Search Results (82,823)

Higher Education Institutions (HEIs) are increasingly recognized as strategic contributors to a sustainable society. Although sustainable procurement is widely acknowledged as a key mechanism for advancing sustainability goals, many HEIs encounter persistent barriers to its effective implementation. Within the academic research, sustainable procurement in HEIs is a largely overlooked topic. This study explores an often neglected perspective: the experiences of staff-level employees involved in procurement processes. Through focus group research conducted among staff members at five universities of applied sciences in the Netherlands, we identified barriers at the organizational and functional levels. Findings underscore the critical importance of (other) top management priorities, financial considerations and the lack of clear goals and guidelines for implementing sustainable procurement. Focus group participants identified the invisibility of sustainable procurement’s impact as a key challenge in generating buy-in and enthusiasm among colleagues. This invisibility is closely linked to difficulties in measurement and to inadequate monitoring systems. In addition, contract and supplier management appear to be blind spots within HEIs. Staff-level employees feel that they could greatly benefit from the experiences of peers in other institutions. The results of this study highlight untapped potential for advancement in both professional practice and academic research. Full article

Metabolic stress caused by lipid overload is a key driver of cellular dysfunction in aging and disease. Excess saturated fatty acids such as palmitate impair fatty acid oxidation (FAO), promote lipid accumulation, and increase reactive oxygen species (ROS), ultimately triggering premature senescence-like states. Senescence further amplifies vulnerability by worsening mitochondrial dysfunction, enhancing lipid imbalance, and sustaining pro-inflammatory signaling. Here, we investigated the role of the neuron-enriched RNA-binding protein HuD (ELAVL4) in protecting cells against lipotoxic stress. Using Neuro2a neuroblastoma cells, we found that HuD knockdown suppressed FAO, leading to increased lipid accumulation and elevated ROS following palmitate exposure. HuD-deficient cells also exhibited cytosolic mitochondrial DNA release, IRF phosphorylation, and upregulation of senescence markers. Mechanistically, RNA immunoprecipitation revealed that HuD binds directly to PPARα mRNA, sustaining its expression by competing with the PPARα-targeting microRNAs miR-9-5p and miR-22-3p. Loss of HuD reduced PPARα levels, thereby weakening the FAO capacity and sensitizing cells to palmitate-induced lipotoxic stress. These findings identify a previously unrecognized HuD–PPARα–FAO axis that restrains metabolic stress and senescence. By linking post-transcriptional regulation to lipid metabolism and inflammatory signaling, this work highlights stress-induced premature senescence as both an outcome and a propagator of metabolic dysfunction, providing insight into mechanisms of aging-related vulnerability. Full article

The Four-Leg Three-Phase Voltage Source Inverter (4LVSI) is a versatile solution for integrating renewable energy sources (RESs) into distribution networks, as it compensates unbalanced voltages and currents while providing a path for zero-sequence components. Accurate current control is essential to ensure power quality and reliable operation under these conditions. Conventional controllers such as proportional–integral, resonant, or feedback-linearization methods achieve acceptable tracking under static dc-link conditions, but their performance degrades when dc-link voltage dynamics arise due to renewable-source fluctuations. This paper proposes a data-driven model reference neural control (MRNC) strategy for a four-leg inverter connected to RESs, explicitly accounting for dc-link voltage variations. The proposed controller reformulates the classical Model Reference Adaptive Control (MRAC) as a lightweight single-layer neural network whose adaptive weights are updated online using the Recursive Least Squares (RLS) algorithm. In this framework, the dc-link variations are not modeled explicitly but are implicitly learned through the data-driven adaptation process, as their influence is captured in the neural network regressors formed from real-time input–output measurements. This allows the controller to continuously identify the inverter dynamics and compensate the effect of dc-link fluctuations without requiring additional observers or prior modeling. The proposed approach is validated through detailed time-domain simulations and real-time Hardware-in-the-Loop (HIL) experiments implemented at a 10 kHz switching frequency. The results indicated that the RLS-based MRNC controller achieved the lowest steady-state current error, reducing it by approximately 1.85% and 1% compared to the Proportional-Resonant (PR) and One-Step-Ahead (OSAC) controllers, respectively. Moreover, under dc-link voltage variations, the proposed controller significantly reduced the current overshoot, achieving decreases of 5.9 A and 6.36 A relative to the PR controller. Full article

