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Microplastics (MPs), as new pollutants in agroecosystems, have already attracted widespread attention from scientists. However, our understanding of MP geographic distribution and its influencing factors across spatial scales remains poor. Here, a regional-scale field investigation was conducted to assess the distribution characteristic of MPs in five major rice-growing regions of China, and we explored the roles of biological and abiotic factors, especially stoichiometry and microbial influences on MP distribution. MPs were observed in all sampling sites, averaging 6,390 ± 2,031 items⋅kg–1. Sizes less than 0.5 mm and black and transparent MPs dominated. Fiber, classified as one of the MP shapes, occurred most frequently. MP community analysis, firstly used in paddy soil, revealed more black MPs abundance in Henan (HE), more rayon, blue, and other colors MPs in Hunan (HN), more transparent MPs in Tianjing (TJ), and more PE MPs in Heilongjiang (DB). Higher MP community diversity was found in most south paddy soils of this study, due to a broader range of sources. C/N showed a positive relationship with pellet-shaped MP abundance and MPs of size between 2 and 5 mm (P < 0.05). Chao1 index of soil microbial communities was positively correlated with the MP abundance, MPs of size less than 0.5 mm, and fiber abundance. The minimum temperature was positively correlated with MP abundance (P < 0.05), implying the potential effects of the freeze-thaw process might exist. The regression analysis highlighted the important role of population quantity in determining MP abundance (R = 0.421, P = 0.02). This study confirmed the wide distribution of MPs in different soil depths of paddy lands in China and demonstrated that its distribution was influenced by population quantity and environmental variables, such as microbiology. These findings could provide a basis for the toxicological behavior of MPs and the potential risk to human health.

Cancer stem cells (CSCs) are involved in tumorigenesis, recurrence, and therapy resistance. To identify critical regulators of sarcoma CSCs, we performed a reporter-based genome-wide CRISPR-Cas9 screen and uncovered Kruppel-like factor 11 (KLF11) as top candidate. In vitro and in vivo functional annotation defined a negative role of KLF11 in CSCs. Mechanistically, KLF11 and YAP/TEAD bound to adjacent DNA sites along with direct interaction. KLF11 recruited SIN3A/HDAC to suppress the transcriptional output of YAP/TEAD, which, in turn, promoted KLF11 transcription, forming a negative feedback loop. However, in CSCs, this negative feedback was lost because of epigenetic silence of KLF11, causing sustained YAP activation. Low KLF11 was associated with poor prognosis and chemotherapy response in patients with sarcoma. Pharmacological activation of KLF11 by thiazolidinedione effectively restored chemotherapy response. Collectively, our study identifies KLF11 as a negative regulator in sarcoma CSCs and potential therapeutic target.

Cancer stem cells (CSCs) are involved in tumorigenesis, recurrence, and therapy resistance. To identify critical regulators of sarcoma CSCs, we performed a reporter-based genome-wide CRISPR-Cas9 screen and uncovered Kruppel-like factor 11 (KLF11) as top candidate. In vitro and in vivo functional annotation defined a negative role of KLF11 in CSCs. Mechanistically, KLF11 and YAP/TEAD bound to adjacent DNA sites along with direct interaction. KLF11 recruited SIN3A/HDAC to suppress the transcriptional output of YAP/TEAD, which, in turn, promoted KLF11 transcription, forming a negative feedback loop. However, in CSCs, this negative feedback was lost because of epigenetic silence of KLF11, causing sustained YAP activation. Low KLF11 was associated with poor prognosis and chemotherapy response in patients with sarcoma. Pharmacological activation of KLF11 by thiazolidinedione effectively restored chemotherapy response. Collectively, our study identifies KLF11 as a negative regulator in sarcoma CSCs and potential therapeutic target.

As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrains early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in light-and heavy-duty application. Based on the power ratio between powertrains power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to the most efficient conditions, or by eliminating the engine operation from poorly efficient operating points to pure electric vehicle operation. A turning point is found to meet the requirement of the final state of energy of the battery, which is charge-sustaining mode in this study. The GRAB-ECO was tested with both light- and heavy-duty parallel hybrid electric vehicles, and validated in terms of the minimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumption with less than 6% of errors for both light-and heavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagins Minimum Principle) approaches.

As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrains early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in light-and heavy-duty application. Based on the power ratio between powertrains power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to the most efficient conditions, or by eliminating the engine operation from poorly efficient operating points to pure electric vehicle operation. A turning point is found to meet the requirement of the final state of energy of the battery, which is charge-sustaining mode in this study. The GRAB-ECO was tested with both light- and heavy-duty parallel hybrid electric vehicles, and validated in terms of the minimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumption with less than 6% of errors for both light-and heavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagins Minimum Principle) approaches.

