Trends and patterns in stroke incidence, mortality, DALYs and case-fatality by sociodemographic index worldwide: an age-period-cohort analysis using the Global Burden of Disease 2019 study.

OBJECTIVES: Stroke is a significant public health burden worldwide. This study aimed to explore the trends and patterns of stroke incidence, mortality, disability-adjusted life years (DALYs) and case-fatality percent (CFP) worldwide from 1990 to 2019. STUDY DESIGN: Age-period-cohort analysis. METHODS: Trends in stroke burden worldwide were evaluated using data from the Global Burden of Disease 2019 study. In addition, the relationship between the burden of stroke and sociodemographic index (SDI) was examined by quantile regression. Age, period and cohort patterns in stroke burden across different SDI groups were estimated using age-period-cohort analysis. RESULTS: Between 1990 and 2019, the age-standardised rates (ASRs) of stroke incidence, mortality and DALYs declined significantly worldwide, with decreases of -16.89% (95% uncertainty interval [UI]: -18.41 to -15.29), -36.43% (95% UI: -41.65 to -31.20) and -35.23% (95% UI: -40.49 to -30.49), respectively. Regions with ASRs in the 75th percentile and below experienced significant decreases in ASRs with increasing SDI. After 2014, there was a stable or slightly increased period effect for stroke incidence in all groups, while mortality, DALYs and CFP increased only in the high SDI group. The cohort effect of stroke incidence remained constant in the high SDI group from the 1960-1964 cohort onwards. CONCLUSIONS: Although high SDI regions had a lower stroke burden and a faster overall decline in burden, the recent relative risk data suggest a potential deceleration in the progress of reducing stroke burden in these areas. There is a need for more active measures to reduce the stroke burden in areas with the highest incidence, mortality and DALYs, as increasing SDI alone cannot lower the burden in these regions.

Trends and age-period-cohort effects on mortality of the three major gynecologic cancers in China from 1990 to 2019: Cervical, ovarian and uterine cancer.

BACKGROUND: Gynecologic cancers seriously threaten women's life and health. This study aims to assess the long-term trends of mortality from the three major gynecologic cancers in China and to examine the age-, period-, and cohort-specific effects behind them during the period 1990 to 2019. METHODS: The mortality data of cervical, ovarian, and uterine cancer in China were obtained from the Global Burden of Disease Study 2019 and were analyzed with the age-period-cohort framework. RESULTS: It was found that the net drift for cervical cancer mortality was -0.19% (95% CI, -0.46% to 0.08%) per year, for ovarian cancer was 0.76% (95% CI, 0.57% to 0.95%) per year, and for uterine cancer was -3.09% (95% CI, -3.44% to -2.76%) per year from 1990 to 2019. During this period, while cervical cancer remained the most common cause of death among gynecologic cancers among Chinese women, ovarian cancer replaced uterine cancer as the second leading cause of death in gynecologic cancers after about 2005. Significant age, cohort, and period effects were found for the mortality trends of all three major gynecologic cancers. CONCLUSIONS: The secular trends of mortality from the three major gynecologic cancers in China and their underlying age, period, and cohort effects are likely to reflect the progress of diagnosis and treatment, rapid socio-economic transitions, and the accompanying lifestyle and behavior changes. More priorities of further epidemiology studies and efforts on the prevention and control should be given to three major gynecologic cancers.

Alantolactone inhibits cell autophagy and promotes apoptosis via AP2M1 in acute lymphoblastic leukemia.

