Search Results (340)

Stress granule formation is a type of liquid–liquid phase separation in the cytoplasm, leading to RNA–protein condensates that are associated with various cellular stress responses and implicated in numerous pathologies, including cancer, neurodegeneration, inflammation, and cellular senescence. One of the key components of mammalian stress granules is the DEAD-box RNA helicase DDX3, which unwinds RNA in an ATP-dependent manner. DDX3 is involved in multiple steps of RNA metabolism, facilitating gene transcription, splicing, and nuclear export and regulating cytoplasmic translation. In this study, we investigate the role of the RNA helicase DDX3’s enzymatic activity in shaping the RNA content of ribonucleoprotein (RNP) condensates formed during arsenite-induced stress by inhibiting DDX3 activity with RK-33, a small molecule previously shown to be effective in cancer clinical studies. Using the human osteosarcoma U2OS cell line, we purified the RNP granule fraction and performed RNA sequencing to assess changes in the RNA pool. Our results reveal that RK-33 treatment alters the composition of non-coding RNAs within the RNP granule fraction. We observed a DDX3-dependent increase in circular RNA (circRNA) content and alterations in the granule-associated intronic RNAs, suggesting a novel role for DDX3 in regulating the cytoplasmic redistribution of non-coding RNAs. Full article

This study presents a hybrid sensor placement methodology that combines criterion-based candidate selection with advanced optimization algorithms. Four established selection criteria—modal kinetic energy (MKE), modal strain energy (MSE), modal assurance criterion (MAC) sensitivity, and mutual information (MI)—are used to evaluate DOF sensitivity and generate candidate pools. These are followed by one of four optimization algorithms—greedy, genetic algorithm (GA), particle swarm optimization (PSO), or simulated annealing (SA)—to identify the optimal subset of sensor locations. A key feature of the proposed approach is the incorporation of constraint dynamics using the Udwadia–Kalaba (U–K) generalized inverse formulation, which enables the accurate expansion of structural responses from sparse sensor data. The framework assumes a noise-free environment during the initial sensor design phase, but robustness is verified through extensive Monte Carlo simulations under multiple noise levels in a numerical experiment. This combined methodology offers an effective and flexible solution for data-driven sensor deployment in structural health monitoring. To clarify the rationale for using the Udwadia–Kalaba (U–K) generalized inverse, we note that unlike conventional pseudo-inverses, the U–K method incorporates physical constraints derived from partial mode shapes. This allows a more accurate and physically consistent reconstruction of unmeasured responses, particularly under sparse sensing. To clarify the benefit of using the U–K generalized inverse over conventional pseudo-inverses, we emphasize that the U–K method allows the incorporation of physical constraints derived from partial mode shapes directly into the reconstruction process. This leads to a constrained dynamic solution that not only reflects the known structural behavior but also improves numerical conditioning, particularly in underdetermined or ill-posed cases. Unlike conventional Moore–Penrose pseudo-inverses, which yield purely algebraic solutions without physical insight, the U–K formulation ensures that reconstructed responses adhere to dynamic compatibility, thereby reducing artifacts caused by sparse measurements or noise. Compared to unconstrained least-squares solutions, the U–K approach improves stability and interpretability in practical SHM scenarios. Full article

To determine optimal light conditions for Hopea hainanensis Merr. & Chun seedling growth, this study examined growth and physiological parameters under four shading treatments (0%, 30%, 60%, and 90% irradiance reduction) over 12 months. Shading significantly affected the growth adaptability of seedlings. As shading increased, height, leaf traits (area, length, width), and light saturation point all initially increased, peaked at 30% shading, and then decreased. Conversely, basal diameter, leaf thickness, the maximum net photosynthetic rate, net photosynthetic rate, photosynthetic quantum efficiency, transpiration rate, and stomatal conductance progressively declined as shading increased. Biomass accumulation (in stems and roots), dark respiration rate, and light compensation point exhibited a U-shaped response to shading, being minimized under low or moderate shading. All shading treatments significantly reduced biomass and photosynthetic performance compared to controls. Multivariate analysis identified 0%–30% shading as optimal for cultivation, with 30% shading enhancing photomorphogenic responses while maintaining photosynthetic efficiency. The study findings suggest a novel seedling cultivation protocol for nursery use, in which initial establishment occurs under 30% shading to maximize vertical elongation, followed by the progressive reduction in shading to stimulate radial growth and optimal biomass partitioning. This approach mimics natural canopy gap dynamics, effectively mimicking natural regeneration in tropical rainforest ecosystems. Full article

