Search Results (2,187)

Carbon flow tracking and spatial pattern optimization at the scale of urban functional zones are key scientific challenges in achieving carbon neutrality. However, due to the complexity of carbon metabolism processes within urban functional zones, related studies remain limited. To address these scientific challenges, this study, based on the “source–sink–flow” ecosystem services framework, develops an integrated analytical approach at the scale of urban functional zones. The carbon balance is quantified using the CASA model in combination with multi-source data. A network model is employed to trace carbon flow pathways, identify critical nodes and interruption points, and optimize the urban spatial pattern through a low-carbon land use structure model. The research results indicate that the overall carbon balance in Hangzhou exhibits a spatial pattern of “deficit in the center and surplus in the periphery.” The main urban area shows a significant carbon deficit and relatively poor connectivity in the carbon flow network. Carbon sequestration services primarily flow from peripheral areas (such as Fuyang and Yuhang) with green spaces and agricultural functional zones toward high-emission residential–commercial and commercial–public functional zones in the central area. However, due to the interruption of multiple carbon flow paths, the overall carbon flow transmission capacity is significantly constrained. Through spatial optimization, some carbon deficit nodes were successfully converted into carbon surplus nodes, and disrupted carbon flow edges were repaired, particularly in the main urban area, where 369 carbon flow edges were restored, resulting in a significant improvement in the overall transmission efficiency of the carbon flow network. The carbon flow visualization and spatial optimization methods proposed in this paper provide a new perspective for urban carbon metabolism analysis and offer theoretical support for low-carbon city planning practices. Full article

Multimodal sentiment analysis (MSA) benefits from integrating diverse modalities (e.g., text, video, and audio). However, challenges remain in effectively aligning non-text features and mitigating redundant information, which may limit potential performance improvements. To address these challenges, we propose a Hierarchical Text-Guided Refinement Network (HTRN), a novel framework that refines and aligns non-text modalities using hierarchical textual representations. We introduce Shuffle-Insert Fusion (SIF) and the Text-Guided Alignment Layer (TAL) to enhance crossmodal interactions and suppress irrelevant signals. In SIF, empty tokens are inserted at fixed intervals in unimodal feature sequences, disrupting local correlations and promoting more generalized representations with improved feature diversity. The TAL guides the refinement of audio and visual representations by leveraging textual semantics and dynamically adjusting their contributions through learnable gating factors, ensuring that non-text modalities remain semantically coherent while retaining essential crossmodal interactions. Experiments demonstrate that the HTRN achieves state-of-the-art performance with accuracies of 86.3% (Acc-2) on CMU-MOSI, 86.7% (Acc-2) on CMU-MOSEI, and 80.3% (Acc-2) on CH-SIMS, outperforming existing methods by 0.8–3.45%. Ablation studies validate the contributions of SIF and the TAL, showing 1.9–2.1% performance gains over baselines. By integrating these components, the HTRN establishes a robust multimodal representation learning framework. Full article

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is a systemic ciliopathy resulting from loss-of-function mutations in the PKD1 and PKD2 genes, which encode polycystin-1 (PC1) and polycystin-2 (PC2), respectively. PC1 and PC2 regulate mechanosensation, calcium signaling, and key pathways controlling tubular epithelial structure and function. Loss of PC1/PC2 disrupts calcium homeostasis, elevates cAMP, and activates proliferative cascades such as PKA–B-Raf–MEK–ERK, mTOR, and Wnt, driving cystogenesis via epithelial proliferation, impaired apoptosis, fluid secretion, and fibrosis. Recent evidence also implicates novel signaling axes in ADPKD progression including, the Hippo pathway, where dysregulated YAP/TAZ activity enhances c-Myc-mediated proliferation; the stimulator of interferon genes (STING) pathway, which is activated by mitochondrial DNA release and linked to NF-κB-driven inflammation and fibrosis; and the TWEAK/Fn14 pathway, which mediates pro-inflammatory and pro-apoptotic responses via ERK and NF-κB activation in tubular cells. Mitochondrial dysfunction, oxidative stress, and maladaptive extracellular matrix remodeling further exacerbate disease progression. A refined understanding of ADPKD’s complex signaling networks provides a foundation for precision medicine and next-generation therapeutics. This review gathers recent molecular insights and highlights both established and emerging targets to guide targeted treatment strategies in ADPKD. Full article

