Search Results (107)

Background/Objective: Osteoarthritis lacks disease-modifying therapy, and NF-κB signaling is among the best-supported intervention points in cartilage. Sinomenine suppresses this pathway in chondrocytes, but only its downstream consequences are known, and network pharmacology rarely measures its own accuracy. Methods: Targets from six prediction resources were intersected with osteoarthritis genes from five databases and with cartilage and synovial differentially expressed genes. Candidates underwent topological analysis and unrestricted enrichment; prioritized targets were examined by docking and triplicate 100 ns molecular dynamics. Benchmarking used a curated bioactivity reference set, with a variant correcting input-validation overlap. Predictions were tested by thermal shift, limited proteolysis, NMR, thermophoresis, and kinase and silencing assays in interleukin-1β-challenged chondrocytes and in mice after medial meniscus destabilization. Results: Integration yielded 96 candidates, 34 transcriptionally corroborated, giving a network of 78 nodes and 241 edges with 12 consensus hubs. NF-κB signaling ranked first among 74 enriched pathways (adjusted p = 2.7 × 10⁻²⁰), and convergent criteria prioritized IKBKB, RELA, TNF, PTGS2 and MMP9. Benchmarking gave an area under the curve that fell from 0.81 to 0.74 and sensitivity from 0.73 to 0.57 after correcting for circularity. Sinomenine raised the melting temperature of IKBKB by 4.3 °C, bound it at 8.7 μM and inhibited it ATP-competitively, whereas RELA and CHUK showed no engagement. Nuclear p65 fell from 71.3% to 34.8%, IKBKB silencing abolished most of the MMP13 response, and cartilage damage scores fell from 5.0 to 2.5 at 40 mg/kg. Conclusions: Sinomenine engages IKBKB directly and acts principally at the IKK-dependent activation step. The generating pipeline proved only moderately accurate once circularity was corrected, which argues for reporting such metrics routinely. Full article

Can we conclude that rapid digital transformation leads to geographically equitable development? This research paper investigates the simultaneous and spatial dynamics of digital development and digital inclusion within the administrative regions of Saudi Arabia from 2012 to 2024. The research employs β-convergence, σ-convergence, Theil inequality decomposition techniques, and Spatial Durbin Models (SDM) to determine whether successful digital advancement results in better inclusion. The findings present a significant discrepancy between technological improvement and its results in terms of equity. The Digital Progress Index (DPI) reveals that convergence occurs at 4.71% annually, while the Digital Inclusion Score (DIS) reaches only 1.41% per year. While there is a significant reduction in the spread of digital progress, the outcome for digital inclusion inequality is only 15%, which has been stagnant after 2020. The Theil decomposition indicates that the inequality component among the regions has dropped from 69.7% to 39.8%, and the inequality gap among regions has increased. The SD estimates demonstrate that digital infrastructure has a positive influence across the regions, indicating that digital advancement also produces wider benefits. However, they are insufficient to solve the inclusion issues. The results refute the belief that rapid digitalization brings about geographically inclusive development, as the report argues that the processes of digital advancement and digital inclusion occur along separate convergence trajectories. As a result, the question raised by this research is how to migrate from infrastructure-based digitalization to place-based policies that will enable investments in digital capabilities, affordability, accessibility, and economic impediments, affecting the implementation of Vision 2030 in Saudi Arabia, among other rapidly digitalized economies. Full article

Human induced pluripotent stem cells (hiPSCs) have revolutionized cardiovascular research by providing a renewable source of patient-specific cardiomyocytes for disease modeling, drug discovery, precision medicine, and regenerative therapies. Temporal modulation of canonical Wnt/β-catenin signaling has established the current gold standard for efficient and reproducible cardiac differentiation under chemically defined conditions. However, conventional Wnt-based protocols consistently generate cardiomyocytes with fetal-like structural, electrophysiological, metabolic, and contractile characteristics, highlighting that lineage specification alone is insufficient to achieve functional maturation. This review discusses recent advances in engineering the cardiac developmental niche by integrating extracellular matrix remodeling, biomaterials, biomechanical and bioelectrical stimulation, metabolic regulation, multicellular interactions, and microfluidic technologies to better recapitulate the dynamic microenvironment of human cardiogenesis. We further examine how emerging bioengineered platforms, including engineered heart tissues, cardiac organoids, and heart-on-chip systems, enhance the physiological relevance of hiPSC-derived cardiac models. Finally, we discuss future perspectives arising from the convergence of developmental biology, tissue engineering, biomaterials, artificial intelligence, and microphysiological systems, proposing that the next generation of cardiac differentiation platforms will depend on integrating canonical Wnt signaling within biomimetic developmental microenvironments to generate mature human cardiac tissues with enhanced translational potential. By advancing physiologically relevant human cardiac models for disease modeling, drug discovery, and regenerative medicine, this work also supports the research and innovation priorities underlying Sustainable Development Goal 3 (SDG 3), particularly those related to reducing the burden of non-communicable diseases and strengthening health-related research and development. Full article

