Search Results (688)

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. Although the aetiology of IBD remains largely unknown, several studies suggest that an individual’s genetic susceptibility, external environmental factors, intestinal microbial flora, and immune responses are all factors involved in and functionally linked to the pathogenesis of IBD. Beyond the gastrointestinal manifestations, IBD patients frequently suffer from psychiatric comorbidities, particularly depression and anxiety. It remains unclear whether these disorders arise solely from reduced quality of life or whether they share overlapping biological mechanisms with IBD. This review aims to explore the bidirectional relationship between IBD and depressive disorders (DDs), with a focus on four key shared mechanisms: immune dysregulation, genetic susceptibility, alterations in gut microbiota composition, and dysfunction of the hypothalamic–pituitary–adrenal (HPA) axis. By examining recent literature, we highlight how these interconnected systems may contribute to both intestinal inflammation and mood disturbances. Furthermore, we discuss the reciprocal pharmacologic interactions between IBD and DDs: treatments for IBD, such as TNF-alpha and integrin inhibitors, have demonstrated effects on mood and anxiety symptoms, while certain antidepressants appear to exert independent anti-inflammatory properties, potentially reducing the risk or severity of IBD. Overall, this review underscores the need for a multidisciplinary approach to the care of IBD patients, integrating psychological and gastroenterological assessment. A better understanding of the shared pathophysiology may help refine therapeutic strategies and support the development of personalized, gut–brain-targeted interventions. Full article

In the digital transformation era, understanding the relationship between digital and real economies is vital for regional development. This study analyses the interaction between these two economies in Henan Province using panel data from 18 cities (2011–2023). It incorporates policy support intensity through fuzzy set theory, applies an integrated weighting method to measure development levels, and uses regression models to assess the digital economy’s impact on the real economy. The coupling coordination degree model, kernel density estimation, and Gini coefficient reveal the coordination status and spatial distribution, while the ecological Lotka–Volterra model identifies the symbiotic patterns. The key findings are as follows: (1) The digital economy does not directly determine the state of the real economy. For example, cities such as Zhoukou and Zhumadian have low digital economy levels but high real economy levels. However, the development of the digital economy promotes the real economy without signs of diminishing returns. (2) The two economies are generally coordinated but differ spatially, with greater coordination in the Central Plains urban agglomeration. (3) The digital and real economies exhibit both collaboration and competition, with reciprocal mutualism as the dominant mode of integration. These insights provide guidance for policymakers and offer a new perspective on the integration of both economies. Full article

Polymicrobial biofilms involving fungal and bacterial species are increasingly recognized as contributors to persistent infections, particularly in the oral cavity. Candida albicans and Aggregatibacter actinomycetemcomitans are two commensals that can turn into opportunistic pathogens and are able to form robust biofilms. Objectives: This study aimed to assess the interaction dynamics between these two microorganisms and to evaluate their susceptibility to fluconazole and azithromycin in single- and mixed-species forms. Methods: Biofilm biomass was quantified using crystal violet assays, while biofilm cell viability was assessed through CFU enumeration (biofilm viability assay). To assess the resistance properties of single versus mixed-species coincubations, we applied the antimicrobial susceptibility test (AST) to each drug, and analysed spatial organization with confocal laser scanning microscopy, using PNA-FISH. Results: The results indicated that both species can coexist without significant mutual inhibition. However, a non-reciprocal synergism was also observed, whereby mixed-species biofilm conditions promoted the growth of A. actinomycetemcomitans, while C. albicans growth remained stable. As expected, antimicrobial tolerance was elevated in mixed cultures, likely due to enhanced extracellular matrix production and potential quorum-sensing interactions, contributing to increased resistance against azithromycin and fluconazole. Conclusions: This study provides novel insights into previously rarely explored interactions between C. albicans and A. actinomycetemcomitans. These findings underscore the importance of investigating interspecies interactions within polymicrobial biofilms, as understanding their mechanisms, such as quorum-sensing molecules and metabolic cooperation, can contribute to improved diagnostics and more effective targeted therapeutic strategies against polymicrobial infections. Full article