Road networks are essential for access, resource distribution, and population evacuation during natural events. These challenges are pronounced in rural areas, where network redundancy is limited and communities may have social disparities. While traditional risk management systems often focus on the physical consequences of hazard events alone, specialized literature increasingly suggests the development of a more comprehensive approach for risk assessment, where not only physical aspects associated with infrastructure, such as damage level or disruptions, but also the social and economic attributes of the affected population are considered. Consequently, this paper proposes a Vulnerability Access Index (VAI) to support road network decision-making that integrates the social vulnerability of rural communities exposed to natural events, their accessibility to nearby critical infrastructure, and physical risk. The research methodology considers (i) the Social Vulnerability Index (SVI) calculation based on socioeconomic variables, (ii) Importance Index estimation (I_imp) to evaluate access to critical infrastructure, (iii) VAI calculation combining SVI and I_imp, and (iv) application to a case study in the influence area of the Villarrica volcano in southern Chile. The results show that when incorporating social variables and accessibility, infrastructure criticality varies significantly compared to the infrastructure criticality assessment based solely on physical risk, modifying the decision-making regarding road infrastructure robustness and resilience improvements. Full article

Insulin-regulated glucose uptake is a central mechanism in maintaining systemic glucose homeostasis, primarily occurring in skeletal muscle and adipose tissue. This process relies on the insulin-stimulated translocation of the glucose transporter, GLUT4, from specialized intracellular compartments, known as GLUT4 storage vesicles (GSVs), to the plasma membrane. Disruption of this pathway is a hallmark of insulin resistance and a key contributor to the pathogenesis of type 2 diabetes. Recent advances have provided critical insights into both the insulin signalling cascades and the complex biogenesis, as well as the trafficking and fusion dynamics of GSVs. This review synthesizes the current understanding of the molecular mechanisms governing GSV mobilization and membrane fusion, highlighting key regulatory nodes that may become dysfunctional in metabolic disease. By elucidating these pathways, we propose new therapeutic avenues targeting GSV trafficking to improve insulin sensitivity and combat type 2 diabetes. Full article

Background/Objectives: Male infertility is a major health concern with a complex etiopathology, yet a substantial proportion of cases remain idiopathic. Mitochondrial dysfunction and non-coding RNA (ncRNA) deregulation have both been implicated in impaired spermatogenesis, but their interplay remains poorly understood. This study aimed to identify infertility-specific variants in ncRNAs that affect mitochondrial dynamics and homeostasis and to explore their roles. Methods: Whole-genome sequencing (WGS) was performed on genomic DNA samples from teratozoospermic, asthenozoospermic, oligozoospermic, and normozoospermic men. Variants uniquely present in infertile individuals and mapped to ncRNAs that affect mitochondrial dynamics were selected and prioritized using bioinformatics tools. An independent transcriptomic validation was conducted using RNA-sequencing data from testicular biopsies of men with non-obstructive azoospermia (NOA) to determine whether the ncRNAs harboring WGS-derived variants were transcriptionally altered. Results: We identified several infertility-specific variants located in lncRNAs known to interact with mitochondrial regulators, including GAS5, HOTAIR, PVT1, MEG3, and CDKN2B-AS1. Transcriptomic analysis confirmed significant deregulation of these lncRNAs in azoospermic testicular samples. Bioinformatic analysis also implicated the disruption of lncRNA–miRNA–mitochondria networks, potentially contributing to mitochondrial membrane potential loss, elevated reactive oxygen species (ROS) production, impaired mitophagy, and germ cell apoptosis. Conclusions: Our integrative genomic and transcriptomic analysis highlights lncRNA–mitochondrial gene interactions as a novel regulatory layer in male infertility, while the identified lncRNAs hold promise as biomarkers and therapeutic targets. However, future functional studies are warranted to elucidate their mechanistic roles and potential for clinical translation in reproductive medicine. Full article