Environmental lead (Pb) exposure remains a significant public health concern, and its association with cerebrovascular injury and Alzheimer’s disease (AD) is increasingly recognized. In this study, we demonstrated using an in vitro system that Pb exposure significantly increased the expression and release of endothelial plasminogen activator inhibitor-1 (PAI-1). A conditioned medium collected from Pb-treated endothelial cells induced the formation of complement component 3 (C3)⁺ decorin⁺ A1-like astrocytes, which had been shown to be specifically associated with vascular amyloid. Immunoprecipitation with the PAI-1 antibody to remove PAI-1 from the culture medium, or treatment of endothelial cells with PAI-1 inhibitors, significantly inhibited the formation of C3⁺ decorin⁺ A1-like astrocytes. Furthermore, in vivo studies further supported this finding, indicating that lead does indeed increase the number of perivascular C3⁺ decorin⁺ A1-like astrocytes, and that the PAI-1 inhibitor blocked this induction. Building upon our previous findings, we demonstrate that lead exposure may induce cerebral amyloid angiopathy (CAA) pathology through the formation of C3⁺ decorin⁺ A1-like astrocytes mediated by endothelial cell PAI-1. Our results strongly suggest that PAI-1 is a key mediator linking endothelial stress and lead-induced vascular amyloidosis pathology. Full article

Background: Keloids can extend beyond the boundaries of the original wound and often cause itching or pain. Although the skin microbiome is known to influence various skin conditions, it is still unclear how the microbiota inside keloid tissues differ between active and inactive stages. Methods: We enrolled 43 patients with active keloids and 20 patients with inactive lesions. Tissue samples were collected from keloids and from nearby normal skin. In active lesions, both the relatively unstable and stable regions were also sampled. Microbial composition and predicted functions were analyzed using 16S Ribosomal RNA (rRNA) sequencing and standard bioinformatic approaches. Results: Active keloids exhibited a distinct microbial profile compared to normal skin. Acinetobacter and Pseudomonas were more abundant in active lesions, while Cutibacterium was more common in normal skin. Functional prediction also indicated changes in lipid-related pathways in active lesions. In contrast, inactive keloids showed no significant differences from normal skin, and different regions within active lesions had similar microbial features. Conclusions: This study indicates that alterations in the microbiota are linked to the activity of keloids. Potential microbiome-based translational pathways should be explored for monitoring and managing keloid activity in the future. Full article

High-strength bolted connections are fundamental load-bearing components in critical engineering infrastructures such as wind turbines, bridges, and heavy machinery. Under complex service environments involving dynamic loading, vibration, corrosion, and temperature variations, bolts are prone to interacting failure mechanisms, including fatigue fracture, corrosion-assisted cracking, hydrogen embrittlement, and progressive preload loss, which pose significant challenges for reliable condition monitoring and early fault diagnosis. This review provides a structured synthesis of recent advances in bolt health monitoring and intelligent fault diagnosis. A unified framework is established to link multi-physics failure mechanisms with multi-modal sensing technologies and data-driven diagnostic methods. Key sensing approaches—such as piezoelectric impedance techniques, ultrasonic phased array inspection, and computer vision-based monitoring—are critically reviewed in terms of their physical principles, diagnostic capabilities, and limitations. Furthermore, the transition from traditional model-based and signal-processing-driven methods to machine learning- and deep learning-based approaches is examined, with emphasis on multi-modal data fusion, real-time monitoring, and lifecycle-oriented health management enabled by IoT and digital twin technologies. Finally, key challenges and future research directions toward robust and scalable intelligent bolt health management systems are outlined. This review’s primary contribution lies in establishing a novel, integrated framework that links failure physics to sensing and diagnosis, thereby providing a structured roadmap for transitioning from isolated component monitoring to lifecycle-oriented, intelligent health management systems for critical bolted connections. Full article

