Search Results (5,883)

Prolonged spaceflight and sustained bed rest induce mechanical unloading, leading to disuse osteoporosis and an elevated risk of fractures. Although post-translational modifications are increasingly recognized as key contributors to the pathogenesis of disuse bone loss, the functional role and underlying molecular mechanisms of O-linked N-acetylglucosaminylation (O-GlcNAcylation) remain poorly understood. Here, we demonstrate that mechanical unloading via 2D clinorotation downregulates the levels of O-GlcNAc transferase (OGT) and global protein O-GlcNAcylation in MC3T3-E1 cells, whereas osteogenic induction elicits the opposite effect. Both small interfering RNA (siRNA) targeting OGT and pharmacological inhibition using OSMI-1 recapitulated unloading-induced deficits, significantly impairing osteogenic differentiation and matrix mineralization. Conversely, OGT overexpression or inhibition of O-GlcNAcase (OGA) with Thiamet-G enhanced these processes. Importantly, OGT re-expression partially reversed the deficits caused by mechanical unloading. Notably, exogenous elevation of global O-GlcNAcylation levels via Thiamet-G treatment even after OGT knockdown also partially restored osteogenic capacity. Together, these findings establish the OGT/O-GlcNAcylation axis as a critical regulator of unloading-induced suppression of osteogenesis and identify it as a promising therapeutic target for disuse osteoporosis. Full article

Aging and glycative stress are major, interrelated drivers of skeletal fragility, yet the extent to which they act through shared versus distinct biological pathways remains poorly defined, limiting integrated therapeutic strategies. This review compares the convergent and divergent mechanisms by which aging and glycative stress affect osteocytes, osteoblasts, and osteoclasts, extracellular matrix properties, and bone mechanotransduction. Both conditions converge on oxidative stress, mitochondrial dysfunction, chronic low-grade inflammation, cellular senescence, impaired autophagy, NLRP3 inflammasome activation, and ferroptosis, ultimately reducing osteocyte viability and disrupting RANKL/OPG-mediated remodeling. They diverge in their primary drivers: Aging is characterized by hormonal decline, stem-cell exhaustion, and progressive loss of bone mass and microarchitecture, whereas glycative stress acts through AGE–RAGE signaling and collagen cross-linking, compromising bone quality and mechanosensitivity while often preserving bone mineral density, explaining the disproportionate fracture risk seen in diabetes. Since current anabolic and anti-resorptive therapies do not specifically target AGE-related pathways, combined strategies incorporating senolytic, antiglycative, and mechanoprotective approaches—alongside lifestyle interventions—may be needed to more effectively reduce fracture risk in aged and diabetic populations. Full article

The hypothalamic–pituitary–adrenal (HPA) axis is the central neuroendocrine system that controls physiological stress responses and maintains homeostasis through the coordinated interactions among the hypothalamus, pituitary gland, and adrenal cortex. Dysregulation of the HPA axis is associated with stress-related psychiatric conditions and neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis. Chronic stress creates a detrimental environment in the brain, inducing structural changes and accelerating brain aging and the loss of neurons. Receptor tyrosine-protein kinase ERBB4 (ERBB4), a member of the epidermal growth factor receptor (EGFR) family, is activated primarily by neuregulin ligands and plays an essential role in neuronal development, synaptic plasticity, and cell survival. Emerging evidence suggests that ERBB4 signaling influences neuroendocrine regulation and stress responsivity. While further studies are needed to provide direct mechanistic evidence linking ERBB4-mediated HPA axis dysregulation to neurodegenerative cell death, this manuscript critically evaluated the preclinical models and proposes a possible feed-forward framework wherein ERBB4 served as a permissive homeostatic modulator at the intersection of stress endocrinology and neuroinflammation. Furthermore, the impact of ERBB4 dysregulation and its mutations on neurodegenerative diseases has been presented, focusing on potential mechanisms of oxidative stress, synaptic dysfunction, and neuronal apoptosis. Taken together, ERBB4 represents an important molecular interface between stress signaling and neurodegenerative pathology. Understanding the regulation of ERBB4 in the HPA axis has provided new insights into the mechanisms underlying neurodegenerative diseases and could identify novel therapeutic targets for stress-associated neurological disorders. Full article