Perfluoroalkyl substances (PFASs) possess immunosuppressive properties. However, their association with rheumatoid arthritis (RA) risk remains inconclusive across epidemiological studies. This study integrates population-based and mechanistic evidence to clarify the relationship between PFAS exposure and RA. We analyzed 8743 U.S. adults from the NHANES (2005–2018), assessing individual and mixed exposures to PFOA, PFOS, PFNA, and PFHxS using multivariable logistic regression, Bayesian kernel machine regression, quantile g-computation, and weighted quantile sum models. Network toxicology and molecular docking were utilized to identify core targets mediating immune disruption. The results showed that elevated PFOA (OR = 1.63, 95% CI: 1.41–1.89), PFOS (OR = 1.41, 1.25–1.58), and PFNA (OR = 1.40, 1.20–1.63) levels significantly increased RA risk. Mixture analyses indicated a positive joint effect (WQS OR = 1.06, 1.02–1.10; qgcomp OR = 1.26, 1.16–1.38), with PFOA as the primary contributor. Stratified analyses revealed stronger effects in females (PFOA Q4 OR = 3.75, 2.36–5.97) and older adults (≥60 years). Core targets included EGFR, SRC, TP53, and CTNNB1. PFAS mixtures increase RA risk, dominated by PFOA and modulated by sex/age. These findings help reconcile prior contradictions by identifying key molecular targets and vulnerable subpopulations, supporting regulatory attention to PFAS mixture exposure. Full article

Schizophrenia (SZ) is a complex neuropsychiatric disorder characterized by heterogeneous symptoms, relatively poor clinical outcome, and widespread disruptions in neural connectivity and oscillatory dynamics. This article attempts to review current evidence linking genomic and proteomic alterations with aberrant neural oscillations observed in SZ, including aberrations in all oscillatory frequency bands obtained via human EEG. The numerous genes discussed are mainly involved in modulating synaptic transmission, synaptic function, interneuron excitability, and excitation/inhibition balance, thereby influencing the generation and synchronization of neural oscillations at specific frequency bands (e.g., gamma frequency band) critical for different cognitive, emotional, and perceptual processes in humans. The review highlights how polygenic influences and gene–circuit interactions underlie the neural oscillatory and connectivity abnormalities central to SZ pathophysiology, providing a framework for future research on common genetic-neural function interactions and on potential therapeutic interventions targeting local and global network-level neural dysfunction in SZ patients. As will be discussed, many of these genes affecting neural oscillations in SZ also affect other neurological disorders, ranging from autism to epilepsy. In time, it is hoped that future research will show why the same genetic anomaly leads to one illness in one person and to another illness in a different person. Full article

Produce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO₂ concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California’s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions. Full article