Time-fractional generalizations of the Lindblad master equation describe open quantum systems whose coupling to the environment exhibits power-law memory. We develop the optimal-control theory of such systems and analyse the consistency of the adjoint calculus on which every gradient-based pulse-design method relies. Casting the density operator in a fractional Bochner–Sobolev space of Hilbert–Schmidt operator valued functions, we establish well-posedness through Mittag–Leffler resolvent families, prove that the completely positive trace-preserving (CPTP) structure is preserved for the controlled, time-dependent generator without recourse to subordination, and obtain existence and uniqueness of optimal controls by the direct method. The adjoint is governed by the right Riemann–Liouville derivative with a fractional-integral terminal condition, a structure established for Caputo dynamics with a Mayer cost by Bergounioux and Bourdin, who also showed that a pointwise terminal costate cannot exist. Our central result concerns the discrete counterpart of that fact, where existence is never lost: imposed on the right-Caputo adjoint of a convergent scheme, the pointwise condition yields a bounded costate and a well-defined reduced gradient carrying an error that is mesh-independent. We further establish a sharp rate in the classical limit: the defect vanishes exactly linearly, $\parallel \Delta \left(\beta \right)\parallel =C(1-\beta )+O\left({(1-\beta )}^2\right)$, with C given in closed form through a digamma series. Two consequences follow: monotonicity of the defect in the memory order is proved near $\beta =1$, and the memory order is locally identifiable from gradient data alone. A corrected adjoint restores consistency with proven convergence rates. Numerical experiments on two-level, three-level and two-qubit open systems (Liouville dimension up to 16) confirm the mesh-independence, reproduce C to three significant digits, and recover the full rate on graded meshes. Full article

We study a class of evolutionary variational inequalities in a Hilbert space that models the long-run balanced-growth equilibrium of a competitive economy with transaction costs, time-dependent production and infrastructure constraints, and exogenous price dynamics. The paper makes four contributions. First, we introduce a parametrized monotonicity functional ${\mu }_{\alpha }(t;F;u,v;p)$ and prove an exact equivalence theorem: the inequality ${\mu }_{\alpha }\ge \beta {∥u-v∥}^2$ holds if and only if the operator F is strongly monotone with the explicitly computed constant $m=\beta -\alpha (1+{∥p∥}_{\infty })$. This turns the growth parameter $\alpha$ and the price level into explicit terms of a single admissibility threshold and, for $\beta <\alpha (1+{∥p∥}_{\infty })$, produces a scale of conditions that covers operators which are not monotone, i.e., economies with a bounded degree of increasing returns. Second, we prove well-posedness: for every admissible initial state there is exactly one Lipschitz equilibrium trajectory $u^{*}(·)$, obtained through Moreau’s catching-up algorithm for the associated perturbed sweeping process, together with the explicit velocity bound $∥{\dot{u}}^{*}∥\le L_K+2C_F$. Third, we derive one comparison estimate from which global exponential stability, the convergence rate $∥u\left(t\right)-u^{*}\left(t\right)∥\le r e^{-mt}+L_p{m}^{-1}\sup ∥\Delta p∥+\epsilon m^{-1}$, and robustness with respect to perturbations of prices and of the operator all follow; we also show that, when the constraint sets stabilize, the trajectory converges to the stationary equilibrium of the limit problem. Fourth, we prove that strong monotonicity implies the c-covering property with $c=m$, so that the shock-absorbing capacity of the economy is governed by the same constant as the speed of convergence. Two examples—a two-resource system and an n-market network with nonlinear transaction costs—are worked out with a complete verification of every hypothesis and with explicit numerical constants. Full article

