Bayesian tensor network structure search and its application to tensor completion.

Tensor network (TN) has demonstrated remarkable efficacy in the compact representation of high-order data. In contrast to the TN methods with pre-determined structures, the recently introduced tensor network structure search (TNSS) methods automatically learn a compact TN structure from the data, gaining increasing attention. Nonetheless, TNSS requires time-consuming manual adjustments of the penalty parameters that control the model complexity to achieve better performance, especially in the presence of missing or noisy data. To provide an effective solution to this problem, in this paper, we propose a parameters tuning-free TNSS algorithm based on Bayesian modeling, aiming at conducting TNSS in a fully data-driven manner. Specifically, the uncertainty in the data corruption is well-incorporated in the prior setting of the probabilistic model. For TN structure determination, we reframe it as a rank learning problem of the fully-connected tensor network (FCTN), integrating the generalized inverse Gaussian (GIG) distribution for low-rank promotion. To eliminate the need for hyperparameter tuning, we adopt a fully Bayesian approach and propose an efficient Markov chain Monte Carlo (MCMC) algorithm for posterior distribution sampling. Compared with the previous TNSS method, experiment results demonstrate the proposed algorithm can effectively and efficiently find the latent TN structures of the data under various missing and noise conditions and achieves the best recovery results. Furthermore, our method exhibits superior performance in tensor completion with real-world data compared to other state-of-the-art tensor-decomposition-based completion methods.

Comprehensive assessment of HF-rTMS treatment mechanism for post-stroke dysphagia in rats by integration of fecal metabolomics and 16S rRNA sequencing.

Background: The mechanism by which high-frequency repetitive transcranial magnetic stimulation (HF-rTMS) improves swallowing function by regulating intestinal flora remains unexplored. We aimed to evaluate this using fecal metabolomics and 16S rRNA sequencing. Methods: A Post-stroke dysphagia (PSD) rat model was established by middle cerebral artery occlusion. The magnetic stimulation group received HF-rTMS from the 7th day post-operation up to 14th day post-surgery. Swallowing function was assessed using a videofluoroscopic swallowing study (VFSS). Hematoxylin-eosin (H&E) staining was used to assess histopathological changes in the intestinal tissue. Intestinal flora levels were evaluated by sequencing the 16S rRNA V3-V4 region. Metabolite changes within the intestinal flora were evaluated by fecal metabolomics using liquid chromatography-tandem mass spectrometry. Results: VFSS showed that the bolus area and pharyngeal bolus speed were significantly decreased in PSD rats, while the bolus area increased and pharyngeal transit time decreased after HF-rTMS administration (p < 0.05). In the PSD groups, H&E staining revealed damaged surface epithelial cells and disrupted cryptal glands, whereas HF-rTMS reinforced the integrity of the intestinal epithelial cells. 16S rRNA sequencing indicated that PSD can disturb the intestinal flora and its associated metabolites, whereas HF-rTMS can significantly regulate the composition of the intestinal microflora. Firmicutes and Lactobacillus abundances were lower in the PSD group than in the baseline group at the phylum and genus levels, respectively; however, both increased after HF-rTMS administration. Levels of ceramides (Cer), free fatty acids (FA), phosphatidylethanolamine (PE), triacylglycerol (TAG), and sulfoquinovosyl diacylglycerol were increased in the PSD group. The Cer, FA, and DG levels decreased after HF-rTMS treatment, whereas the TAG levels increased. Peptococcaceae was negatively correlated with Cer, Streptococcus was negatively correlated with DG, and Acutalibacter was positively correlated with FA and Cer. However, these changes were effectively restored by HF-rTMS, resulting in recovery from dysphagia. Conclusion: These findings suggest a synergistic role for the gut microbiota and fecal metabolites in the development of PSD and the therapeutic mechanisms underlying HF-rTMS.

Rapid automated extracellular vesicle isolation and miRNA preparation on a cost-effective digital microfluidic platform.

