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Background and Objectives: Potential anti-neoplastic effects of resveratrol, which has antioxidant features combined with clomipramine, which has antineoplastic features, or with gemcitabine, used as a nucleoside analog widely used in chemotherapy, were evaluated together and individually on the HL-60 leukemia cells in this in vitro screening study. Materials and Methods: HL-60 cells were treated with gemcitabine, clomipramine, resveratrol, or their combinations at concentrations ranging from 1 to 200 µM. Cell viability was assessed at 24, 48, and 72 h using the trypan blue exclusion method, and results are expressed as a percentage of time-matched untreated controls. Cell proliferation was further evaluated by bromodeoxyuridine (BrdU) immunohistochemical labeling. All experiments were performed in triplicate, and statistical analyses were conducted using one-way analysis of variance (ANOVA) with post hoc comparisons. Results: Gemcitabine markedly reduced HL-60 cell viability at all concentrations and time points (p < 0.001), indicating strong time-dependent cytotoxicity, with a significant drop in BrdU proliferation index at 48 h (p < 0.001). Clomipramine exhibited a biphasic response: high concentrations decreased viability (p < 0.05), while low concentrations allowed partial recovery by 72 h. Resveratrol showed concentration-dependent cytotoxicity, with reduced viability at high concentration and near-control levels at low concentration by 72 h; BrdU indices remained significantly lower than control (p < 0.001). Combination treatments with gemcitabine showed no additive cytotoxic or antiproliferative effects (p > 0.05). A transient enhanced effect was observed in the clomipramine + resveratrol group at 24 h (p < 0.01 vs. clomipramine; p < 0.05 vs. gemcitabine). Conclusions: Gemcitabine, clomipramine, and resveratrol all exhibited inhibitory effects on cell proliferation in HL-60 cell cultures. However, the combination treatments did not show additional cytotoxicity or additive effects. These findings suggest that while each of these compounds individually has the potential to inhibit cell growth, their combined application does not enhance the cytotoxic effects beyond those observed with single treatments. These findings highlight the necessity of a rational approach when considering novel drug combinations. Full article

Palmitic acid (PA), the most abundant saturated fatty acid in the human body, is implicated in lipotoxicity under hyperlipidemic conditions, with potential consequences for bone metabolism. To investigate its impact on developing bone tissue, this study used an ex vivo organotypic embryonic chick femur model, exposing femora to control (0 µM), low (50 µM), and high (200 µM) PA concentrations. A multimodal approach, integrating microtomographic, histochemical, ultrastructural, and gene expression analyses, was used to assess tissue architecture, matrix composition, mineralization, and molecular adaptations. PA exposure significantly reduced longitudinal femoral growth, as evidenced by decreased femoral length and tissue volume. Gene expression analysis revealed reduced expression of selected osteogenic differentiation-related markers, including RUNX2, BMP2, and SPP1. However, COL1A2 expression was upregulated, correlating with increased collagenous matrix deposition and enhanced mineralization in PA-treated groups. Alcian blue staining further suggested reduced proteoglycan-rich cartilage matrix, particularly at 200 µM PA. Additionally, PA modulated the expression of both pro-inflammatory and anti-inflammatory mediators, along with increased autophagy-associated responses, as suggested by the upregulation of autophagy-related genes and the presence of autophagosomes and autolysosomes. These findings indicate that PA does not simply exert a deleterious effect on bone tissue but rather redirects the developmental trajectory of the organotypic femur by reducing longitudinal growth while promoting collagen-rich matrix maturation and mineral compaction. This response may involve altered cartilage-associated endochondral processes, fatty-acid-driven metabolic adaptation, osteoblast/osteocyte maturation, and autophagy-associated matrix processing under lipid-enriched conditions. Full article