Alkalihalophilus marmarensis is an obligate alkaliphile with exceptional tolerance to high-pH environments, making it a promising candidate for industrial bioprocesses that require contamination-resistant and extremophilic production platforms. However, its practical deployment is hindered by limited biomass formation under extreme conditions, which constrains overall productivity. This study presents a model-driven investigation of how pH (8.8 and 10.5), culture duration (24 and 48 h), and nitrogen source composition (peptone and meat extract) affect cell dry mass, lactate, and protease synthesis. Using the response surface methodology and multi-objective optimization, we established predictive models (R² up to 0.92) and uncovered key trade-offs in biomass and metabolite yields. Our findings reveal that peptone concentration critically shapes the metabolic output, with low levels inhibiting growth and high levels suppressing protease activity. Maximum cell dry mass (4.5 g/L), lactate (19.3 g/L), and protease activity (43.5 U/mL) were achieved under distinct conditions, highlighting the potential for targeted process tuning. While the model validation confirmed predictions for lactate, deviations in cell dry mass and protease outputs underscore the complexity of growth–product interdependencies under nutrient-limited regimes. This work delivers a foundational framework for developing fermentations with A. marmarensis and advancing its application in sustainable, high-pH industrial bioprocesses. The insights gained here can be further leveraged through synthetic biology and bioprocess engineering to fully exploit the metabolic potential of obligate alkaliphiles like A. marmarensis. Full article

Despite a general decline in smoking rates among the U.S. population, smoking among low-income populations remains disproportionately high, likely due to the social determinants of health. To inform tailored approaches and responsive public health policies, the aim of this study was to qualitatively explore the sociocultural contexts, attitudes, and behaviors regarding smoking and quitting in a sample of low-income adults who smoke. In-depth, semi-structured qualitative interviews were conducted with 20 adults. Participants were recruited through local safety-net primary care clinics and community sites. A thematic analytic approach was utilized to analyze transcribed interviews. In exploring smoking and quitting within the context of low-income individuals, the following six themes were identified: caught between health and tobacco use; the nuances of context; roadblocks to quitting; motivation without movement; a temporary escape; and one size does not fit all. Insights into sociocultural and environmental contexts that shape smoking and quitting among low-income individuals revealed a complex interplay of factors that perpetuate smoking behavior and make it difficult to achieve sustained cessation. The study findings point to the importance of patient-centered and collaborative approaches that tailor smoking cessation efforts to the unique needs and lived experiences of low-income people who smoke. Full article

In this paper, a novel type of polarization-insensitive terahertz metal metasurface with cross-shaped holes is presented, which is designed based on the theory of bound states in continuous media. The fundamental unit of the metasurface comprises a metal tungsten sheet with a cross-shaped hole structure. A thorough analysis of the optical properties and the quasi-BIC response is conducted using the finite element method. Utilizing the symmetry-breaking theory, the symmetry of the metal metasurface is broken, allowing the excitation of double quasi-BIC resonance modes with a high quality factor and high sensitivity to be achieved. Analysis of the multipole power distribution diagram and the spatial distribution of the electric field at the two quasi-BIC resonances verifies that the two quasi-BIC resonances of the metasurface are excited by electric dipoles and electric quadrupoles, respectively. Further simulation analysis demonstrates that the refractive index sensitivities of the two quasi-BIC modes of the metasurface reach $404.5 \mathrm{G}\mathrm{H}\mathrm{z}/\mathrm{R}\mathrm{I}\mathrm{U}$ and $578.6 \mathrm{G}\mathrm{H}\mathrm{z}/\mathrm{R}\mathrm{I}\mathrm{U}$, respectively. Finally, the functional material PHMB is introduced into the metasurface to achieve highly sensitive sensing and detection of CO₂ gas concentrations. The proposed metallic metasurface structure exhibits significant advantages, including high sensitivity, ease of preparation, and a high Q-value, which renders it highly promising for a broad range of applications in the domains of terahertz biosensing and highly sensitive gas sensing. Full article

