Multidisciplinary Digital Publishing Institute (Switzerland)
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Osteoporosis After Menopause and After Drug Therapy: The Molecular Mechanism of Bone Loss and Its Treatment
No full textOsteoporosis is a prevalent skeletal disorder characterized by reduced bone mass and microarchitectural deterioration, leading to increased fracture risk, particularly in aging populations. Postmenopausal osteoporosis (PMOP) remains the most common primary form and results from abrupt estrogen deficiency after menopause, which disrupts bone remodeling by accelerating the receptor activator of nuclear factor-κB ligand (RANKL)-mediated osteoclastogenesis, suppressing Wnt/β-catenin signaling, and promoting inflammatory cytokine production. In contrast, drug-induced osteoporosis (DIOP) encompasses a heterogeneous group of secondary bone disorders arising from pharmacologic exposures. Glucocorticoids suppress osteoblastogenesis, enhance osteoclast activity, and increase reactive oxygen species; long-term bisphosphonate therapy may oversuppress bone turnover, resulting in microdamage accumulation; denosumab withdrawal triggers a unique rebound surge in RANKL activity, often leading to rapid bone loss and multiple vertebral fractures. Medications including aromatase inhibitors, SSRIs, proton pump inhibitors, heparin, and antiepileptic drugs impair bone quality through diverse mechanisms. Standard antiresorptive agents remain first-line therapies, while anabolic agents such as teriparatide, abaloparatide, and romosozumab provide enhanced benefits in high-risk or drug-suppressed bone states. Transitional bisphosphonate therapy is essential when discontinuing denosumab, and individualized treatment plans—including drug holidays, lifestyle interventions, and monitoring vulnerable patients—are critical for optimizing outcomes. Emerging approaches such as small interfering RNA (siRNA)-based therapeutics, anti-sclerostin agents, digital monitoring technologies, and regenerative strategies show promise for future precision medicine management. Understanding the distinct and overlapping molecular mechanisms of osteoporosis is essential for improving fracture prevention and long-term skeletal health
Pain and Suicide Behavior in Cancer Patients: Implications for Personalized Treatment—A Systematic Review
No full textObjective: Pain is among the most common and debilitating symptoms experienced by oncology patients and has been associated with adverse mental health outcomes, including depression and suicide. Nevertheless, the relationship between pain and suicide in oncology populations remains insufficiently characterized. A clearer understanding of this interplay is essential to guide personalized approaches aimed at reducing cancer-related burden and improving quality of life. Methods: We searched PubMed and PsycInfo without imposing limits regarding publication date using pain* AND (suicid* OR “self-harm” OR “self-injurious behavior” OR “self-inflicted injury” or “self-killing”) AND (cancer* OR oncolog* OR tumor* OR neoplasm* OR metasta*). A total of 832 articles were identified, and 15 of them were included in our review. Results: Inadequately managed pain in cancer patients is associated with a significantly elevated risk of suicidal ideation. This association is further exacerbated in individuals presenting with depressive symptoms, advanced-stage disease, or limited access to timely psychological support. These factors may interact synergistically, intensifying the emotional and cognitive burden of pain, thereby increasing vulnerability in cancer patients. Conclusions: Cancer-related pain should be conceptualized as a highly variable indicator of psychological vulnerability. Factors influencing this variability include cancer type and severity, as well as the presence of past psychopathology. These findings support the need for a personalized medicine approach, whereby pain management and psychosocial interventions are tailored to patient-specific factors such as disease stage, psychological comorbidity, and access to supportive care
Crocin Modified Drugs for Neuronal Trans-Differentiation: A Future Regenerative Approach
