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Janus particles (JPs), as a special material with anisotropic chemical or physical partitioning, show great potential for application in the fields of material science, biomedicine, energy, and environment. How to achieve fine structural control and large-scale synthesis of JPs is the key point and difficulty for JPs. Seeded emulsion polymerization, as a simple and efficient method, plays an important role in the controlled fabrication of JPs. Here, we provide a comprehensive review of the research progress in the preparation of JPs via seeded emulsion polymerization. We systematically summarize the process mechanisms and key parameters influencing the formation of Janus structures, with particular emphasis on the effects of seed characteristics, polymerization conditions, and component selection on particle morphology and anisotropy.

Designed ecology aims to proactively create sustainable ecosystems, yet quantifying the ecological effects of design parameters remains challenging due to the complexity of mathematical models and the high cost of long-term field observations. This study presents a scaled physical model system simulating nonpoint source pollution processes in sloping landscapes, enabling rapid and controlled analysis of key design parameters in designed ecology. The results indicate that (1) through 24 laboratory experiments (slope length 0.25–1 m), runoff pollutant concentrations consistently follow a power-law decay over time, with 17 groups achieving a goodness-of-fit above 0.90. (2) Orthogonal analysis identified slope material and soil thickness as the most influential factors, while slope length and width had limited effects. (3) Field validation in navel orange orchards (slope length 4–16 m) in the Three Gorges Reservoir area demonstrated that the physical model reliably reproduced the trends of runoff and pollutant loss observed in real slopes. These findings demonstrate that scaled physical models can effectively bridge laboratory and field studies, providing actionable guidance for parameter selection in landscape design, and supporting the implementation of nature-based solutions for water ecosystem restoration.

Background The Composite Dietary Antioxidant Index (CDAI) is a dietary antioxidant score that plays a protective role in many diseases, including depression, osteoporosis, papillomavirus infection, etc. However, the association between CDAI and coronary heart disease (CHD) is currently unclear. We aim to explore the correlations between CDAI and the risk of CHD. Methods Eligible participants were obtained from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018. All participants in this cross-sectional study are required to undergo two separate 24-h dietary recall interviews. Average daily intakes of dietary antioxidants were used to calculate CDAI. CHD status was determined through a questionnaire. Weighted multiple logistic regression models were used to evaluate the relationship between CDAI and CHD. Moreover, we also used restricted cubic spline to explore Non-linear correlations. Sensitivity analysis using unweighted logistic analysis and subgroup analysis were used to demonstrate the stability of the results. Results A total of 34,699 participants were eligible for analysis.Compared to the participants without CHD, the participants with CHD showed lower levels of CDAI. After adjusting confounding factors in the multivariate weighted logistic regression model, CDAI was inversely associated with CHD (Q4 vs. Q1, OR = 0.65 (0.51–0.82, P  < 0.001). Restricted cubic spline showed that there was a negative non-linear correlation (L-shaped) between CDAI and CHD, suggesting a potential saturation effect at higher CDAI levels, with the inflection point of 0.16. Sensitivity analysis showed that the results were stable. No significant statistically interaction was showed in subgroup analysis. Conclusions There was a negative non-linear correlation between CDAI and CHD in US adults. However, further prospective studies are still needed to reveal their relationship.