As a prerequisite for extracellular vesicle (EV) -based studies and diagnosis, effective isolation, enrichment and retrieval of EV biomarkers are crucial to subsequent analyses, such as miRNA-based liquid biopsy for non-small-cell lung cancer (NSCLC). However, most conventional approaches for EV isolation suffer from lengthy procedure, high cost, and intense labor. Herein, we introduce the digital microfluidic (DMF) technology to EV pretreatment protocols and demonstrate a rapid and fully automated sample preparation platform for clinical tumor liquid biopsy. Combining a reusable DMF chip technique with a low-cost EV isolation and miRNA preparation protocol, the platform completes automated sample processing in 20-30 min, supporting immediate RT-qPCR analyses on EV-derived miRNAs (EV-miRNAs). The utility and reliability of the platform was validated via clinical sample processing for EV-miRNA detection. With 23 tumor and 20 non-tumor clinical plasma samples, we concluded that EV-miR-486-5p and miR-21-5p are effective biomarkers for NSCLC with a small sample volumn (20-40 µL). The result was consistent to that of a commercial exosome miRNA extraction kit. These results demonstrate the effectiveness of DMF in EV pretreatment for miRNA detection, providing a facile solution to EV isolation for liquid biopsy.

RAPID-ED: A predictive model for risk assessment of patient's early in-hospital deterioration from emergency department.

Introduction: The objective of this multi-center retrospective cohort study was to devise a predictive tool known as RAPID-ED. This model identifies non-traumatic adult patients at significant risk for cardiac arrest within 48 hours post-admission from the emergency department. Methods: Data from 224,413 patients admitted through the emergency department (2016-2020) was analyzed, incorporating vital signs, lab tests, and administered therapies. A multivariable regression model was devised to anticipate early cardiac arrest. The efficacy of the RAPID-ED model was evaluated against traditional scoring systems like National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) and its predictive ability was gauged via the area under the receiver operating characteristic curve (AUC) in both hold-out validation set and external validation set. Results: RAPID-ED outperformed traditional models in predicting cardiac arrest with an AUC of 0.819 in the hold-out validation set and 0.807 in the external validation set. In this critical care update, RAPID-ED offers an innovative approach to assessing patient risk, aiding emergency physicians in post-discharge care decisions from the emergency department. High-risk score patients (≥13) may benefit from early ICU admission for intensive monitoring. Conclusion: As we progress with advancements in critical care, tools like RAPID-ED will prove instrumental in refining care strategies for critically ill patients, fostering an improved prognosis and potentially mitigating mortality rates.

Persistence of severe global inequalities in the burden of Hypertension Heart Disease from 1990 to 2019: findings from the global burden of disease study 2019.

AIMS: Assessing the global burden and health inequalities of Hypertension Heart Disease (HHD) during the period from 1990 to 2019. METHODS: Secondary analysis of the Global Burden of Disease (GBD) study in 2019, focusing on the burden of diseases, injuries, and risk factors worldwide. Disability-Adjusted Life Years (DALYs) data related to HHD are extracted from the 2019 GBD. Inequality Slope Index (SII) and Concentration Index are calculated to assess health inequalities across regions and countries. RESULTS: The total DALYs for HHD reached 21.51 million, demonstrating a substantial increase of 54.25% compared to the figures recorded in 1990, while the age-standardized DALY rates per 100,000 population for HHD in 2019 showed a notable decline to 268.19 (95% UI 204.57, 298.07), reflecting a significant decrease of 26.4% compared to the rates observed in 1990. The DALYs rate of hypertensive heart disease increases with age. Countries with moderate SDI accounted for 38.72% of the global burden of HHD in terms of DALYs. The highest age-standardized DALY rates (per 100,000) are predominantly concentrated in underdeveloped areas. In 1990 and 2019, the SII (per 100,000 population) for DALYs were - 121.6398 (95% CI -187.3729 to -55.90684) and - 1.592634 (95% CI -53.11027 to 49.925) respectively. The significant decline suggests a reduction in the inequality of age-standardized burden of HHD between high-income and low-income countries during this period. CONCLUSION: The unequal prevalence of HHD across different populations can hinder the achievement of the "health for all" objective. Persistent disparities in HHD have been observed globally over the past thirty years. It is crucial to prioritize efforts towards reducing avoidable health inequalities associated with hypertension-related heart disease, particularly in low-income and middle-income countries.

