidity (CM). RESEARCH QUESTION: Does pulmonary function have different risk magnitudes for cardiometabolic diseases and CM? STUDY DESIGN AND METHODS: This study used data from the UK Biobank, including 357,433 individuals with no cardiometabolic diseases at baseline (stage I) and 35,034 individuals with one cardiometabolic disease at baseline (stage II). Pulmonary function was measured by FVC or FEV1. We defined CM as the coexistence of at least two cardiometabolic diseases: type 2 diabetes (T2D), coronary heart disease (CHD), and stroke. Multinomial logistic regression models and Cox proportional hazards models were performed to estimate ORs or hazard ratios (HRs) and their 95% CIs for the longitudinal relationship between baseline pulmonary function and incident cardiometabolic outcomes. RESULTS: In stage I, FVC showed the most pronounced associations with new-onset CM and T2D among the four mutually exclusive end points. Compared with the lowest quartile (quartile 1), the adjusted ORs of quartile 4 of FVC were 0.525 (95% CI, 0.468-0.589) for CM, 0.534 (95% CI, 0.498-0.572) for T2D alone, 0.817 (95% CI, 0.751-0.888) for stroke alone, and 0.800 (95% CI, 0.764-0.837) for CHD alone. In stage II, FVC also was associated with the risk of CM in patients with T2D (HR of quartile 4, 0.727; 95% CI, 0.649-0.814), patients with CHD (HR, 0.635; 95% CI, 0.555-0.727), and patients who experienced stroke (HR, 0.783, 95% CI, 0.642-0.955). Similar results were observed for FEV1 in both stages. INTERPRETATION: This study revealed the different risk associations of pulmonary function with individual cardiometabolic diseases and CM. Tailor-made screening and monitoring through pulmonary function may be applicable for the precise prevention and control of these conditions.

Improving depression prediction using a novel feature selection algorithm coupled with context-aware analysis.

BACKGROUND: Developing machine learning based depression prediction method with information from long-term recordings is important and challenging to clinical diagnosis of depression. METHODS: We developed a novel two-stage feature selection algorithm conducted on the high-dimensional (over thirty thousand) features constructed by a context-aware analysis on the data set of DAIC-WOZ, including audio, video, and semantic features. The prediction performance was compared with seven reference models. The preferred topics and feature categories related to the retained features were also analyzed respectively. RESULTS: Parsimonious subsets (tens of features) were selected by the proposed method in each case of prediction. We obtained the best performance in depression classification with F1-score as 0.96 (0.67), Precision as 1.00 (0.63), and Recall as 0.92 (0.71) on the development set (test set). We also achieved promising results in depression severity estimation with RMSE as 4.43 (5.11) and MAE as 3.22 (3.98), having a marginal difference with the best reference model (random forest with 'Selected-Text' features). Five most important topics related to depression were revealed. The audio features were predominant to the other feature categories in depression classification while the contributions of the three feature categories to severity estimation were almost equal. LIMITATIONS: More depression samples in the database we used should be further included. The second stage of feature selection is relatively time-consuming. CONCLUSION: This pipeline of depression recognition as well as the preferred topics and feature categories are expected to be useful in supporting the diagnosis of psychological distress conditions.

Source analysis of heavy metal pollution in agricultural soil irrigated with sewage in Wuqing, Tianjin.

In this study, the contents of heavy metals and Cd and Pb isotope ratios of agricultural soil and potential source samples collected from farmland receiving sewage irrigation in Wuqing District, Tianjin, China were determined. Multiple methods were used for source analysis, including positive matrix factorization (PMF), correlation analysis, principal component analysis (PCA), and the Cd and Pb isotope ratio method. The results showed that agricultural soil was slightly contaminated by heavy metals in the research area, with relatively higher Cd and Pb accumulation levels compared to those of other heavy metals. Four types of pollution sources, including the soil parent material sources, industrial emission sources, agricultural practice sources, and mixed sources of sewage irrigation and transportation were apportioned and quantified by PMF, combined with the results of PCA and correlation analysis. The contribution rates quantified by the Cd and Pb isotope ratio method were similar, suggesting that no single source dominates Pb and Cd pollution. The contribution rates of Pb analyzed by the isotope ratio method were almost identical to those of the PMF model, indicating the rationality of the PMF result. Our results suggested that correlation analysis and PCA should be utilized to provide information for obtaining reasonable results and defining source categories for PMF, whereas the isotope ratio method should be applied to verify the accuracy of source contributions analyzed by PMF.