No full textNeurodegeneration—driven by oxidative stress, chronic inflammation, and protein aggregation—underlies disorders such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and stroke. Current pharmacological treatments are largely symptomatic and do not restore lost neural circuitry, motivating regenerative approaches. Mesenchymal stem cells (MSCs) provide neurotrophic and immunomodulatory benefits and can support synaptic repair, yet robust conversion into mature, electrophysiologically functional neurons remain challenging and often depends on complex inducer cocktails with translational limitations. Crocin, a saffron-derived carotenoid, is reported to enhance neurogenesis and neuroprotection in preclinical models through pathways including Wnt/β-catenin, Notch1, CREB/BDNF, and modulation of GSK-3β, while reducing apoptosis and inflammatory signaling. Here, we synthesize evidence supporting crocin’s neuroprotective and proneurogenic activity and propose a testable hypothesis that crocin-based or crocin-modified formulations could be evaluated as adjuncts to guide MSC neuronal lineage commitment. Importantly, direct evidence that crocin alone can drive MSC trans-differentiation into fully functional neurons is currently insufficient; future work should define functional benchmarks (electrophysiology, synaptogenesis, and phenotypic stability) and rigorously validate safety, dosing, and delivery strategies for neuroregenerative translation
Free Vibration and Static Behavior of Bio-Inspired Helicoidal Composite Spherical Caps on Elastic Foundations Applying a 3D Finite Element Method
No full textSpherical caps exploit their intrinsic curvature to achieve efficient stress distribution, delivering exceptional strength-to-weight ratios. This advantage renders them indispensable for aerospace systems, pressurized containers, architectural domes, and structures operating in extreme environments, such as deep-sea or nuclear containment. Their superior load-bearing capacity enables diverse applications, including satellite casings and high-pressure vessels. Meticulous optimization of geometric parameters and material selection ensures robustness in demanding scenarios. Given their significance, this study examines the natural frequency and static response of bio-inspired helicoidally laminated carbon fiber–reinforced polymer matrix composite spherical panels surrounded by Winkler elastic foundation support. Utilizing a 3D elasticity approach and the finite element method (FEM), the governing equations of motion are derived via Hamilton’s Principle. The study compares five helicoidal stacking configurations—recursive, exponential, linear, semicircular, and Fibonacci—with traditional laminate designs, including cross-ply, quasi-isotropic, and unidirectional arrangements. Parametric analyses explore the influence of lamination patterns, number of plies, panel thickness, support rigidity, polar angles, and edge constraints on natural frequencies, static deflections, and stress distributions. The analysis reveals that the quasi-isotropic (QI) laminate configuration yields optimal vibrational performance, attaining the highest fundamental frequency. In contrast, the cross-ply (CP) laminate demonstrates marginally best static performance, exhibiting minimal deflection. The unidirectional (UD) laminate consistently shows the poorest performance across both static and dynamic metrics. These investigations reveal stress transfer mechanisms across layers and elucidate vibration and bending behaviors in laminated spherical shells. Crucially, the results underscore the ability of helicoidal arrangements in augmenting mechanical and structural performance in engineering applications
Predictive Models for Early Infection Detection in Nursing Home Residents: Evaluation of Imputation Techniques and Complementary Data Sources
No full textBackground: Aging in Western societies poses a growing challenge, placing increasing pressure on healthcare costs. Early identification of infections in elderly nursing home residents is crucial to reduce complications, mortality, and the burden on emergency departments. Methods: We performed a comparative analysis of machine learning models using XGBoost classifiers for infection detection, addressing incomplete daily physiological measurements (Heart Rate, Oxygen Saturation, Body Temperature, and Electrodermal Activity) through strict imputation protocols. We evaluated three model variants—Basic (clinical only), Air Pollution-added, and Social Media-integrated—while incorporating a novel Basal Module to personalize physiological baselines for each resident. Results: Results from the binary model indicate that physiological data provides a necessary baseline for immediate screening. Notably, social media integration emerged as a powerful forecasting tool, extending the predictive horizon to a 6-day lead time with an F1-score of 0.97. Complementarily, air pollution data ensured robust immediate detection (“nowcasting”). In the multiclass scenario, external data resolved the “semantic gap” of vital signs, improving sensitivity for specific infections (e.g., acute respiratory and urinary tract infections) to over 90%. Conclusions: These findings highlight that the strategic integration of environmental and digital signals transforms the system from a reactive monitor into a proactive early warning tool for long-term care facilities