Understanding pathological processes remains challenging, because clinical descriptions still rely predominantly on phenotypic observations, while the underlying dynamical mechanisms that generate, maintain, and transform pathological conditions often remain implicit. This Perspective article introduces forms dynamics as a physically grounded framework for interpreting pathology as the dynamical evolution of structured configurations sustained by continuous exchanges of energy, mass, and regulatory information with the environment. The proposed perspective integrates concepts from non-equilibrium thermodynamics, complex systems modeling, systems ecology, and Gestalt-inspired structural reasoning. Within this framework, pathological systems are represented through physically meaningful state variables and fluxes whose interactions can be expressed through coupled balance equations or equivalent graphical schematizations. Empirical observations, including clinical data, diagnostic measurements, and network-based representations of biological interactions, guide the identification of relevant variables, pathways, and couplings. Calibration and validation are discussed as procedures through which admissible dynamical regimes are constrained using physiological ranges, characteristic timescales, observed trajectories, and responses to perturbations. In this perspective, physiological and pathological conditions are interpreted as dynamically maintained regimes emerging from the coupling of variables and fluxes rather than as purely static structural states. As a foundational contribution, this article does not present a disease-specific case study but establishes the conceptual basis, illustrative mathematical structure, and operational workflow through which future disease-specific implementations may be developed. In this sense, forms dynamics is proposed as a unifying modeling perspective for complex diseases and as a possible foundation for future translational applications, including physics-informed digital twins and more interpretable computational tools for biomedical research and clinical support. Full article

In this study, density functional theory (DFT)-based investigations are carried out using the CASTEP code. The plane-wave pseudopotential method is used to explore the multifunctional properties, including the structural, electronic spectra, thermo-mechanical and hydrogen storage properties, of hydrogen-rich mixed-anionic (Li₃H₄N₂X, where X = F, Cl, Br, and I) halides. The exchange–correlation interactions are treated within the generalized gradient approximation (GGA) using the Perdew–Burke–Ernzerhof (PBE) functional, while the hybrid HSE06 function is used for accurate band gap predictions. Moreover, the optical properties of the halides are analyzed under the influence of UV–Vis radiation instances. The band gap values of these orthorhombic-structured halides lie in the visible-to-UV regions of radiation, with values of 2.97 eV, 3.12 eV, 3.06 eV and 3.28 eV, respectively. Such band gap values allow these materials to absorb nearly 75% to 90% of incoming radiation, with absorption values around (10⁵ cm⁻¹). These favorable opto-electronic responses make these halides suitable for solar radiation energy conversion applications. Stable thermodynamic responses and the mechanical nature of the mixes (brittle for Li₃H₄N₂Br and ductile for the rest) reveal their practical applicability for flexible photonics. Moreover, due to the presence of rich hydrogen atoms, the Li₃H₄N₂F halide exhibits a gravimetric ratio of around 6.0 wt%, which is higher than the standard (5.5 wt%) value defined by the US DOE. Similarly, GHSC values of 2.5 wt% for Li₃H₄N₂I, 3.5 wt% for Li₃H₄N₂Br, and 5.0 wt% for Li₃H₄N₂Cl are reported; these values indicate that these compounds possess strong potential for use in the hydrogen fuel cells required in light-duty vehicles. Full article

The reliability of hygrothermal models depends on the quality of their inputs. Conventionally, thermal and moisture properties are treated as temperature-independent, yet previous studies have shown that many of these properties are temperature-dependent. This paper investigates the impact of using temperature-dependent material properties on hygrothermal simulation results compared to standard temperature-independent properties at the building envelope level. A representative exterior wood-frame wall assembly is modelled with constant material properties, including water vapour permeability, sorption isotherm, and water absorption coefficient corresponding to values measured at 3 °C, 21 °C, and 45 °C, as well as a case in which the properties vary with temperature. The variation in hygrothermal response is evaluated under several scenarios, including different climates (Toronto and Vancouver, Canada), cladding types (fibre cement and stucco), sheathing materials (oriented strand board (OSB) and plywood), and with and without rain-penetration load. Results indicate that the variation attributed to temperature-dependent material properties was greater for Vancouver than for Toronto and increased with rain penetration. In particular, the choice of cladding seemed to have a greater impact than the choice of sheathing material, with stucco showing greater differences than fibre cement. Overall, however, the temperature at which material properties are defined has a minimal impact on hygrothermal simulation results and wall performance assessments, with maximum hourly differences in sheathing moisture content (MC) differences ranging from 1.18 to 4.32 wt% without rain penetration. These findings demonstrate that the use of temperature-dependent material properties does not have a significant impact on the hygrothermal simulation results or the performance assessment of exterior wood-frame wall assemblies. Full article