Assessment of ADHD Subtypes Using Motion Tracking Recognition Based on Stroop Color-Word Tests.

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder known for its significant heterogeneity and varied symptom presentation. Describing the different subtypes as predominantly inattentive (ADHD-I), combined (ADHD-C), and hyperactive-impulsive (ADHD-H) relies primarily on clinical observations, which can be subjective. To address the need for more objective diagnostic methods, this pilot study implemented a Microsoft Kinect-based Stroop Color-Word Test (KSWCT) with the objective of investigating the potential differences in executive function and motor control between different subtypes in a group of children and adolescents with ADHD. A series of linear mixture modeling were used to encompass the performance accuracy, reaction times, and extraneous movements during the tests. Our findings suggested that age plays a critical role, and older subjects showed improvements in KSWCT performance; however, no significant divergence in activity level between the subtypes (ADHD-I and ADHD-H/C) was established. Patients with ADHD-H/C showed tendencies toward deficits in motor planning and executive control, exhibited by shorter reaction times for incorrect responses and more difficulty suppressing erroneous responses. This study provides preliminary evidence of unique executive characteristics among ADHD subtypes, advances our understanding of the heterogeneity of the disorder, and lays the foundation for the development of refined and objective diagnostic tools for ADHD.

Characterization and risk assessment of novel SXT/R391 integrative and conjugative elements with multidrug resistance in Proteus mirabilis isolated from China, 2018-2020.

Proteus mirabilis can transfer transposons, insertion sequences, and gene cassettes to the chromosomes of other hosts through SXT/R391 integrative and conjugative elements (ICEs), significantly increasing the possibility of antibiotic resistance gene (ARG) evolution and expanding the risk of ARGs transmission among bacteria. A total of 103 strains of P. mirabilis were isolated from 25 farms in China from 2018 to 2020. The positive detection rate of SXT/R391 ICEs was 25.2% (26/103). All SXT/R391 ICEs positive P. mirabilis exhibited a high level of overall drug resistance. Conjugation experiments showed that all 26 SXT/R391 ICEs could efficiently transfer to Escherichia coli EC600 with a frequency of 2.0 × 10-7 to 6.0 × 10-5. The acquired ARGs, genetic structures, homology relationships, and conservation sequences of 26 (19 different subtypes) SXT/R391 ICEs were investigated by high-throughput sequencing, whole-genome typing, and phylogenetic tree construction. ICEPmiChnHBRJC2 carries erm (42), which have never been found within an SXT/R391 ICE in P. mirabilis, and ICEPmiChnSC1111 carries 19 ARGs, including clinically important cfr, blaCTX-M-65, and aac(6')-Ib-cr, making it the ICE with the most ARGs reported to date. Through genetic stability, growth curve, and competition experiments, it was found that the transconjugant of ICEPmiChnSCNNC12 did not have a significant fitness cost on the recipient bacterium EC600 and may have a higher risk of transmission and dissemination. Although the transconjugant of ICEPmiChnSCSZC20 had a relatively obvious fitness cost on EC600, long-term resistance selection pressure may improve bacterial fitness through compensatory adaptation, providing scientific evidence for risk assessment of horizontal transfer and dissemination of SXT/R391 ICEs in P. mirabilis.IMPORTANCEThe spread of antibiotic resistance genes (ARGs) is a major public health concern. The study investigated the prevalence and genetic diversity of integrative and conjugative elements (ICEs) in Proteus mirabilis, which can transfer ARGs to other hosts. The study found that all of the P. mirabilis strains carrying ICEs exhibited a high level of drug resistance and a higher risk of transmission and dissemination of ARGs. The analysis of novel multidrug-resistant ICEs highlighted the potential for the evolution and spread of novel resistance mechanisms. These findings emphasize the importance of monitoring the spread of ICEs carrying ARGs and the urgent need for effective strategies to combat antibiotic resistance. Understanding the genetic diversity and potential for transmission of ARGs among bacteria is crucial for developing targeted interventions to mitigate the threat of antibiotic resistance.

