Search Results (154,301)

The intestine–liver–muscle axis plays an essential role in drug and nutrient absorption, metabolism, and energy balance. Yet in vitro models capable of recapitulating this inter-organ communication remain limited. Here, we present a pump-free, 3D-printed multi-organ-on-a-chip device that enables dynamic co-culture of Caco-2 intestinal epithelial cells, HepG2 hepatocytes, and primary human skeletal myoblasts (HSkMs) under gravity-driven oscillatory flow. The device consists of five interconnected chambers designed to accommodate Transwell cell culture inserts for intestine and muscle compartments and hydrogel-embedded hepatocyte spheroids in the central hepatic compartment. The device was fabricated by low-cost fused deposition modeling (FDM) using acrylonitrile butadiene styrene (ABS) polymers. Under dynamic rocking, oscillatory perfusion promoted inter-organ communication without the need for external pumps or complex tubing. Biological assessments revealed that dynamic co-culture significantly enhanced the characteristics of skeletal muscle, as indicated by increased myosin heavy chain expression and elevated lactate production, while HepG2 spheroids exhibited improved hepatic function with higher albumin expression compared with monoculture. Additionally, Caco-2 cells maintained stable tight junctions and transepithelial electrical resistance, demonstrating preserved intestinal barrier integrity under dynamic flow. These results establish the device as a versatile, accessible 3D-printed platform for modeling the intestine–liver–muscle axis and investigating metabolic cross-talk in drug discovery and disease modeling. Full article

The K-means clustering algorithm is widely applied in various clustering tasks due to its high computational efficiency and simple implementation. However, its performance significantly deteriorates when dealing with non-convex structures, fuzzy boundaries, or noisy data, as it relies on the assumption that clusters are spherical or linearly separable. To address these limitations, this paper proposes a Gaussian membership-driven fuzzy granular K-means clustering method. In this approach, multi-function Gaussian membership functions are used for fuzzy granulation at the single-feature level to generate fuzzy granules, while fuzzy granule vectors are constructed in the multi-feature space. A novel distance metric for fuzzy granules is defined along with operational rules, for which axiomatic proof is provided. This Gaussian-based granulation enables effective modeling of nonlinear separability in complex data structures, leading to the development of a new fuzzy granular K-means clustering framework. Experimental results on multiple public UCI datasets demonstrate that the proposed method significantly outperforms traditional K-means and other baseline methods in clustering tasks involving complex geometric data (e.g., circular and spiral structures), showing improved robustness and adaptability. This offers an effective solution for clustering data with intricate distributions. Full article

Background: Digital transformation in healthcare has advanced rapidly in hospitals and primary care, while long-term care facilities have often lagged behind. In nursing homes, nurses play a central role in coordinating care and accessing medical expertise, yet digital tools to support these tasks remain inconsistently implemented. The CareConnect study, funded under the German Model Program for Telecare (§ 125a SGB XI), aimed to develop and implement a multiprofessional telecare system tailored to nursing home care. Objective: This implementation study examined the feasibility, acceptability, and early adoption of a multiprofessional telecare system in nursing homes, focusing on implementation processes, contextual influences, and facilitators and barriers to integration into routine nursing workflows. Methods: A participatory implementation design was employed over 15 months (June 2024–August 2025), involving a university hospital, two nursing homes (NHs), and four medical practices in an urban region in Germany. The telecare intervention consisted of scheduled video-based teleconsultations and interdisciplinary case discussions supported by diagnostic devices (e.g., otoscopes, dermatoscopes, ECGs). The implementation strategy followed the Standards for Reporting Implementation Studies (StaRI) and was informed by the Consolidated Framework for Implementation Research (CFIR). Data sources included telecare documentation, nurse surveys, researcher observations, and structured feedback discussions. Quantitative and qualitative data were analyzed descriptively and triangulated to assess implementation outcomes and mechanisms. Results: A total of 152 documented telecare contacts were conducted with 69 participating residents. Most interactions occurred with general practitioners (48.7%) and dermatologists (23%). Across all contacts, in 79% of cases, there was no need for an in-person visit or transportation. Physicians rated most cases as suitable for digital management, as indicated by a mean of 4.09 (SD = 1.00) on a 5-point Likert scale. Nurses reported improved communication, time savings, and enhanced technical and diagnostic skills. Key challenges included delayed technical integration, interoperability issues, and varying interpretations of data protection requirements across facilities. Conclusions: This pilot study suggests that telecare can be feasibly introduced and accepted in nursing home settings when implemented through context-sensitive, participatory strategies. Implementation science approaches are essential for understanding how telecare can be sustainably embedded into routine nursing home practice. Full article