BACKGROUND: Acute lymphoblastic leukemia (ALL) is an aggressive hematopoietic malignancy that is most commonly observed in children. Alantolactone (ALT) has been reported to exhibit anti-tumor activity in different types of cancer. The aim of the present study was to investigate the anti-tumor activity and molecular mechanism of ALT in ALL. METHODS: ALL cell lines were treated with 1, 5 and 10 µM ALT, and cell viability was assessed using an MTT assay and RNA sequencing. Flow cytometry, JC-1 staining and immunofluorescence staining assays were used to measure cell apoptosis and autophagy. Additionally, western blot analysis was used to detect expression of apoptosis and autophagy related proteins. Finally, the effects of ALT on tumor growth were assessed in a BV173 xenograft nude mouse model. RESULTS: ALT inhibited the proliferation of ALL cells in a dose-dependent manner. Additionally, it was demonstrated that ALT inhibited cell proliferation, colony formation, autophagy, induced apoptosis and reduced tumor growth in vivo through upregulating the expression of adaptor related protein complex 2 subunit mu 1 (AP2M1). Moreover, the autophagy activator rapamycin, attenuated the pro-apoptotic effects of ALT on BV173 and NALM6 cell lines. Overexpression of AP2M1 decreased the expression of Beclin1 and the LC3-II/LC3-1 ratio, and increased p62 expression. Knockdown of Beclin1 increased the levels of bax, cleaved caspase 3 and cytochrome C, and decreased bcl-2 expression. CONCLUSIONS: The present study demonstrated that ALT exerts anti-tumor activity through inducing apoptosis and inhibiting autophagy by upregulating AP2M1 in ALL, highlighting a potential therapeutic strategy for treatment of ALL.

The Chinese version of the Perceived Stress Questionnaire: development and validation amongst medical students and workers.

BACKGROUND: A valid and efficient stress measure is important for clinical and community settings. The objectives of this study were to translate the English version of the Perceived Stress Questionnaire (PSQ) into Chinese and to assess the psychometric properties of the Chinese version of the PSQ (C-PSQ). The C-PSQ evaluates subjective experiences of stress instead of a specific and objective status. METHODS: Forward translations and back translations were used to translate the PSQ into Chinese. We used the C-PSQ to survey 2798 medical students and workers at three study sites in China from 2015 to 2017. Applying Rasch analysis (RA) and factor analysis (FA), we examined the measurement properties of the C-PSQ. Data were analyzed using the Rasch model for item fit, local dependence (LD), differential item functioning (DIF), unidimensionality, separation and reliability, response forms and person-item map. We first optimized the item selection in the Chinese version to maximize its psychometric quality. Second, we used cross-validation, by exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), to determine the best fitting model in comparison to the different variants. Measurement invariance (MI) was tested using multi-group CFA across subgroups (medical students vs. medical workers). We evaluated validity of the C-PSQ using the criterion instruments, such as the Chinese version of the Perceived Stress Scale (PSS-10), the Short Form-8 Health Survey (SF-8) and the Goldberg Anxiety and Depression Scale (GADS). Reliability was assessed using internal consistency (Cronbach's alpha, Guttman's lambda-2, and McDonald's omegas) and reproducibility (test-retest correlation and intraclass correlation coefficient, [ICC]). RESULTS: Infit and/or outfit values indicated that all items fitted the Rasch model. Three item pairs presented local dependency (residual correlations > 0.30). Ten items showed DIF. Dimensionality instruction suggested that eight items should be deleted. One item showed low discrimination. Thirteen items from the original PSQ were retained in the C-PSQ adaptation (i.e. C-PSQ-13). We tested and verified four feasible models to perform EFA. Built on the EFA models, the optimal CFA model included two first-order factors (i.e. constraint and imbalance) and a second-order factor (i.e., perceived stress). The first-order model had acceptable goodness of fit (Normed Chi-square = 8.489, TLI = 0.957, CFI = 0.965, WRMR = 1.637, RMSEA [90% CI] = 0.078 [0.072, 0.084]). The second-order model showed identical model fit. Person separation index (PSI) and person reliability (PR) were 2.42 and 0.85, respectively. Response forms were adequate, item difficulty matched respondents' ability levels, and unidimensionality was found in the two factors. Multi-group CFA showed validity of the optimal model. Concurrent validity of the C-PSQ-13 was 0.777, - 0.595 and 0.584 (Spearman correlation, P < 0.001, the same hereinafter) for the Chinese version of the PSS-10, SF-8, and GADS. For reliability analyses, internal consistency of the C-PSQ-13 was 0.878 (Cronbach's alpha), 0.880 (Guttman's lambda-2), and 0.880 (McDonald's omegas); test-retest correlation and ICC were 0.782 and 0.805 in a 2-day interval, respectively. CONCLUSION: The C-PSQ-13 shows good metric characteristics for most indicators, which could contribute to stress research given its validity and economy. This study also contributes to the evidence based regarding between-group factorial structure analysis.