Toxicological studies of pesticides in animal models provide critical insights into their mechanisms of action, while adsorption strategies offer potential solutions for decontaminating polluted waters. We evaluated toxicity induced by tetraethyl pyrophosphate (TEPP), an organophosphate pesticide and AChE inhibitor, on zebrafish (Danio rerio) development and behavior, alongside the efficacy of wine cork granules as a natural adsorbent. TEPP exposure reduced embryo viability following an inverted U-shaped dose–response curve, suggesting non-monotonic neurodevelopmental effects, but did not alter developmental timing or morphology in survivors. In juveniles, TEPP increased preference for dark environments (33% vs. controls) and enhanced swimming endurance approximately 3-fold, indicating disrupted phototaxis and stress responses. Most strikingly, water treated with cork granules retained toxicity, increasing mortality, delaying embryogenesis, and altering behavior. This directly contradicts in vitro adsorption studies that suggested cork’s efficacy. These results demonstrate the high sensitivity of zebrafish to TEPP at nanomolar concentrations, which contrasts with in vitro models that require doses approximately 1000 times higher. Our findings not only highlight TEPP’s ecological risks but also reveal unexpected limitations of cork granules for environmental remediation, urging caution in their application. Full article

Given the serious economic burden that citrus diseases impose on fruit farmers and related industries, achieving rapid and accurate disease detection is particularly crucial. In response to the challenges posed by resource-limited platforms and complex backgrounds, this paper designs and proposes a lightweight method for the identification and localization of citrus diseases based on the RT-DETR-r18 model—GYS-RT-DETR. This paper proposes an optimization method for target detection that significantly enhances model performance through multi-dimensional technology integration. First, this paper introduces the following innovations in model structure: (1) A Gather-and-Distribute Mechanism is introduced in the Neck section, which effectively enhances the model’s ability to detect medium to large targets through global feature fusion and high-level information injection.(2) Scale Sequence Feature Fusion (SSFF) is used to optimize the Neck structure to improve the detection performance of the model for small targets in complex environments. (3) The Focaler-ShapeIoU loss function is used to solve the problems of unbalanced training samples and inaccurate positioning. Secondly, the model adopts two model optimization strategies: (1) The Group_taylor local pruning algorithm is used to reduce memory occupation and the number of computing parameters of the model. (2) The feature-logic knowledge distillation framework is proposed and adopted to solve the problem of information loss caused by the structural difference between teachers and students, and to ensure a good detection performance, while realizing the lightweight character of the model. The experimental results show that the GYS-RT-DETR model has a precision of 79.1%, a recall of 77.9%, an F1 score of 78.0%, a model size of 23.0 MB, and an mAP value of 77.8%. Compared to the original model, the precision, recall, the F1 score, the mAP value, and the FPS value have improved by 3.5%, 5.3%, 5.0%, 5.3%, and 10.3 f/s, respectively. Additionally, the memory usage of the GYS-RT-DETR model has decreased by 25.5 MB compared to the original model. The GYS-RT-DETR model proposed in this article can effectively detect various citrus diseases in complex backgrounds, addressing the time-consuming nature of manual detection and improving the accuracy of model detection, thereby providing an effective theoretical basis for the automated detection of citrus diseases. Full article