Rural freight mobility and logistics face persistent challenges, including inadequate road infrastructure, high transportation costs, safety risks, tolls at link access points, and dispersed demand. Traditional inventory routing models often fail to address these complexities, especially in rural contexts where alternative routing options and integrated in-haul/back-haul operations are essential for improving efficiency and reducing empty miles. This study proposes a bi-objective mathematical model for the inventory routing problem in rural logistics, incorporating multiple routing attributes (transportation costs, risks, link-access tolls, and distances) and inventory dynamics (integrated in-haul and back-haul visits). The model aims to minimize total logistics costs and accident risk while balancing operational expenses and safety considerations. Risk estimation is derived from crash data along rural road links connecting distribution nodes. A real-world case study involving Walmart distribution centers in Macclenny, Baker County, Florida, and several rural Supercenters is conducted to validate the model. A modified Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is developed and compared with CPLEX for solution efficiency across small and large-scale problem instances. Results indicate that the proposed approach outperforms classical methods, improves routing decisions in rural logistics systems, and achieves cost savings of up to 17% for the evaluated objectives, emphasizing the importance of using multi-attribute, multi-route network structures in rural logistics optimization. Full article

Postprandial inflammation, characterized by elevated cytokines, is linked to metabolic diseases. Polyphenol-rich fruits like strawberries possess anti-inflammatory properties that may help reduce this response. Because clinical studies are often costly and time-consuming, this study aimed to develop an in vitro model using whole blood to examine the effect of bioactive components such as polyphenols on postprandial inflammation. Whole blood from healthy adults was exposed to lipopolysaccharides (LPS) and high glucose concentrations (250/500 mg/dL), as well as strawberry extract (100 ng/mL). Cytokines (interleukin-6 and -1 beta; IL-6, IL-1β, and Tumor Necrosis Factor-alpha; TNF-α) were quantified using the Luminex multiplex assay. High glucose levels caused non-significant increases in IL-6 (p > 0.05), while strawberry extracts significantly reduced LPS-induced cytokines (p < 0.05). These findings demonstrate the potential of using whole blood in vitro systems to model inflammation and to explore the anti-inflammatory effects of fruit components such as polyphenols from strawberries. Full article

Precision nutrition has emerged as a promising strategy for the prevention of type 2 diabetes mellitus (T2DM) by targeting molecular pathways underlying insulin resistance and impaired glucose metabolism. Accumulating evidence indicates that dietary patterns, caloric intake, and specific nutrients can modulate gene expression and epigenetic mechanisms involved in insulin signaling, inflammation, and energy homeostasis. This narrative review synthesizes recent human and experimental studies (2025–2026) examining how dietary components influence transcriptional and epigenetic regulation of insulin signaling and glucose metabolism in the context of T2DM prevention. A total of 29 peer-reviewed studies were included, encompassing dietary patterns, macronutrient manipulation, micronutrient and bioactive supplementation, and gene–diet interactions. Very-low-calorie diets consistently induced coordinated modulation of key metabolic genes, including downregulation of glucose transporter type 4 (GLUT4) and upregulation of PDK4, CPT1, and AMPK, reflecting a metabolic shift toward enhanced fatty acid oxidation and improved insulin sensitivity. In contrast, high-fat and fructose-rich diets promoted proinflammatory gene expression and immune activation, contributing to insulin resistance. Plant-based and vegan dietary patterns were associated with reduced epigenetic aging and improved insulin sensitivity through DNA methylation changes. Targeted interventions, including vitamin D combined with probiotics, dietary fiber, nucleotides, and trace elements such as copper, further demonstrated favorable transcriptional and epigenetic effects linked to improved glycemic control. Collectively, these findings highlight diet-driven modulation of insulin signaling and glucose metabolism at the molecular level and support nutrigenomics-guided precision nutrition as a viable preventive approach for T2DM. Integrating genetic and epigenetic insights into dietary strategies may enable more personalized and effective interventions to curb the growing global burden of type 2 diabetes. Full article