Age-Period-Cohort Analysis of Stroke Mortality in China: Data From the Global Burden of Disease Study 2013.

BACKGROUND AND PURPOSE: Stroke has been the leading cause of death in China. The aim of this study is to assess the long-term trends of stroke mortality in China between 1994 and 2013. METHODS: The mortality data were obtained from the GBD 2013 (Global Burden of Disease Study 2013) and were analyzed with the age-period-cohort framework. RESULTS: We found that the net drift was -2.665% (95% confidence interval, -2.854% to -2.474%) per year for men and -4.064% (95% confidence interval, -4.279% to -3.849%) per year for women, and the local drift values were below 0 in all age groups (P<0.05 for all) in both sexes during the period of 1994 to 2013. In the same birth cohort, the risk of death from stroke rose exponentially with age for both sexes after controlling for period deviations. The estimated period and cohort relative risks were found in similar monotonic downward patterns (significantly with P<0.05 for all) for both sexes, with more quickly decreasing for women than for men during the whole period (significantly with P<0.05 for both). CONCLUSIONS: The decreased mortality rates of stroke in China are likely to be related to improvements in medical care and techniques, spectacular economic growth and fast urbanization, and better early life nutrition conditions of Chinese people. Besides, better education and better awareness of stroke-related knowledge in successive generations could also probably play a role.

Age-period-cohort analysis of suicide mortality by gender among white and black Americans, 1983-2012.

BACKGROUND: Previous studies suggested that the racial differences in U.S. suicide rates are decreasing, particularly for African Americans, but the cause behind the temporal variations has yet to be determined. This study aims to investigate the long-term trends in suicide mortality in the U.S. between 1983 and 2012 and to examine age-, period-, and cohort-specific effects by gender and race. METHOD: Suicide mortality data were collected from the Web-based Injury Statistics Query and Reporting System (WISQARS) and analyzed with the Joinpoint regression and age-period-cohort (APC) analysis. RESULTS: We found that although age-standardized rate of suicide in white males, white females, black males, and black females all changed at different degrees, the overall situation almost has not changed since these changes offset each other. By APC analysis, while the age effect on suicide demonstrate an obvious difference between white males and females (with the peak at 75 to 79 for white males and 45 to 54 for white females), young black people are predominantly susceptible to suicide (risk peaks in early 20s for black males and late 20s for black females). Cohort effects all showed a descending trend, except that in white males and females which showed an obvious increase peaked in around cohort 1960. There was a similar period effect trend between different genders in the same race group, but between the races, differences were found in the period before 1990 and after 2000. CONCLUSION: We confirmed that the distinction in age-specific suicide rate patterns does exist by gender and by race after controlling for period and cohort effects, which suggested that minorities' age patterns of suicide may have been masked up by the white people in the whole population. The differences of period effects and cohort effects between white and black Americans were likely to be mainly explained by the difference in race susceptibility to economic depression.

The influence of temperature on mortality and its Lag effect: a study in four Chinese cities with different latitudes.