GLP-1RAs improve glycemia and body weight, but their effects extend beyond insulin secretion and appetite suppression. Experimental evidence indicates that GLP-1 receptor signaling can relieve lipotoxic stress by reducing lipid influx, restoring lipid trafficking, promoting cholesterol efflux, improving mitochondrial and endoplasmic reticulum homeostasis, and suppressing inflammatory and apoptotic signaling. In pancreatic beta cells, saturated fatty acids, oxidized low-density lipoprotein and excess free cholesterol disrupt membrane microdomains, insulin-granule trafficking, calcium signaling, autophagic flux and beta-cell identity. Preclinical studies with individual GLP-1RAs, principally exendin-4 and liraglutide, implicate cAMP/PKA, PI3K/Akt, ERK1/2, AMPK, Nrf2 and autophagy-related pathways in these protective responses. A relevant mechanism is induction of ATP-binding cassette transporter A1 (ABCA1): exendin-4 stimulates ABCA1 transcription through the CaMKK/CaMKIV/PREB axis, linking incretin signaling to cholesterol export and preservation of glucose-stimulated insulin secretion. Recent work indicates spatially organized GLP-1R signaling at endoplasmic reticulum–mitochondria contact sites. Preclinical genetic evidence in mouse metabolic dysfunction-associated steatohepatitis (MASH) models indicates that pericentral liver sinusoidal endothelial GLP-1 receptors contribute to weight-loss-independent semaglutide-mediated improvements in steatosis, fibrosis and immune remodeling; whether an analogous causal mechanism operates in human MASH remains unknown. This review integrates systemic nutrient unloading, beta-cell cholesterol homeostasis and intrahepatic endothelial signaling as complementary mechanisms of metabolic protection. Full article

Extreme events threaten distribution network security. When remote-controlled switches (RCSs) lose remote operability during extreme events while remaining manually operable, faulted areas may no longer be isolated through remote switching alone. This paper proposes a multi-stage resilience enhancement method that coordinates RCSs and switch operation crews under RCS fault conditions. A four-stage framework is established, comprising pre-event prevention, degradation, fault isolation, and service restoration. Normal RCSs can be remotely opened to shrink the faulted zone during isolation, while faulty RCSs remain frozen and can change their switching states only through on-site crew intervention during restoration. A unified operation constraint is formulated for the isolation stage, and a crew-assisted switching constraint links crew presence at faulty-RCS locations to their switching operability during restoration. The problem is cast as a scenario-based mixed-integer linear program minimizing expected weighted load shedding across all post-event stages. Case studies on the modified IEEE 33-bus system demonstrate the effectiveness of the proposed method under different RCS availability conditions. Under the same line-fault configuration, loss of RCS remote operability increases cumulative weighted load shedding by 28.09% and delays complete load restoration by one time interval. The reported four-scenario computation required approximately 7128 s. Full article

Background/Objectives: Tinnitus becomes more common with age, and age-related hearing loss accounts for an increasing share of cases in later life, whereas modifiable behavioural factors may contribute relatively more in midlife. Population-based evidence linking sitting time—a construct distinct from physical inactivity—to tinnitus is limited and has not accounted for psychological and sleep-related correlates. Methods: We analysed Korean women aged 40–64 years in the Korea National Health and Nutrition Examination Survey (KNHANES) 2014–2018, a nationwide complex-sample survey (N = 7239; current tinnitus prevalence 21.9%). Self-reported daily sedentary time was categorised into survey-weighted quartiles (cut-points 5, 7, and 10 h/day). Survey-weighted modified-Poisson regression estimated adjusted prevalence ratios (aPRs), adjusting for demographic, socioeconomic, behavioural, aerobic-activity, and auditory factors; further models added perceived stress, depressive symptoms, physician-diagnosed depression, sleep duration, menopausal status, and non-occupational noise. Results: Tinnitus prevalence rose across quartiles (weighted 19.7%, 21.6%, 23.2%, and 24.9%; model-standardised 19.4%, 21.9%, 23.5%, and 24.9%). Relative to the lowest quartile, aPRs were 1.13 (95% confidence interval 0.98–1.31), 1.21 (1.07–1.36), and 1.29 (1.11–1.49; p = 0.0007), with a trend of 1.09 per quartile (p = 0.0001). The estimate was 1.26 (1.09–1.46) after mental-health and sleep adjustment, and 1.27 (1.10–1.47) when fully adjusted. A similar association was seen in men (1.22, 1.03–1.45; sedentary-by-sex interaction p = 0.93); in women aged 65 years and over it was absent (0.86, 0.74–1.01). Conclusions: Longer sedentary time was associated with a modestly higher prevalence of current tinnitus, not accounted for by the measured covariates. The design is cross-sectional, the absolute difference was small (5.6 percentage points), and reverse causation cannot be excluded; prospective confirmation is required. Full article

