Search Results (15,916)

The photothermal effect is an important part of biological tissue optics. The reasonable use of temperature changes caused by the photothermal effect is of great value for the treatment of lesions. However, it is not easy to measure changes in light and heat temperatures in tissues experimentally. This paper combines Monte Carlo simulation and finite-element numerical calculation based on the Pennes biological tissue heat transfer equation to simulate light transmission and distributions of light and heat in biological tissues, including single-layer uniform biological tissue simulations and a classic three-layer skin optical model. Through the simulation of single-layer uniform biological tissue, the overall trend and range of biological tissue temperature change under different parameters are obtained in this work. Third, in the classic three-layer skin optical model simulation, this work combines a data-fitting method to derive a formula relating internal temperature and tissue depth to the absorption coefficient. Compared with the simulation standard results, the error of the above fitting formula is within 1.2%, and it can be applied in the field of photothermal therapy in the future to help medical workers understand the range of temperature changes in biological tissues. Full article

Background: Endometrial cancer (EC) is the most common gynecologic malignancy in developed countries and one of the few solid tumors with a steadily rising incidence, paralleling global trends in obesity and insulin resistance. Its strong epidemiologic association with systemic metabolic dysfunction positions EC as a uniquely accessible model for metabolically informed chemoprevention. Methods: This narrative review was conducted through a systematic search of PubMed/MEDLINE and Embase using the following terms: “endometrial cancer” AND (“insulin resistance” OR “metabolic syndrome” OR “PI3K” OR “chemoprevention” OR “bariatric surgery” OR “metformin” OR “cellular senescence”). Searches were limited to English-language publications; no date restriction was applied for foundational molecular studies, while clinical and translational evidence was reviewed from 2000 to 2025. Additional references were identified through manual review of reference lists of included articles. Results: We examine metabolic amplification as a conceptual framework in which hyperinsulinemia, inflammatory reinforcement, and redox-epigenetic modulation intensify proliferative signaling in biologically susceptible endometrial tissue, particularly within molecular subtypes enriched for PI3K pathway activation such as tumors lacking a specific molecular profile (NSMP). Bariatric surgery offers the strongest human evidence supporting the principle that durable metabolic correction can substantially reduce EC incidence. In contrast, pharmacologic interventions including metformin, anti-inflammatory agents, and nutraceutical compounds demonstrate variable or limited preventive efficacy, and short-term biomarker modulation cannot substitute for validated reduction in cancer risk. The endometrial intraepithelial neoplasia (EIN) model provides a uniquely accessible platform for biomarker-guided intervention. Conclusions: Integration of genomic subtype classification with metabolic profiling may enable precision prevention strategies in clearly defined high-risk populations. Effective chemoprevention will require molecular enrichment, confirmation of tissue-level target engagement, and clinically meaningful endpoints, while acknowledging the translational limits of pathway-directed approaches. Full article

Osteoarthritis (OA) is a complex degenerative joint disease for which early diagnosis and clear molecular characterization remain limited. DNA methylation has been increasingly recognized as an important regulatory factor in OA pathogenesis. In this study, we proposed an integrative computational framework combining statistical analysis, machine learning, deep learning, and functional genomics to identify and validate OA-associated genes and methylation biomarkers for diagnostic and biological interpretation. Candidate CpG sites were obtained using two complementary strategies: differential methylation analysis and selection of loci located near transcription start sites of previously reported OA-related genes. Key features were further refined using support vector machine recursive feature elimination and random forest algorithms. Based on the selected loci, we developed a feature-fusion diagnostic model that combines Transformer and convolutional neural networks with adaptive weighting to capture both global dependency structures and local methylation patterns. A panel of 220 methylation sites demonstrated stable and reproducible diagnostic performance in an independent cohort. Functional annotation and pathway analysis highlighted several established OA-associated genes, including TGFBR2, SMAD3, PPARG, and MAPK3, and suggested INHBB as a potential novel effector gene, with additional support for AMH and INHBE involvement. Overall, this study presents a robust methylation-based framework for identifying key OA-associated genes and provides new insights into the epigenetic mechanisms underlying OA. Full article