We analyzed large-scale post-translational modification (PTM) data to outline cell signaling pathways affected by tyrosine kinase inhibitors (TKIs) in ten lung cancer cell lines. Tyrosine phosphorylated, lysine ubiquitinated, and lysine acetylated proteins were concomitantly identified using sequential enrichment of post translational modification (SEPTM) proteomics. Machine learning was used to identify PTM clusters that represent functional modules that respond to TKIs. To model lung cancer signaling at the protein level, PTM clusters were used to create a co-cluster correlation network (CCCN) and select protein-protein interactions (PPIs) from a large network of curated PPIs to create a cluster-filtered network (CFN). Next, we constructed a Pathway Crosstalk Network (PCN) by connecting pathways from NCATS BioPlanet whose member proteins have PTMs that co-cluster. Interrogating the CCCN, CFN, and PCN individually and in combination yields insights into the response of lung cancer cells to TKIs. We highlight examples where cell signaling pathways involving EGFR and ALK exhibit crosstalk with BioPlanet pathways: Transmembrane transport of small molecules; and Glycolysis and gluconeogenesis. These data identify known and previously unappreciated connections between receptor tyrosine kinase (RTK) signal transduction and oncogenic metabolic reprogramming in lung cancer. Comparison to a CFN generated from a previous multi-PTM analysis of lung cancer cell lines reveals a common core of PPIs involving heat shock/chaperone proteins, metabolic enzymes, cytoskeletal components, and RNA-binding proteins. Elucidation of points of crosstalk among signaling pathways employing different PTMs reveals new potential drug targets and candidates for synergistic attack through combination drug therapy.

Agroforestry intercropping is increasingly recognized for improving soil quality and crop productivity, yet its effects on soil nutrient dynamics, enzyme activities across soil profiles, and tea yield remain insufficiently understood. Here, we assessed how four systems—monoculture tea (CK), Osmanthus–tea (OT), Michelia–tea (MT), and Osmanthus–Michelia–tea (OMT)—influence soil properties and spring tea yield in hilly plantations of southern China. Across systems, the OMT configuration produced the highest spring tea yield, representing a 39.5% increase relative to CK, accompanied by a 19.0% increase in tea bud density. In the 0–20 cm soil layer, OMT markedly enhanced soil organic matter by 48.4%, total nitrogen by 25.8%, and available nitrogen and phosphorus by 24.9% and significant margins, respectively, while also stimulating enzyme activities—urease (+34.1%), sucrase (+17.2%), dehydrogenase (+43.9%), amylase (+17.2%), and cellulase (+60.7%). In the 20–40 cm layer, OMT increased soil organic matter (+48.4%), total nitrogen (+25.8%), and available nitrogen, and elevated key enzyme activities, including sucrase (+46.5%), acid phosphatase (+16.3%), and polyphenol oxidase (+20.1%). Correlation and principal component analyses further revealed strong positive associations among nutrient enrichment, enzyme activation, and tea yield. These findings demonstrate that the OMT agroforestry configuration enhances nutrient availability and enzymatic function throughout the soil profile, thereby promoting higher tea yield. Overall, OMT substantially improved spring-season soil fertility and productivity, highlighting its potential for sustainable tea plantation management.

The remote sensing ecological index (RSEI) is an important tool for assessing ecosystem quality. However, its land surface temperature (LST) component poses challenges due to complex calculations and mismatched spatial resolution with other indicators. This study proposed an improved remote sensing ecological index (DRSEI). By replacing the LST component in RSEI with the difference index (DI) (representing PM 2.5 concentration), the new index better reflects air pollution’s impact on ecosystem quality. The results demonstrated that DRSEI outperformed the RSEI in assessing ecosystem quality in Chongqing’s urban area. It exhibited three advantages: stronger correlation with the ecological index (EI), standard deviation values closer to EI’s baseline, and lower root mean square error. The applicability of the DRSEI and RSEI varied across different regions: the DRSEI proved to be more suitable for highly urbanized areas, whereas the RSEI performed better in suburban regions. Further analysis revealed that the spatial variability of indicators influenced their loadings in principal component analysis, thereby affecting ecosystem quality assessment results. This study emphasizes the importance of considering the spatial distribution of indicators when constructing ecological indices. The findings suggest DRSEI could effectively assess ecosystem quality in urbanized areas. This approach provides new insights for urban ecological monitoring and environmental management.