Man-made floods from dams are intentional for different purposes, e.g., spreading sediment and helping deltaic development. Less is known about their effects on slack-water deposits (SWDs) in downstream channels. Since the implementation of the Water and Sediment Regulation Project (WSRP) through a large dam on China’s Yellow River (YR) in 2002, the dynamic sedimentary environment of the river has undergone significant changes. To understand the sedimentary responses of the downstream channels to the man-made floods, this study was conducted following a 24-day man-made flood period in 2021 to investigate SWDs on the floodplains. Sediment samples were collected from four floodplain sites in the lowermost reach of the YR. The study showed that the median grain size (D₅₀) of the man-made flood SWDs on the floodplains ranges from 17 to 131 μm, with an average of 44.14 μm, classifying them as fine-grained deposits. Spatially, D₅₀ of 57.2% of the sampled SWDs exhibited an increasing trend from the riverbank to the main channel. This finding indicates that during the deposition process of floodplain floods, differences may exist in the direction perpendicular to the riverbank. Along the upstream-to-downstream direction, no obvious regularity was observed. Moreover, there is no positive correlation between sediment discharge and the average grain size of suspended sediment. These findings indicate that large man-made floods by a dam will not allow finer particles to settle. Such changes in sediment transport may have a long-term effect on Yellow River deltaic development and stability. Full article

Photocatalytic degradation of tetracycline (TC) is considered a viable technology due to its stable molecular structure and resistance to absorption by biological organisms. As a promising photocatalyst, TiO₂ suffers from a wide bandgap and rapid charge recombination rates. In this work, the S-scheme heterojunctions of g-C₃N₄/TiO₂ (CNTOx, x = 10, 30, and 70) were synthesized via solvothermal, calcination, and impregnation methods. Furthermore, carbon quantum dots (CQDs) were incorporated into the CNTO30 samples, resulting in yCQDs-CNTO30 (y = 0.5, 1, and 3). The 1CQDs-CNTO30 demonstrat an impressive TC degradation efficiency of 76.7% in 60 min under visible light, which is higher than that of CNTO30 (59.8%). This enhanced efficiency is ascribed to the effective charge separation induced by the dual-effect of S-scheme heterojunction and the CQDs. The built-in electric field within the heterojunction drives the separation of electrons and holes. Meanwhile, the highly conductive CQDs accelerate the electron transport, thereby promoting the charge separation. Additionally, the CQDs improve the ability of absorption light. This research provides critical insights into the strategic development of efficient ternary photocatalytic S-scheme heterojunctions for environmental remediation. Full article

This study investigates the geological, mineralogical, and geochemical features of the Alday ore occurrence (Central Kalba, East Kazakhstan) and aims to identify indicators of rare-metal mineralization, with lithium considered to be one of its principal components. In this study, the structural–stratigraphic position of the occurrence is refined; three series of albite–spodumene pegmatites are identified; the compositions of the ore-bearing schists and the granitoids of the Kunush and Kalba complexes are compared; and the role of metasomatic alteration in the concentration of Li, Ta, Nb, Be, and Sn is established. The plagiogranites and dikes of the Kunush complex are characterized by Li anomalies (up to 306 g/t), Ta (up to 64 g/t), and a fractionated REE spectrum (La/Yb up to 108). In addition, the following predictive criteria are formulated: the presence of tectonically disrupted dikes in the Kunush complex with Na₂O/K₂O > 4, the presence of albite and muscovite alteration zones, and the presence of ladder-type spodumene-bearing pegmatites controlled by northwest-trending faults. The ⁴⁰Ar/³⁹Ar muscovite age of the Alday pegmatites (~292 Ma) aligns with the age range of the Kalba granite complex. Based on the main principles of rare-metal pegmatite generation, it is determined that the Tochka pegmatites were formed during the fluid–magmatic fractionation of magma in large granitic reservoirs of the Kalba complex. The Karagoin–Saryozek zone—located between several large granite massifs of the Kalba complex, where host rocks function as a roof—may be promising for investigating rare-metal pegmatite mineralization. Full article