Functional dyspepsia (FD) is a disorder of gut–brain interaction affecting approximately 7% of the global population under Rome IV criteria, characterised by postprandial fullness, early satiation, epigastric pain, and/or epigastric burning in the absence of identifiable organic disease. Meal ingestion is the dominant symptom trigger in the majority of patients, yet the relationship between diet and FD is bidirectional: dietary exposures drive symptoms through established pathophysiological mechanisms, while FD itself can promote maladaptive eating behaviours and progressive dietary restriction with nutritional and psychological consequences. The pathophysiological substrate linking diet to symptom generation encompasses impaired gastric accommodation and emptying, visceral hypersensitivity to mechanical and chemical stimuli, low-grade duodenal mucosal immune activation and epithelial barrier impairment, alterations of the small intestinal microbiota, and gut–brain axis dysregulation. Dietary fat is the macronutrient most consistently implicated, acting through cholecystokinin-mediated chemosensory and mechanosensory pathways. Cross-sectional population data suggest that a high protein intake may also be associated with epigastric pain, although this association did not persist after multivariable adjustment, while the evidence linking total carbohydrate intake to symptoms remains sparse and inconsistent, so that no recommendation on total carbohydrate intake can currently be made. Cognitive factors, including learned food beliefs, expectancy, and nocebo effects, further modulate symptom perception independently of actual nutrient content. Among dietary patterns, Mediterranean-style eating offers the most coherent mechanistic rationale and the strongest observational support, while a diet low in fermentable oligosaccharides, disaccharides, monosaccharides, and polyols (FODMAP) shows selective benefit in patients with postprandial distress syndrome features or prominent bloating. Common triggers including spicy foods, coffee, and alcohol show heterogeneous evidence driven by individual sensitivity rather than dose-related effects. Nutritional concerns are substantial: clinically significant weight loss affects approximately 35% of tertiary-care patients, and nearly 40% screen positive for avoidant/restrictive food intake behaviour using validated screening tools. Dietary management should therefore be individualised, nutritionally adequate, and integrated within a broader biopsychosocial framework, with screening for disordered eating before any elimination strategy is initiated. Full article

Neuroinflammation is a coordinated response to central nervous system injury and disease involving resident glia, neurons, the neurovascular unit, and infiltrating immune cells. Although transient inflammatory signaling supports host defense, debris clearance, and repair, persistent activation contributes to synaptic dysfunction, demyelination, blood–brain barrier disruption, and neuronal loss. Neuregulin-1 (NRG1), a pleiotropic epidermal growth factor family ligand, has emerged as a potential regulator of this balance. Through ErbB receptor complexes, particularly ErbB4-containing dimers, NRG1 influences neural development, myelination, synaptic function, cell survival, and inflammatory signaling. Experimental evidence indicates that NRG1 can restrain NF-κB-dependent transcription, alter microglial activation states, enhance alpha7 nicotinic acetylcholine receptor-associated anti-inflammatory signaling, support oligodendroglial lineage cells, and stabilize neurovascular integrity. However, these actions are context-dependent; in spinal nociceptive circuits, ErbB2-linked signaling can promote microglial activation and pain hypersensitivity. This review examines NRG1 isoform biology, ErbB receptor architecture, cellular targets, and disease-specific evidence across demyelinating disease, stroke, traumatic brain injury, neurodegeneration, cerebral malaria, sickle cell disease, and neuropathic pain. Translation will require isoform-specific, receptor-biased, and anatomically targeted approaches supported by rigorous in vivo validation and verified biomarkers. Full article

