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ObjectivesWe aimed to provide the most updated estimates on the global burden of inflammatory bowel disease (IBD) to improve management strategies.DesignWe extracted data from the Global Burden of Disease (GBD) 2019 database to evaluate IBD burden with different measures in 204 countries and territories from 1990 to 2019.SettingStudies from the GBD 2019 database generated by population-representative data sources identified through a literature review and research collaborations were included.ParticipantsPatients with an IBD diagnosis.OutcomesTotal numbers, age-standardised rates of prevalence, mortality and disability-adjusted life-years (DALYs), and their estimated annual percentage changes (EAPCs) were the main outcomes.ResultsIn 2019, there were approximately 4.9 million cases of IBD worldwide, with China and the USA having the highest number of cases (911 405 and 762 890 (66.9 and 245.3 cases per 100 000 people, respectively)). Between 1990 and 2019, the global age-standardised rates of prevalence, deaths and DALYs decreased (EAPCs=−0.66,–0.69 and −1.04, respectively). However, the age-standardised prevalence rate increased in 13 out of 21 GBD regions. A total of 147 out of 204 countries or territories experienced an increase in the age-standardised prevalence rate. From 1990 to 2019, IBD prevalent cases, deaths and DALYs were higher among females than among males. A higher Socio-demographic Index was associated with higher age-standardised prevalence rates.ConclusionsIBD will continue to be a major public health burden due to increasing numbers of prevalent cases, deaths and DALYs. The epidemiological trends and disease burden of IBD have changed dramatically at the regional and national levels, so understanding these changes would be beneficial for policy makers to tackle IBD.

Based on Conservation of Resources (COR) theory and a socio-technical systems perspective, this study examines how technology-enacted abusive supervision (TAS) influences employees’ counterproductive work behavior (CWB) in digitalized organizational contexts. Conceptualizing TAS as a system-embedded form of digitally mediated control, we argue that technology-amplified supervisory power constitutes a persistent resource threat that reshapes employees’ behavioral regulation strategies. Using three-wave time-lagged survey data from 428 employees working in digital-intensive enterprises in China, we develop and test a moderated mediation model. The results indicate that TAS is positively associated with CWB, with defensive silence serving as a critical mediating mechanism. Although defensive silence may temporarily reduce interpersonal risk, it disrupts feedback and resource replenishment processes, leading to cumulative resource depletion and a higher likelihood of counterproductive behavior over time. Moreover, power distance significantly moderates this indirect effect, such that the mediating role of defensive silence is stronger among employees with higher-power-distance orientations. By integrating leadership research, COR theory, cultural value orientations, and a socio-technical systems perspective, this study advances our understanding of covert resistance and behavioral risk in technology-driven work systems and offers important implications for digital governance and sustainable organizational performance.

In today’s dynamic business environment, organizations increasingly adopt empowering leadership to foster autonomy and flexibility. However, differentiated empowering leadership (DEL), which distributes authority unequally among employees, may inadvertently lead to negative consequences. This study examines the impact of DEL on knowledge hiding among Generation MZ employees, emphasizing the mediating role of knowledge-based psychological ownership and the moderating effect of task interdependence. Drawing on conservation of resources (COR) theory, we argue that employees who perceive an unfair distribution of authority may develop a defensive ownership of their knowledge, leading them to engage in knowledge hiding as a protective mechanism. Utilizing survey data from 393 employees across 94 teams in 12 Chinese firms, we employed hierarchical linear modeling (HLM) to test our hypotheses. The results indicate that DEL significantly increases knowledge hiding through heightened psychological ownership of knowledge. Additionally, task interdependence moderates this relationship, such that employees in highly interdependent tasks exhibit reduced tendencies to withhold knowledge. This study contributes to leadership and management literature by demonstrating how the perception of unequal empowerment influences employee behaviors. It highlights the paradoxical effect of psychological ownership, which, while traditionally associated with positive outcomes, can also drive detrimental behaviors like knowledge hiding. Furthermore, the study underscores the role of task interdependence as a mitigating factor, suggesting that fostering collaborative work environments can alleviate the adverse effects of DEL.

Rapid urbanization and alterations in the built environment have exacerbated transportation energy consumption and environmental pollution, making transportation-related carbon emissions a significant barrier to low-carbon urban development. This study examines the influence of the built environment on commuting carbon emissions in the central urban area of Jinan, addressing the increasing challenge of transportation-induced emissions in rapidly urbanizing cities. Through the integration of multi-source big data, including travel trajectory, urban land use, and street view data, the research analyzes the spatial patterns of commuting behavior and emissions. Utilizing spatial autocorrelation, multiple linear regression, and geographically weighted regression (GWR), the study identifies critical factors influencing emissions, such as residential and commercial land area, transportation hubs, road network density, and floor area ratio. The results reveal that commuting emissions exhibit a monocentric pattern, with higher emissions in suburban areas due to lower population density and limited access to public transportation. Conversely, the central urban area of Jinan experience lower emissions, attributed to greater use of public transportation and shorter commuting distances. The GWR model uncovers spatial heterogeneity in the impact of the built environment, emphasizing the necessity for context-specific urban planning strategies. This research presents a comprehensive framework for reducing commuting carbon emissions, providing valuable insights for medium-sized cities striving to promote low-carbon transportation and optimize urban structures. The findings contribute to the formulation of targeted, data-driven policies for sustainable urban planning.