Household unclean fuel use, indoor pollution and self-rated health: risk assessment of environmental pollution caused by energy poverty from a public health perspective.

The lack of access to clean energy remains one of the major challenges in the global energy sector. Access to clean, sustainable and affordable energy, outlined in the seventh Sustainable Development Goals (SDG 7) of the United Nations, plays a crucial role in advancing health (SDG 3), as unclean cooking energy may endanger people's health by causing air pollution. However, due to endogeneity problems such as reverse causality, the health consequences of environmental pollution caused by unclean fuel usage are difficult to be scientifically and accurately evaluated. This paper aims to systematically assess the health cost of unclean fuel usage based on tackling endogeneity, using the data from Chinese General Social Survey. The ordinary least squares model, ordered regression methods, instrumental variable approach, penalized machine learning methods, placebo test, and mediation models are applied in this research. Analytical results demonstrate that households' unclean fuel use significantly damages people's health. Specifically, the use of dirty fuel leads to an average of about a one-standard-deviation decline in self-rated health, demonstrating its notable negative effect. The findings are robust to a series of robustness and endogeneity tests. The impact mechanism is that unclean fuel usage reduces people's self-rated health through increasing indoor pollution. Meanwhile, the negative effect of dirty fuel use on health has significant heterogeneity among different subgroups. The consequences are more prominent for the vulnerable groups who are female, younger, living in rural areas and older buildings, with lower socio-economic status and uncovered by social security. Therefore, necessary measures should be taken to improve energy infrastructure to make clean cooking energy more affordable and accessible as well as to enhance people's health. Besides, more attention should be paid to the energy needs of the above specific vulnerable groups faced with energy poverty.

Economic Burden among Patients with Vitiligo in the United States: A Retrospective Database Claims Study.

Patients with vitiligo incur direct and indirect costs associated with their condition; however, data regarding the economic burden of vitiligo are scarce and outdated. In this retrospective cohort analysis of the Merative MarketScan Commercial Database, healthcare costs and healthcare resource utilization (HCRU) were evaluated among United States patients with vitiligo. Patients with vitiligo were matched (1:2) with individuals without vitiligo (controls) between January 2007 and December 2021. Outcomes included all-cause and vitiligo-related costs (2021 dollars) and all-cause HCRU, including mental health-related HCRU, during a 1-year postindex period. Subgroup analyses were completed for patients on vitiligo treatments with systemic effects (such as phototherapy and oral steroids) or a new mental health diagnosis. The analysis was focused solely on direct costs. Baseline demographics were well-balanced between matched vitiligo (49,512) and control (99,024) cohorts. Patients with vitiligo incurred significantly higher all-cause ($15,551 vs $7735) and vitiligo-related ($3490 vs $54) costs than controls (P < .0001). All-cause and mental health-related HCRU were also significantly higher among patients with vitiligo (P < .0001). Differences in all-cause and vitiligo-related healthcare costs remained significantly higher in patients on treatments with systemic effects/mental health diagnoses than in controls (P < .0001). Taken together, healthcare costs and HCRU were significantly higher among patients with vitiligo than among controls.

A systematic review of cost-effectiveness analysis of different screening strategies for familial hypercholesterolemia.