Waist-to-height ratio, waist circumference, body mass index, waist divided by height0.5 and the risk of cardiometabolic multimorbidity: A national longitudinal cohort study.

BACKGROUND AND AIMS: Cardiometabolic multimorbidity (CM) is an increasing public health burden. This study aimed to evaluate the association of waist-to-height ratio (WHtR), waist circumference (WC), waist divided by height0.5 (WHT.5R) and body mass index (BMI) with the risk of CM. METHODS AND RESULTS: We used data from the China Health and Retirement Longitudinal Study (CHARLS). A total of 10,521 participants aged 45 years and over were recruited, including 8807 individuals with 0 cardiometabolic diseases at baseline (stage I) and 1714 individuals with 1 cardiometabolic disease at baseline (stage II). CM was defined as self-reporting of two or more of the following conditions: stroke, diabetes and heart disease. Logistic regression was conducted to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). The net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to evaluate the incremental predictive value beyond conventional factors. In stage I, an increased risk of CM was observed among participants with WHtR ≥0.5 (OR: 1.76, 95% CI: 1.05-2.97), WC ≥ 90 cm (men) + WC ≥ 80 cm (women) (OR: 2.06, 95% CI: 1.29-3.27), WHT.5R ≥ 6.54 cm0.5 (OR: 1.81, 95% CI: 1.16-2.83) or BMI ≥24 kg/m2 (OR: 1.48, 95% CI: 0.98-2.24). Furthermore, the NRI and IDI of WHtR, WC and WHT.5R were all higher than those of BMI. In stage II, the adjusted ORs (95% CIs) of WHtR, WC, WHT.5R and BMI were 2.04 (1.24-3.35), 1.89 (1.29-2.77), 1.86 (1.24-2.78) and 1.47 (1.06-2.04), respectively. In addition, WC exhibited the highest NRI and IDI. CONCLUSION: WHtR, WC, WHT.5R and BMI are independent predictors of CM in the middle-aged and older Chinese population. WHtR, WC and WHT.5R show better abilities in predicting CM than BMI.

Role of handgrip strength in predicting new-onset diabetes: findings from the survey of health, ageing and retirement in Europe.

BACKGROUND: Diabetes is a major concern for the global health burden. This study aimed to investigate the relationship between handgrip strength (HGS) and the risk of new-onset diabetes and to compare the predictive abilities between relative HGS and dominant HGS. METHODS: This longitudinal study used data from the Survey of Health, Ageing and Retirement in Europe (SHARE), including 66,100 European participants aged 50 years or older free of diabetes at baseline. The Cox proportional hazard model was used to analyze the relationship between HGS and diabetes, and the Harrell's C index, net reclassification index (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the predictive abilities of different HGS expressions. RESULTS: There were 5,661 diabetes events occurred during follow-up. Compared with individuals with lowest quartiles, the hazard ratios (95 % confidence intervals) of the 2nd-4th quartiles were 0.88 (0.81-0.94), 0.82 (0.76-0.89) and 0.85 (0.78-0.93) for dominant HGS, and 0.95 (0.88-1.02), 0.82 (0.76-0.89) and 0.60 (0.54-0.67) for relative HGS. After adding dominant HGS to an office-based risk score (including age, gender, body mass index, smoking, and hypertension), the incremental values of the Harrell's C index, NRI, IDI of relative HGS were all slightly higher than those of dominant HGS in both training and validation sets. CONCLUSIONS: Our findings supported that HGS was an independent predictor of new-onset diabetes in the middle-aged and older European population. Moreover, relative HGS exhibited a slightly higher predictive ability than dominant HGS.

Recent Progress of Toxic Gas Sensors Based on 3D Graphene Frameworks.

Air pollution is becoming an increasingly important global issue. Toxic gases such as ammonia, nitrogen dioxide, and volatile organic compounds (VOCs) like phenol are very common air pollutants. To date, various sensing methods have been proposed to detect these toxic gases. Researchers are trying their best to build sensors with the lowest detection limit, the highest sensitivity, and the best selectivity. As a 2D material, graphene is very sensitive to many gases and so can be used for gas sensors. Recent studies have shown that graphene with a 3D structure can increase the gas sensitivity of the sensors. The limit of detection (LOD) of the sensors can be upgraded from ppm level to several ppb level. In this review, the recent progress of the gas sensors based on 3D graphene frameworks in the detection of harmful gases is summarized and discussed.