Climate change impacts on the Sado River (southwest Portugal) flow rates (FRs) were assessed for the first time under the 2041–2060 Shared Socioeconomic Pathways: 1–2.6 W/m² (SSP1-2.6), 3–7.0 W/m² (SSP3-7.0), and 5–8.5 W/m² (SSP5-8.5), using bias-adjusted and downscaled General Circulation Model (GCM) ensemble projections from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b-Sado). ISIMIP3b-Sado was used to estimate future precipitation and temperature changes, and as input for Hydrological Simulation Program—FORTRAN (HSPF) simulations. The HSPF projected decreases in the Sado FRs, mainly under SSP3-7.0 and SSP5-8.5, due to temperature increases and autumn/spring precipitation decreases. The FR decreases may lead to 29%/33% reductions in yearly accumulated riverine water volume under SSP3-7.0/SSP5-8.5 and a 31% summertime riverine water deficit increase under SSP3-7.0. Surface-water demand fulfilment in the Sado Basin could suffer a 22-day delay, and the wintertime precipitation range is projected to increase. Hence, in the near-future, summertime surface-water needs and reservoir recharge in the Sado Basin could become more dependent on wintertime precipitation. With Sado being an agricultural region, our results should prompt agriculture stakeholders and decision makers to improve wintertime surface water storage and management to sustain summertime crop irrigation needs. Full article

The agrarian sector, as the key source of livelihood in Sub-Saharan Africa (SSA), has become highly vulnerable to changes in extension service deliveries. Farmers mainly lack access to technical advice, financial credits, farming inputs and mechanization tools while environmental challenges reinforce the adaptation of sustainable management practices. Therefore, an understanding how multi-functional actor relationships determine agricultural knowledge and information (AKI) sharing is required. This study contributes to filling this gap by characterizing horizontal and vertical interactions. By applying a social network analysis, we mapped actor relations along public–private-community co-operations to provide insights into structural dependencies at different administrative levels. Related to three sites distributed over Burkina Faso and Ghana, local perceptions were collected in stakeholder workshops to generate social network narratives. These narratives were analyzed by various metrics to identify patterns of partnerships and key actors. Study results reveal for Burkina Faso a slight shared network topology, while both sites in Ghana reflect a top-down flow of AKI. The statistical findings indicate that agricultural extension services are primarily delivered to farmers through a few key actors such as NGOs and farm-based organizations/cooperatives. Especially at the community level, the results show many reciprocal links between farmers, business actors and NGOs. This highlights a shift toward a pluralistic agricultural extension service system and underpins the demand for policies to support the long-term viability of these actors, in particular for regions where public extension agents are under-represented. Full article

Background and Objectives: Chronic tinnitus in patients with bilateral sensorineural hearing loss (SNHL) is frequently linked to psychological distress and affective temperament traits. This study examined audiological characteristics, psychological profiles, and their interrelations in adults with tinnitus. Materials and Methods: In this cross-sectional single-centre study, 38 adults with chronic tinnitus and bilateral SNHL underwent otoscopy, tympanometry, and pure-tone audiometry. Participants were classified into two audiometric groups: high-frequency gently sloping (N = 19) and ski-slope hearing loss (N = 19). The audiological and psychological assessment included the THI, TFI, TEMPS-A, and STAXI-2. Groups were compared using non-parametric statistics (Mann–Whitney U, Chi-square). Relationships between anger and psychological variables were examined using Spearman correlations. Results: Females were more frequently represented in the gently sloping group (p = 0.044) and showed greater quality-of-life impairment (p = 0.045) and lower hyperthymic scores (p = 0.004). Patients with gently sloping loss had longer tinnitus duration (p = 0.026), while cyclothymic temperament was higher in the ski-slope group (p = 0.013). THI scores differed significantly between audiometric groups (p = 0.011). State and trait anger were strongly associated with several affective temperaments, and sleep disturbance correlated with both anger and anxious temperament. THI correlated positively with anxious temperament and sleep impairment. Conclusions: Audiometric phenotype, affective temperament, and anger-related traits are closely intertwined with tinnitus severity and its psychological burden. These findings support the need for multidisciplinary assessment in the management of tinnitus. Full article

Lipoprotein(a) [Lp(a)] is a causal, genetically determined risk factor for atherosclerotic cardiovascular disease (ASCVD) and calcific aortic valve stenosis (CAVS). Although elevated Lp(a) affects approximately 20% of the global population, specific pharmacological options have long been unavailable, leaving a major gap in residual risk management. This review synthesizes current understanding of Lp(a) molecular architecture, genetics, and metabolism, and integrates mechanistic evidence linking Lp(a) to pro-atherogenic, pro-inflammatory, and pro-thrombotic pathways. We summarize epidemiological and genetic data associating Lp(a) with a broad spectrum of cardiovascular outcomes and discuss current clinical guidelines on screening and risk stratification. Furthermore, we provide an up-to-date overview of the emerging therapeutic landscape, including RNA-targeted therapies and novel oral small molecules. With pivotal phase 3 outcome trials nearing completion, the field is transitioning from viewing Lp(a) as an untreatable biomarker to an actionable therapeutic target, with important implications for precision cardiovascular prevention. Full article