As typical environmental hormones, endocrine-disrupting chemicals (EDCs) have become a global environmental health issue of high concern due to their property of interfering with the endocrine systems of organisms. As a commonly used substitute for bisphenol A (BPA), bisphenol E (BPE) has been frequently detected in environmental matrices such as soil and water in recent years. Existing research has unveiled the developmental and reproductive toxicity of BPE; however, only one in vitro cellular experiment has preliminarily indicated potential neurotoxic risks, with its underlying mechanisms remaining largely unelucidated in the current literature. Potential toxic mechanisms and action targets of BPE were predicted using the zebrafish model via network toxicology and molecular docking, with RT-qPCRs being simultaneously applied to uncover neurotoxic effects and associated mechanisms of BPE. A significant decrease (p < 0.05) in the frequency of embryonic spontaneous movements was observed in zebrafish at exposure concentrations ≥ 0.01 mg/L. At 72 hpf and 144 hpf, the larval body length began to shorten significantly from 0.1 mg/L to 1 mg/L, respectively (p < 0.01), accompanied by a reduced neuronal fluorescence intensity and a shortened neural axon length (p < 0.01). By 144 hpf, the motor behavior in zebrafish larvae was inhibited. Through network toxicology and molecular docking, HSP90AB1 was identified as the core target, with the cGMP/PKG signaling pathway determined to be the primary route through which BPE induces neurotoxicity in zebrafish larvae. BPE induces neuronal apoptosis and disrupts neurodevelopment by inhibiting the cGMP/PKG signaling pathway, ultimately suppressing the larval motor behavior. To further validate the experimental outcomes, we measured the expression levels of genes associated with neurodevelopment (elavl3, mbp, gap43, syn2a), serotonergic synaptic signaling (5-ht1ar, 5-ht2ar), the cGMP/PKG pathway (nos3), and apoptosis (caspase-3, caspase-9). These results offer crucial theoretical underpinnings for evaluating the ecological risks of BPE and developing environmental management plans, as well as crucial evidence for a thorough comprehension of the toxic effects and mechanisms of BPE on neurodevelopment in zebrafish larvae. Full article

Ochratoxin A (OTA), a prevalent food contaminant, has been proposed as a potential contributor to the development of prostate cancer, although its precise mechanisms remain unclear. This study employed a comprehensive approach that integrated network toxicology, machine learning, and molecular docking to clarify the role of OTA in prostate cancer. The findings indicated that OTA interacts with 364 targets related to prostate cancer, and machine learning was employed to identify five key molecular targets as priorities (ESR1, TP53, TNF, INS, and EGFR). In conjunction with the results of a functional enrichment analysis, OTA was found to possibly facilitate cancer progression by disrupting endocrine function, activating oncogenic signaling pathways, reprogramming metabolism, and modulating the tumor microenvironment. Full article

Traditional Pavement Condition Index (PCI) assessments are highly resource-intensive, demanding substantial time and labor while generating significant carbon emissions through extensive field operations. To address these sustainability challenges, this research presents an innovative methodology utilizing Gene Expression Programming (GEP) to determine PCI values based on International Roughness Index (IRI) measurements from Iraqi road networks, offering an environmentally conscious and resource-efficient approach to pavement management. The study incorporated 401 samples of IRI and PCI data through comprehensive visual inspection procedures. The developed GEP model exhibited exceptional predictive performance, with coefficient of determination (R²) values achieving 0.821 for training, 0.858 for validation, and 0.8233 overall, successfully accounting for approximately 82–85% of PCI variance. Prediction accuracy remained robust with Mean Absolute Error (MAE) values of 12–13 units and Root Mean Square Error (RMSE) values of 11.209 and 11.00 for training and validation sets, respectively. The lower validation RMSE suggests effective generalization without overfitting. Strong correlations between predicted and measured values exceeded 0.90, with acceptable relative absolute error values ranging from 0.403 to 0.387, confirming model effectiveness. Comparative analysis reveals GEP outperforms alternative regression methods in generalization capacity, particularly in real-world applications. This sustainable methodology represents a cost-effective alternative to conventional PCI evaluation, significantly reducing environmental impact through decreased field operations, lower fuel consumption, and minimized traffic disruption. By streamlining pavement management while maintaining assessment reliability and accuracy, this approach supports environmentally responsible transportation systems and aligns contemporary sustainability goals in infrastructure management. Full article