The global energy sector is undergoing rapid and, in many respects, irreversible transformation driven by the convergence of digital disruption, sustainability mandates, and shifting investor expectations. Technologies such as artificial intelligence (AI), blockchain, and digital twin systems are fundamentally reshaping energy operations and strategic decision-making, while ESG governance quality and renewable energy adoption have emerged as two of the most consequential determinants of corporate financial competitiveness and equity valuation. Despite growing practitioner and regulatory interest in these dynamics, limited empirical evidence exists on how ESG governance, renewable adoption, and digital disruption jointly influence financial performance and environmental outcomes across multiple sectors simultaneously. This study addresses that gap using panel data from 26 large-cap US-listed firms across five sectors over 2015–2022 (N = 208 firm-year observations for Revenue/Market Cap/ROA models; N = 91 for the CO₂ model). A multi-method econometric framework is employed, comprising Fixed Effects and Random Effects panel regression with Hausman specification testing, Difference in Differences quasi-experimental analysis, and sequential OLS path analysis with HC3 robust standard errors. Three of four hypotheses are supported. ESG governance quality generates a significant market capitalisation premium of approximately 10–14% per unit Bloomberg ESG Score improvement, after controlling for firm size and R&D intensity; no significant revenue channel effect is found once firm size is properly accounted for. Renewable energy adoption shows a marginal association with market capitalisation at the 10% significance level (FE β = 0.019, p = 0.086; RE β = 0.016, p = 0.077), suggesting capital markets may price clean energy adoption as a forward-looking signal. ESG governance quality drives within-firm CO₂ emission reduction substantially more powerfully than renewable energy quantity alone, with the Fixed Effects estimator identifying a governance-led eco-efficiency mechanism. Firm profitability functions as a cross-model financial capacity moderator, enabling simultaneous ESG investment and environmental improvement. The findings carry direct implications for corporate managers, institutional investors, and policymakers aligned with SDG 7, SDG 9, and SDG 13. Full article

Background: The aggressive progression of mesothelioma is driven not only by intrinsic tumor cell plasticity but also by dynamic interactions between tumor cells and the surrounding stromal microenvironment; however, the mechanisms by which stromal populations regulate epithelial–mesenchymal transition (EMT), tumor evolution, and therapeutic resistance remain unclear. Methods: We integrated longitudinal transcriptomic profiling with single-cell RNA sequencing in a murine intraperitoneal mesothelioma model spanning disease progression from week 0 to week 8 to identify stromal-EMT programs associated with tumor progression. In vitro fibroblast–tumor co-culture systems were used to assess how different fibroblast-to-tumor cell ratios influence transcriptional reprogramming and mesenchymal transition. Results: Single-cell analysis revealed marked stromal heterogeneity, identifying eight distinct cancer-associated fibroblast (CAF) subtypes: myCAF, mCAF, iCAF, TGF-βCAF, vCAF, plCAF, apCAF, and meCAF. These subsets showed specialized transcriptional programs associated with developmental signaling and metabolic adaptation. Functional analyses demonstrated coordinated intercellular communication across six interconnected modules, including mesenchymal transition, fibrotic remodeling, TGF-β/metabolic adaptation, adhesion signaling, WNT activation, and inflammatory crosstalk. Notably, mCAF, TGF-βCAF, and plCAF populations showed transcriptional convergence, suggesting cooperative formation of a desmoplastic, immunoregulatory niche. Co-culture experiments confirmed that fibroblast-derived signaling induces ratio-dependent transcriptional changes, promoting a shift from epithelioid to mesenchymal phenotypes. Conclusions: These findings highlight stromal regulation of EMT as a key driver of mesothelioma progression, sarcomatoid transition, and therapy resistance, and identify tumor–stroma signaling networks as potential therapeutic targets. Full article

