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Transcription factors play crucial roles in regulating gene expression, and any dysregulation in their levels could be involved in cancer progression. The role of androgen receptors (AR) and zinc finger (ZNF) proteins in tumors, like prostate cancer (PC), remains poorly understood. Moreover, due to the multifaceted transcriptional behavior of ARs and ZNFs, their biological role in cancer progression may also depend on the interplay with micro-RNAs (miRNAs). Based on The Cancer Genome Atlas (TCGA) database, we analyzed the expression levels of zinc finger transcripts and ARs in PC. Specifically, exploring their involvement in cancer progression and regulation by miRNAs. The analysis relied on several tools to create a multivariate combination of the original biomarkers to improve their diagnostic efficacy. Multidimensional Scaling (MDS) identified two new dimensions that were entered into a regression analysis to determine the best predictors of overall survival (OS) and disease-free interval (DFI). A combination of both dimensions predicted almost 50% (R² = 0.46) of the original variance of OS. Kaplan–Meier survival analysis also confirmed the significance of these two dimensions regarding the clinical output. This study showed preliminary evidence that several transcription factor expression levels belonging to the zinc family and related miRNAs can effectively predict patients’ overall PC survivability. Full article

The paper studies the behavior of homogeneous isotropic materials by performing appropriate numerical analyses and utilizing suitable FEMs to reproduce the Brazilian splitting test. Starting with a theoretical approach and adopting suitable numerical simulations, a new formula that is able to characterize the Young’s modulus is presented. To this end, in addition to the analysis of the specimen’s response in terms of stresses and strains, the real displacement field resulting from the real kinematical constraints on the specimen is determined. Therefore, the Brazilian test is taken as a reference test and the specimen’s behavior is derived by taking advantage of both the theoretical approach and numerical simulations developed in the ANSYS 2021 R1 environment. The latter allows us to define a new mathematical relation representing the missing part of the kinematical field. Furthermore, a new formula which explicitly relates the Young’s modulus of the material to the geometrical characteristics of the specimen, to the acting force, and to a measured selected displacement is proposed. Future developments will include adopting the proposed formulas for the identification of other mechanical parameters of the material, e.g., by adopting a full-field contactless approach to displacement measurement and studying the behavior of specimens with different geometrical characteristics. Full article

This narrative review explores the role of additive manufacturing (AM) technologies in the production of dental implants, focusing on materials and key AM methods. The study discusses several materials used in implant fabrication, including porous titanium, trabecular tantalum, zirconium dioxide, polymers, and composite materials. These materials are evaluated for their mechanical properties, biocompatibility, and suitability for AM processes. Additionally, the review examines the main AM technologies used in dental implant production, such as selective laser melting (SLM), electron beam melting (EBM), stereolithography (SLA), selective laser sintering (SLS), and direct metal laser sintering (DMLS). These technologies are compared based on their accuracy, material limitations, customization potential, and applicability in dental practice. The final section presents a data source analysis of the Web of Science and Scopus databases, based on keyword searches. The analysis evaluates the research trends using three criteria: publication category, document type, and year of publication. This provides an insight into the evolution and current trends in the field of additive manufacturing for dental implants. The findings highlight the growing importance of AM technologies in producing customized and efficient dental implants. Full article

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

This study investigates the use of waste glass powder derived from fluorescent lamps as a partial replacement for cement in mortar production, aiming to valorize this Waste from Electrical and Electronic Equipment (WEEE) and enhance sustainability in the construction sector. Mortars were formulated by substituting 25% of cement by volume with glass powders from fluorescent lamp glass and green bottle glass. The experimental program evaluated mechanical strength, durability parameters and ecotoxicological performance. Results revealed that clean fluorescent lamp mortars showed the most promising mechanical behavior, exceeding the reference in long-term compressive (54.8 MPa) and flexural strength (10.0 MPa). All glass mortars exhibited significantly reduced chloride diffusion coefficients (85–89%) and increased electrical resistivity (almost 4 times higher), indicating improved durability. Leaching tests confirmed that the incorporation of fluorescent lamp waste did not lead to hazardous levels of heavy metals in the cured mortars, suggesting effective encapsulation. By addressing both technical (mechanical and durability) and ecotoxic performance, this research contributes in an original and relevant way to the development of more sustainable building materials. Full article