BACKGROUND: Global climate change is one of the most serious environmental issues faced by humanity, and the resultant change in frequency and intensity of heat waves and cold spells could increase mortality. The influence of temperature on human health could be immediate or delayed. Latitude, relative humidity, and air pollution may influence the temperature-mortality relationship. We studied the influence of temperature on mortality and its lag effect in four Chinese cities with a range of latitudes over 2008-2011, adjusting for relative humidity and air pollution. METHODS: We recorded the city-specific distributions of temperature and mortality by month and adopted a Poisson regression model combined with a distributed lag nonlinear model to investigate the lag effect of temperature on mortality. RESULTS: We found that the coldest months in the study area are December through March and the hottest months are June through September. The ratios of deaths during cold months to hot months were 1.43, 1.54, 1.37 and 1.12 for the cities of Wuhan, Changsha, Guilin and Haikou, respectively. The effects of extremely high temperatures generally persisted for 3 days, whereas the risk of extremely low temperatures could persist for 21 days. Compared with the optimum temperature of each city, at a lag of 21 days, the relative risks (95 % confidence interval) of extreme cold temperatures were 4.78 (3.63, 6.29), 2.38 (1.35, 4.19), 2.62 (1.15, 5.95) and 2.62 (1.44, 4.79) for Wuhan, Changsha, Guilin and Haikou, respectively. The respective risks were 1.35 (1.18, 1.55), 1.19 (0.96, 1.48), 1.22 (0.82, 1.82) and 2.47 (1.61, 3.78) for extreme hot temperatures, at a lag of 3 days. CONCLUSIONS: Temperature-mortality relationships vary among cities at different latitudes. Local governments should establish regional prevention and protection measures to more effectively confront and adapt to local climate change. The effects of hot temperatures predominantly occur over the short term, whereas those of cold temperatures can persist for an extended number of days.

Multiobjective Combinatorial Optimization Using a Single Deep Reinforcement Learning Model.

This article proposes utilizing a single deep reinforcement learning model to solve combinatorial multiobjective optimization problems. We use the well-known multiobjective traveling salesman problem (MOTSP) as an example. Our proposed method employs an encoder-decoder framework to learn the mapping from the MOTSP instance to its Pareto-optimal set. Specifically, it leverages a novel routing encoder to extract information for both the entire multiobjective aspect and every individual objective from the MOTSP instance. The global embeddings and each objective's embeddings are adaptively aggregated via a routing network to form the subproblems' embedding that can well represent the MOTSP features. Using a modified context embedding, the subproblems' embeddings are fed into a decoder to produce a set of approximate Pareto-optimal solutions in parallel. Additionally, we develop a Top-k baseline to enable more efficient data utilization and lightweight training for our proposed method. We compare our method with heuristic-based and learning-based ones on various types of MOTSP instances, and the experimental results show that our method can solve MOTSP instances in real-time and outperform the other algorithms, especially on large-scale problem instances.

MT4MTL-KD: A Multi-Teacher Knowledge Distillation Framework for Triplet Recognition.

The recognition of surgical triplets plays a critical role in the practical application of surgical videos. It involves the sub-tasks of recognizing instruments, verbs, and targets, while establishing precise associations between them. Existing methods face two significant challenges in triplet recognition: 1) the imbalanced class distribution of surgical triplets may lead to spurious task association learning, and 2) the feature extractors cannot reconcile local and global context modeling. To overcome these challenges, this paper presents a novel multi-teacher knowledge distillation framework for multi-task triplet learning, known as MT4MTL-KD. MT4MTL-KD leverages teacher models trained on less imbalanced sub-tasks to assist multi-task student learning for triplet recognition. Moreover, we adopt different categories of backbones for the teacher and student models, facilitating the integration of local and global context modeling. To further align the semantic knowledge between the triplet task and its sub-tasks, we propose a novel feature attention module (FAM). This module utilizes attention mechanisms to assign multi-task features to specific sub-tasks. We evaluate the performance of MT4MTL-KD on both the 5-fold cross-validation and the CholecTriplet challenge splits of the CholecT45 dataset. The experimental results consistently demonstrate the superiority of our framework over state-of-the-art methods, achieving significant improvements of up to 6.4% on the cross-validation split.