AIMS: Diagnosis rate of familial hypercholesterolemia (FH) remained less than 10 % globally and the economic evaluation results of different FH screening strategies varied. This study aimed to systematically review the methodology and results of cost effectiveness analysis (CEA) of FH screening, which will provide evidence support for health-related decision-making. METHODS: The Medline/PubMed, Embase, Cochrane Library, Web of science, National Health Service Economic Evaluation Database (NHSEED) and CEA Registry databases were electronically searched to collect full economic evaluation from the establishment of the databases to June 30, 2022. The quality of included studies was evaluated by the Consolidated Health Economic Evaluation Reporting Standards statement 2022 (CHEERS 2022) checklist. RESULTS: Among 232 retrieved studies, 18 economic evaluations were included and all of them are from developed countries, with an average quality score of 0.73. The decision tree model and/or Markov model were constructed by thirteen articles (72 %). Twelve studies (67 %) adopted the healthcare perspective and the lifetime horizon to compare the costs and health outcome of different screening strategies. The results of eight studies indicated that cascade screening was a cost-effective strategy compared with no screening, which was more pronounced in younger adults. Universal screening in young adults aged 16 years or 18-40 years (n=3) and in children aged 1-2 years combined with reverse cascade screening (n=3) are both cost-effective. The probability of being cost-effective for cascade screening (n=6) and universal screening (n=1) of young aged 18-40 years were greater than 95 %. CONCLUSIONS: Our review demonstrated the economic advantages of cascade screening, universal screening of young adults, and universal screening of newborns combined with reverse cascade screening. Further health economic evaluation is needed in children and in low- and middle-income countries.

Assessment of 13 essential and toxic trace elements in tumor and peritumoral brain tissues from human glioblastoma.

Trace elements within the brain are important for proper neurological function, but their imbalance has been rarely investigated in glioblastoma. This study enrolled a total of 14 patients with glioblastoma, and the tumor and peritumoral brain tissues were collected while undergoing surgery. The concentrations of Mg, Ca, Cr, Mn, Fe, Co, Cu, Zn, Se, As, Cd, Tl and Pb were determined using a well-evaluated ICP-MS method. The Cu- and Cd-binding proteomes were further analyzed using the anatomic transcriptional atlas from Ivy GAP. Histological evaluation was based on rubeanic acid staining and immunohistochemistry, respectively. The 13 trace element concentrations were obtained, and the highest were Ca, Mn, Fe, Zn and Cu, ranging from a few to dozens of ug/g. Correlation analysis suggested the existence of two intra-correlated clusters: essential metals (Cu-Ca-Zn-Mg) and heavy metals (Pb-As-Cd-Tl-Co-Cr-Mn). Compared to the tumor samples, significantly higher levels of Cu and Cd were observed in the peritumoral region. Further analysis of the Cu- and Cd-binding proteins from the anatomic view suggested that DBH and NOS1 were obviously increased in the leading edge than the central tumor region. Consistent with the above findings, histological evaluation of Cu and DBH further confirmed more copper and DBH expressions in the peritumoral area compared to the tumor core. Trace elements differ in tumor and peritumoral brain zone in glioblastoma, which may associate with tumor angiogenesis.

Trace metal exposure and risk assessment of local dominant fish species in the Beijiang River Basin of China: A 60 years' follow-up study.

The Beijiang River, one of the Pearl River tributaries located in Guangdong, China, plays a critical role in providing water and fishery resources for the Pearl River Delta and receiving a large amount of domestic and industrial wastewater. However, due to the lack of historical monitoring data, we are unable to fully understand the relationship between the industrial and agricultural development and the environment. In this study, fish specimens collected from the Beijiang River Basin over a span of nearly 60 years (1963-2021) are used as research objects and the concentrations of ten trace metals (TMs) in two locally dominant fish species were determined by an inductively coupled plasma mass spectrometer. The human health risks caused by consuming fishes were assessed. Results show a correlation between the levels of TMs in fish muscle and the degree of industrialization. The concentrations of Cr, Mn, Ni, and Cu peaked during the period of 1981-1983, when China's industrial development was rapidly expanding while the environmental protection facilities were incomplete. However, with the implementation of Ecological Civilization policy, the levels of Cr, Mn, Ni, Cu, Cd, and Ba showed a downward trend in the period from 2018 to 2021. Cu concentrations in both fish muscle and viscera exhibit analogous change patterns across different periods, indicating that Cu serves as a significant indicator of TM pollution in the Beijiang River Basin. The presence of TMs in fish muscle often exhibits long-term enrichment, while those in the viscera demonstrate short-term accumulation. Based on the estimated daily intake, the target hazard quotient (THQ), and total THQ value, the overall health risk associated with TMs in fish from the Beijiang River Basin is low. However, certain TMs in the fish rebounded during 2018-2021, posing a potential risk for aquatic biology and ecosystems, which is worth our attention.