Background: Aging is the strongest risk factor for prostate cancer (PCa). It is accompanied by progressive epigenomic divergence, known as epigenetic drift, particularly affecting DNA methylation at regulatory regions. However, the extent to which age-associated promoter methylation contributes to coordinated microRNA (miRNA) expression changes in PCa remains incompletely characterized. Methods: We conducted an integrative in silico analysis of 449 primary tumors from the TCGA-PRAD cohort. Age was modeled as a continuous variable. Age-related miRNA expression changes were estimated from miRNA-seq data using DESeq2. Promoter DNA methylation changes (±2 kb from transcription start sites) were assessed using Illumina 450K arrays and linear regression. MiRNAs showing significant age-associated alterations at both expression and methylation levels were classified as concordant or discordant based on directionality and prioritized using an effect size-based concordance score. We analyzed experimentally validated targets of prioritized miRNAs through functional enrichment and network-based approaches to identify convergent regulatory pathways. Results: Initially, we identified 105 age-associated miRNAs. After filtering, 65 candidates remained. Of these, we found 37 miRNAs with significant age-associated changes at both layers, including 20 concordant and 17 discordant miRNAs. These comprised well-characterized cancer-associated miRNAs and lesser-studied candidates enriched in CpG-rich regulatory regions. Network analyses revealed a limited set of genes under convergent regulation by multiple age-associated miRNAs. These implicated pathways are related to cell cycle control, apoptosis, stress response, and epigenetic regulation. Conclusions: Our findings support a model in which age-dependent promoter methylation drift contributes to coordinated miRNA deregulation in PCa. This convergence highlights biologically plausible miRNA biomarkers and age-sensitive epigenetic circuits relevant to prostate carcinogenesis. Full article

DNA mixture interpretation remains one of the most technically demanding challenges in forensic genetics. While probabilistic genotyping (PG) systems have substantially advanced likelihood ratio (LR) evaluation, comparatively less attention has been devoted to the systematic reconstruction of contributor genotypes, particularly in no-suspect and database-search contexts. This review synthesizes recent developments in DNA mixture deconvolution through a four-strategy framework: (i) physical and biological separation, (ii) high-information genetic markers, (iii) continuous probabilistic algorithms, and (iv) integration with database searching infrastructures. Upstream approaches, including single-cell isolation and sequencing, reduce mixture complexity at the molecular level. Marker innovations such as microhaplotypes, MiniHaps and DIP-STRs increase per-locus information content and enhance resistance to degradation. Downstream probabilistic models—extended from STRs to SNPs and microhaplotypes—leverage quantitative signal data to infer contributor genotypes, with recent advances in Hamiltonian Monte Carlo, variational inference, and deep learning improving inferential stability and reconstruction accuracy. Importantly, genotype deconvolution and LR evaluation represent mathematically distinct objectives, requiring different validation metrics and potentially separate architectural optimization. The convergence of molecular innovation, algorithmic refinement, and LR-based database searching is progressively transforming mixture interpretation from a purely evidential assessment into an integrated investigative framework. Future progress will depend on standardized marker panels, deconvolution-specific performance metrics, and scalable LR-enabled database infrastructures. Full article