This study investigates the potential of using downgraded chestnuts, which are unsuitable for commercial sale, from five distinct Greek regions to produce chestnut flour and formulate gluten-free biscuits. Chestnuts were dried and milled into flour, which was then used as the sole flour ingredient in the biscuit formulation, in order to assess its nutritional and functional contribution. The moisture, lipid, protein, and ash contents were analyzed in chestnut flour samples, which showed significant regional differences. Chestnut flour biscuits (CFB) were compared to wheat flour biscuits (WFB). CFB exhibited significantly higher ash content (3.01% compared to 0.94% in WFB) and greater antioxidant capacity, with DPPH scavenging activity reaching 70.83%, as opposed to 61.67% in WFB, while maintaining similar moisture and lipid levels. Although CFB showed slightly lower protein content, the elevated mineral and phenolic compound levels contributed to its functional value. These findings indicate that downgraded chestnuts can be upcycled into gluten-free bakery products with improved functional characteristics. Given their antioxidant activity and mineral content, chestnut flour biscuits may serve as a valuable option for gluten-free diets, supporting circular economy principles and reducing food waste. Full article

Cell culture models are of central importance for the investigation of cellular metabolism, proliferation and stress responses. In this study, the effects of different concentrations of glucose (1 g/L vs. 4.5 g/L) and fetal bovine serum (FBS; 5%, 10%, 15%) on viability, mitochondrial function and autophagy are investigated in four human cell lines: MRC-5, HeLa, Caco-2 and SW-620. Cells were cultured in defined media for 72 h, and viability was assessed by LDH release, mitochondrial membrane potential using Rhodamine 123, ATP content by luminescence and autophagy activity by dual fluorescence staining. The results showed that HeLa and SW-620 cancer cells exhibited increased proliferation and mitochondrial activity under high glucose conditions, while low glucose media resulted in decreased ATP content and increased membrane permeability in HeLa cells. MRC-5 fibroblasts and Caco-2 cells showed greater resilience to nutrient stress, with minimal changes in LDH release and consistent proliferation. Autophagy was activated under all conditions, with a significant increase only in selected cell-medium combinations. These results highlight the importance of medium composition in influencing cellular bioenergetics and stress responses, which has implications for cancer research, metabolic disease modelling and the development of serum-free culture systems for regenerative medicine. Full article

The rise in multidrug-resistant bacterial strains and persistent infections such as Lyme disease caused by Borrelia burgdorferi highlights the need for novel antimicrobial agents. The present study explores the antioxidant, antibacterial, and cytotoxic properties of extracts from submerged mycelial biomass of Fomitopsis pinicola, cultivated in synthetic and lignocellulosic media. Four extracts were obtained using hot water and 80% ethanol. The provided analysis of extracts confirmed the presence of various bioactive compounds, including flavonoids, alkaloids, and polyphenols. All extracts showed dose-dependent antioxidant activity (IC₅₀: 1.9–6.7 mg/mL). Antibacterial tests revealed that Klebsiella pneumoniae was most sensitive, with the L2 extract producing the largest inhibition zone (15.33 ± 0.47 mm), while the strongest bactericidal effect was observed against Acinetobacter baumannii (MBC as low as 0.5 mg/mL for L1). Notably, all extracts significantly reduced the viability of stationary-phase B. burgdorferi cells, with L2 reducing viability to 42 ± 2% at 5 mg/mL, and decreased biofilm mass, especially with S2. Cytotoxicity assays showed minimal effects on NIH 3T3 cells, with slight toxicity in HEK 293 cells for S2 and L1. These results suggest that F. pinicola extracts, particularly ethanolic L2 and S2, may offer promising natural antimicrobial and antioxidant agents for managing resistant infections. Full article

China is one of the countries severely affected by earthquakes, making precise and timely identification of earthquake precursors essential for reducing casualties and property damage. A novel method is proposed that combines a rock acoustic emission (AE) detection technique with deep learning methods to facilitate real-time monitoring and advance earthquake precursor detection. The AE equipment and seismometers were installed in a granite tunnel 150 m deep in the mountains of eastern Guangdong, China, allowing for the collection of experimental data on the correlation between rock AE and seismic activity. The deep learning model uses features from rock AE time series, including AE events, rate, frequency, and amplitude, as inputs, and estimates the likelihood of seismic events as the output. Precursor features are extracted to create the AE and seismic dataset, and three deep learning models are trained using neural networks, with validation and testing. The results show that after 1000 training cycles, the deep learning model achieves an accuracy of 98.7% on the validation set. On the test set, it reaches a recognition accuracy of 97.6%, with a recall rate of 99.6% and an F₁ score of 0.975. Additionally, it successfully identified the two biggest seismic events during the monitoring period, confirming its effectiveness in practical applications. Compared to traditional analysis methods, the deep learning model can automatically process and analyse recorded massive AE data, enabling real-time monitoring of seismic events and timely earthquake warning in the future. This study serves as a valuable reference for earthquake disaster prevention and intelligent early warning. Full article