This study explores how to support Turkish–American secondary school students to co-develop covariational reasoning (CR) and representational fluency (RF) in solving contextually based quadratic function tasks in an after-school community center learning setting. We conducted a teaching experiment (n = 8) at a community center. Ongoing and retrospective analyses of classroom interaction and video transcripts revealed a culturally inclusive mathematics learning environment framework with several intertwined components: co-developing CR and RF and community-based practices. This study provides evidence that students coordinate symbolic, tabular, and graphical representations, which not only deepen their understanding of how quantities change in relation to one another but also enable them to interpret and construct representations in increasingly flexible ways. This reciprocal process of co-developing CR and RF allowed students to recognize and express quantitative relationships as meaningful functional relationships, demonstrating a dynamic interplay between reasoning about change and fluency across representations. This study situates learning within culturally inclusive learning environments and acknowledges the reflexive positionality of the teacher–researcher in relation to students. We highlight how shared community-based practices can enhance mathematics teaching and learning. Full article

Cancer is no longer considered as an isolated event. Rather, it occurs because of a complex biological drive orchestrating different cell types, growth factors, cytokines, and signaling pathways within the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are the most populous stromal cells within the complex ecosystem of TME, with significant heterogeneity and plasticity in origin and functional phenotypes. Very enigmatic cells, CAFs determine the progress and outcomes of tumors through extensive reciprocal signaling with different tumors infiltrating immune cells in the TME. In their biological drive, CAFs release numerous chemical mediators and utilize various signaling pathways to recruit and modulate tumor-infiltrating immune cells. The CAF-induced secretome and exosomes render immune cells ineffective for their antitumor activities. Moreover, by upregulating immune inhibitory checkpoints, CAFs create an immunosuppressive TME that impedes the susceptibility of tumor cells to tumor-infiltrating lymphocytes (TILs). Further, by depositing and remodeling extracellular matrix (ECM), CAFs reshape the TME, which enhances tumor growth, invasion, metastasis, and chemoresistance. Understanding of CAF biology and its crosstalk with tumor-infiltrating immune cells is crucial not only to gain insight in tumorigenesis but to optimize the potential of novel targeted immunotherapies for cancers. The complex relationships between CAFs and tumor-infiltrating immune cells remain unclear and need further study. Herein, in this narrative review we have focused on updates of CAF biology and its interactions with tumor-infiltrating immune cells in generating immunosuppressive TME and resistance to cell death. Full article

Recent breakthroughs in cancer immunotherapy have shown remarkable success, yet treatment efficacy varies significantly among individuals. Emerging evidence highlights the gut microbiota as a key modulator of immunotherapy response, while vitamin D (VD), an immunomodulatory hormone, has garnered increasing attention for its potential interactions with gut microbiota and immunotherapy outcomes. However, the precise mechanisms and clinical applications of VD in this context remain controversial. This study systematically analyzed peer-reviewed evidence from PubMed, Scopus, Web of Science, PsycINFO, and MEDLINE (January 2000–May 2025) to investigate the complex interplay among VD, gut microbiota, and cancer immunotherapy. This review demonstrates that VD exerts dual immunomodulatory effects by directly activating immune cells through vitamin D receptor (VDR) signaling while simultaneously reshaping gut microbial composition to enhance antitumor immunity. Clinical data reveal paradoxical outcomes: optimal VD levels correlate with improved immunotherapy responses and reduced toxicity in some studies yet are associated with immunosuppression and poorer survival in others. The bidirectional VD–microbiota interaction further complicates this relationship: VD supplementation enriches beneficial bacteria, which reciprocally regulate VD metabolism and amplify immune responses, whereas excessive VD intake may disrupt this balance, leading to dysbiosis and compromised therapeutic efficacy. These findings underscore the need to elucidate VD’s dose-dependent and microbiota-mediated mechanisms to optimize its clinical application in immunotherapy regimens. Future research should prioritize mechanistic studies of VD’s immunoregulatory pathways, personalized strategies accounting for host–microbiota variability, and large-scale clinical trials to validate VD’s role as an adjuvant in precision immunotherapy. Full article