Zhenheng Wang,* Kaiwen Xue,* Maosheng Bai, Zhantao Deng, Jingjing Gan, Gang Zhou, Hongbo Qian,* Nirong Bao, Jianning Zhao Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, People’s Republic of China *These authors contributed equally to this work Abstract: Wear particle-induced inflammatory osteolysis is the primary cause of aseptic loosening, which is the most common reason for total hip arthroplasty (THA) failure in the med- and long term. Recent studies have suggested an important role of gut microbiota (GM) in modulating the host metabolism and immune system, leading to alterations in bone mass. Probiotic bacteria administered in adequate amounts can alter the composition of GM and confer health benefits to the host. Given the inflammatory osteolysis that occurs in wear debris-induced prosthesis loosening, we examined whether the probiotic Lactobacillus casei could reduce osteolysis in a mouse calvarial resorption model. In this study, L. casei markedly protected mice from CoCrMo particles (CoPs)-induced osteolysis. Osteoclast gene markers and the number of osteoclasts were significantly decreased in L. casei-treated mice. Probiotic treatment decreased the M1-like macrophage phenotype indicated by downregulation of tumor necrosis factor α (TNF-α), interleukin (IL)-6 and inducible nitric oxide synthase (iNOS) and increased the M2-like macrophage phenotype indicated by upregulation of IL-4, IL-10 and arginase. Collectively, these results indicated that the L. casei treatment modulated the immune status and suppressed wear particle-induced osteolysis in vivo. Thus, probiotic treatment may represent a potential preventive and therapeutic approach to reduced wear debris-induced osteolysis. Keywords: wear particles, gut microbiota, nanotoxicity, macrophage polarization, inflammatory cytokines, aseptic loosening

Zhantao Deng,1–3,* Jiewen Jin,2,3,* Zhenheng Wang,1 Yong Wang,2,3 Qian Gao,2,3 Jianning Zhao1 1Department of Orthopedics, Jinling Hospital, School of Medicine, Nanjing University, 2Center for Translational Medicine, Nanjing University Medical School, 3Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China *These authors contributed equally to this work Abstract: Aseptic loosening is the most common cause of total hip arthroplasty (THA) failure, and osteolysis induced by wear particles plays a major role in aseptic loosening. Various pathways in multiple cell types contribute to the pathogenesis of osteolysis, but the role of Sirtuin 1 (SIRT1), which can regulate inflammatory responses through its deacetylation, has never been investigated. We hypothesized that the downregulation of SIRT1 in macrophages induced by metal nanoparticles was one of the reasons for osteolysis in THA failure. In this study, the expression of SIRT1 was examined in macrophages stimulated with metal nanoparticles from materials used in prosthetics and in specimens from patients suffering from aseptic loosening. To address whether SIRT1 downregulation triggers these inflammatory responses, the effects of the SIRT1 activator resveratrol on the expression of inflammatory cytokines in metal nanoparticle-stimulated macrophages were tested. The results demonstrated that SIRT1 expression was significantly downregulated in metal nanoparticle-stimulated macrophages and clinical specimens of prosthesis loosening. Pharmacological activation of SIRT1 dramatically reduced the particle-induced expression of inflammatory cytokines in vitro and osteolysis in vivo. Furthermore, SIRT1 regulated particle-induced inflammatory responses through nuclear factor kappa B (NF-κB) acetylation. Thus, the results of this study suggest that SIRT1 plays a key role in metal nanoparticle-induced inflammatory responses and th

As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrains early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in light-and heavy-duty application. Based on the power ratio between powertrains power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to the most efficient conditions, or by eliminating the engine operation from poorly efficient operating points to pure electric vehicle operation. A turning point is found to meet the requirement of the final state of energy of the battery, which is charge-sustaining mode in this study. The GRAB-ECO was tested with both light- and heavy-duty parallel hybrid electric vehicles, and validated in terms of the minimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumption with less than 6% of errors for both light-and heavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagins Minimum Principle) approaches.