Spatio-temporal variation and hazard assessment of potentially toxic metal element contamination in sediments and water before and after a water-level fluctuation cycle in the Three Gorges Reservoir, Wanzhou, China.

Previous investigations on heavy metals in the water-sediment compartment focused on their spatial distribution, and the influence of sediment pH and organic matter (OM) on metal environmental occurrences. However, there are limited studies on the effects of physicochemical properties on the migration and transformation of heavy metals in the water-sediment compartments. This study investigated the relationship between the physicochemical properties of sediments and the distribution and chemical speciation of heavy metals, and the potential environmental risk of heavy metals in water and sediment using Risk Assessment Code (RAC) values and the Tessier five-step extraction method. Adsorption and desorption experiments showed that the sediment had weak adsorption and the strongest desorption capacity for Cd. Results of the pH, OM, surface element content, and X-ray diffraction (XRD) patterns suggested that cadmium (Cd) was more likely to partition into the water phase from the sediment during the flooding and water storage periods. When pH was 7-8 and OM content was 3.6-5.9%, the sediment-water distribution coefficient of Cd was low due to its large ionic radius, and the surface adsorption sites were saturated by other elements. These studies can provide a theoretical basis for the management and pollution control of the Three Gorges Reservoir.

Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.

BACKGROUND: The development of machine learning models for aiding in the diagnosis of mental disorder is recognized as a significant breakthrough in the field of psychiatry. However, clinical practice of such models remains a challenge, with poor generalizability being a major limitation. METHODS: Here, we conducted a pre-registered meta-research assessment on neuroimaging-based models in the psychiatric literature, quantitatively examining global and regional sampling issues over recent decades, from a view that has been relatively underexplored. A total of 476 studies (n = 118,137) were included in the current assessment. Based on these findings, we built a comprehensive 5-star rating system to quantitatively evaluate the quality of existing machine learning models for psychiatric diagnoses. RESULTS: A global sampling inequality in these models was revealed quantitatively (sampling Gini coefficient (G) = 0.81, p < .01), varying across different countries (regions) (e.g., China, G = 0.47; the USA, G = 0.58; Germany, G = 0.78; the UK, G = 0.87). Furthermore, the severity of this sampling inequality was significantly predicted by national economic levels (ß = - 2.75, p < .001, R2adj = 0.40; r = - .84, 95% CI: - .41 to - .97), and was plausibly predictable for model performance, with higher sampling inequality for reporting higher classification accuracy. Further analyses showed that lack of independent testing (84.24% of models, 95% CI: 81.0-87.5%), improper cross-validation (51.68% of models, 95% CI: 47.2-56.2%), and poor technical transparency (87.8% of models, 95% CI: 84.9-90.8%)/availability (80.88% of models, 95% CI: 77.3-84.4%) are prevailing in current diagnostic classifiers despite improvements over time. Relating to these observations, model performances were found decreased in studies with independent cross-country sampling validations (all p < .001, BF10 > 15). In light of this, we proposed a purpose-built quantitative assessment checklist, which demonstrated that the overall ratings of these models increased by publication year but were negatively associated with model performance. CONCLUSIONS: Together, improving sampling economic equality and hence the quality of machine learning models may be a crucial facet to plausibly translating neuroimaging-based diagnostic classifiers into clinical practice.

Inappropriate nighttime light reduces living comfort.