The Spur-thighed tortoise (Testudo graeca) is a long-lived terrestrial reptile listed as ‘Vulnerable’ on the IUCN Red List and protected under CITES Appendix II. As an ecosystem engineer, it plays a vital role in Mediterranean landscapes, yet it frequently faces anthropogenic pressures in urban environments. This study provides an ecological and ethological assessment of a captive T. graeca population (n = 42) in the historical Münire Madrasa Handicrafts Bazaar in Kastamonu, Türkiye. The methodology integrated spatial carrying capacity modeling (Boullon model), systematic ethogram-based observations (120 h), and ethnozoological surveys (n = 200). Spatial analysis revealed that the population exceeds the corrected Real Carrying Capacity (RCC ≈ 10) by four times (Overcapacity Index: 4.2) within the 70 m² area. Ethological findings documented chronic stress, with stereotypic pacing (H1) occupying 32% of the time budget, alongside a significant loss of anti-predator mechanisms due to anthropogenic habituation (İ1). While stakeholders (100%, 95% CI: 98.1–100%) perceive the tortoises as cultural symbols of abundance, the biological reality indicates severe welfare risks, including potential metabolic bone disease from a monotonous anthropogenic diet and a disrupted Ca:P ratio. The site is categorized as a ‘High-Constraint Interaction Zone’. We propose a management transition toward a monitored ‘Urban Wildlife Education Station’ to align local cultural values with international animal welfare and conservation standards. Full article

In this paper, a novel multiband microwave resonator is proposed and investigated for non-invasive glucose sensing applications. The structure is based on a compact, planar spiral-like geometry fed by a Coplanar waveguide (CPW) transmission line, designed to support multiple resonant modes through nested concentric rings. A full electromagnetic model was developed to predict the resonance behavior analytically, achieving excellent agreement with Computer Simulated Technology (CST) simulations across four resonant frequencies (2.7, 6.44, 8.0, and 12.8 GHz). The sensor demonstrated high glucose sensitivity at multiple frequencies, with peak values reaching 0.05 dB/mg/dL and 0.038 dB/mg/dL at 10.1 GHz and 6.22 GHz, respectively. To enhance conformability and skin contact, the antenna was further transformed into a semi-cylindrical flexible form suitable for finger-wrapping. Despite the mechanical deformation, the structure preserved its resonance while offering enhanced near-field interaction with biological tissues. The folded sensor achieved a sensitivity of 0.032 dB/mg/dL at 5.25 GHz and a peak gain of 6.05 dB, validating its robustness for wearable deployment. The clear correlation between reflection magnitude and glucose level (with R > 0.99) confirms the sensor’s potential as a passive, multiband, and non-invasive glucose monitoring platform. The physics-informed residual deep learning framework significantly enhances prediction accuracy, achieving an RMSE of 0.28 mg/dL, MARD of 0.13%, and confining 100% of both training and holdout predictions within the <5% ISO-like risk region, thereby ensuring robust and clinically reliable non-invasive glucose estimation. Full article

The effective treatment of neurodegenerative diseases (NDDs), such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis, remains a critical challenge in modern medicine. Given the limitations of current therapies, alternative strategies to slow neurodegeneration are urgently needed. This study presents a critical review of the current evidence regarding low-dose ionizing radiation (IR) as a promising modality for modulating neurodegenerative processes. This study examines current experimental data on the effects of low-dose IR (LDIR) on cellular protective and compensatory mechanisms, including evidence from in vivo models of NDDs. Our analysis demonstrates that LDIR enhances antioxidant activity and DNA repair, stimulates autophagy and neuroplasticity, and modulates neuroinflammatory signaling. Collectively, these findings support the hypothesis of the neuroprotective potential of LDIR, underscoring its translational viability provided that strict dosimetric guidelines are followed and individual biological responses are rigorously monitored. Full article

There is an increasing interest in functional food formulations with added bioactive compounds, such as vitamins, probiotics, polyphenols and bioactive peptides, specifically in dairy and plant-based foods, bakery, and beverages. However, their stability in the food system, release rates and biological activity after consumption/digestion play an important role in the effectiveness of functional foods. There are technical challenges in maintaining the stability and acceptability of added compounds in the formulation design of food items. A novel approach to delivering bioactive compounds in functional foods is their microencapsulation, where stability-sensitive compounds are protected against their degradation during processing and physiological digestion, with targeted release in the gastrointestinal tract (GIT) and elicited cellular responses. Microencapsulation of bioactive compounds has been proven to be beneficial in in vitro models for the stability, antioxidant and immunomodulatory action, and acceptability compared to free (non-capsulated) forms. This technology is worth considering relative to the protection of health benefits of compounds used in food products, with their necessary bioactivity after physiological digestion in GIT. This article reviews important bioactive compounds, challenges, and strategies in the development of functional foods to ensure the required stability for the bioavailability of added compounds. Full article