Curved bridges subjected to strong ground motions have shown high seismic vulnerability in many countries. Several published studies analyze curved-bridge failures, focusing on collapses observed after severe earthquakes, which are frequently linked to loss of seating length. Other studies assess seismic fragility based on expected pier damage, and most published work uses numerical models derived from existing bridge portfolios that do not include specific real bridges. Many studies also aim to correlate the dynamic properties of existing bridges, estimated from ambient vibration measurements, with those of numerical models. The approaches mentioned above estimate the expected seismic response for specific bridge types that may not accurately represent real structures, and examine the most common failure mechanisms. Unlike these studies, the current research provides valuable and novel insights into the expected behavior of curved viaducts designed in accordance with modern standards and regulations. It shows that, in these cases, the most frequently reported failure in the literature, loss of seating length, is less likely than other failure mechanisms. The results apply to a real curved bridge whose numerical model was previously calibrated using ambient vibration measurements. Another distinctive feature is the assessment of reliability indices for a real structure, evaluating the values that current regulations would expect to observe during infrequent seismic events. Uncertainties in site amplification are reduced because a nearby seismic station is available. Nonlinear analyses were performed using two sets of seismic records from interplate and intraplate earthquake sources, scaled to match the expected seismic intensity at the bridge site, to assess damage progression in the bridge under both design and infrequent earthquake intensities. The study also emphasizes the significant effects of the selected ground-motion population and the frequency content of interplate and intraplate earthquakes on bridge seismic performance. Unlike the failure mechanism most commonly observed in curved bridges during high-intensity seismic events, which involves loss of superstructure seating length, this case study of a curved bridge designed under modern seismic regulations shows failure when shear demands exceed the bridge piers’ shear capacity. Full article

Type 2 diabetes mellitus (T2DM) is associated with heterogeneous cognitive and functional trajectories rather than a single diabetes-specific encephalopathy. This structured narrative review proposes a conceptual, hypothesis-generating exposure–injury–structure–function framework linking metabolic, vascular, and frailty-related exposures with molecular and neurovascular injury, structural change, cognitive decline, and loss of independence. Its contribution is the temporal assignment of measurements, lagged testing between adjacent levels, and comparison with clinical-risk and unordered biomarker models. For example, a study-specific threshold of at least 10% improvement in held-out root-mean-square error for 24–36-month executive/processing-speed decline could indicate incremental value. Repeated failure of a specified temporal link challenges that link; failure to improve prediction rejects incremental predictive value, not biological plausibility. Molecular hypotheses focus on AGE–RAGE signalling, NLRP3–IL-1β activation, mitochondrial quality control, endothelial dysfunction, and neuroglial injury, although human timing is uncertain. Sodium–glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are considered complementary therapeutic probes. Both offer systemic benefits, but neither has proven efficacy in preventing cognitive decline or direct target engagement in the human brain. Visceral adiposity, skeletal-muscle health, sarcopenia, sex/gender, kidney function, co-pathology, and reserve are treated as exposures or modifiers. This framework is intended for longitudinal research, not clinical staging or treatment selection. Full article

(1) Background: The nasolabial fold is a key determinant of midfacial aging, influenced by both static volume loss and dynamic muscular activity. Botulinum toxin type A (BoNT-A) and hyaluronic acid (HA) fillers are widely used in aesthetic medicine, but limited evidence exists regarding the sequential use of these treatments to address both static and dynamic components of the nasolabial fold. (2) Methods: This prospective interventional case series included 23 patients with clinically evident nasolabial folds and depressor anguli oris (DAO) hyperactivity. All patients received BoNT-A injections into the DAO muscle, followed by HA filler augmentation in selected cases according to baseline severity. Patients were classified into three treatment groups in accordance with the treatment strategy selected at baseline: BoNT-A alone, BoNT-A plus 0.5 mL HA per side, and BoNT-A plus 1 mL HA per side. Outcomes were assessed using the Wrinkle Severity Rating Scale (WSRS) in both static and dynamic conditions and the Global Aesthetic Improvement Scale (GAIS), evaluated by two independent blinded physicians. (3) Results: All treatment groups demonstrated a reduction in dynamic WSRS scores following BoNT-A injection, reflecting decreased DAO activity and reduced dynamic accentuation of the nasolabial fold. Patients receiving combined BoNT-A and HA treatment showed additional improvement in static fold severity. Overall, GAIS scores indicated much to very much aesthetic improvement, with the highest outcomes observed in patients receiving 1 mL HA augmentation. Interobserver agreement was good across evaluations. (4) Conclusions: Botulinum toxin treatment of the DAO was linked to reduced dynamic accentuation of the nasolabial fold, while hyaluronic acid augmentation led to additional improvement in static fold severity. These preliminary findings indicate that sequential treatment might address both dynamic and static components of nasolabial fold appearance. However, larger randomized studies with longer follow-up are necessary to confirm these findings. Full article