The oral microbiota represents a complex and dynamic microbial ecosystem that plays a critical role in preserving both oral and systemic homeostasis. Emerging evidence suggests that alterations in oral microbial milieu (dysbiosis) may contribute to the pathogenesis of neurodegenerative disorders, especially Alzheimer’s disease (AD), through the oral–brain axis. This review synthesizes current evidence on the pathways linking oral microbiota to cognitive decline, integrating microbial, immunological, and vascular perspectives. Oral pathogens may access the central nervous system via hematogenous dissemination or neural routes, including the trigeminal nerve, while simultaneously promoting systemic inflammation, immune activation, and blood–brain barrier disruption. These processes converge on key neurodegenerative mechanisms, including chronic neuroinflammation, amyloid-β accumulation, and tau pathology. In parallel, alterations in oral microbial composition have been linked to disease severity, supporting a potential role of dysbiosis in both initiation and progression of cognitive impairment. Diet emerges as a critical modifiable determinant of oral microbial ecology. Diets rich in refined sugars may promote dysbiosis and inflammatory signaling, whereas (poly)phenols, probiotics, and prebiotics may support microbial eubiosis and exert neuroprotective effects through modulation of host–microbe interactions. Although current evidence remains largely observational and mechanistic, the diet–oral microbiota–brain axis represents a promising target for preventive and therapeutic strategies aimed at mitigating cognitive decline and promoting healthy aging. Future longitudinal and interventional studies are required to establish causality and translate these insights into clinical practice. Full article

Background: Immune checkpoint blockade (ICB) targeting the PD-1/PD-L1 axis has improved outcomes in non-small cell lung cancer (NSCLC), although reliable biomarkers for predicting benefit are still limited. Methods: In this exploratory study, we conducted a longitudinal analysis of the peripheral T-cell receptor (TCR) β repertoire in 28 patients with unresectable stage IIIb non-small cell lung cancer (NSCLC) who received anti-PD-L1 immunotherapy following chemoradiotherapy. Blood samples were collected at baseline and three months after treatment initiation. Results: At the cohort level, global TCR repertoire features such as diversity and richness did not change significantly over time. However, when looking at individual patients, more specific patterns became evident. Patients could be broadly separated based on changes in clonotype richness, with reductions generally accompanied by lower diversity and decreased convergent TCR frequency. We also observed differences in TRBV gene usage in relation to clinical outcome, with higher TRBV20-1 and lower TRBV28 frequencies tending to associate with improved survival and delayed disease progression. Interestingly, the disappearance of dominant clonotypes from the peripheral blood during treatment was linked to longer progression-free survival (PFS). In addition, patients with higher baseline blood plasma tumor mutational burden (bTMB) showed greater clonotype richness and were more likely to exhibit this clonotype loss. The combination of high bTMB and clonotype disappearance identified a subgroup of patients with particularly favorable outcomes. Conclusions: Overall, these results suggest that early responses to PD-L1 blockade may be reflected less in global TCR repertoire shifts, including clonality and diversity measures, and more in subtle changes in clonotype composition and dynamics, since the frequencies of certain TRBV genes and the disappearance of dominant clonotypes following ICB were associated with clinical outcomes integrating TCR profiling with bTMB and could therefore help refine patient stratification and improve the understanding of immune responses in NSCLC. Nevertheless, due to the small number of recruited patients, our study is exploratory and hypothesis-generating, and further validation in larger patient cohorts is warranted. Full article

Heritable thoracic aortic diseases (HTADs) comprise a genetically heterogeneous group of disorders predisposing patients to thoracic aortic aneurysm and dissection, yet current medical therapies remain limited to slowing disease progression rather than preventing aortic wall failure. Although pathogenic variants affect diverse genes encoding extracellular matrix (ECM) components, smooth muscle contractile proteins, and signaling molecules, these defects converge on disruption of the mechanobiological systems that maintain aortic wall integrity. The thoracic aorta functions as a mechanically integrated tissue in which endothelial cells, vascular smooth muscle cells, fibroblasts, immune cells and ECM continuously sense and respond to pulsatile biomechanical forces. Genetic perturbations affecting ECM architecture, contractile force generation, or growth factor signaling alter force transmission across this multicellular network, leading to maladaptive mechanotransduction, cellular phenotypic modulation, and progressive aneurysm formation. Using Marfan syndrome as a paradigmatic ECM-driven aortic disease, this review synthesizes current understanding of how altered biomechanics, biochemical signaling and immune responses reshape intercellular communication and activate disease-associated signaling pathways, including dysregulated TGF-β, nitric oxide, angiotensin receptor, calcium-dependent, and metabolic signaling. We highlight how single-cell transcriptomic analyses have elaborated changes in different cell-level functions including, ECM degradation, iron homeostasis, circadian/stress responses. Changes in iron metabolism in different cell types in the aorta suggest possible coordinated metabolic changes in aneurysm progression. These mechanistic insights enable the identification of cell-type–specific pathogenic programs and therapeutic discovery through systems-level approaches. We highlight the translational opportunities and challenges emerging from mouse models and human studies, emphasizing that therapeutic efficacy depends not only on pathway selection but also on disease stage, cellular context, and timing of intervention. Together, these findings support a model in which HTAD progression reflects dynamic, multicellular failure of mechanobiological homeostasis and provide a framework for the development of more precise, mechanism-based therapies. Full article