Parental practices strongly influence offspring development, and parental alcohol use may affect parenting behavior. However, most studies have focused on child-related outcomes. This review instead examined associations between parental drinking and parenting practices. Following PRISMA guidelines, a systematic search in MEDLINE, PsycINFO, Embase, and Scopus identified 9053 articles. Of these, 222 full texts were screened by two reviewers, and 77 were included for critical appraisal. After quality assessment, 68 studies published between 1991 and 2026 were reviewed. Studies were included if they (i) measured parental alcohol use as a predictor and parenting practices as an outcome, (ii) involved offspring under 20 years, (iii) had a quantitative design, (iv) were peer-reviewed and published in English, and (v) excluded pregnancy measures and alcohol/parenting treatment interventions. Parenting factors (e.g., parent–child relationship, monitoring, communication, discipline, conflict, abuse) were categorized and grouped into general and alcohol-specific practices. Parental drinking was categorized into alcohol use disorders (AUD) and non-dependent alcohol use. Sixty-four studies reported at least one significant association between parental drinking and poorer parenting practices. Mixed results were observed for non-dependent drinking and alcohol-specific parenting. Some associations varied with parental gender. Overall, different drinking patterns appear to be linked to impaired parenting quality. Despite being the most common pattern of alcohol use, non-dependent drinking remains understudied in parenting research. The present review highlights several critical gaps in the literature, particularly regarding the relationship between non-dependent drinking, maternal AUD, and parenting practices. Moreover, contextual factors, such as socioeconomic status and gender differences, are insufficiently explored, limiting the understanding of heterogeneity in risk and outcomes. Future research would benefit from employing robust longitudinal designs and expanding geographical representation, in order to capture variation across sociocultural contexts and enhance the generalizability of findings. Full article

Addressing the growing need for sustainable innovation in PVC materials, this study presents an illustrative framework that develops and demonstrates an ontological system that integrates lifecycle simulation using Granta EduPack, systematic literature analysis (including bibliometric, thematic, and content analytics) of peer-reviewed publications, and Protégé-based semantic reasoning, and their combination, in a holistic manner. Material and use-phase data for PVC, HDPE, PP, PET, and FRP cooling-tower components were sourced from ANSYS Granta EduPack Level-3 Polymer Sustainability 2023 R2 Version; 23.2.1, and a systematic analysis of the literature was then encoded as ontology classes, properties, and individuals following the Seven-Step ontology development method. Eco-audit simulations, standardised to a functional unit of 1 kg cooling tower fill material, reveal that the use phase dominates environmental impact (67 MJ primary energy, ~80% of total lifecycle), while material production and end-of-life recycling contribute ~15% and credits of ~900 MJ and 28 kg CO₂ via recycling offsets. Ontology reasoning with corrected SWRL rules and SPARQL queries classifies VirginPVCRef and PVC10ES as strong structural materials (tensile strength ≥ 40 MPa), identifies PVCRH40 as high-moisture-risk (water absorption > 0.10 g/g), and ranks hydro-thermal dechlorination (recyclability 0.90) over mechanical recycling (0.55). A systematic analysis of 40 Scopus-indexed publications (2015–2025) highlighted key themes in recycling technologies, LCA emissions, additive toxicity, ontology frameworks, machine learning integration, circular economy policy, and cooling-tower applications. Demonstrated via a simulation-based cooling-tower case study, hybrid PVC-FRP designs yield the highest justified Material Sustainability Performance Index (MSPI), outperforming PVC-only and FRP-only alternatives. This framework provides a conceptual decision-support tool for exploring PVC material optimisation, illustrating pathways to enhancing circularity and environmental responsibility in industrial applications. The proposed framework is, therefore, not intended as a validated decision-support tool, nor does it claim analytical optimisation or predictive performance but rather serves as a method of illustration that shows how domain knowledge can be formally structured using ontology principles linked to simulation representations, and that was examined for internal logical consistency. Full article