Degradation-Aware Multi-Stage Fusion for Underwater Image Enhancement
No full textUnderwater images frequently suffer from color casts, low illumination, and blur due to wavelength-dependent absorption and scattering. We present a practical two-stage, modular, and degradation-aware framework designed for real-time enhancement, prioritizing deployability on edge devices. Stage I employs a lightweight CNN to classify inputs into three dominant degradation classes (color cast, low light, blur) with 91.85% accuracy on an EUVP subset. Stage II applies three scene-specific lightweight enhancement pipelines and fuses their outputs using two alternative learnable modules: a global Linear Fusion and a LiteUNetFusion (spatially adaptive weighting with optional residual correction). Compared to the three single-scene optimizers (average PSNR = 19.0 dB; mean UCIQE ≈ 0.597; mean UIQM ≈ 2.07), the Linear Fusion improves PSNR by +2.6 dB on average and yields roughly +20.7% in UCIQE and +21.0% in UIQM, while maintaining low latency (~90 ms per 640 × 480 frame on an Intel i5-13400F (Intel Corporation, Santa Clara, CA, USA). The LiteUNetFusion further refines results: it raises PSNR by +1.5 dB over the Linear model (23.1 vs. 21.6 dB), brings modest perceptual gains (UCIQE from 0.72 to 0.74, UIQM 2.5 to 2.8) at a runtime of ≈125 ms per 640 × 480 frame, and better preserves local texture and color consistency in mixed-degradation scenes. We release implementation details for reproducibility and discuss limitations (e.g., occasional blur/noise amplification and domain generalization) together with future directions
Dynamic Changes in Gut Microbiota Composition and Function over Time in Suckling Raccoon Dogs
No full textRaccoon dog fur is a commercially valuable animal product. As the scale of raccoon dog breeding continues to expand, ensuring the health of these animals has become an urgent priority. The gut microbiota plays a central role in regulating animal health; however, current research on the composition of raccoon dog gut microbiota remains limited. This study aimed to characterize changes in the gut microbiota of suckling raccoon dogs across different stages, providing a foundation for future scientific feeding practices. Fecal samples of eight lactating raccoon dogs were collected and tested for microbiota on days 14, 21, and 45. Our results showed that the richness and diversity of microbiota increased with age in suckling raccoon dogs, peaking on the 45th day. Significant separation between groups was observed in both PCoA and NMDS analyses. UPGMA analysis indicated temporal fluctuations in gut microbiota composition. At the phylum level, Firmicutes and Bacteroidetes were the dominant taxa across all stages. LEfSe analysis at the genus level showed that Bacteroides was the most enriched taxon on the 14th day, Fusobacterium on the 21st day, and Prevotella_9 on the 45th day. Tax4Fun and PICRUSt analyses identified metabolism and genetic information processing as the primary functional roles of the gut microbiota. Further investigation suggested that the microbiota may benefit raccoon dogs through membrane transport, carbohydrate metabolism, amino acid metabolism, and energy metabolism. These findings establish a theoretical basis for improving the survival rate of suckling raccoon dogs and developing scientifically informed feeding and management protocols
Exercise and Sports Among Working-Age Citizens in Lithuania Since the COVID-19 Pandemic: An Annual Comparative Study (2021–2024)
No full textBackground and Objectives: The COVID-19 pandemic had a significant impact on physical activity among various populations. Due to a lack of country-representative studies on the prevailing trends in leisure-time physical activity since the COVID-19 pandemic, the aim of this study was to assess the temporal, social, and demographic inequalities in the prevalence of engagement in exercise and sports among working-age citizens of Lithuania from 2021 to 2024. Materials and Methods: This study included four samples of working-age citizens (1600 per year, 6400 in total). Four surveys were conducted, and the distribution of respondents among the groups was compared. Results: In general, the prevalence of engagement in exercise and sports did not change over a four-year period (48.8%, p = 0.256). The prevalence of regular exercise and sports increased, while engagement in irregular exercise and sports decreased (p = 