Overcoming the immunosuppressive tumor microenvironment and identifying widely used immunosuppressants with minimal side effects are two major challenges currently hampering cancer immunotherapy. Regulatory T cells (Tregs) are present in almost all cancer tissues and play an important role in preserving autoimmune tolerance and tissue homeostasis. The tumor inflammatory microenvironment causes the reprogramming of Tregs, resulting in the conversion of Tregs to immunosuppressive phenotypes. This process ultimately facilitates tumor immune escape or tumor progression. However, current systemic Treg depletion therapies may lead to severe autoimmune toxicity. Therefore, it is crucial to understand the mechanism of Treg reprogramming and develop immunotherapies that selectively target Tregs within tumors. This article provides a comprehensive review of the potential mechanisms involved in Treg cell reprogramming and explores the application of Treg cell immunotherapy. The interference with reprogramming pathways has shown promise in reducing the number of tumor-associated Tregs or impairing their function during immunotherapy, thereby improving anti-tumor immune responses. Furthermore, a deeper understanding of the mechanisms that drive Treg cell reprogramming could reveal new molecular targets for future treatments.

BRAF plays an indispensable role in activating the MEK/ERK pathway to drive tumorigenesis. Receptor tyrosine kinase and RAS-mediated BRAF activation have been extensively characterized, however, it remains undefined how BRAF function is fine-tuned by stimuli other than growth factors. Here, we report that in response to proinflammatory cytokines, BRAF is subjected to lysine 27-linked poly-ubiquitination in melanoma cells by the ITCH ubiquitin E3 ligase. Lysine 27-linked ubiquitination of BRAF recruits PP2A to antagonize the S365 phosphorylation and disrupts the inhibitory interaction with 14–3–3, leading to sustained BRAF activation and subsequent elevation of the MEK/ERK signaling. Physiologically, proinflammatory cytokines activate ITCH to maintain BRAF activity and to promote proliferation and invasion of melanoma cells, whereas the ubiquitination-deficient BRAF mutant displays compromised kinase activity and reduced tumorigenicity. Collectively, our study reveals a pivotal role for ITCH-mediated BRAF ubiquitination in coordinating the signals between cytokines and the MAPK pathway activation in melanoma cells. BRAF drives MEK/ERK activation to facilitate tumorigenesis. Here, the authors show that in response to pro-inflammatory cytokines, ITCH mediates a non-proteolytic ubiquitination and activation of BRAF, which in turn sustains MEK/ERK signaling to facilitate melanoma cell growth.

Conventional AC voltage sensorless predictive current control methods for grid-tied inverter are often sensitive to current DC offset errors, resulting in worse control performance. To solve this problem, this paper proposed an improved grid voltage observer as well as a new lumped DC offset observation method. First, the drawbacks of the conventional grid voltage observer are reviewed. Then, based on the backstepping design approach, an improved grid voltage observer is designed, which can remove the influences of the current DC offsets. Third, the effects of the current DC offset on the current control is analyzed, and a new lumped DC offset observation method is designed, which can estimate and compensate the current DC offset well. Fourth, based on the two proposed observers, a new AC voltage sensorless predictive current control method is achieved with enhanced robustness against current DC offset. Finally, experimental studies are carried out, which verify the strong robustness against current DC offsets of the proposed method.

Short-term exposure to a forest environment is beneficial to human physiological and psychological health. However, there is little known about the relationship between the restorative perception of environment and physiological and psychological restoration achieved by experiencing the forest environment. This study evaluated the relationship between the restorative perception of different types of forests and human physiological and psychological effects. A sample of 30 young adult students from Beijing Forestry University was exposed to coniferous, deciduous, and mixed forests as well as an urban site. Restorative perception of the environment was measured using the PRS questionnaire. Restorative effects were measured using physiological indicators (blood pressure and heart rate) and three psychological questionnaires (Restorative Outcome Scale; Subjective Vitality Scale; Warwick–Edinburgh Mental Well-being Scale). The results demonstrated the following: (1) There were significant differences in the perceived restorative power of the three types of forests, with the highest level in the mixed forest, followed by the coniferous forest and the deciduous forest. (2) All types of forests were beneficial to physiological and psychological restoration. The mixed forest had the greatest effect in lowering blood pressure and heart rate as well as increasing vitality, while the coniferous forest had the strongest increases in psychological restoration and positive mental health. (3) The level of perceived restorative power of environment was positively related to the physiological and psychological restoration. These findings provide practical evidence for forest therapy that can maximize the restorative potential of forests.