Neuropathic pain (NP) is a prevalent clinical condition resulting from diseases or injuries affecting the somatosensory system. Conventional analgesics often exhibit limited efficacy, leading to suboptimal therapeutic outcomes. The pathogenesis of NP is complex and involves multiple mechanisms. The existing evidence suggests that maladaptive neuronal plasticity plays a central role in NP development. Additionally, emerging research highlights the contribution of neuroinflammatory responses mediated by glial cells in the onset of NP and associated sensory hypersensitivity. Among non-invasive neuromodulation techniques, transcranial direct current stimulation (tDCS) has gained prominence as a potential treatment for NP. Numerous studies have demonstrated its analgesic effects; however, the precise regulatory mechanisms remain unclear. The current evidence indicates that tDCS may alleviate NP by enhancing glial–neuronal interactions, which suppress nociceptive signaling pathways and reduce pain sensitivity. The reciprocal modulation between tDCS-mediated anti-inflammatory actions, as evidenced by decreased levels of pro-inflammatory cytokines and increased levels of anti-inflammatory mediators, and its facilitation of adaptive neural plasticity represents a particularly compelling therapeutic axis. This review elucidates inflammatory regulation by tDCS as a fundamental mechanism for NP alleviation, while delineating important unresolved questions regarding these complex interactions. Full article

Background/objectives: The interplay between genetic factors and nutritional patterns is critical in understanding metabolic health. This analysis evaluated the potential reciprocal relationships between the TNF-α -308 G/A gene polymorphism, the Composite Dietary Antioxidant Index (CDAI), and insulin-related variables in Spanish adults with obesity. Methods: A cross-sectional analysis was conducted in 292 adults with obesity. Anthropometric, biochemical, and dietary variables were assessed. TNF-α -308 G/A genotyping was performed. Associations and potential interactions between CDAI and genotype on insulin and homeostatic model assessment for insulin resistance (HOMA-IR) were examined using multivariate regression and two-way ANOVA. Results: Higher CDAI scores were significantly associated with lower insulin levels (p < 0.001) and HOMA-IR (p < 0.001), regardless of genotype. Carriers of the A allele (GA/AA) showed a non-significant trend toward higher insulin levels (p = 0.087) and a steeper decrease in insulin levels with increasing CDAI, with a significant interaction observed between TNF-α genotype and CDAI (interaction p = 0.003). Multivariate analyses confirmed that CDAI and TNF-α genotype were independently associated with insulin and HOMA-IR levels. However, interaction terms were not consistently significant across all models. Conclusions: These findings emphasize the potential of antioxidant-rich diets to help modulate the influence of pro-inflammatory genotypes on insulin resistance, highlighting the relevance of integrating genetic and dietary factors in managing obesity-related metabolic risks. Further studies are warranted to confirm these preliminary findings and to better understand the mechanisms underlying gene–diet interactions in metabolic regulation. Full article

The control of lubricity induced by electric potential is appealing for numerous applications. On the other hand, the high polarity of ionic liquids facilitates the adsorption of equally charged molecules onto polar surfaces. This phenomenon and its consequences are well understood at the nanoscale; however, they have recently garnered significant attention at the macroscale. This study investigates the lubricity of trihexyltetradecylphosphonium dicyanamide, a phosphonium ionic liquid, when used as a neat lubricant in reciprocating sliding under electrically charged conditions. Two different polarities with the same potential were applied to the friction pair of bearing steel against bearing steel while monitoring electrical contact resistance. The lubricity was evaluated through measurements of friction, wear, surface morphology, and composition. It was found that the application of electric potential significantly alters the lubricity of the investigated ionic liquid where a positive potential applied to the ball resulted in the least damaging situation. The recorded electrical contact resistance enabled the monitoring of tribofilm formation during reciprocation. It was found that there was minimal to no separation between interacting surfaces when the ball was changing direction. Full article