Proportions of Pseudomonas aeruginosa and Antimicrobial-Resistant P aeruginosa Among Patients With Surgical Site Infections in China: A Systematic Review and Meta-analysis.

Background: Pseudomonas aeruginosa is one of the most common pathogens in surgical site infections (SSIs). However, comprehensive epidemiological and antibiotic resistance details for P aeruginosa in Chinese SSIs are lacking. We evaluated the proportions and antimicrobial resistance of P aeruginosa among patients with SSIs in China. Methods: Relevant papers from January 2010 to August 2022 were searched in databases including PubMed, Embase, Web of Science, China Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang, and Weipu. A meta-analysis was performed to analyze the proportions and 95% confidence interval (CIs) of P aeruginosa among patients with SSIs. Meta-regression analysis was used to investigate the proportion difference among different subgroups and antimicrobial resistance. Results: A total of 72 studies met inclusion criteria, involving 33 050 isolated strains. The overall proportion of P aeruginosa among patients with SSIs was 16.0% (95% CI, 13.9%-18.2%). Subgroup analysis showed higher proportions in orthopedic (18.3% [95% CI, 15.6%-21.0%]) and abdominal surgery (17.3% [95% CI, 9.9%-26.2%]). The proportion in the central region (18.6% [95% CI, 15.3%-22.1%]) was slightly higher than that in other regions. Antibiotic resistance rates significantly increased after 2015: cefoperazone (36.2%), ceftriaxone (38.9%), levofloxacin (20.5%), and aztreonam (24.0%). Notably, P aeruginosa resistance to ampicillin and cefazolin exceeded 90.0%. Conclusions: The proportion of P aeruginosa infection among patients with SSIs was higher than the data reported by the Chinese Antimicrobial Resistance Surveillance System, indicating rising antimicrobial resistance. The existing antimicrobial drug management plan should be strengthened to prevent a hospital epidemic of drug-resistant P aeruginosa strains.

Distribution of Nosocomial Pathogens and Antimicrobial Resistance among Patients with Burn Injuries in China: A Comprehensive Research Synopsis and Meta-Analysis.

INTRODUCTION: Over the past decade, numerous studies have described the types of pathogens and their antibiotic resistance patterns in patients with burn injuries in China; however, the findings have generally been inconsistent. We conducted a literature search and meta-analysis to summarize the infection spectra and antimicrobial resistance patterns in patients with burn injuries. METHODS: We searched the PubMed, Embase, Web of Science, China National Knowledge Infrastructure, China Biomedical Literature, Wanfang, and Weipu databases for relevant articles published between January 2010 and December 2023. The DerSimonian-Laird random-effects model was used to estimate the proportions and 95% confidence intervals (CIs) of pathogens among Chinese patients with burn injuries. Meta-regression analyses were performed to explore differences in the proportions of pathogens among different subgroups and their resistance patterns. This study was registered with PROSPERO (CRD42024514386). RESULTS: The database searches yielded 2017 records; after removing duplicates and conducting initial screening, 219 articles underwent full-text screening. Ultimately, 60 studies comprising a total of 62,819 isolated strains reported the proportions of pathogens in patients with burn injuries and were included in this meta-analysis. Meta-analyses were conducted on 18 types of pathogens. The most common pathogens causing infections in Chinese patients with burn injuries were Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae, and Staphylococcus epidermidis. Similar results were observed in the subgroup analysis focusing on wound infections. Since 2015, there has been a significant decrease in the proportion of Pseudomonas aeruginosa (R2 = 4.89%) and a significant increase in the proportion of Klebsiella pneumoniae (R2 = 9.60%). In terms of antibiotic resistance, there has been a significant decrease in the resistance of Staphylococcus aureus to multiple antibiotics and an increasing trend in the resistance of Klebsiella pneumoniae. CONCLUSIONS: We systematically summarized the epidemiological characteristics and antibiotic resistance patterns of pathogens among individuals suffering from burns in China, thus providing guidance for controlling wound infections and promoting optimal empirical antimicrobial therapy. The observed high levels of antibiotic resistance underscore the need for ongoing monitoring of antibiotic usage trends.