Urban tourism has evolved into a complex adaptive system, where unregulated expansion disrupts the ecological balance and intensifies resource stress. Understanding the dynamic evolution and resilience mechanisms of the tourism ecological health network (TEHN) is essential for supporting sustainable urban tourism as a coupled human–natural system. Using Shanghai as a case study, we applied the “vigor–organization–resilience–services” (VORS) framework to evaluate ecosystem health, which served as a constraint for constructing the TEHN, using the minimum cumulative resistance (MCR) model for the period from 2001 to 2023. A resilience framework integrating structural and functional dimensions was further developed to assess spatiotemporal evolution and guide targeted enhancement strategies. The results indicated that as ecosystem health degraded, particularly in peripheral areas, the urban TEHN in Shanghai shifted from a dispersed to a centralized structure, with limited connectivity in the periphery. The resilience of the TEHN continued to grow, with structural resilience remaining at a high level, while functional resilience still required enhancement. Specifically, the low integration and limited choice between the tourism network and the transportation system hindered tourists from selecting routes with higher ecosystem health indices. Enhancing functional resilience, while sustaining structural resilience, is essential for transforming the TEHN into a multi-centered, multi-level system that promotes efficient connectivity, ecological sustainability, and long-term adaptability. The results contribute to a systems-level understanding of tourism–ecology interactions and support the development of adaptive strategies for balancing network efficiency and environmental integrity. Full article

Hormone-dependent breast cancer, particularly in its treatment-resistant forms, remains a significant therapeutic challenge. In this study, we applied a fully computational strategy to design steroid-based compounds capable of simultaneously targeting three key receptors involved in disease progression: progesterone receptor (PR), estrogen receptor alpha (ER-α), and HER2. Using a robust 3D-QSAR model (R² = 0.86; Q²_LOO = 0.86) built from 52 steroidal structures, we identified molecular features associated with high anticancer potential, specifically increased polarizability and reduced electronegativity. From a virtual library of 271 DFT-optimized analogs, 31 compounds were selected based on predicted potency (pIC₅₀ > 7.0) and screened via molecular docking against PR (PDB 2W8Y), HER2 (PDB 7JXH), and ER-α (PDB 6VJD). Seven candidates showed strong binding affinities (ΔG ≤ −9 kcal/mol for at least two targets), with Estero-255 emerging as the most promising. This compound demonstrated excellent conformational stability, a robust hydrogen-bonding network, and consistent multitarget engagement. Molecular dynamics simulations over 100 nanoseconds confirmed the structural integrity of the top ligands, with low RMSD values, compact radii of gyration, and stable binding energy profiles. Key interactions included hydrophobic contacts, π–π stacking, halogen–π interactions, and classical hydrogen bonds with conserved residues across all three targets. These findings highlight Estero-255, alongside Estero-261 and Estero-264, as strong multitarget candidates for further development. By potentially disrupting the PI3K/AKT/mTOR signaling pathway, these compounds offer a promising strategy for overcoming resistance in hormone-driven breast cancer. Experimental validation, including cytotoxicity assays and ADME/Tox profiling, is recommended to confirm their therapeutic potential. Full article

The siphon effect between airports has amplified the polarization in passenger throughput, undermining the balanced development and sustainability of airport clusters. The airport siphon effect occurs when one airport attracts a disproportionate share of passengers, concentrating traffic at the expense of others, which affects the overall resilience of the entire airport cluster. To address this issue, this study proposes a siphon index, expands the range of ground transportation options for passengers, and establishes a zero-siphon model to assess the impact of siphoning on the resiliency of airport clusters. Using this framework, four major airport clusters in China were selected as research subjects, with regional aviation accessibility serving as a measure of resilience. The results showed that among the four airport clusters, the siphon effect is most pronounced in the Guangzhou region. To explore the implications of this effect further, three airport disruption scenarios were simulated to assess the resilience of the Pearl River Delta airport cluster. The results indicated that the intensity and timing of disruptive events significantly affect airport cluster resilience, with hub airports being particularly sensitive. This study analyzes the risks associated with excessive route concentration, providing policymakers with critical insights to enhance the sustainability, equity, and resilience of airport clusters. The proposed strategies facilitate coordinated infrastructure development, optimized air–ground intermodal connectivity, and risk mitigation. These measures contribute to building more sustainable and adaptive aviation networks in rapidly urbanizing regions. Full article