0.014). Binary logistic regression analysis showed that younger age, male sex, being single, having no children under 18 years of age, selecting foods for health strengthening, positive self-assessment of nutrition and health status, use of dietary supplements, attention to purchasing healthy products, and university education attainment were associated with engagement in exercise and sports (regular or irregular) (p < 0.05). Analysis focused specifically on regular exercise and sports revealed associations with a longer time since the onset of the COVID-19 pandemic, younger age, urban residence, selection of foods for health strengthening, positive assessment of nutrition and health status, and university education attainment (p < 0.05), while no significant associations were observed with sex, marital status, presence of children under 18 years of age, use of dietary supplements, or attention to purchasing healthy products (p > 0.05). Conclusions: The overall prevalence of physical activity engagement among working-aged Lithuanian citizens did not change from 2021 to 2024, engagement in regular and irregular exercise and sports has changed. Engagement in regular and irregular exercise and sports is associated with different social profiles
Three-Dimensional Radar Echo Extrapolation Using a Physics-Constrained Deep Learning Model
No full textAccurate nowcasting of severe convective storms is crucial for disaster mitigation, yet storm complexity challenges conventional deep learning models. Existing methods often use single-level radar data and lack physical constraints, limiting skill in predicting small-scale convective systems. To address this, we propose DIFF-3DRformer, a novel deep learning framework for 3D radar echo extrapolation. This model unifies a mesoscale evolution network, embedded with 3D advection equation neural operators and a 3D continuity equation-informed loss function, and a convective-scale denoising generative network based on a diffusion model, within an end-to-end architecture optimized for prediction accuracy. Evaluated on severe storm events over Jiangsu, China, DIFF-3DRformer demonstrates robust predictive skill across various convective scales. It outperforms NowcastNet, improving the comprehensive score by 44.8% for reflectivity thresholds ≥35 dBZ. Utilizing 19 vertical levels of radar data as input significantly enhances the morphology and intensity prediction of convective echoes, boosting performance by 4.63% compared to using only composite reflectivity. Furthermore, the incorporation of physical constraints refines the forecasted echo structure and spatial placement, yielding additional improvements. DIFF-3DRformer provides accurate short-term evolution forecasts of convective systems, offering a promising solution for developing nowcasting methods that directly characterize the 3D structure of convective storms
Impact of Urban Morphology on Microclimate and Thermal Comfort in Arid Cities: A Comparative Study and Modeling in Béchar
No full textUrban morphology plays a decisive role in regulating microclimate and outdoor thermal comfort in arid cities, where extreme heat and intense solar radiation amplify thermal stress. This study examines the influence of four contrasting urban fabrics in Béchar (Algerian Sahara): the vernacular Ksar, the regular-grid colonial fabric, a modern large-scale residential estate, and low-density detached housing, on local microclimatic conditions. An integrated methodological framework is adopted, combining qualitative morphological analysis, quantitative indicators including density, porosity, height-to-width ratio, and sky view factor, in situ microclimatic measurements, and high-resolution ENVI-met simulations performed for the hottest summer day. Results show that compact urban forms, characterized by low sky view factor values, markedly reduce radiative exposure and improve thermal performance. The vernacular Ksar, exhibiting the lowest SVF, records the lowest mean radiant temperature (approximately 45 °C) and the most favorable average comfort conditions (PMV = 3.77; UTCI = 38.37 °C), representing a reduction of about 3 °C, while its high-thermal-inertia earthen materials ensure effective nocturnal thermal recovery (PMV ≈ 1.06; UTCI = 27.8 °C at 06:00). In contrast, more open modern fabrics, including the colonial grid, large-scale estates, and low-density housing, experience higher thermal stress, reflecting vulnerability to solar exposure and limited thermal inertia. Validation against field measurements confirms model reliability. These findings highlight the continued relevance of vernacular bioclimatic principles for sustainable urban design in arid climates