Choose Appropriate Subproblems for Collaborative Modeling in Expensive Multiobjective Optimization.

In dealing with the expensive multiobjective optimization problem, some algorithms convert it into a number of single-objective subproblems for optimization. At each iteration, these algorithms conduct surrogate-assisted optimization on one or multiple subproblems. However, these subproblems may be unnecessary or resolved. Operating on such subproblems can cause server inefficiencies, especially in the case of expensive optimization. To overcome this shortcoming, we propose an adaptive subproblem selection (ASS) strategy to identify the most promising subproblems for further modeling. To better leverage the cross information between the subproblems, we use the collaborative multioutput Gaussian process surrogate to model them jointly. Moreover, the commonly used acquisition functions (also known as infill criteria) are investigated in this article. Our analysis reveals that these acquisition functions may cause severe imbalances between exploitation and exploration in multiobjective optimization scenarios. Consequently, we develop a new acquisition function, namely, adaptive lower confidence bound (ALCB), to cope with it. The experimental results on three different sets of benchmark problems indicate that our proposed algorithm is competitive. Beyond that, we also quantitatively validate the effectiveness of the ASS strategy, the CoMOGP model, and the ALCB acquisition function.

EVA1A regulates hematopoietic stem cell regeneration via ER-mitochondria mediated apoptosis.

Excessive protein synthesis upon enhanced cell proliferation frequently results in an increase of unfolded or misfolded proteins. During hematopoietic regeneration, to replenish the hematopoietic system, hematopoietic stem cells (HSCs) are activated and undergo a rapid proliferation. But how the activated HSCs respond to the proliferation pressure is still ambiguous; The proper control of the functional reservoir in the activated HSCs remains poorly understood. Here, we show a significant upregulation of EVA1A protein associated with the increase of ER stress during hematopoietic regeneration. Deletion of Eva1a significantly enhances the regeneration capacity of HSCs by inhibiting the ER stress-induced apoptosis. Mechanistically, the expression of EVA1A protein was upregulated by CHOP, and thereby promoted the ER-mitochondria interlinking via MCL1, which resulted in mitochondria-mediated apoptosis. These findings reveal a pathway for ER stress responses of HSCs by the EVA1A mediated apoptosis, which play an important role in HSCs regeneration.

CholecTriplet2022: Show me a tool and tell me the triplet - An endoscopic vision challenge for surgical action triplet detection.

Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. The benefit is that this formalization helps to obtain a more detailed understanding of tool-tissue interaction which can be used to develop better Artificial Intelligence assistance for image-guided surgery. Earlier efforts and the CholecTriplet challenge introduced in 2021 have put together techniques aimed at recognizing these triplets from surgical footage. Estimating also the spatial locations of the triplets would offer a more precise intraoperative context-aware decision support for computer-assisted intervention. This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection. It includes weakly-supervised bounding box localization of every visible surgical instrument (or tool), as the key actors, and the modeling of each tool-activity in the form of triplet. The paper describes a baseline method and 10 new deep learning algorithms presented at the challenge to solve the task. It also provides thorough methodological comparisons of the methods, an in-depth analysis of the obtained results across multiple metrics, visual and procedural challenges; their significance, and useful insights for future research directions and applications in surgery.

Green stocks, crypto asset, crude oil and COVID19 pandemic: Application of rolling window multiple correlation.