With the rapid development of graph neural networks and physics-informed machine learning for critical infrastructure risk, reliable assessment of submarine telecommunication cables has become both a practical resilience requirement and a demanding cross-domain learning problem. These cables carry more than 99% of international data traffic, yet fault risk modeling faces four explicit challenges: (1) modality misalignment, because marine evidence combines gridded environmental fields with irregular vessel trajectories; (2) relational heterogeneity, because hazards interact through semantically distinct spatial links; (3) physical inconsistency, because unconstrained predictions may violate seabed geomechanics under geographic shift; and (4) decision uncertainty, because safety-critical inspection and routing require uncertainty rather than point estimates alone. The closest approaches leave identifiable gaps. Makrakis and colleagues optimized static cable routes without learned hazard interactions or uncertainty; Taghizadeh and colleagues constrained flood graph predictions without cable-specific heterogeneous entities; and Guo and colleagues fused maritime trajectories without forecasting cable faults or screening routes. No existing approaches combine these missing capabilities under geographically held-out cable basins. To address this gap, the present paper proposes MarineGuard-GNN, a physics-informed multimodal heterogeneous graph neural network. Its Cross-Modal Spatiotemporal Tokenizer maps GEBCO bathymetry, CMEMS ocean fields, and NOAA AIS trajectories into a shared 256-dimensional space; a relation-aware Heterogeneous Graph Transformer represents four semantic node types and four physical relation types; a differentiable Mohr–Coulomb loss regularizes geomechanical consistency; and a Monte Carlo dropout risk head estimates segment-level epistemic uncertainty for inspection and routing. Under 4-fold geographic cross-validation at natural prevalence on 15,110 cable nodes (847 faults), MarineGuard-GNN attains cross-basin AUC-ROC, average-precision, and F1 ranges of $0.72$–$0.76$, $0.18$–$0.24$, and $0.29$–$0.36$, respectively; average precision corresponds to a $3.21$–$4.28\times$ lift over the $0.0561$ no-skill prevalence baseline. Paired basin-stratified bootstrap analysis and Holm-corrected tests confirm improvements over the strongest tabular and graph baselines ($\Delta$AUC-ROC $\ge 0.02$, $\Delta$AP $\ge 0.03$; $p_{\mathrm{adj}}<0.05$). Matched ablation shows that removing the corrected mechanics term reduces AUC-ROC by $0.005$ and average precision by $0.010$ without improving calibration. Across three densely sampled public cable corridors, uncertainty-aware routing reduces mean predicted risk by at least $5\%$ while limiting distance overhead to below $3\%$; the conclusion remains stable for risk thresholds from $0.45$ to $0.60$. These results demonstrate statistically supported cross-basin generalization, establishing the proposed framework as a reproducible decision support method. Full article

The current study combines solar photovoltaic (PV) power, energy storage batteries and wind power to propose a novel and effective method for energy management and optimisation of hybrid renewable energy systems. Optimising the management and coordination of many energy sources is becoming essential, as the world moves towards sustainable energy choices. This study seeks to improve system performance, reliability and operating costs, using a unique hybrid control and power management paradigm, the Improved Human Evolutionary Optimisation (IHEO) algorithm, presented as a novel optimisation method that balances energy flow, generation, storage and consumption. This study shows that the proposed model greatly improves the efficiency of the operation of hybrid systems. The optimisation’s main objective is to reduce the overall cost of energy production while maintaining a smart energy management system. In this context, the cost function accounts for energy losses during electricity distribution as well as the generation costs of solar, wind, and battery storage. By minimising energy losses and optimising power flow between energy sources (wind, solar), storage (battery) and load demand, this can be used to assess system performance. The applied approach ensures system stability, optimises the use of renewable energy sources and reduces the power imbalance. The improved effectiveness of the IHEO algorithm in this study in minimising energy losses, lowering operating costs and enhancing overall system efficiency is demonstrated by thorough comparison with conventional particle swarm optimisation (PSO). Further to this, the integration of MPPT with PV systems and the IHEO algorithm enhances energy extraction efficiency by dynamically optimising power flow, ensuring maximum output from renewable sources under varying environmental conditions. Additionally, the BESS charging current ripple is also reduced from ±15 A to ±3 A using the model applied in this study, confirming smoother and safer battery charging operation. The key novelty lies in using IHEO for global exploration to find the best solution and PSO for local refinement to improve battery coordination with renewables and smooth DC-link regulation, which is then compared with conventional WOA. Full article

