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Solid polymer electrolytes are light-weight, flexible, and non-flammable and provide a feasible solution to the safety issues facing lithium-ion batteries through the replacement of organic liquid electrolytes. Substantial research efforts have been devoted to achieving the next generation of solid-state polymer lithium batteries. Herein, we provide a review of the development of solid polymer electrolytes and provide comprehensive insights into emerging developments. In particular, we discuss the different molecular structures of the solid polymer matrices, including polyether, polyester, polyacrylonitrile, and polysiloxane, and their interfacial compatibility with lithium, as well as the factors that govern the properties of the polymer electrolytes. The discussion aims to give perspective to allow the strategic design of state-of-the-art solid polymer electrolytes, and we hope it will provide clear guidance for the exploration of high-performance lithium batteries.

To assess the efficacy of probiotic Lactobacillus on serum lipids using a meta-analysis of randomized, controlled trials. Fifteen studies containing 15 trials, with 976 subjects were included. The pooled WMD was calculated by random effects model. Probiotic Lactobacillus consumption significantly reduced TC by 0.26mmol/l (95% CI, -0.40 to -0.12) and LDL-C by 0.23mmol/l (95% CI, -0.36 to -0.10). Subgroup analysis of trials found significantly reduction of TC using L. plantarum and reduction of LDL-C using L. plantarum or L. reuteri. No significant effects were found on TG and HDL-C levels after supplementation with probiotic Lactobacillus. While, subgroup analysis found significantly beneficial effects on TG and HDL-C by consuming synbiotic food, containing L. sporogenes and inulin. Consuming probiotic Lactobacillus, especially L. reuteri and L. plantarm, could reduce TC and LDL-C significantly. The study also suggested significantly beneficial effects on TG and HDL-C by consuming synbiotic food, containing L. sporogenes and inulin.

•BOLD and calcium signals were simultaneously measured in awake rats.•Robust couplings between calcium and BOLD signals were observed.•The efficacy of different rsfMRI data preprocessing pipelines was assessed basedon Ca2+ data. The blood oxygenation level-dependent (BOLD)-based resting-state functional magnetic resonance imaging (rsfMRI) has been widely used as a non-invasive tool to map brain-wide connectivity architecture. However, the neural basis underpinning the resting-state BOLD signal remains elusive. In this study, we combined simultaneous calcium-based fiber photometry with rsfMRI in awake animals to examine the relationship of the BOLD signal and spiking activity at the resting state. We observed robust couplings between calcium and BOLD signals in the dorsal hippocampus as well as other distributed areas in the default mode network (DMN), suggesting that the calcium measurement can reliably predict the rsfMRI signal. In addition, using the calcium signal recorded as the ground truth, we assessed the impacts of different rsfMRI data preprocessing pipelines on functional connectivity mapping. Overall, our results provide important evidence suggesting that spiking activity measured by the calcium signal plays a key role in the neural mechanism of resting-state BOLD signal.

The integration of digital and intelligent technologies has created new opportunities for the innovative growth of Specialized, Refined, Differential, and Innovative (SRDI) enterprises in China. This study examines SRDI enterprises listed on the Shanghai/Shenzhen A-share from 2014 to 2022. A three-stage Data Envelopment Analysis, incorporating a knowledge breadth framework, is employed to evaluate their innovation performance. Furthermore, an empirical analysis is conducted to assess the influence of digital intelligence on innovation outcomes. The results indicate that: (1) Digital intelligence, measured by datafication, digitization, and the adoption of intelligent technologies, significantly improves the innovation performance of SRDI enterprises, with intelligent technologies exerting the greatest effect; (2) Digital intelligence effectively mitigates financing constraints, allowing firms to allocate more resources to innovation; and (3) Heterogeneity analysis shows that the positive impact of digital intelligence is more pronounced among non-state-owned enterprises, manufacturing firms, and those located in Eastern China. These findings provides valuable guidance for policymakers seeking to develop targeted and differentiated strategies to enhance the innovation capacity of SRDI enterprises. In particular, the results underscore the role of digital intelligence in easing financing constraints. By accounting for firm-level heterogeneity, this study offers a robust theoretical and empirical foundation for policy design and delivers actionable recommendations for enterprises aiming to optimize resource allocation and strengthen innovation capabilities through digital transformation.

In human-robot collaboration, imitation learning and autonomous adaptation to new scenarios are pivotal concerns for robotic arms. To address these challenges, a novel framework ( DMP-PSO ) for trajectories planning in robotic arm is presented by integrating dynamical movement primitives ( DMP ) with particle swarm optimization ( PSO ) in this paper. Firstly, DMP is employed to learn and generalize motion trajectories. Secondly, the initial state and search region of PSO are enhanced based on the generalized trajectories to rapidly generate obstacle avoidance trajectories within the search region. Finally, the proposed DMP-PSO framework autonomously generates diverse trajectories for robotic arms encompassing obstacle avoidance paths through its ingenious design. The effectiveness of this framework is validated through various means. The numerical simulation results show that the trajectory planning based on DMP-PSO has good adaptability and strong consistency, and significantly improves the efficiency. Furthermore, virtual simulations along with physical experiments corroborate the exceptional robustness and practicality exhibited by the proposed framework.

[This corrects the article DOI: 10.1371/journal.pone.0339567.].