Zhenheng Wang,* Kaiwen Xue,* Maosheng Bai, Zhantao Deng, Jingjing Gan, Gang Zhou, Hongbo Qian,* Nirong Bao, Jianning Zhao Department of Orthopaedics, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, People’s Republic of China *These authors contributed equally to this work Abstract: Wear particle-induced inflammatory osteolysis is the primary cause of aseptic loosening, which is the most common reason for total hip arthroplasty (THA) failure in the med- and long term. Recent studies have suggested an important role of gut microbiota (GM) in modulating the host metabolism and immune system, leading to alterations in bone mass. Probiotic bacteria administered in adequate amounts can alter the composition of GM and confer health benefits to the host. Given the inflammatory osteolysis that occurs in wear debris-induced prosthesis loosening, we examined whether the probiotic Lactobacillus casei could reduce osteolysis in a mouse calvarial resorption model. In this study, L. casei markedly protected mice from CoCrMo particles (CoPs)-induced osteolysis. Osteoclast gene markers and the number of osteoclasts were significantly decreased in L. casei-treated mice. Probiotic treatment decreased the M1-like macrophage phenotype indicated by downregulation of tumor necrosis factor α (TNF-α), interleukin (IL)-6 and inducible nitric oxide synthase (iNOS) and increased the M2-like macrophage phenotype indicated by upregulation of IL-4, IL-10 and arginase. Collectively, these results indicated that the L. casei treatment modulated the immune status and suppressed wear particle-induced osteolysis in vivo. Thus, probiotic treatment may represent a potential preventive and therapeutic approach to reduced wear debris-induced osteolysis. Keywords: wear particles, gut microbiota, nanotoxicity, macrophage polarization, inflammatory cytokines, aseptic loosening

Zhantao Deng,1–3,* Jiewen Jin,2,3,* Zhenheng Wang,1 Yong Wang,2,3 Qian Gao,2,3 Jianning Zhao1 1Department of Orthopedics, Jinling Hospital, School of Medicine, Nanjing University, 2Center for Translational Medicine, Nanjing University Medical School, 3Jiangsu Key Laboratory for Molecular Medicine, Nanjing University Medical School, Nanjing, Jiangsu, People’s Republic of China *These authors contributed equally to this work Abstract: Aseptic loosening is the most common cause of total hip arthroplasty (THA) failure, and osteolysis induced by wear particles plays a major role in aseptic loosening. Various pathways in multiple cell types contribute to the pathogenesis of osteolysis, but the role of Sirtuin 1 (SIRT1), which can regulate inflammatory responses through its deacetylation, has never been investigated. We hypothesized that the downregulation of SIRT1 in macrophages induced by metal nanoparticles was one of the reasons for osteolysis in THA failure. In this study, the expression of SIRT1 was examined in macrophages stimulated with metal nanoparticles from materials used in prosthetics and in specimens from patients suffering from aseptic loosening. To address whether SIRT1 downregulation triggers these inflammatory responses, the effects of the SIRT1 activator resveratrol on the expression of inflammatory cytokines in metal nanoparticle-stimulated macrophages were tested. The results demonstrated that SIRT1 expression was significantly downregulated in metal nanoparticle-stimulated macrophages and clinical specimens of prosthesis loosening. Pharmacological activation of SIRT1 dramatically reduced the particle-induced expression of inflammatory cytokines in vitro and osteolysis in vivo. Furthermore, SIRT1 regulated particle-induced inflammatory responses through nuclear factor kappa B (NF-κB) acetylation. Thus, the results of this study suggest that SIRT1 plays a key role in metal nanoparticle-induced inflammatory responses and th

As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrains early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in light-and heavy-duty application. Based on the power ratio between powertrains power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to the most efficient conditions, or by eliminating the engine operation from poorly efficient operating points to pure electric vehicle operation. A turning point is found to meet the requirement of the final state of energy of the battery, which is charge-sustaining mode in this study. The GRAB-ECO was tested with both light- and heavy-duty parallel hybrid electric vehicles, and validated in terms of the minimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumption with less than 6% of errors for both light-and heavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagins Minimum Principle) approaches.

As a promising solution to the reduction of fuel consumption and CO2 emissions in road transport sector, hybrid electric powertrains are confronted with complex control techniques for the evaluation of the minimal fuel consumption, particularly the excessively long computation time of the design-parameter optimization in the powertrains early design stage. In this work, a novel and simple GRaphical-Analysis-Based method of fuel Energy Consumption Optimization (GRAB-ECO) is developed to estimate the minimal fuel consumption for parallel hybrid electric powertrains in light-and heavy-duty application. Based on the power ratio between powertrains power demand and the most efficient engine power, GRAB-ECO maximizes the average operating efficiency of the internal combustion engine by shifting operating points to the most efficient conditions, or by eliminating the engine operation from poorly efficient operating points to pure electric vehicle operation. A turning point is found to meet the requirement of the final state of energy of the battery, which is charge-sustaining mode in this study. The GRAB-ECO was tested with both light- and heavy-duty parallel hybrid electric vehicles, and validated in terms of the minimal fuel consumption and the computation time. Results show that GRAB-ECO accurately approximates the minimal fuel consumption with less than 6% of errors for both light-and heavy-duty parallel hybrid electric powertrains. Meanwhile, GRAB-ECO reduces computation time by orders of magnitude compared with PMP-based (Pontryagins Minimum Principle) approaches.