The COVID-19 pandemic disrupted almost all spares of global social, psychological, and economic life. The emergence of various variants and corresponding variations in daily infection asymmetrically influenced economic indicators. This study extends the existing literature by exploring the hedging potential of crude oil, carbon efficiency index of green firms, and bitcoin during this pandemic. This objective is realized by employing the recently advanced rolling window multiple correlation of Polanco-Martínez (2020). This approach is based on the new p-value corrected method, which has advantages over other correlation methods. The sample observations are based on daily data from 1/22/2020 to 12/20/2021. In the bivariate case, we find a significant positive correlation between COVID-19 and CEI, while a negative impact is observed between COVID-19 and WTI. Similarly, we observe a significant and nonlinear association between COVID-19 and BTC. However, our findings show positive and significant correlations among variables in the multivariate case. The overall findings show that CEI and BTC can be safe havens for investors during this worse pandemic. The study's robust findings can be used to derive important policy implications worldwide during the COVID-19 pandemic.

Memory-based variable neighborhood search for green vehicle routing problem with passing-by drivers: a comprehensive perspective.

A business delivery model with professional vehicles as well as occasional passing-by vehicles is investigated in this paper. The drivers deliver parcels from the distribution center to customers and the passing-by driver can get a certain amount of compensation in return. To give a satisfactory solution from the perspective of platform owner, customers, professional drivers, occasional drivers, and authority, a multi-layer comprehensive model is proposed. To effectively solve the proposed model, we introduce an improved variable neighborhood search (VNS) with a memory-based restart mechanism. The new algorithm is evaluated on instances derived from Solomon's benchmark and real-life beer delivery instances. Taguchi experiment is used to tune parameters in the proposed VNS, followed by component analysis and real-life experiments. Experimental results indicate that the proposed strategies are effective and the new delivery model in this paper has some advantages over traditional and single-delivery ones from the comprehensive perspectives of stakeholders in the crowdsourcing logistics system.

Systematic Analysis of the Global, Regional and National Burden of Cardiovascular Diseases from 1990 to 2017.

BACKGROUND: Previous studies on the burden of cardiovascular diseases (CVDs) were mainly based on limited data of the study period or area, or did not include detailed risk factor analysis. OBJECTIVE: To investigate up-to-date temporal and regional trends and risk factors of mortality and disability-adjusted life years (DALYs) attributed to CVDs by age, sex, and disease throughout the world. METHODS: Data for the disease burden of CVDs in 195 countries and territories from 1990 to 2017, including mortality, DALYs, age-standardized mortality rates, and age-standardized DALY rates, were estimated from the Global Burden of Disease Study 2017. Risk factors attributable to deaths and DALYs for CVDs were also estimated using the comparative risk assessment framework. RESULTS: The number of deaths from CVDs increased by 48.62%, from 11.94 (95% UI 11.78-12.18) million in 1990 to 17.79 (17.53-18.04) million in 2017. However, the age-standardized mortality rate decreased by an average of - 1.45% (- 1.72% to - 1.18%) annually. After fluctuation in the expected age-standardized mortality rate of CVDs in most of the socio-demographic index (SDI) scale, these rates decrease rapidly for SDI values of 0.7 and higher. In 2017, metabolic risks accounted for 73.48% of deaths and 73.25% of DALYs due to CVDs, behavioral factors accounted for 63.23% of deaths and 66.71% of attributable DALYs. CONCLUSION: CVDs remain a major global health burden due to the increment in death numbers and DALYs. Aging and the main risk factors are the main drivers of mortality and health loss. More attention to main risk factors should be paid with supportive health policies.

Road to entire insulation for resonances from a forced mechanical system.