This paper revisits the international finance trilemma by analyzing how different monetary policy objectives and exchange rate regimes shape the transmission of global risk shocks. Using a structural vector autoregressive model with exogenous variables (SVARX), we examine the monetary policy responses and exchange rate fluctuations of ASEAN+4 economies—China, Japan, Korea, and Hong Kong—to external shocks including U.S. monetary policy changes, oil price fluctuations, global policy uncertainty, and financial risk during 2010–2022. Economies are grouped according to their trilemma configurations: floating exchange rates with free capital flows, fixed exchange rates, and capital control regimes. Our findings broadly support the trilemma hypothesis: fixed-rate economies align with U.S. interest rate movements, capital control economies retain greater monetary autonomy, and open, floating regimes show partial responsiveness. More importantly, monetary responses vary by global shock type: U.S. monetary policy drives the most synchronized policy reactions, while oil price and uncertainty shocks produce more heterogeneous outcomes. Robustness checks include alternative model specifications, where global shocks are treated as endogenous, and extensions, such as using Japan’s monetary base as a proxy for unconventional monetary policy. These results refine the empirical understanding of the trilemma by showing that its dynamics depend not only on institutional arrangements but also on the nature of global shocks—underscoring the need for more tailored and, where possible, regionally coordinated monetary policy strategies. Full article

Sjögren’s disease (SjD) is an autoimmune disease of exocrine tissues. Prior research has shown that ETS proto-oncogene 1 (ETS1), STAT1, and IL33 may contribute to the disease’s pathology. However, the regulatory mechanisms of these genes remain poorly characterized. Our objective was to explore the mechanisms of SjD pathology and to identify dysfunctional regulators of these genes by immunostimulation of SjD and sicca relevant cell lines. We used immortalized salivary gland epithelial cell lines (iSGECs) from Sjögren’s disease (pSS1) and sicca (nSS2) patients, previously developed in our lab, and control cell line A253 to dose with immunostimulants IFN-γ or poly(I:C) (0 to 1000 ng/mL and 0 to 1000 µg/mL, respectively) over a 72 h time course. Gene expression was determined using qRT-PCR delta-delta-CT method based on glyceraldehyde-3-phosphate dehydrogenase (GAPDH) for mRNA and U6 small nuclear RNA 1 (U6) for miRNA, using normalized relative fold changes 48 h post-immunostimulation. Protein expression was quantified 72 h post-stimulation by Western blotting. Reference-based RNA-seq of immunostimulated pSS1 and nSS2 cells was performed to characterize the reactome of genes conserved across all used doses. The expression of ETS1 and STAT1 protein was upregulated (p < 0.05) in IFN-γ-treated pSS1 and nSS2, as compared to A253 cells. IFN-γ-treated nSS2 cell showed significant IL33 upregulation. Also, IL33 had a correlated (p < 0.01) U-shaped response for low-mid-range doses for IFN-γ- and poly(I:C)-treated pSS1 cells. RNA-seq showed 175 conserved differentially expressed (DE) genes between nSS2 and pSS1 immunostimulated cells. Of these, 44 were shown to interact and 39 were more abundant (p < 0.05) in pSS1 cells. Western blotting demonstrated nSS2 cells expressing ETS1 uniformly across treatments compared to pSS1 cells, despite similar mRNA abundance. miR-145b and miR-193b were significantly under-expressed in IFN-γ-treated nSS2 cells compared to pSS1 cells (p < 0.01). ETS1 and IL33 showed disproportionate mRNA and protein abundances between immunostimulated Sjögren’s disease-derived (pSS1), and sicca-derived (nSS2) cell lines. Such differences could be explained by higher levels of miR-145b and miR-193b present in pSS1 cells. Also, RNA-seq results suggested an increased sensitivity of pSS1 cells to immunostimulation. These results reflect current pathobiology aspects, confirming the relevance of immortalized salivary gland epithelial cell lines. Full article