Lymphatic metastases are closely associated with tumor relapse and reduced survival in colorectal cancer (CRC). How tumor cells disseminate within the lymphatic network remains largely unknown. Here, we analyze the subclonal structure of 94 tumor samples, covering the primary tumors, lymph node metastases (LNMs), and liver metastases from 10 CRC patients. We portray a high-resolution lymphatic metastatic map for CRC by dividing LNMs into paracolic, intermediate, and central subgroups. Among the 61 metastatic routes identified, 38 (62.3%) are initiated from the primary tumors, 22 (36.1%) from LNMs, and 1 from liver metastasis (1.6%). In 5 patients, we find 6 LNMs that reseed 2 or more LNMs. We summarize 3 diverse modes of metastasis in CRC and show that skip spreading of tumor cells within the lymphatic network is common. Our study sheds light on the complicated metastatic pattern in CRC and has great clinical implications. Lymphatic metastases are closely associated with tumor relapse and reduced survival in colorectal cancer (CRC). Here, the authors analysed the primary tumours, lymph node metastasis and liver metastasis of ten CRC patients and reveal co-existence of diverse modes of metastasis in the same patient.

The slope of open-pit mines is typically characterized by an interaction structure involving multiple weak layers, with these structural characteristics serving as key factors in determining rock slope stability. Under the influence of random factors such as engineering activities and geological structures, the weak layers of the slope and the intact rock layers undergo relative changes. This interaction leads to a more pronounced spatial variability in the geotechnical parameters that inherently exist. Consequently, twenty generalized models of the rock slope, each with different structural characteristics were established by varying the slope angle, weak layer dip, and slope height. The Latin Hypercube Sampling (LHS) method was employed to efficiently generate parameters random fields. Utilizing mathematics software and FLAC3D, these random fields were assigned to the numerical model via an independent program. The variations in statistical characteristics of both the deformation and safety factor of the slope were obtained through the strength reduction method. The results indicate that, for both bedding and anti-dip slopes with stochastic geotechnical parameters, an increase in the slope angle results in a decrease in the safety factor, albeit to varying degrees. Additionally an increase in slope height leads to a reduction in the safety factor of the bedding slope. Reducing the slope angle is more effective than decreasing the slope height in improving stability. As the angle of the weak layers increases, the mean safety factor of the bedding rock slope decreases, while that of the anti-dip slope increases. The stability of the anti-dip slope is significantly greater than that of the bedding slope. The dip of the weak layer has a pronounced effect on the stability of the bedding slope; as the dip angle increases, the failure mode shifts from slip failure along the weak layer to slip-toppling failure. In contrast, the potential slip surface of the anti-dip slope typically manifests as an arc shape that intersects multiple weak layers. The sensitivity of the safety factor to structural characteristics follows the order of slope angle, weak layer dip, and slope height from most to least significant.

Background Long non-coding RNA PTENP1, the pseudogene of PTEN tumor suppressor, has been reported to exert its tumor suppressive function via modulation of PTEN expression in many malignancies, including breast cancer (BC). However, whether the PTENP1/miR-20a/PTEN axis exists and how it functions in BC progression remains elusive. Methods The levels of PTENP1, PTEN and miR-20a were measured by qRT-PCR. Furthermore, the breast cancer cells proliferation was further measured by CCK8 assay, colony formation assays, EDU and Ki67 staining. The migratory and invasive ability was determined by transwell assay. Flow cytometry, JC-1 and TUNEL assays were conducted to show the occurrence of apoptosis. Xenograft model was used to show the tumorigenesis of breast cancer cells. Results We analyzed PTENP1 and PTEN levels in clinical BC samples and cell lines, and found that PTENP1 and PTEN were confirmed and closely correlated with the malignancy of BC cell lines and poor clinical prognosis. Moreover, alteration of PTENP1 affects BC cell proliferation, invasion, tumorigenesis and chemoresistance to adriamycin (ADR). Bioinformatic analysis and dual-luciferase reporter gene assay predicted that PTENP1 was a direct target of miR-20a, which was clarified an alternative effect on BC aggressiveness phenotype. In addition, PTENP1 functioned as an endogenous sponge of miR-20a to regulate PTEN expression, which mediated BC cells proliferation, invasion and drug resistance via activation the phosphatidylinositol-3 kinase (PI3K)/AKT pathway. PI3K inhibitor LY294002 or siAkt also prevented BC cells progression. Conclusion Collectively, these data indicated that PTENP1/miR-20a/PTEN axis involved in the malignant behaviors of BC cells, illuminating the possible mechanism mediated by PTEN via PI3K/Akt pathway. Targeting PTENP1/miR-20a/PTEN may provide a potential diagnosis and treatment strategy for BC.

Full-depth reclamation with Portland cement (FDR-PC) is a pavement rehabilitation technology that has garnered significant attention and research interest due to its ability to fully utilize existing pavement materials in situ and address deep structural issues within the pavement. This paper evaluates the advantages of FDR-PC in terms of carbon emission compared to traditional asphalt pavement rehabilitation technologies. Firstly, under the same service life conditions, the structural configurations of asphalt pavements were designed using 3D-Move Analysis for three different technologies: removal and reconstruction, cold central plant recycling, and FDR-PC. Subsequently, carbon emission models were established based on the life cycle assessment (LCA) method and the construction processes, allowing for a comparison of carbon emissions and energy consumption among the three technologies. Finally, a sensitivity analysis was conducted to assess the impact of various factors on carbon emissions during the FDR-PC construction process. The results indicate that in terms of carbon emissions from the pavement base layer, FDR-PC accounts for 92% and 90% of those produced by removal and reconstruction and cold central plant recycling, respectively, while its energy consumption is 60% and 70% of the latter two technologies. Notably, during the transportation phase, FDR-PC demonstrates carbon emissions and energy consumption levels at merely 4% each compared to conventional removal and reconstruction, and 6% each relative to cold central plant recycling. The sensitivity analysis further reveals that the cement content is the most influential factor affecting the carbon emissions of FDR-PC.