The effective solution to avoid machinery damage caused by resonance has been perplexing the field of engineering as a core research direction since the resonance phenomenon was discovered by Euler in 1750. Numerous attempts have been performed to reduce the influence of resonance since the earlier of last century, by introducing a nonlinear structure or a closed-loop control system. However, the existed methodologies cannot eliminate resonance completely even extra problems were introduced inevitably, which means the technical choke-point of resonance-free remains unsolved. Here we propose a designable archetype model, which establishes a mapping between the mechanical properties and its structure. A general inverse method for structure construction is proposed based upon the required property for the system with quasi-zero stiffness of any designed finite order and the zero-stiffness properties. It is shown that an ellipse trajectory tracking of the designed model is the sufficient and necessary condition to satisfy the zero-stiffness property. Theoretical analysis shows that no resonant response happens in a zero-stiffness system to the full-band frequency excitation, or equivalently, the system can completely isolate the energy transfer between the load and environment, when the damping ratio approaches zero. Finally, an experimental rig for the prototype structure is built up according to the sufficient and necessary condition of the zero-stiffness system, for which the special dynamic behaviours are verified through experiments of frequency-sweep and random-vibration as well. Experimental results show that the prototype of the initial vibration isolation frequency of zero-stiffness system is much lower than 0.37 Hz, and the vibration attenuation of the proposed model is about 16.86 dB, 45.63 dB, and 112.37 dB at frequencies of 0.37 Hz, 1 Hz, and 10 Hz, respectively. The distinguished geometric structure of the zero-stiffness system leads to a new inspiration for the design of resonance-free in metamaterial unit and the inverse method can even adapt the design for a more targeted applications based on an arbitrary complex dynamic requirement.

Multiobjective Optimization-Aided Decision-Making System for Large-Scale Manufacturing Planning.

This work is geared toward a real-world manufacturing planning (MP) task, whose two objectives are to maximize the order fulfillment rate and minimize the total cost. More important, the requirements and constraints in real manufacturing make the MP task very challenging in several aspects. For example, the MP needs to cover many production components of multiple plants over a 30-day horizon, which means that it involves a large number of decision variables. Furthermore, the MP task's two objectives have extremely different magnitudes, and some constraints are difficult to handle. Facing these uncompromising practical requirements, we introduce an interactive multiobjective optimization-based MP system in this article. It can help the decision maker reach a satisfactory tradeoff between the two objectives without consuming massive calculations. In the MP system, the submitted MP task is modeled as a multiobjective integer programming (MOIP) problem. Then, the MOIP problem is addressed via a two-stage multiobjective optimization algorithm (TSMOA). To alleviate the heavy calculation burden, TSMOA transforms the optimization of the MOIP problem into the optimization of a series of single-objective problems (SOPs). Meanwhile, a new SOP solving strategy is used in the MP system to further reduce the computational cost. It utilizes two sequential easier SOPs as the approximator of the original complex SOP for optimization. As part of the MP system, TSMOA and the SOP solving strategy are demonstrated to be efficient in real-world MP applications. In addition, the effectiveness of TSMOA is also validated on benchmark problems. The results indicate that TSMOA as well as the MP system are promising.

Membrane dynamics of ATG4B and LC3 in autophagosome formation.

The biogenesis of autophagosomes provides the basis for macroautophagy to capture and degrade intracellular cargoes. Binding of the autophagy-related protein ATG8/LC3 to autophagic membranes is essential to autophagosome formation, which involves the specific and dynamic processing of ATG8/LC3 by cysteine protease ATG4. However, to date, the mechanism whereby ATG4 is recruited to the membranes, the interaction of ATG4 and ATG8/LC3 on the membranes, and its role in the growth of phagophore are not completely understood. Here, we used fluorescence recovery after photobleaching to monitor the turnover of GFP-tagged ATG4B and LC3B in living animal cells. The data show that ATG4B localizes to early autophagic membranes in an LC3B-dependent manner. During autophagy, ATG4B and LC3B undergo rapid cytosol/isolation membrane exchange but not at the cytosol/completed autophagosome. In addition, ATG4B activity controls the efficiency of autophagosome formation by impacting the membrane binding/dissociation of LC3B. These data suggest that ATG4 and LC3 play interdependent roles in the formation of autophagosomes.