Yaks have long inhabited the Qinghai-Tibetan Plateau. This region features low-oxygen, frigid temperatures and pronounced seasonal variation in nutrient availability. They have evolved adaptive phenotypes centered on energy metabolism reprogramming, tissue structure remodeling, and stress homeostasis maintenance. In recent years, non-coding RNAs (ncRNAs) have been confirmed as an important component of the yak’s post-transcriptional regulatory network. They play a key bridging role between environmental stress perception and phenotypic output through mechanisms such as influencing RNA splicing, stability, translation activity, and constructing competitive endogenous RNA (ceRNA) networks. This article systematically reviews the biogenesis pathways and core regulatory patterns of circular RNAs (circRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs). It focuses on summarizing the expression profile characteristics and dynamic spatiotemporal changes of these three types of ncRNAs in physiological contexts such as muscle and fat deposition, mammary gland lactation, testicular development, and hypoxia response in the heart, lungs, and vascular system of yaks. Current research evidence indicates that the regulatory network of yaks ncRNAs shows significant convergence on multiple key signaling pathways, mainly concentrating on lipid metabolism (PPAR/AMPK), nutrition and growth signals (PI3K-Akt/MAPK/mTOR), extracellular matrix remodeling (ECM-receptor interaction, Wnt/TGF-β), and cell stress fate determination (apoptosis, oxidative stress/ferroptosis) modules. Among them, some core circRNA and lncRNA-miRNA-mRNA regulatory axes have been functionally validated in vitro. Despite the phased progress, current research on ncRNA in yaks still faces bottlenecks: the multi-omics molecular atlases (encompassing genomics, transcriptomics, proteomics, and metabolomics) of key high-altitude adaptive organs remain incomplete, analysis processes lack sufficient standardization, and most studies stay at the association network level with limited causal mechanism validation. To address these limitations, future research should focus on building a standardized evidence chain, integrating multi-omics and single-cell/spatial transcriptome technologies, and conducting mechanism verification for traits in independent populations, thereby providing a solid theoretical basis for understanding the extreme environmental adaptation mechanisms of yaks and molecular breeding improvement. Full article

Voltage source converters (VSCs), together with their inner current and outer power/voltage control loops, are fundamental building blocks in the modern, converter-dominated power systems, particularly within high-voltage DC (HVDC) frameworks. Selecting effective control methods for VSCs is essential to ensure the stability, power quality, and dynamic performance of HVDC grids. This paper seeks to advance the current body of research by delivering an in-depth, consistent, unified framework and systematic examination of VSC control architectures within HVDC networks. It thoroughly explores various control strategies for VSCs interfacing with HVDC grids, such as grid-following and grid-forming strategies, with particular emphasis on both stationary ($\alpha \beta$) and synchronous (dq) reference frames. Moreover, the paper provides a comprehensive analysis of the theoretical underpinnings and decoupled control strategies, like the feedforward decoupling of the d- and q-axis currents in the dq frame and the inherently decoupled structure of the αβ frame. Additionally, advanced filtering techniques, including Moving Average Filter (MAF), Cascaded Delayed Signal Cancellation (DSC), and LCL filters, are analyzed. In addition, harmonic mitigation strategies, like parallel/multiple resonant (PR) terms in the αβ frame and cascaded notch filters in the dq frame, are presented. Furthermore, precise power control approaches and synchronization methods are discussed in detail. Also, this paper presents a detailed comparison of the performance characteristics of phase-locked loop (PLL) and frequency-locked loop (FLL) in response to grid frequency variations. Moreover, this paper proposes circuit representations and VSC models in both synchronous and stationary reference frames. The simulation results corroborate the theoretical insights discussed in the paper under various operational conditions, including initial responses, grid disturbances, three-phase-to-ground temporary fault scenarios, harmonic distortions, and load imbalances, in terms of overshoot, settling time, active- and reactive-power fluctuation reduction, voltage unbalance factor, total harmonic distortion, and post-fault convergence time, all evaluated in accordance with the limits defined in EN-50160. This comprehensive comparison of the presented control strategies facilitates researchers in identifying the most appropriate controller depending on their specific application requirements. Full article