Lumbar spine disorders often require surgical intervention using medical implants to stabilize or replace damaged structures. As the prevalence of these surgeries increases due to an aging population, rigorous preclinical evaluation is critical. This narrative review aims to summarize current testing methods, identify gaps in clinical translatability, and explore the role of emerging computational technologies. Mechanical testing protocols established by the American Society for Testing and Materials (ASTM) and the International Organization for Standardization (ISO) provide essential standardized data on structural integrity but fail to replicate the complex biological interactions of the human spine. Similarly, animal models offer insights into biological responses like osseointegration but are limited by quadrupedal biomechanics and anatomical differences. Recent advancements in Artificial Intelligence (AI) and Finite Element Analysis (FEA) enable rapid, patient-specific modeling and high-throughput screening, significantly reducing the time and cost of physical testing. Future innovations include 3D-printed personalized implants, bio-responsive materials, and genetically modified animal models to bridge existing translatability gaps. In conclusion, improving the clinical success of lumbar spine implants requires an integrated framework that combines mechanical, biological, and computational approaches. This interdisciplinary collaboration is vital for developing safer and more effective treatments for patients. Full article

The global restriction of antimicrobial growth promoters has intensified the search for alternative strategies to sustain poultry health and productivity. One proposed mechanism underlying the historical efficacy of antibiotic performance enhancers is the modulation of intestinal inflammation. In this context, meloxicam (MLX), a preferential COX-2 inhibitor and non-steroidal anti-inflammatory drug, has emerged as a potential candidate for investigation. However, pharmacokinetic data in broiler chickens remain limited, particularly for practical oral formulations intended for production systems. This study aimed to characterize the pharmacokinetic profile of a novel granulated MLX formulation in male Cobb 500 broiler chickens following single-dose administration. Seventy-two 21-day-old broilers received MLX granulate (19.24% m/m) via oral gavage at 3.6 mg/kg body weight. Plasma samples were collected over 48 h post administration. MLX concentrations were quantified using validated high-performance liquid chromatography, and pharmacokinetic parameters were estimated using nonlinear mixed-effects modelling (NLME). Mean pharmacokinetic parameters included AUC_0–∞ of 79.97 μg·h/mL, C_max of 14.43 μg/mL, and T_max of 1 h, indicating rapid absorption and substantial systemic exposure. These findings provide novel insights into MLX disposition from the granulated formulation in broilers and provide pharmacokinetic information to support future investigations evaluating its potential biological effects in poultry production systems. Full article

Soil health is essential for food security, ecosystem stability, and sustainable development, yet its spatial heterogeneity and driving mechanisms remain insufficiently understood at regional scales. This study investigates soil health in Heilongjiang Province, China. A Soil Health Index (SHI) was constructed using eight indicators covering physical, chemical, and biological properties based on multi-source datasets at 1 km spatial resolution. A random forest (RF) model was applied to identify key environmental drivers, and Moran’s I and Getis–Ord Gi* statistics were used to analyze spatial clustering. The results showed that SHI values ranged from 0.19 to 0.70, with a mean of 0.45. The RF model achieved strong performance (R² = 0.6666, RMSE = 0.03184, MAE = 0.02372), significantly outperforming linear regression (R² ≈ 0.17). Significant spatial clustering was observed, where “hotspots” refer to statistically significant clusters of high SHI values, and “coldspots” indicate clusters of low SHI values based on Getis–Ord Gi* analysis. Climate factors (temperature and precipitation) and elevation were the dominant drivers. Significant spatial clustering was observed, with clear hotspot and coldspot patterns. These findings provide spatial evidence for sustainable land-use planning and zonal soil management. However, the analysis is limited by data resolution and model interpretability, which may affect the representation of fine-scale variability. Full article