Hydrogen sulfide (H₂S) can be produced from the metabolism of foods containing sulfur in the gastrointestinal tract (GIT). At low doses, H₂S regulates the gut microbial community and supports GIT health, but depending on dose, age, and individual health conditions, it may also contribute to inflammatory responses and gut barrier dysfunction. Controlling H₂S production in the GIT is important for maintaining a healthy gut microbiome. However, research on this subject is limited due to the gaseous nature of the chemical and the difficulty of accessing the GIT in situ. In the present ex vivo experiment, we used a single-dose sodium sulfide preparation (SSP) as a H₂S precursor to test the effect of H₂S on the human gut microbiome across different age groups, including breastfed infants, toddlers, adults, and older adults. Metagenomic sequencing and metabolite measurements revealed that the development of the gut microbial community and the production of short-chain fatty-acids (SCFAs) were age-dependent; that the infant and the older adult groups were more sensitive to SSP exposure; that exogeneous SSP suppressed SCFA production across all age groups, except for butyrate in the older adult group, suggesting that H₂S selectively favors specific gut microbial processes. Full article

Carbon monoxide (CO) is a major toxic gas emitted from vehicle exhaust, industrial processes, and incomplete fuel combustion, posing serious environmental and health risks. Catalytic oxidation of CO into less harmful CO₂ is an effective strategy to reduce these emissions. In this study, we investigated the catalytic performance of platinum (Pt) single atoms doped on C₃N monolayers with various vacancy defects, including single carbon (C_V) and nitrogen (N_V) vacancies, using density functional theory (DFT) calculations. Our results demonstrate that Pt@N_V-C₃N exhibited the most favorable catalytic properties, with the highest O₂ adsorption energy (−3.07 eV). This performance significantly outperforms Pt atoms doped at other vacancies. It can be attributed to the strong binding between Pt and nitrogen vacancies, which contributes to its excellent resistance to Pt aggregation. CO oxidation on Pt@N_V-C₃N proceeds via the Eley–Rideal (ER2) mechanism with a low activation barrier of 0.41 eV for the rate-determining step, indicating high catalytic efficiency at low temperatures. These findings suggest that Pt@N_V-C₃N is a promising candidate for CO oxidation, contributing to developing cost-effective and environmentally sustainable catalysts. The strong binding of Pt atoms to the nitrogen vacancies prevents aggregation, ensuring the stability and durability of the catalyst. The kinetic modeling further revealed that the ER2 mechanism offers the highest reaction rate constants over a wide temperature range (273–700 K). The low activation energy barrier also facilitates CO oxidation at lower temperatures, addressing critical challenges in automotive and industrial pollution control. This study provides valuable theoretical insights for designing advanced single-atom catalysts for environmental remediation applications. Full article

This research investigates enhancing the performance of an Archimedes screw-type hydrokinetic turbine (ASHT). A 3D transient computational model employing the six degrees of freedom (6-DOF) methodology within the ANSYS Fluent software 2022 R1, was selected for this purpose. A central composite design (CCD) methodology was applied within the response surface methodology (RSM) to enhance the turbine’s power coefficient (Cp). Key independent factors, including blade length (L), blade inclination angle (γ), and external diameter (De), were systematically varied to determine their optimal values. The optimization process yielded a maximum Cp of 0.337 for L, γ, and De values of 168.921 mm, 51.341°, and 245.645 mm, respectively. Experimental validation was conducted in a hydraulic channel, yielding results that demonstrated a strong correlation with the numerical predictions. This research underscores the importance of geometric design optimization in improving the energy capture efficiency of the ASHT, contributing to its potential viability as a competitive renewable energy solution in the pre-commercial phase of development. Full article