Living comfort is an important aspect of human well-being and a critical index of sustainable environments. Many environmental factors are associated with living comfort. Nighttime light (NTL) is remote sensing data that is widely used to reflect development level and economic status, and it also represents the lighting intensity in living environments. However, the relationship between NTL and living comfort is poorly understood. Here, we employ linear regression and a random forest model to investigate the direct impact of NTL on living comfort. Our results show that increased NTL is negatively associated with living comfort, but this relationship may be obscured by other factors, such as infrastructure. According to the nonlinear relationship, when the NTL is approximately 10 nW/cm2∙sr, there is a peak in living comfort. Hence, ensuring a reasonable level of lighting is a key to promoting sustainable development. Our research offers crucial insights that can aid in developing sustainable development policies to enhance livability.

The Nonlinear Relationship Between Body Mass Index (BMI) and Perceived Depression in the Chinese Population.

Purpose: Existing studies on the association between BMI and depression report conflicting results with some demonstrating a positive relationship, while others a negative link or insignificant correlation. Very limited research on the nonlinear relationship between BMI and depression has yet to clarify the reliability and robustness of the potential nonlinearity and whether a more complex association exists. This paper aims to systematically investigate the nonlinear relationship between the two factors applying rigorous statistical methods, as well as explore the heterogeneity of their association. Materials and Methods: A large-scale nationally representative dataset, Chinese General Social Survey, is used to empirically analyze the nonlinear relationship between BMI and perceived depression. Various statistical tests are employed to check the robustness of the nonlinearity. Results: Results indicate that there is a U-shaped relationship between BMI and perceived depression, with the turning point (25.718) very close to while slightly larger than the upper limit of the range of healthy weight (18.500 ≤ BMI < 25.000) defined by World Health Organization. Both very high and low BMIs are associated with increased risk for depressive disorders. Furthermore, perceived depression is higher at almost all BMI levels among individuals who are older, female, lower educated, unmarried, in rural areas, belonging to ethnic minorities, non-Communist Party of China members, as well as those with lower income and uncovered by social security. In addition, these subgroups have smaller inflection points and their self-rated depression is more sensitive to BMI. Conclusion: This paper confirms a significant U-shaped trend in the association between BMI and depression. Therefore, it is important to account for the variations in this relationship across different BMI categories when using BMI to predict depression risk. Besides, this study clarifies the management goals for achieving an appropriate BMI from a mental health perspective and identifies vulnerable subgroups at higher risk of depression.

Does exercise participation promote happiness?: Mediations and heterogeneities.

This paper uses a nationally representative and large-scale dataset from China to empirically examine the relationship between exercise participation and happiness. To address the problem of reverse causality between the two factors, the instrumental variable (IV) approach is used to deal with endogeneity to some extent. It is demonstrated that higher frequencies of exercise participation are positively related to happiness. Findings also demonstrate that physical exercise could significantly decrease depressive disorders, improves self-rated health conditions and reduces the frequency of health problems affecting people's work and life. At the same time, all of above health factors significantly influence subjective wellbeing. When these health variables are included in regressions, the correlation between exercise participation and happiness declines. This confirms that physical activity helps to improve happiness by enhancing mental and overall health conditions. In addition, results show that physical activities are more prominently related to happiness for male, older and unmarried individuals and those living in rural areas, lacking social security and with higher levels of depression as well as lower socioeconomic status. Furthermore, a series of robustness checks are carried out and exercise participation's positive role in improving happiness is further confirmed using different happiness measures and instrumental variables, various IV models, as well as penalized machine learning methods and placebo tests. With the increasing emphasis of improving happiness as an important goal in the global public health policy, findings of this paper have important policy implications for enhancing subjective wellbeing.

Projected rapid growth in diabetes disease burden and economic burden in China: a spatio-temporal study from 2020 to 2030.