Longitudinal Follow-Up Studies on the Bidirectional Association between ADL/IADL Disability and Multimorbidity: Results from Two National Sample Cohorts of Middle-Aged and Elderly Adults.

BACKGROUND AND OBJECTIVES: Few studies have investigated the bidirectional relationship between disability and multimorbidity, which are common conditions among the older population. Based on the data from the China Health and Retirement Longitudinal Study (CHARLS) and the Survey of Health, Ageing and Retirement in Europe (SHARE), we aimed to investigate the bidirectional relationship between disability and multimorbidity. METHODS: The activities of daily living (ADLs) and the instrumental activities of daily living (IADLs) scales were used to measure disability. In stage I, we used multinomial logistic regression to assess the longitudinal association between ADL/IADL disability and follow-up multimorbidity. In stage II, binary logistic regression was used to evaluate the multimorbidity effect on future disability. RESULTS: Compared with those free of disability, people with disability possessed ascending risks for developing an increasing number of diseases. For ADL disability, the odds ratio (OR) (95% confidence interval [CI]) values of developing ≥4 diseases were 4.10 (2.58, 6.51) and 6.59 (4.54, 9.56) in CHARLS and SHARE; for IADL disability, the OR (95% CI) values were 2.55 (1.69, 3.84) and 4.85 (3.51, 6.70) in CHARLS and SHARE. Meanwhile, the number of diseases at baseline was associated, in a dose-response manner, with future disability. Compared with those without chronic diseases, participants carrying ≥4 diseases had OR (95% CI) values of 4.82 (3.73, 6.21)/4.66 (3.65, 5.95) in CHARLS and 3.19 (2.59, 3.94)/3.28 (2.71, 3.98) in SHARE for developing ADL/IADL disability. CONCLUSION: The consistent findings across 2 national longitudinal studies supported a strong bidirectional association between disability and multimorbidity among middle-aged and elderly adults. Thus, tailored interventions should be taken to prevent the mutual development of disability and multimorbidity.

Role of depressive symptoms in cardiometabolic diseases and subsequent transitions to all-cause mortality: an application of multistate models in a prospective cohort study.

BACKGROUND AND PURPOSE: The role of depression in the development and outcome of cardiometabolic diseases remains to be clarified. We aimed to examine the extent to which depressive symptoms affect the transitions from healthy to diabetes, stroke, heart disease and subsequent all-cause mortality in a middle-aged and elderly European population. METHODS: A total of 78 212 individuals aged ≥50 years from the Survey of Health Ageing and Retirement in Europe were included. Participants with any baseline cardiometabolic diseases including diabetes, stroke and heart disease were excluded. Depressive symptoms were measured by the Euro-Depression scale at baseline. Participants were followed up to determine the occurrence of cardiometabolic diseases and all-cause mortality. We used multistate models to estimate the transition-specific HRs and 95% CIs after adjustment of confounders. RESULTS: During 500 711 person-years of follow-up, 4742 participants developed diabetes, 2173 had stroke, 5487 developed heart disease and 7182 died. Depressive symptoms were significantly associated with transitions from healthy to diabetes (HR: 1.12, 95% CI: 1.05 to 1.20), stroke (HR: 1.31, 95% CI: 1.18 to 1.44), heart disease (HR: 1.26, 95% CI: 1.18 to 1.34) and all-cause mortality (HR: 1.41, 95% CI: 1.34 to 1.49). After cardiometabolic diseases, depressive symptoms were associated with the increased risk of all-cause mortality in patients with diabetes (HR: 1.54, 95% CI: 1.25 to 1.89), patients who had stroke (HR: 1.29, 95% CI: 1.03 to 1.61) and patients with heart disease (HR: 1.21, 95% CI: 1.02 to 1.44). CONCLUSIONS: Depressive symptoms increase the risk of diabetes, stroke and heart disease, and affect the risk of mortality after the onset of these cardiometabolic conditions. Screening and treatment of depressive symptoms may have profound implications for the prevention and prognosis of cardiometabolic diseases.