This article discusses rheumatoid arthritis (RA) as a chronic, systemic autoimmune disease leading to progressive joint damage and multi-organ complications. The complex pathogenesis of the disease is presented, involving the interaction of environmental, genetic, and immunological factors, including the role of autoantibodies and proinflammatory cytokines. Particular attention is paid to leflunomide, a disease-modifying antirheumatic drug (DMARD), which primarily works by inhibiting the DHODH enzyme, leading to reduced T and B cell proliferation. The additional anti-inflammatory properties of the drug’s active metabolite, teriflunomide, and its impact on signaling pathways related to the immune response are also discussed. This article examines the variability in patient responses to leflunomide treatment in terms of both efficacy and toxicity, with particular emphasis on the potential role of pharmacogenetic factors. It was pointed out that polymorphisms in genes related to drug metabolism, transport, and mechanism of action may influence the pharmacokinetics and safety of the therapy. It was also emphasized that the available data are primarily derived from observational studies and small cohorts, and the results are often inconsistent. Although some genetic variants and plasma teriflunomide concentrations show potential as predictors of treatment response, the current level of evidence does not support the routine use of pharmacogenetic testing in clinical practice. The article emphasizes that the pharmacogenetics of leflunomide represents a promising, yet still exploratory, avenue of research in the context of personalized RA therapy. It emphasizes the need for larger, well-designed clinical trials and the development of standardized guidelines, which would be necessary before the potential implementation of such strategies in routine clinical practice. Full article

As a non-pathogenic oomycete, Pythium oligandrum possesses unique advantages, particularly in the context of being a biological control agent. With the increasing awareness of consumer consciousness, people are paying more attention to the use of environmentally friendly strategies in plant disease prevention and control. Pythium oligandrum is a type of biocontrol oomycete that can be developed as a biological control agent, and it does not have adverse effects on humans in the prevention and control of plant diseases. Consequently, there is increasing scientific interest in the beneficial plant–microbe interactions mediated by P. oligandrum. Currently, the main points of focus regarding the beneficial role of P. oligandrum in plant interactions are as follows: (i) P. oligandrum can activate plant defense responses and cause plants to produce resistance, thus protecting them from disease attacks; (ii) it is a strong mycoparasite that can coil around various oomycetes and fungi, directly killing pathogenic microorganisms; (iii) in addition, it can also promote plant growth. In this paper, we will discuss the aforementioned three main features in detail. Full article

Vulnerability management (VM) is becoming increasingly important as organizations face growing cybersecurity threats. This study examines how organizations adapt their vulnerability management routines in response to evolving vulnerability signals through the integration of artificial intelligence (AI) and automation. Drawing on data from an international fast-moving consumer goods (FMCG) company, we investigate how human expertise and AI interact across the full VM process, from triage to remediation. Using Organizational Routine Theory (ORT), we show that AI does not simply automate tasks but acts as a co-performer, influencing how decisions are made, work is coordinated, and actions are adapted. We develop a three-phase model capturing (1) the integration of AI-enabled automation into strained routines, (2) the manifestation of tensions between human expertise and automation as well as between usability and system complexity, and (3) the stabilization of hybrid routines through iterative adaptation and feedback loops. We identify two key tensions in this process: technology versus human expertise, and usability versus the complexity of multi-vendor tools. These tensions create frictions in practice but also open opportunities for learning and improvement. Rather than treating AI as a technical tool, our findings highlight its role as an active routine participant. Importantly, we show that routine evolution enables organizations to improve how vulnerability signals are interpreted and acted upon, thereby supporting more coordinated and adaptive cybersecurity practices. This has both theoretical implications for understanding how routines evolve with technology and practical relevance for improving adaptive cybersecurity practices. By linking micro-level routine dynamics to broader organizational outcomes, this study contributes to explaining how organizations sustain stable and adaptive operations under conditions of continuous cyber threat exposure. Full article