Gram-negative bacteria surround their cytoplasmic membrane with a peptidoglycan (PG) cell wall and an outer membrane (OM) with an outer leaflet composed of lipopolysaccharide (LPS) 1 . This complex envelope presents a formidable barrier to drug entry and is a major determinant of the intrinsic antibiotic resistance of these organisms 2 . The biogenesis pathways that build the surface are also targets of many of our most effective antibacterial therapies 3 . Understanding the molecular mechanisms underlying the assembly of the Gram-negative envelope therefore promises to aid the development of new treatments effective against the growing problem of drug-resistant infections. Although the individual pathways for PG and OM synthesis and assembly are well characterized, almost nothing is known about how the biogenesis of these essential surface layers is coordinated. Here we report the discovery of a regulatory interaction between the committed enzymes for the PG and LPS synthesis pathways in the Gram-negative pathogen Pseudomonas aeruginosa . We show that the PG synthesis enzyme MurA interacts directly and specifically with the LPS synthesis enzyme LpxC. Moreover, MurA was shown to stimulate LpxC activity in cells and in a purified system. Our results support a model in which the assembly of the PG and OM layers in many proteobacterial species is coordinated by linking the activities of the committed enzymes in their respective synthesis pathways. A study demonstrates that specific interactions between the two committed enzymes for the synthesis of lipopolysaccharide and peptidoglycan enable coordinated assembly of the outer membrane and cell wall in the Gram-negative pathogen Pseudomonas aeruginosa .

Objectives: Whether Internet use improves older people’s health is an open question. This study empirically investigated the impact of Internet use on older people’s mental health with a focus on the heterogeneity among subgroups. Method: Data come from the 2018 China Health Retirement Longitudinal Study ( n = 8,505). An instrumental variable quantile regression method (IVQR) combines the instrumental variable and quantile regression to resolve the endogeneity and heterogeneity generally challenged in ordinary least squares (OLS). Results: Although Internet use generally improves older people’s mental health, there is enormous heterogeneity in the effects on older adults with different mental health conditions. Specifically, Internet use only has a mitigating impact on older adults with poor mental health. Those heterogeneities are also found between rural and urban residents but not between genders. Conclusion: Our findings shed light on active and healthy aging strategies. Two policy priorities include, on the one hand, the Internet user environment should be improved in parallel with Internet technology; on the other hand, multiple measurements are urgent to be developed to deal with the heterogeneity and unevenness of the impact of Internet technology on older people.

The energetic demands of a cell are believed to increase during mitosis, but the rates of ATP synthesis and consumption during mitosis have not been quantified. Here, we monitor mitochondrial membrane potential of single lymphocytic leukemia cells and demonstrate that mitochondria hyperpolarize from the G2/M transition until the metaphase-anaphase transition. This hyperpolarization was dependent on cyclin-dependent kinase 1 (CDK1) activity. By using an electrical circuit model of mitochondria, we quantify mitochondrial ATP synthesis rates in mitosis from the single-cell time-dynamics of mitochondrial membrane potential. We find that mitochondrial ATP synthesis decreases by approximately 50% during early mitosis and increases back to G2 levels during cytokinesis. Consistently, ATP levels and ATP synthesis are lower in mitosis than in G2 in synchronized cell populations. Overall, our results provide insights into mitotic bioenergetics and suggest that cell division is not a highly energy demanding process. ATP drives most cellular processes, although ATP production and consumption levels during mitosis remain unreported. Here, the authors combine metabolic measurements and modeling to quantify ATP levels and synthesis dynamics, revealing that ATP synthesis and consumption are lowered during mitosis.

The carbon trading market has become a powerful weapon in alleviating carbon emissions in China, and the carbon price is at the core of its operation. Hence, the carbon trading market serves as an indispensable component in forecasting the carbon price accurately in advance. This paper innovatively explores an ensemble‐driven long short‐term memory network (LSTM) model based on complementary ensemble empirical mode decomposition (CEEMD) for carbon price forecasting, applying it to all eight carbon trading pilots in China. The CEEMD was initially implemented for mode transformation in order to decompose the original complicated mode into a set of simple modes. Then, the partial autocorrelation function selected time‐lagged features as inputs for each mode. Subsequently, the LSTM was used to model the mapping between time‐lagged factors as well as each mode's target values, constructing multiple LSTM models for ensemble learning. Finally, the inverse CEEMD computation was introduced to integrate the anticipated results of the multi‐mode into the final results. Its practical application simultaneously embraced all eight carbon pilots in China, covering their corresponding carbon price data over a considerably long period. The obtained results illustrated that the proposed model driven by ensemble learning possessed sufficient accuracy in carbon price forecasting in China compared with the single LSTM model as well as other conventional artificial neural network models. Furthermore, according to the scope of its application, the innovative model exhibited strong stability and universality. Carbon trading market has become one of the powerful weapons to alleviate carbon emission in China, and carbon price is at the core of determining its operation, so, it is indispensable to accurately and comprehensively forecast the carbon price in advance. This paper innovatively explores an ensemble‐driven long short‐term memory network (LSTM) model based on complementary ensemble empirical mode decomposition (CEEMD) for carbon prices forecasting and applies it on all eight carbon trading pilots of China.