Pangasius (Pangasianodon hypophthalmus) minced muscle with 1 and 2% salt was treated with different high-pressure processing and thermal methods, including conventional heat-induced gels (HIGs), high-pressure processing (HPP) prior to cooking (PC), HPP prior to setting (PS), and setting prior to HPP (SP), to evaluate for their effects on the selected physicochemical properties. The results showed that the PC treatment produced gels with a significantly higher gel strength (496.72–501.26 N·mm), hardness (9.62–10.14 N), and water-holding capacity (87.79–89.74%) compared to the HIG treatment, which showed a gel strength of 391.24 N·mm, a hardness of 7.36 N, and a water-holding capacity of 77.98%. PC gels also exhibited the typical microstructure of pressure-induced gels, with a denser and homogeneous microstructure compared to the rough and loosely connected structure of HIGs. In contrast, SP treatment exhibited the poorest gel quality in all parameters, with gel strength ranging from 319.79 to 338.34 N·mm, hardness from 5.87 to 6.31 N, and WHC from 71.91 to 73.72%. Meanwhile, the PS treatment showed a comparable gel quality to HIGs. SDS-PAGE analysis revealed protein degradation and aggregation in HPP-treated samples, with a decrease in the intensity of myosin heavy chains and actin bands. Fourier-transform infrared spectroscopy (FTIR) analysis showed minor shifts in protein secondary structures, with the PC treatment showing a significant increase in α-helices (28.09 ± 0.51%) and a decrease in random coil content (6.69 ± 0.92%) compared to α-helices (23.61 ± 0.83) and random coil structures (9.47 ± 1.48) in HIGs (p < 0.05). Only the PC treatment resulted in a significant reduction in total plate count (TPC) (1.51–1.58 log CFU/g) compared to 2.33 ± 0.33 log CFU/g in the HIG treatment. These findings suggest that HPP should be applied prior to thermal treatments (cooking or setting) to achieve an improved gel quality in reduced-salt pangasius products. Full article

In this paper, we address the problem of intelligent operation of Distribution Static Synchronous Compensators (D-STATCOMs) in power distribution systems to reduce energy losses and CO₂ emissions while improving system operating conditions. In addition, we consider the entire set of constraints inherent in the operation of such networks in an environment with D-STATCOMs. To solve such a problem, we used three master–slave methodologies based on sequential programming methods. In the proposed methodologies, the master stage solves the problem of intelligent D-STATCOM operation using the continuous versions of the Monte Carlo (MC) method, the population-based genetic algorithm (PGA), and the Particle Swarm Optimizer (PSO). The slave stage, for its part, evaluates the solutions proposed by the algorithms to determine their impact on the objective functions and constraints representing the problem. This is accomplished by running an Hourly Power Flow (HPF) based on the method of successive approximations. As test scenarios, we employed the 33- and 69-node radial test systems, considering data on power demand and CO₂ emissions reported for the city of Medellín in Colombia (as documented in the literature). Furthermore, a test system was adapted in this work to the demand characteristics of a feeder located in the city of Talca in Chile. This adaptation involved adjusting the conductors and voltage limits to include a test system with variations in power demand due to seasonal changes throughout the year (spring, winter, autumn, and summer). Demand curves were obtained by analyzing data reported by the local network operator, i.e., Compañía General de Electricidad. To assess the robustness and performance of the proposed optimization approach, each scenario was simulated 100 times. The evaluation metrics included average solution quality, standard deviation, and repeatability. Across all scenarios, the PGA consistently outperformed the other methods tested. Specifically, in the 33-node system, the PGA achieved a 24.646% reduction in energy losses and a 0.9109% reduction in CO₂ emissions compared to the base case. In the 69-node system, reductions reached 26.0823% in energy losses and 0.9784% in CO₂ emissions compared to the base case. Notably, in the case of the Talca feeder—particularly during summer, the most demanding season—the PGA yielded the most significant improvements, reducing energy losses by 33.4902% and CO₂ emissions by 1.2805%. Additionally, an uncertainty analysis was conducted to validate the effectiveness and robustness of the proposed optimization methodology under realistic operating variability. A total of 100 randomized demand profiles for both active and reactive power were evaluated. The results demonstrated the scalability and consistent performance of the proposed strategy, confirming its effectiveness under diverse and practical operating conditions. Full article