With the continued rise in outpatient surgical procedures, modern medicine requires more advanced tools for pain and anxiety monitoring and management. The current standard of care requires patient responses on visual analog scales, which may be subjective and are difficult to assess when a subject is unresponsive. Electrodermal activity (EDA) and pulse rate variability (PRV), two non-invasive, wearable, and objective measurements of sympathetic nervous system activity, can help provide insight into a patient’s psychological or emotional state without user input, allowing for continued monitoring even when a patient is unable to respond. However, methods based on these measurements have largely been relegated to longer duration (>60 s) or post hoc analysis, which does not suit the needs of medical care environments. Here we propose new methods for handling ultra-short (<10 s) signals to allow rapid evaluation of pain and anxiety state. We show how machine learning models trained on these signals can obtain high degrees of classification performance (AUC > 0.88) between no pain or anxiety and medium or higher pain and anxiety on signals obtained during two different forms of painful stimulation. We also show how these signals can measure the degree of stimulation irrespective of perceived pain from the patient. Further development of these algorithms will allow for greater monitoring and control of patient comfort in a clinical setting. Full article

Artificial intelligence (AI) is transforming the modern workplace by offering unprecedented opportunities to enhance employee creativity and organizational innovation. In the context of digital transformation, organizations are striving to ensure sustainable performance; however, research remains limited on how perceived AI fairness and attitudes toward AI jointly influence creativity. Grounded in Social Exchange Theory and the Technology Acceptance Model, this study proposes a moderated mediation model to examine how perceived AI fairness shapes employees’ attitudes toward AI and, in turn, their creativity, with gender acting as a moderator of the relationship between fairness perceptions and attitudes toward AI. Data were collected from 214 highly skilled employees from diverse cultural backgrounds working in technologically advanced environments. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings reveal a positive association between perceived AI fairness and creativity. Attitudes toward AI partially mediate this relationship; however, gender does not exert a significant moderating effect. The findings highlight the importance of AI fairness, reinforced by positive attitudes toward AI, in enhancing employee creativity. They also underscore the need for responsible and equitable AI practices and provide context-specific insights into the ethical challenges of AI in socio-technologically vulnerable environments. Finally, the findings point to a shift toward a more egalitarian and inclusive organizational landscape, in which gender differences become less salient in the context of digital transformation. Full article

Loading fluctuations and fatigue-related structural demand under turbulent wind conditions are important factors that limit the reliability of small wind turbines. This study investigates the separate effects of turbulence intensity and pitch angle on a 5 kW distributed variable-pitch wind turbine prototype using an OpenFAST-based aeroelastic model validated against field measurements. Under the adopted simulation setup and selected operating conditions, increasing turbulence intensity from 5% to 20% leads to a pronounced increase in the extreme blade-root flapwise bending moment and a substantial reduction in the estimated comparative fatigue life. The analysis also reveals a clear trade-off between aerodynamic efficiency and structural durability: among the tested pitch settings, the 6° case yields the highest power output, but also exhibits the largest load fluctuations and the shortest estimated comparative fatigue life. Adjusting the pitch angle to 0° or 12°, while reducing power to some extent, alleviates fatigue-related structural demand and increases the estimated comparative fatigue life. Overall, the results provide a validated prototype-level comparative assessment of how turbulence intensity and pitch angle influence aerodynamic performance, structural response, and fatigue-related demand in the studied turbine. Because the present work focuses on one prototype and does not include cross-turbine comparison or a full stochastic convergence study, the reported quantitative results should not be interpreted as directly generalizable to other turbine configurations. These findings may nevertheless provide a useful basis for future studies on load-aware pitch regulation under turbulent inflow. Full article