This study examines income convergence among EU NUTS-2 regions from 2000 to 2023 using a combination of Phillips-Sul (PS) club convergence methodology, $\beta$-convergence, and spatial econometric models. The results reveal that regional convergence in Europe is heterogeneous and nonlinear: four stable convergence clubs emerge, while overall convergence is rejected. Convergence was faster before 2012 and weakened afterward. A single income threshold and two structural breaks (2005 and 2012) mark shifts in growth dynamics. Spatial models reveal that neighboring regions affect each other’s growth, indicating that regional development in Europe depends on both local conditions and interactions across regions. Full article

Under increasing land constraints and food security pressures, understanding the direction of agricultural technological change is essential for improving land use efficiency. This study investigates the regional disparities, distributional dynamics, and spatial convergence of biased technological change in Chinese agriculture. Dagum Gini decomposition is used to identify regional differences and their sources, kernel density estimation examines distributional dynamics, and spatial econometric models test convergence patterns. The results show that agricultural technological progress in China is predominantly biased toward labor and capital, with labor–land bias being the strongest and continuously increasing. This indicates a gradual shift from land-dependent growth toward more intensive use of non-land inputs under farmland constraints. Regional disparities in technological bias have widened over time, mainly driven by interregional differences and distributional overlap. Kernel density analysis reveals dynamic but largely non-polarized evolution, suggesting gradual adjustment rather than structural divergence. Although no σ-convergence is observed, both absolute and conditional β-convergence exist, with faster convergence in the labor–land dimension and under conditional settings. These findings imply that regions tend to adapt to land constraints through differentiated technological pathways, resulting in uneven improvements in land-related productivity. Overall, biased technological change plays an important role in shaping land use efficiency under resource constraints. The study provides evidence for understanding agricultural adaptation to land scarcity and offers implications for sustainable agricultural development, farmland protection, and long-term food security. Full article

To investigate the dynamics of paralytic shellfish toxins (PSTs) and tetrodotoxins (TTX) in scallops, PSTs and TTX were analyzed in the hemolymph supernatant (hemolymph-S) and digestive gland in Yesso and Akazara scallops cultured in eastern Japan. In Yesso scallops sampled between 22 April 2025 and 21 October 2025, the PST concentrations in the hemolymph-S were 1.6–17% of those in the digestive gland, showing a positive correlation (r = 0.753). However, the PST composition in the hemolymph-S and digestive gland differed; the hemolymph-S composition initially resembled that of laboratory-cultured dinoflagellates, coinciding with typical onset of toxic dinoflagellate blooms in late April. Following this period, the PST composition in the hemolymph-S gradually converged with that of the digestive gland, via chemical transformation in the digestive gland followed by release into the hemolymph. The ratios of 11β-OSO₃H toxins (C2, GTX4, GTX3) to 11α-OSO₃H toxins (C1, GTX1, GTX2), which exist in chemical equilibrium, exhibited a similar trend. TTX was detected in both tissues of Yesso and Akazara scallops collected from 28 August 2025 to 27 January 2026, with the hemolymph-S concentration being 0.5–5.4% of that in the digestive gland. These results suggest that these toxins are sequestered into the digestive gland from the PST-producing dinoflagellates and certain TTX-bearing organisms, and then they partially flow into the hemolymph for circulation throughout the body. Full article