The SH-SY5Y cell line is widely used as an in vitro model for pharmacological and molecular investigations of Parkinson’s disease (PD). The use of SH-SY5Y cells in PD research critically relies on their ability to differentiate into a mature, post-mitotic, dopaminergic (DAergic) neuronal phenotype. However, SH-SY5Y cells are inherently heterogeneous since they are firstly catecholaminergic cells and may express diverse phenotypic markers besides the DAergic ones. These properties seem to be determined by the differentiation protocol that is employed, thus meaning it is crucial to obtain proper cell types. This systematic review aims to discuss the main differentiation protocols used in PD research over the last 30 years. They include inducers such as retinoic acid (RA), the phorbol ester TPA, and the BDNF. Among the 514 studies that were screened, 249 employed these inducers. Then, we quantitatively report the ability of these protocols to differentiate SH-SY5Y cells in mature DAergic neurons, evaluating morphology, differentiation markers, and DAergic markers among the studies that specifically compared differentiated to undifferentiated SH-SY5Y cells (61 studies over 249). As our research shows, despite the highest usage of the RA differentiation protocol, the combination of RA with the BDNF inducer seems to increase the expression and the acquisition of a DAergic phenotype. Nevertheless, during this analysis, some limitations emerged, highlighting the intrinsic phenotypic heterogeneity of these cells, thereby limiting their suitability according to the specific biological question under investigation. A deep investigation into the literature about the molecular phenotypic features of differentiated SH-SY5Y cells may eventually help us to understand the advantages and disadvantages of each protocol that was employed, and adequately set experiments around the PD research. Full article

This research introduces a new hydroxyapatite-based composite, designed as a bone-implant scaffold—easy, quick, economical, and closely mimicking the structure of natural bone. Additive manufacture was used to print bioactive material to form a scaffold structure. Thus, during the experimental research, three different composite materials were made to examine both their mechanical and morphological properties. Numerical modeling was used to maximize and prove the mechanical and biological performance of the HA-polymer grafts. The obtained results indicated that incorporating HA and Mg particles into a polymeric matrix allows the structure to be used in tissue engineering. Best results were obtained using a structure, designed from PLA and PHA at 30%, PHB at 25%, Mg at 5%, and HA at 10%. The composite was distinguished by its lightness, strength, and biocompatibility, making it suitable for tissue engineering. Full article

Utilizing food-derived bioactive polysaccharides in advanced biomedical applications offers significant potential. To effectively harness the inherent bioactivity of Poria cocos, a renowned edible and medicinal fungus, we developed a multifunctional double-network composite hydrogel (CPS) via a feasible one-pot strategy. This was achieved by incorporating functional carboxymethyl pachymaran (CMP) into a matrix of food-grade sodium alginate (SA) and polyacrylamide (PAM). This formulation endows the hydrogel with excellent extensibility, rapid self-healing capabilities, and strong tissue adhesion, all while preserving the biological activity of the natural macromolecules. In a mouse full-thickness skin defect model, the CPS significantly accelerated wound recovery, achieving a healing rate of 51.17 ± 4.87% by day 7. Mechanistically, the food-derived CMP synergistically promoted skin tissue regeneration by downregulating the expression of the early pro-inflammatory cytokine TNF-α and upregulating the angiogenic marker CD31, thereby actively modulating the local microenvironment. Ultimately, these findings demonstrate the viability of using edible fungal polysaccharides as primary bioactive components in advanced wound dressings, providing a novel approach for utilizing food macromolecules in biomedicine. Full article