Background: This study projects the trend of disease burden and economic burden of diabetes in 33 Chinese provinces and nationally during 2020-2030 and investigates its spatial disparities. Methods: Time series prediction on the prevalence and disability-adjusted life-year (DALY) rates of diabetes was conducted using a Bayesian modelling approach in 2020-2030. The top-down method and the human capital method were used to predict the direct and indirect costs of diabetes for each Chinese province. Global and local spatial autocorrelation analyses were used to identify geographic clusters of low-or high-burden areas. Findings: Diabetes prevalence in Chinese adults aged 20-79 years was projected to increase from 8.2% to 9.7% during 2020-2030. During the same period, the total costs of diabetes would increase from $250.2 billion to $460.4 billion, corresponding to an annual growth rate of 6.32%. The total costs of diabetes as a percentage of GDP would increase from 1.58% to 1.69% in China during 2020-2030, suggesting a faster growth in the economic burden of diabetes than China's economic growth. Consistently, the per-capita economic burden of diabetes would increase from $231 to $414 in China during 2020-2030, with an annual growth rate of 6.02%. High disease and economic burden areas were aggregated in Northeast and/or North China. Interpretation: Our study projects a significant growth of disease and economic burden of diabetes in China during 2020-2030, with strong spatial aggregation in northern Chinese regions. The increase in the economic burden of diabetes will exceed that of GDP. Funding: National Natural Science Foundation of China, Outstanding Young Scholars Funding.

Information Disclosure Impacts Intention to Consume Man-Made Meat: Evidence from Urban Residents' Intention to Man-Made Meat in China.

Meat substitutes such as man-made meat are emerging to promote low-carbon healthy consumption, mitigate climate change, and assist healthy economic development; however, most consumers seem reluctant to make the transition. While profound social change may be required to make significant progress in this area, limited efforts have been made to understand the psychological processes that may hinder or facilitate this transition. To clearly identify the factors influencing the public's intention to consume man-made meat and their influencing paths, this study analyzes the mechanism by which man-made meat information disclosure affects the public's intention to consume these products based on the social cognitive theory of "awareness-situation-behavior" and using structural equation modeling, with residents of seven Chinese cities as examples (647 respondents). The results of this study yielded three main findings. First, low-carbon awareness, personal social responsibility awareness, and man-made meat risk perception significantly influence the public's intention to consume man-made meat, with risk perception having the greatest influence (-0.434). Second, low-carbon awareness and man-made meat risk perception have a significant interaction effect on the public's intention to consume man-made meat (-0.694). Third, man-made meat information disclosure has the most significant moderating effect on the relationship between low-carbon awareness and the public's intention to consume man-made meat, as well as a moderating effect on the relationship between man-made meat risk perception and the public's intention to consume man-made meat.

Low-cost and sensitive method for Pb isotope determination using a novel ß-Si3N4 emitter by thermal ionization mass spectrometry.

Thermal ionization mass spectrometry (TIMS) is the workhorse for lead isotopic ratio analysis due to its excellent precision. Silica gel as ionization activator on Re filament is proved to the best emitter that can provide excellent sensitivity even small Pb sample size. However, the price of Re filament is three times that of Ta filament that leads to high experimental cost for TIMS laboratory. Here, we first present a novel silicon nitride (ß-Si3N4) emitter on the Ta filament with good sensitivity for Pb isotopic ratio measurements. Hence, the cost of filament material is cut down ∼70%. The ß-Si3N4 emitter can yield stable and long-life Pb+ signal, about 2-3 V 208Pb and 0.65-0.90 V 208Pb for 20 ng and 5 ng NIST SRM981 sample size that is applicable to the most geological materials for bulk analysis. A suite of silicate reference materials were analyzed to verify the reliability and accuracy of our method. For 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb isotope ratios of geological samples, excellent internal precisions (2 SE) of ±0.005%-0.013% are achieved. Replicate digestions and analyses of the basalt standard BCR-2 and coal fly ash standard GBW08401 demonstrate that good external precision is obtainable that is 0.10-0.18% (n = 6, 2 SD) for 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb ratios.