This paper presents a significant evolution of the Identification of Active Anomalies (IAA) system, moving beyond previous descriptive frameworks by integrating an advanced machine learning pipeline for automated, real-time Structural Health Monitoring (SHM). Utilizing acoustic emission (AE), the upgraded IAA framework combines signal clustering, image recognition, and machine learning to monitor the structural condition of a highway overpass located near a major urban agglomeration. The monitoring results provide a reliable foundation for assessing structural health and implementing automated traffic control, which is essential to ensure safe operations. Unlike baseline implementations, this intelligent system extracts multi-parametric features using Principal Component Analysis (PCA) and transforms temporal wave streams into Continuous Wavelet Transform (CWT) scalograms. These visual representations are processed by a custom 14-layer Deep Convolutional Neural Network (CNN) combined with an unsupervised Self-Organizing Map (SOM) to eliminate operational noise and classify internal failures. AE signals recorded under service loads undergo multi-parametric analysis using pattern recognition techniques and are assigned to specific classes corresponding to active anomalies within the material or structure. Each class is linked to a distinct structural hazard level, ranging from safe operation to a critical loss of structural safety. Corresponding traffic control measures, including vehicle speed and weight restrictions, are dynamically introduced to maintain operational safety. To validate the scalability of the framework, this study synthesizes statistical data across a comprehensive fleet of 180 monitored bridge structures, backed by a predictive ARIMA time-series model that forecasts residual service life. The proposed methodology was experimentally validated on an A2 highway overpass, a vital component of the Łódź transport hub that facilitates north–south and east–west transit in Poland. The IAA system functions as a proactive diagnostic tool for infrastructure management agencies, preventing sudden, unforeseen structural failures. Ultimately, it enables the efficient and safe operation of a Smart City while ensuring that maintenance funds are rationally and optimally allocated. Full article

Alzheimer’s disease is a multifactorial neurodegenerative disorder in which amyloid-β accumulation, tau pathology, neuroinflammation, synaptic dysfunction, vascular injury, and neuronal loss interact across multiple cellular compartments. Although amyloid and tau remain central to disease definition and biomarker staging, growing evidence indicates that inflammatory and regulated cell-death pathways actively shape disease progression. Receptor-interacting protein kinase 1 (RIPK1) has emerged as a context-dependent signaling checkpoint that links inflammatory signaling to cell-fate decisions. In its scaffold and ubiquitinated forms, RIPK1 supports TNFR1-associated NF-κB and MAPK signaling, whereas RIPK1 kinase activation can promote apoptosis and RIPK1-RIPK3-MLKL-dependent necroptosis when regulatory checkpoints fail. In Alzheimer’s disease, RIPK1 signaling has been implicated in disease-associated microglial responses, impaired amyloid-β handling, astrocyte reactivity, tau-associated neuronal stress, neurovascular dysfunction, and necroptotic cell death. Here, we review the molecular regulation of RIPK1; evaluate evidence from human tissue, experimental models, and cellular systems; and discuss how RIPK1 may function as a convergence and amplification node linking amyloid-β, tau, neuroinflammation, and regulated cell death. We also examine the therapeutic rationale for targeting RIPK1, including CNS-penetrant inhibitors, biomarker challenges, timing of intervention, patient selection, and safety considerations. We propose that RIPK1 is an understudied pathway in Alzheimer’s disease pathogenesis and that defining its cell-type-specific and stage-dependent functions will be essential to determine whether RIPK1 inhibition can be developed as a disease-modifying therapeutic strategy. Full article