This study systematically investigated two ecotypes of Ulva prolifera, the dominant species responsible for green tides in the Yellow Sea, classified as Subtype I (strain I08-1) and Subtype II (strain QD-7). Both subtypes produce positively phototactic biflagellate gametes with oval/pear-shaped morphology but exhibit distinct cellular dimensions. Subtype I gametes demonstrated significantly larger cell sizes, with long and short axes measuring 6.55 μm and 4.62 μm, respectively, compared to Subtype II’s dimensions of 6.46 μm (long axis) and 3.03 μm (short axis). Developmental analysis revealed striking morphological divergence at the 6-day germling stage: Subtype I attained an average length of 1301.14 μm, more than doubling Subtype II’s 562.25 μm. Superior growth kinetics were observed in Subtype I, exhibiting enhanced specific growth rates (SGRs) across multiple parameters—main stem length (8.58% vs. 3.55%), primary branch elongation (19.17% vs. 12.59%), main stem width expansion (17.29% vs. 5.00%), and biomass accumulation (41.90% vs. 40.96% fresh weight). Chlorophyll quantification confirmed significantly higher pigment content in Subtype I. Pre-co-culture photosynthetic profiling demonstrated Subtype I’s superior quantum efficiency (α = 0.077 vs. 0.045) with marked differences in regulated energy dissipation (YNPQ) and non-photochemical quenching (NPQ). Post-co-culture physiological adaptation was evident in Subtype II, showing significant elevation of non-regulated energy dissipation quantum yield (YNO) and eventual surpassing of maximum electron transport rate (ETRmax) compared to Subtype I. These findings establish that U. prolifera employs robust photoprotective and thermal adaptation strategies under natural photothermal conditions. Crucially, YNO-based analysis revealed Subtype II’s enhanced high-light protection mechanisms and superior adaptability to intense irradiance environments. This research elucidates ecotype-specific environmental adaptation mechanisms in U. prolifera, providing critical insights for optimizing green tide mitigation strategies and advancing ecological understanding of algal bloom dynamics. Full article

Background: Obstructive sleep apnea (OSA) and abnormal sleep duration are known risk factors for hypertension. However, evidence regarding their combined effect on hypertension is limited and inconsistent. This study aimed to examine the independent and interactive associations of OSA risk and sleep duration with hypertension in Korean adults. Methods: We analyzed data from 14,579 adults aged ≥40 years who participated in the 2019–2022 Korea National Health and Nutrition Examination Survey. OSA risk was assessed using the STOP-Bang questionnaire and classified as low (0–2), moderate (3–4), or high (5–8). Sleep duration was self-reported and categorized as <6, 6–<7, 7–<8, 8–<9, and ≥9 h. Hypertension was defined based on measured blood pressure and antihypertensive medication use. Multivariate logistic regression was conducted to evaluate the associations. Results: A dose–response association was observed between OSA risk and hypertension prevalence: adjusted ORs (95 CIs) were 9.69 (8.37–11.23) for moderate and 36.58 (29.35–45.59) for high OSA risk. Sleep duration alone was not significantly associated with hypertension. However, interaction models showed a U-shaped relationship, with the lowest hypertension prevalence in those sleeping 7–<8 h. Among participants with high OSA risk, both short (<7 h) and long (≥9 h) sleep durations were associated with significantly higher hypertension risk (OR 48.49, 95% CI 19.68–119.50 for ≥9 h). Conclusions: OSA risk and sleep duration jointly affect hypertension risk. Individuals with high OSA risk who are short or long sleepers may require targeted interventions to improve blood pressure control. Full article

Per- and polyfluoroalkyl substances (PFASs) are ubiquitous environmental contaminants with potential endocrine-disrupting properties. This study examines the association between exposure to multiple PFASs and pan-cancers associated with sex hormones (PCSH) while accounting for potential non-linear relationships and interactions. We analyzed data from the National Health and Nutrition Examination Survey (NHANES), spanning two-year cycles from 1999 to 2012 and including 14,373 participants. Serum concentrations of six PFAS—perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonic acid (PFHxS), perfluorodecanoic acid (PFDE), perfluorononanoic acid (PFNA), and perfluoroundecanoic acid (PFUA)—were assessed for their relationship with PCSH. The statistical analyses included descriptive statistics, Spearman and Pearson correlation analyses, and both linear and logistic regression models. Additionally, Bayesian kernel machine regression (BKMR) was applied to capture potential nonlinear relationships and interactions. The initial t-tests showed a statistically significant difference in PFOS levels between individuals with and without PCSH (p = 0.0022), with higher mean PFOS levels in the PCSH group. Chi-square tests revealed a significant association between ethnicity and PCSH (p < 0.001). Linear and logistic regression analyses revealed significant associations for PFOS. BKMR analysis identified PFOA as having the highest posterior inclusion probability, indicating its importance in explaining PCSH risk. Univariate exposure-response analysis revealed limited individual PFAS effects. However, bivariate analysis indicated a complex U-shaped interaction pattern among many joint PFAS assessments. The overall exposure effect analysis suggested that the combined impact of all PFASs was more strongly associated with PCSH at exposure levels below the 0.5 quantile compared to higher levels. Single-variable interaction analyses highlighted PFOA and PFOS as the most interactive PFASs when evaluating their interaction with combined exposure to all other PFASs. In summary, while the initial findings suggested a positive association between PFOS and PCSH, the BKMR analysis revealed complex non-linear relationships and interactions among PFAS. These findings highlight the importance of evaluating PFASs as a mixture rather than as individual chemicals and using techniques that can capture non-linear relationships and interactions. Full article