Background: Nutritional interventions to mitigate age/disease-related skeletal muscle attrition are much needed given the growing older population. Beta-hydroxy beta-methylbutyrate (HMB), an endogenous metabolite of the essential amino acid leucine, has anabolic properties in skeletal muscle: acutely stimulating muscle protein synthesis and attenuating muscle protein breakdown. While the role of supplemental HMB on muscle protein turnover is established, mechanistic effects on the muscle transcriptome have not been examined. Methods: Total RNA was extracted from m. vastus lateralis muscle biopsies of young males (n = 14) before and ~2.5 h after oral consumption of ~3 g HMB. Global changes in the muscle transcriptome were assessed via RNA sequencing, and differential expression in genes between fasted and ‘fed’ (HMB) conditions was determined. To identify the functional biology of differentially expressed genes, gene set enrichment and active subnetwork-orientated enrichment analyses was performed. Results: Of 15,982 genes detected, 468 were significantly upregulated and 326 were significantly downregulated in response to HMB. These genes were found to be associated with molecular pathways regulating muscle protein turnover, most notably, JAK-STAT signalling (e.g., STAM), circadian rhythm (e.g., NR1D1, NR1D2, PER2, PER3), TNFα signalling (e.g., TNFRSF1A, CCL2, CXCL2), and protein synthesis (e.g., POLR1A, POLR2A, POLR3A, PIK3RR, SGK1). HMB also regulated the expression of AA transporters, evoking a robust increase in SLC36A1 (PAT1) and SLC7A5 (LAT1). Conclusions: HMB evokes transcriptional events important in the homeostasis of muscle, supporting a role in proteostasis and one akin to protein intake, i.e., upregulation of AA transporters. Future work should further define HMB’s transcriptomic/proteomic effects in ageing/disease and synergy with exercise. Full article

The catalytic hydrogenation of carbon dioxide (CO₂) represents a transformative approach for reducing greenhouse gas emissions while producing sustainable fuels and chemicals, with ethanol being particularly promising due to its compatibility with existing energy infrastructure. Despite significant progress in converting CO₂ to C₁ products (e.g., methane, methanol), selective synthesis of C₂₊ compounds like ethanol remains challenging because of competing reaction pathways and byproduct formation. Recent advances in thermo-catalytic CO₂ hydrogenation have explored diverse catalyst systems including noble metals (Rh, Pd, Au, Ir, Pt) and non-noble metals (Co, Cu, Fe), supported on zeolites, metal oxides, perovskites, silica, metal–organic frameworks, and carbon-based materials. These studies reveal that catalytic performance hinges on the synergistic effects of multimetallic sites, tailored support properties and controlled reaction micro-environments to optimize CO₂ activation, controlled hydrogenation and C−C coupling. Mechanistic insights highlight the critical balance between CO₂ reduction steps and selective C−C bond formation, supported by thermodynamic analysis, advanced characterization techniques and theoretical calculations. However, challenges persist, such as low ethanol yields and undesired byproducts, necessitating innovative catalyst designs and optimized reactor configurations. Future efforts must integrate computational modeling, in situ/operando studies, and renewable hydrogen sources to advance scalable and economically viable processes. This review consolidates key findings, proposes potential reaction mechanisms, and outlines strategies for designing high-efficiency catalysts, ultimately providing reference for industrial application of CO₂-to-ethanol technologies. Full article

Accurate indoor localization in 5G remains challenging due to multipath propagation, signal blockage, and limited bandwidth in frequency range 1 (FR1). This study evaluates attention-based recurrent neural networks for two-dimensional user equipment (UE) localization using only positioning reference signal (PRS) magnitude data. We compare five models on the xG-Loc dataset (InF-DH scenario at 3.5 GHz, 5 MHz bandwidth): a simple GRU (M1), a deeper GRU with dropout (M2), a GRU optimized via Optuna (M3), a stacked GRU with multi-head attention (M4), and a bidirectional GRU with attention (M5). Model performance is quantified using the area above the cumulative distribution function (CDF) curve (AAC) metric, where lower values indicate better localization accuracy. Attention-based models significantly outperform baselines, and M4 achieves the lowest AAC of 6.71 (17% reduction versus M1’s 8.09), while M5 attains an AAC of 6.90. Statistical analysis confirms that M4 and M5 significantly outperform M3 (ANOVA, p < 0.000001). Optimal performance emerges with moderate numbers of time steps (TS ≈ 500 to 2500), with performance plateauing and degrading at higher values. These findings demonstrate that attention mechanisms substantially enhance 5G indoor localization accuracy using only PRS magnitudes, and that automated hyperparameter optimization improves model robustness. Full article