This study investigates the dynamic relationship between maritime trade and cultural convergence between China and Saudi Arabia, with a particular focus on the roles of creative goods and information and communication technology (ICT) exports as proxies for sociocultural integration. Utilizing quarterly data from 2012 to 2021, the analysis employs the Toda–Yamamoto Granger causality approach within a Vector Autoregression (VAR) framework. This methodology offers a robust means of testing causality without requiring data stationarity or cointegration, thereby reducing estimation bias and enhancing applicability to real-world economic data. The empirical model examines causal interactions among maritime trade, creative goods exports, ICT exports, and population, the latter serving as a control variable to account for demographic scale effects on trade dynamics. The results indicate statistically significant bidirectional causality between maritime trade and both creative goods and ICT exports, suggesting a reciprocal reinforcement between trade and cultural–technological exchange. In contrast, the relationship between maritime trade and population is found to be unidirectional. These findings underscore the strategic importance of cultural and technological flows in shaping maritime trade patterns. Furthermore, the study contextualizes its results within broader policy initiatives, notably China’s Belt and Road Initiative and Saudi Arabia’s Vision 2030, both of which aim to promote mutual economic diversification and regional integration. The study contributes to the literature on international trade and cultural economics by demonstrating how cultural convergence can serve as a catalyst for strengthening bilateral trade relations. Policy implications include the promotion of cultural and technological collaboration, investment in maritime infrastructure, and the incorporation of cultural dimensions into trade policy formulation. Full article

The agricultural products trade network is essentially a complex adaptive system formed by nonlinear interactions between countries. Based on the complex system theory, this study reveals the dynamic self-organization law of the RCEP regional agricultural products trade network by using the panel data of RCEP agricultural products export trade from 2000 to 2023, combining social network analysis (SNA) and the temporal exponential random graph model (TERGM). The results show the following: (1) The RCEP agricultural products trade network presents a “core-edge” hierarchical structure, with China as the core hub to drive regional resource integration and ASEAN countries developing into secondary core nodes to deepen collaborative dependence. (2) The “China-ASEAN-Japan-Korea “riangle trade structure is formed under the RCEP framework, and the network has the characteristics of a “small world”. The leading mode of South–South trade promotes the regional economic order to shift from the traditional vertical division of labor to multiple coordination. (3) The evolution of trade network system is driven by multiple factors: endogenous reciprocity and network expansion are the core structural driving forces; synergistic optimization of supply and demand matching between economic and financial development to promote system upgrading; geographical proximity and cultural convergence effectively reduce transaction costs and enhance system connectivity, but geographical distance is still the key system constraint that restricts the integration of marginal countries. This study provides a systematic and scientific analytical framework for understanding the resilience mechanism and structural evolution of regional agricultural trade networks under global shocks. Full article

Variable-speed reciprocating compressors (VSRCs) have been increasingly used in domestic refrigeration due to their ability to modulate cooling capacity and reduce energy consumption. A detailed understanding of performance-limiting factors such as volumetric and exergetic inefficiencies is essential for optimizing their operation. An experimentally validated simulation model was developed using GT-SUITE to analyze a VSRC operating with R-600a across speeds from 1800 to 6300 rpm. Volumetric inefficiencies were quantified using a stratification methodology, while an exergy-based approach was adopted to assess the main sources of thermodynamic inefficiency in the compressor. Unlike traditional energy analysis, exergy analysis reveals where and why irreversibilities occur, linking them directly to power consumption and providing a framework for optimizing design. Results reveal that neither volumetric nor exergy efficiency varies monotonically with compressor speed. At low speeds, exergetic losses are dominated by the electrical motor (up to 19% of input power) and heat transfer (up to 13.5%). Conversely, at high speeds, irreversibilities from fluid dynamics become critical, with losses from discharge valve throttling reaching 5.8% and bearing friction increasing to 6.5%. Additionally, key volumetric inefficiencies arise from piston–cylinder leakage, which causes up to a 4.5% loss at low speeds, and discharge valve backflow, causing over a 5% loss at certain resonant speeds. The results reveal complex speed-dependent interactions between dynamic and thermodynamic loss mechanisms in VSRCs. The integrated modeling approach offers a robust framework for diagnosing inefficiencies and supports the development of more energy-efficient compressor designs. Full article