This study investigates the short-term and long-term impacts of gross domestic product (GDP), inflation, foreign capital flows, trade balance and interest rate on stock market performance in Saudi Arabia for the period 1990–2023. The autoregressive distributed lag (ARDL) approach and error correction model (ECM) are employed to empirically examine the short-run and long-run relationships. The ARDL-ECM technique is effective for analyzing cointegration and assessing adjustment processes. Additionally, impulse response function (IRF) analysis based on the vector autoregression (VAR) model, estimated using these macroeconomic indicators, is applied in this paper. This study provides novel insights and addresses emerging gaps in the literature concerning Saudi Arabia as a developing economy. The long-term relationship in the bounds test results confirms its existence. In the long run, inflation and interest rate exert a statistically significant negative effect on stock market performance, while the trade balance has a significant positive impact. GDP and foreign capital inflows do not exhibit statistically significant long-run effects. Short-run dynamics indicate persistence in stock market performance along with significant effects from inflation and interest rate changes, while GDP and foreign capital inflows remain statistically insignificant in the long-run scenario. Forecast error variance decomposition (FEVD) results show that approximately 68.5% of the variation in market performance is explained by its own shocks, followed by foreign capital flows (16.3%) and inflation (8.4%). While foreign capital flow does not exhibit statistical significance in the ARDL long-run estimates, its contribution in variance decomposition highlights its role as an important source of external shocks. These findings are relevant to various stakeholders, including investors and policymakers. Additionally, policy emphasis should be placed on controlling inflation and maintaining stable interest rates while improving trade balance conditions. Although foreign capital flow does not show a direct long-run effect, its role in influencing market variability suggests the need for a stable and well-regulated investment environment. Full article

Motivated by the requirements for wide field-of-view (FOV) reception in underwater wireless optical communication (UWOC) systems, this study investigates the performance of multi-faceted receivers based on various regular polyhedral geometries. A truncated Gumbel minimum distribution model with geometric boundary constraints is proposed in order to characterize the statistical properties of the minimum incidence deflection angle associated with the selected receiving facet. Numerical simulations demonstrate that the proposed model effectively captures the angular response characteristics of multi-faceted receivers, with the root mean square error (RMSE) of the fitted cumulative distribution function (CDF) below $2.2\times {10}^{-2}$ for all regular polyhedral structures. Furthermore, this paper evaluates the effects of different polyhedral structures and receiver FOVs on the bit error rate (BER) and outage probability. The results further show that system performance does not vary monotonically with the number of receiving facets. Under the constraints of the same total effective detection area and unified system parameters, the dodecahedral structure achieves the best performance in terms of average BER and outage probability, followed by the cube, whereas the icosahedral structure exhibits the worst performance. Taking typical link distances of 35–40 m as an example, the average BER of the dodecahedral structure is approximately one order of magnitude lower than that of the icosahedral structure. These findings provide design guidance for the structural design and parameter optimization of multi-faceted receivers in UWOC systems. Full article

Employees’ voice is an important source of organizational learning and adaptive change. As algorithmic management is increasingly applied across organizational management processes, an urgent practical question arises: Does it affect employees’ participation in organizational improvement through voice? To address this challenge, drawing on signaling theory, this study examines the differential effects of distinct dimensions of algorithmic management on voice, while also considering work locus of control as a key moderating variable. We collected one-to-one matched data from 351 employees and their supervisors in a large Chinese platform-based enterprise. We tested the hypothesized theoretical model using structural equation modeling and bootstrapping procedures. The results show that algorithmic feedback enhances employees’ felt responsibility for constructive change, which in turn promotes employees’ voice. In contrast, algorithmic directing, algorithmic scheduling, and algorithmic monitoring undermine employees’ felt responsibility for constructive change and thereby inhibit voice. In addition, work locus of control moderates these relationships: employees with an external work locus of control strengthen the negative effects of algorithmic directing, algorithmic scheduling, and algorithmic monitoring, whereas employees with an internal work locus of control strengthen the positive effect of algorithmic feedback. These findings deepen our understanding of how different dimensions of algorithmic management shape voice and offer practical insights for fostering voice in contexts characterized by algorithmic management. Full article

In this study, the degree and characteristics of sedation were assessed using the Grint scale for azaperone and acepromazine in 24 dogs, with the effects on heart rate and systemic blood pressure evaluated simultaneously using oscillometry. Posture, palpebral reflex, eye position, relaxation, response, postural resistance, attitude, systolic pressure, diastolic pressure, mean arterial pressure, and heart rate were analyzed using linear mixed-effects models to evaluate the effects of treatment, time, and their interaction. Significant effects of time were observed for all variables (p < 0.001), including systolic, diastolic, and mean arterial pressure, whereas heart rate was not significantly affected by treatment. Based on these results, we conclude that azaperone produces moderate sedation at 20 min after administration, and it does not induce bradycardia or clinically significant hypotension. Full article