Investigating how climatic and hydrological conditions in ecological resource-enriched zones of marginal seas respond to external forcing, particularly during past greenhouse climates, holds considerable significance for understanding current environmental and resource challenges driven by global warming. In marginal seas, climatic hydrological states, including salinity, redox conditions, and productivity, are key environmental parameters controlling organic matter production, preservation, and ultimately the formation of high-quality shale. Herein, high-resolution cyclostratigraphic and multi-proxy geochemical analyses were conducted on a continuous core from the upper part of Member 4 of the Eocene Shahejie Formation (Es4cu) in Well NY1, Dongying Sag, Bohai Bay Basin. Based on these data, a refined astronomical timescale was accordingly established for the studied interval. By integrating sedimentological observations with multiple proxy indicators, including elemental geochemistry (e.g., Sr/Ba and Ca/Al ratios), organic geochemistry, and mineralogical data, the evolution of climate and paleo-water mass conditions during the study period was reconstructed. Spectral analyses revealed prominent astronomical periodicities in paleosalinity, productivity, and redox proxies, indicating that sedimentation was modulated by cyclic changes in eccentricity, obliquity, and precession. It was hereby proposed that orbital forcing governed periodic shifts in basin hydrology by regulating the intensity and seasonality of the East Asian monsoon. Intervals of enhanced summer monsoon associated with high eccentricity and obliquity were typically accompanied by increased sediment supply and intensified chemical weathering. Increased precipitation and runoff raised the lake level while promoting stronger connectivity with the ocean. In contrast, during weak seasonal monsoon intervals linked to eccentricity minima, basin conditions shifted from humid to arid, characterized by reduced precipitation, lower lake level, decreased sediment supply, and a concomitant decline in proxies for water salinity. The present results demonstrated orbital forcing as a primary external driver of cyclical changes in conditions favorable for resource formation in the Eocene lacustrine strata of the Bohai Bay Basin. Overall, this study yields critical paleoclimate evidence and a mechanistic framework for predicting the spatial-temporal distribution of high-quality shale under comparable astronomical-climate boundary conditions. Full article

This study investigated heat-induced protein aggregation in skim camel milk by monitoring changes in the volume-weighted mean particle size (d_4,3) during isothermal heating (60–90 °C, up to 60 min, four temperature levels and 25 time–temperature conditions). Pronounced increases in d_4,3 with both time and temperature confirmed significant thermal aggregation. The reaction kinetics were described using a generalized exponential growth model, which fitted well at intermediate temperatures (e.g., coefficient of determination (R²) = 0.901 at 70 °C and 0.959 at 80 °C) but deviated at the lower (60 °C) and upper (90 °C) extremes, reflecting more complex behavior. Arrhenius analysis of the rate constant yielded an activation energy of 50.61 kJ mol⁻¹, lower than values typically reported for bovine milk systems, indicating that camel milk proteins require less thermal input to aggregate. In parallel, a machine learning model implemented as an artificial neural network (ANN) predicted d_4,3 from time-temperature inputs with high accuracy (R² > 0.97 across training, validation, and testing), capturing nonlinear patterns without mechanistic assumptions. Together, the kinetic and ANN approaches provide complementary insights into the heat sensitivity of camel milk proteins and offer predictive tools to support the optimization of thermal processing, formulation, and quality control in dairy applications. Full article

As China’s urban underground area grows, deep foundation pit projects in complex geological circumstances, particularly near critical infrastructure, must adhere to tight deformation control guidelines. However, limited research has been conducted on the deformation behavior of internal bracing systems in Sichuan’s sandy cobble strata. This research centers on a deep excavation near civil defense facilities in Pujiang County, Chengdu. We investigated the deformation characteristics of retaining piles and internal bracing systems using field monitoring, finite element simulations, and parameter sensitivity analysis, and proposed optimization solutions for the support scheme. Road settlement, pile-head vertical displacement, building settlement, and deep lateral displacement of retaining piles were all monitored in the field at different phases of excavation. MIDAS/GTS was used to generate a 3D finite element model that included bored piles as a contiguous pile wall. The model was verified against monitored data and showed a maximum variation of 3.7%. Parametric studies were conducted to optimize the equivalent stiffness of the contiguous pile wall and the standardized internal bracing system. The findings indicate that the maximum lateral displacement of retaining piles is the primary optimization restriction. Reducing the equivalent stiffness to 0.6t (relative to the baseline thickness t) causes displacement to surpass the warning threshold (35 mm), whereas increasing it to 1.2t or 1.4t limits deformation without incurring significant costs. Case G of the standardized internal bracing system ensures that the maximum pile displacement (21.95 mm) remains below the warning criterion (24.5 mm) while improving constructability. This work elucidates the deformation characteristics of internal bracing systems in sandy cobble strata near sensitive buildings, offering theoretical and practical assistance for comparable projects. Full article