The statistical mechanics of structured particles with arbitrary size and shape adsorbed onto discrete lattices presents a longstanding theoretical challenge, mainly due to complex spatial correlations and entropic effects that emerge at finite densities. Even for simplified systems such as hard-core linear k-mers, exact solutions remain limited to low-dimensional or highly constrained cases. In this review, we summarize the main theoretical approaches developed by our research group over the past three decades to describe adsorption phenomena involving linear k-mers—also known as multisite occupancy adsorption—on regular lattices. We examine modern approximations such as an extension to two dimensions of the exact thermodynamic functions obtained in one dimension, the Fractional Statistical Theory of Adsorption based on Haldane’s fractional statistics, and the so-called Occupation Balance based on expansion of the reciprocal of the fugacity, and hybrid approaches such as the semi-empirical model obtained by combining exact one-dimensional calculations and the Guggenheim–DiMarzio approach. For interacting systems, statistical thermodynamics is explored within generalized Bragg–Williams and quasi-chemical frameworks. Particular focus is given to the recently proposed Multiple Exclusion statistics, which capture the correlated exclusion effects inherent to non-monomeric particles. Applications to monolayer and multilayer adsorption are analyzed, with relevance to hydrocarbon separation technologies. Finally, computational strategies, including advanced Monte Carlo techniques, are reviewed in the context of high-density regimes. This work provides a unified framework for understanding entropic and cooperative effects in lattice-adsorbed polyatomic systems and highlights promising directions for future theoretical and computational research. Full article

Background/Objectives: In contemporary nursing education, clinical competence and psychological resilience are both essential; however, they are often treated as separate outcomes. Clinical placements are a central component of nursing education, and often expose students to high levels of stress, emotional challenges, and complex clinical demands. Building both clinical competence and psychological resilience during this phase is crucial to preparing students for the realities of professional practice. This narrative review, grounded in Bandura’s social cognitive theory (SCT), explores how educator behaviors, teaching strategies, and learning environments interact to influence both domains in undergraduate nursing students. Methods: A comprehensive search was conducted in PubMed, CINAHL, and PsycINFO for peer-reviewed articles published between 1 January 2000 and 2 May 2025. Relevant studies were thematically analyzed and were guided by Bandura’s SCT constructs, including observational learning, self-efficacy, and reciprocal determinism. No formal study appraisal was conducted due to the narrative nature of the review. Findings: Nineteen studies were included in the review. The findings highlight that reflective practices, structured feedback, peer learning, and strategies to build self-efficacy are central to building resilience and competence. Supportive educator behaviors such as mentoring, emotional support, and professional role modeling, were strongly associated with increased student confidence, emotional regulation, and adaptability. Psychologically safe clinical learning environments further enhanced self-efficacy and active engagement. In contrast, unsupportive or inconsistent environments were linked to student stress, disengagement, and reduced performance. Conclusions: This review highlights the need to move beyond traditional competency-based models toward an integrated approach that equally values psychological preparedness and resilience. Findings suggest a shift toward emotionally and socially integrated clinical education. Full article

Metabolic dysregulation involving glucose and lipids is closely associated with chronic diseases such as type 2 diabetes mellitus. Emerging evidence highlights the regulatory role of bile acid (BA)–gut microbiota interactions in these metabolic disorders. The gut microbiota orchestrates the biotransformation of primary BAs into bioactive secondary BAs, which function as endocrine signaling molecules by activating the nuclear farnesoid X receptor (FXR) and G protein-coupled membrane receptor (TGR5), forming a communication network essential for metabolic homeostasis. BAs also reciprocally modulate gut microbiota composition. This BA–gut microbiota co-metabolism has emerged as a promising therapeutic target for lipid metabolism disorders. This comprehensive review examines the bidirectional interplay between gut microbiota and BA metabolism, focusing on microbial transformation of BAs, host–microbial co-regulatory pathways and mechanisms of BA metabolism, and the therapeutic implications of modulating the gut microbiota–BA axis in addressing glucose and lipid metabolism disorders. The synthesis of current evidence aims to elucidate the intricate crosstalk between microbial ecology and host metabolism mediated by BA signaling pathways, thereby exploring novel therapeutic intervention strategies. Full article