In response to the growing demand for improved operational efficiency in road and bridge networks, constructing parallel bridges in complex river sections has become a crucial strategy. This study focuses on a parallel bridge construction project in the Jinan section of the lower Yellow River, conducting physical model tests to investigate the unique aspects of the impacts of different pier shapes and spans on the flow characteristics of sediment-laden rivers under real-world engineering scenarios. The experimental results demonstrate that the hydraulic physical model of this river section that was constructed is reliable, with a relative error of <20% in sediment deposition, in the simulation of sediment erosion and deposition, flow velocity patterns, water levels, and riverbed morphological changes during parallel bridge construction in bridge-clustered river sections. The newly constructed bridges have a limited influence on the overall regime of this river section, with their impacts on both banks remaining within controllable limits, and the river flow remains largely stable. In areas with denser pier arrangements, the phenomenon of backwater upstream of the bridges is more pronounced, and under characteristic flood conditions, the newly built bridges amplify the water level differences between the upstream and downstream sections near the bridge sites. The ranges of influence of the water level drop downstream of the bridges increase, particularly in the main flow areas. Flow velocities generally increase in the main channel, while significant fluctuations are observed in the floodplain areas. Flood process experiments reveal that the slope at the junction between the main channel and the floodplain becomes gentler, with noticeable scouring occurring in the main channel. After flood events, the river tends to evolve toward a U-shaped channel, posing certain safety risks to the piers located at the junction of the floodplains and the main channel. This research methodology can serve as a reference for studying flow characteristics in similar parallel bridge construction projects in river sections, and the findings hold significant implications for practical engineering. Full article

While small group learning through engineering design activities has been shown to enhance student achievement, motivation, and problem-solving skills, much of the existing research in this area focuses on undergraduate engineering education. Therefore, this study examines how small-group interactions influence design decisions within a sixth-grade engineering design-based English Language Arts unit for multilingual learners. Multilingual Learners make up 21% of the U.S. school-aged population and benefit from early STEM opportunities that shape future educational and career trajectories. Grounded in constructivist learning theories, the research explores collaborative learning in the engineering design process, using a comparative case study design. Specifically, this study explores student interactions and group dynamics in two small groups (Group A and Group B) engaged in a board game design challenge incorporating microelectronics. Video recordings serve as the primary data source, allowing for an in-depth analysis of verbal and nonverbal interactions. The study employed the Social Interdependence Theory to examine how group members collaborate, negotiate roles, and make design decisions. Themes such as positive interdependence, group accountability, promotive interaction, and individual responsibility are used to assess how cooperation influences final design choices. Three key themes emerged: Roles and Dynamics, Conflict, and Teacher Intervention. Group A and Group B exhibited distinct collaboration patterns, with Group A demonstrating stronger leadership dynamics that shaped decision-making, while Group B encountered challenges related to engagement and resource control. The results demonstrate the importance of small-group interactions in shaping design decisions and emphasize the role of group dynamics and teacher intervention in supporting multilingual learners’ engagement and success in integrated STEM curriculum. Full article