Tumors are composed of many different cell types including cancer cells, fibroblasts, and immune cells. Dissecting functional metabolic differences between cell types within a mixed population can be challenging due to the rapid turnover of metabolites relative to the time needed to isolate cells. To overcome this challenge, we traced isotope-labeled nutrients into macromolecules that turn over more slowly than metabolites. This approach was used to assess differences between cancer cell and fibroblast metabolism in murine pancreatic cancer organoid-fibroblast co-cultures and tumors. Pancreatic cancer cells exhibited increased pyruvate carboxylation relative to fibroblasts, and this flux depended on both pyruvate carboxylase and malic enzyme 1 activity. Consequently, expression of both enzymes in cancer cells was necessary for organoid and tumor growth, demonstrating that dissecting the metabolism of specific cell populations within heterogeneous systems can identify dependencies that may not be evident from studying isolated cells in culture or bulk tissue. Tumors contain a mixture of many different types of cells, including cancer cells and non-cancer cells. The interactions between these two groups of cells affect how the cancer cells use nutrients, which, in turn, affects how fast these cells grow and divide. Furthermore, different cell types may use nutrients in diverse ways to make other molecules – known as metabolites – that the cell needs to survive. Fibroblasts are a subset of non-cancer cells that are typically found in tumors and can help them form. Separating fibroblasts from cancer cells in a tumor takes a lot longer than the chemical reactions in each cell of the tumor that produce and use up nutrients, also known as the cell’s metabolism. Therefore, measuring the levels of glucose (the sugar that is the main energy source for cells) and other metabolites in each tumor cell after separating them does not necessarily provide accurate information about the tumor cell’s metabolism. This makes it difficult to study how cancer cells and fibroblasts use nutrients differently. Lau et al. have developed a strategy to study the metabolism of cancer cells and fibroblasts in tumors. Mice with tumors in their pancreas were provided glucose that had been labelled using biochemical techniques. As expected, when the cell processed the glucose, the label was transferred into metabolites that got used up very quickly. But the label also became incorporated into larger, more stable molecules, such as proteins. Unlike the small metabolites, these larger molecules do not change in the time it takes to separate the cancer cells from the fibroblasts. Lau et al. sorted cells from whole pancreatic tumors and analyzed large, stable molecules that can incorporate the label from glucose in cancer cells and fibroblasts. The experiments showed that, in cancer cells, these molecules were more likely to have labeling patterns that are characteristic of two specific enzymes called pyruvate carboxylase and malic enzyme 1. This suggests that these enzymes are more active in cancer cells. Lau et al. also found that pancreatic cancer cells needed these two enzymes to metabolize glucose and to grow into large tumors. Pancreatic cancer is one of the most lethal cancers and current therapies offer limited benefit to many patients. Therefore, it is important to develop new drugs to treat this disease. Understanding how cancer cells and non-cancer cells in pancreatic tumors use nutrients differently is important for developing drugs that only target cancer cells.

The challenge of dendrite growth limiting metal battery lifespan, despite extensive chemical composition optimizations for artificial solid electrolyte interphases (ASEIs), necessitates the development of ASEI design routes. Regulating the ASEI crystallographic microstructure offers a promising yet underexplored solution with efficacy uncertainty. Critical issue lies in what is the optimal crystallographic microstructure state. Using the ZnS ASEI in aqueous Zn batteries as a case study, here we report the effects of grain orientation and grain boundary density on the performance of Zn negative electrode. The results reveal the existence of an optimal microstructure state—predominant in-plane (111) orientation coupled with a critical grain boundary density of ~55 μm/μm 2 —which delivers an 18-fold lifespan extension, and over 3400 cycles with a Coulombic efficiency of 99.92% at 5 mA cm -2 , surpassing the efficacy of most chemical composition manipulations. Mechanistically, the (111) orientation integrates higher electrochemical kinetics and mechanical strength. As grain boundary density increases to tens of μm/μm 2 , the enhancement in electrochemical kinetics coincides with compromised mechanical strength, with their trade-off delineating the critical density that maximizes electrode cycling stability. Our findings exemplify an efficient ASEI design route—crystallographic microstructure engineering. Dendrite growth compromises the cycling life of metal batteries. Here, authors propose a crystallographic microstructure engineering approach to the artificial solid electrolyte interphase, demonstrating a high efficacy in stabilizing the zinc metal electrode during plating/stripping.