Adipocyte browning refers to the inducible transdifferentiation or de novo recruitment of thermogenically active beige adipocytes within white adipose tissue depots. Beige adipocytes, characterized by multilocular lipid droplets and high mitochondrial density, express uncoupling protein 1 and possess a metabolic phenotype similar to that of classical brown adipocytes. This plasticity of adipose tissue is regulated by a complex network of transcriptional coactivators (e.g., PRDM16, PGC-1α), epigenetic modulators, non-coding RNAs, and hormonal signals. Environmental cues, such as chronic cold exposure, exercise, and caloric restriction, further potentiate browning via sympathetic nervous system activation and endocrine crosstalk. At the systemic level, adipocyte browning enhances energy expenditure, improves insulin sensitivity, and mitigates lipid accumulation, making it a promising target for the treatment of obesity, type 2 diabetes mellitus, and other metabolic syndromes. Several browning agents (natural products and repositioned drugs) and novel chemicals that induce browning have been reported. However, the translational application of these agents in humans faces challenges related to interspecies differences, depot-specific responses, and long-term safety. This review critically examines molecular regulators, existing browning agents, and the discovery of novel browning agents, with the aim of harnessing them for metabolic disease intervention. Full article

River and lake health assessment has evolved from a purely ecological concept to a multidimensional framework integrating ecosystem integrity and social service functions. Based on a comprehensive dataset of 1412 papers (1991–2024), this study combines bibliometric mapping with a systematic review to track the evolution of biological monitoring and assessment methodologies. Quantitative analysis of keywords reveals that while traditional focuses on heavy metals, fish, and sediments remain dominant, there is a significant shift towards integrated frameworks where biological indicators (e.g., benthic macroinvertebrate integrity and fish retention) are increasingly coupled with social services. We critically review three assessment paradigms: single-factor bio-indicators, biological predictive models such as RIVPACS and AUSRIVAS, and multi-factor comprehensive models. The study identifies critical gaps in ecological connectivity and the management of transboundary lakes under climate change. Consequently, we propose a strategic roadmap leveraging the National Ecological Connectivity Optimization Platform and mandatory “health audits” for transboundary waters to ensure the long-term sustainability of aquatic biodiversity. This review provides a scientific basis for balancing biodiversity conservation with sustainable water resource utilization. Full article

Background: Chemotherapy is a cornerstone of cancer treatment; however, resistance to first-line chemotherapeutic agents remains a major challenge. ROS1, one of fifty-eight receptor tyrosine kinases, has been implicated in various cancer subtypes, including glioblastoma, non-small-cell lung cancer, and cholangiocarcinoma. Notably, the Gly2032Arg mutation in the ROS1 protein has been linked to resistance against the kinase inhibitor crizotinib. Objectives: Given the challenge, we conducted a comprehensive in silico study to identify new drug candidates. Methods: The study starts with modeling the Gly2032Arg-mutated ROS1 protein, followed by structure-based screening of the PubChem database. Results: Out of 1760 molecules screened, we selected the top 4 molecules (PubChem CID: 67463531, 72544946, 139431449, and 139431487) with structural features similar to crizotinib, a high docking score, and drug likeness. To further validate the effectiveness of the identified compounds, we assessed their binding affinity using the Molecular Mechanics with Generalized Born Surface Area (MM-GBSA) scoring method. To underpin the behavior and stability of protein–ligand complexes, 500 ns molecular dynamics (MD) simulations were conducted, and parameters including RMSD, RMSF, and H-bond dynamics were studied and compared. Density functional theory (DFT) at the B3LYP/6-31G* level was performed to elucidate molecular features of the identified compounds. Conclusions: Overall, this study sheds light on a new series of compounds effective against mutated targets, thereby offering a new horizon in this area. Full article