(1) Background: Intrapartum obstetric violence has become increasingly visible and is portrayed as a cross-cutting and complex phenomenon. Despite numerous international debates and extensive reports in the literature, there is limited consensus on its definition, emphasizing the need to clarify the concept. The aim of this article is to analyze the concept of obstetric violence in the care of women in labor in health institutions; (2) Methods: Search and selection of studies using the scoping review methodology, based on the Joanna Briggs Institute guidelines and Rodgers’ conceptual review method for data extraction and analysis; (3) Results: A sample of 49 studies provided a comprehensive understanding of the concept, revealing in its conceptualization attributes of physical, verbal, psychological, sexual, institutional and structural violence. Identification of antecedents of gender inequality and failure of relational, technical and structural standards at the level of health institutions and their professionals, as the main triggers of obstetric violence. Reporting of consequences with a negative impact on maternal and child health; (4) Conclusions: Conceptual analysis with important contributions to the paradigm shift in the work of health professionals. Multiple dimensions, cultural differences and variations in the concept should continue to be examined to improve its research and application. Full article

Surface texture displays are touch panels that provide tactile feedback. Presenting softness sensations on such rigid surfaces remains a challenge, and effective methods are not yet established. This study explores how low-frequency frictional modulation during finger sliding can evoke the perception of softness. We examined multimodal optimization—whether the optimal tactile parameters vary depending on the type of visually presented fabric. Videos of draping cloth were shown beneath the panel, while spatial wavelength of frictional modulation and finger sliding speed were optimized using response surface methodology. The optimal spatial wavelength did not significantly differ across fabric types: towel (16.8 mm), cotton (16.5 mm), leather (17.1 mm), and suede (15.4 mm), with an overall range of 15–18 mm. In contrast, the optimal sliding speed significantly varied by fabric: towel (144 mm/s), cotton (118 mm/s), leather (167 mm/s), and suede (96 mm/s). These results suggest that frictional variation with a fixed spatial wavelength may serve as a general strategy for presenting softness. The findings contribute to advancing tactile rendering techniques for hard touch surfaces. Full article

Infrastructure facility development and modernization highly contribute to national economic growth, but at the same time, such development also causes local negative impacts on the use of specific land plots, creating losses for their right holders. In Russia, some prerequisites have already been laid down on the issue of compensation for the losses associated with restrictions on the rights and prohibitions of economic activity within zones with special territory use conditions (ZSTUCs). However, the impacts of such facilities lead to environmental pollution and land use disadvantages, such as irregular parcels. The aim of this work is to substantiate a set of approaches to compensating for the cumulative negative impact of infrastructure facilities. The factors causing the negative impacts of infrastructure facilities are grouped into three areas: rights restrictions, territorial deficiencies and environmental pollution. This work uses the SWOT analysis method with the possibility of element-by-element analysis, as a result of which the approaches to the compensation for negative impacts under different external and internal conditions are determined. As a result of this study, a justification for a set of approaches to compensating for the negative impacts of infrastructure facilities on land use was executed, and a new algorithm to compensate the right holders of the land, industry sector or state for such negative impacts was developed. The following approaches to compensating for negative impacts were identified: loss assessment; the establishment of environmental payments; cadastral value adjustment; compensation for industry sector losses; and the use of state regulation tools. The first two approaches were identified as the main ones. The proposed algorithm can be realized only with the help of the abovementioned methodological approaches, which form a basis for further research. Full article

Wilson’s disease is a rare autosomal recessive disorder of copper metabolism characterized by excessive copper accumulation in the liver, brain, and other tissues. This paper provides an overview of the primary pharmacological agents used in its treatment, including penicillamine, trientine, tetrathiomolybdate, and zinc. Their mechanisms of action, therapeutic applications, and side-effect profiles are examined, emphasizing how each agent helps reduce copper overload. Additionally, brief information is given on novel therapies such as gene therapy and artificial intelligence applications. Furthermore, information about the structural and chemical properties of these compounds is provided, highlighting the molecular features that enable them to chelate copper or reduce its intestinal absorption. By integrating pathophysiological insights with chemical and mechanistic perspectives, this paper offers a comprehensive review of existing treatment strategies for Wilson’s disease and stresses the importance of careful, patient-specific management to optimize long-term outcomes. Full article

This research represents the first application of the MOLS method to characterize the conformational energy landscape of an antimicrobial peptide within a solvent environment, providing a novel approach to understanding peptide behavior in solution. This method’s exhaustive nature ensures that all minimum-energy conformations for a given amino acid sequence are sampled. In this work, we employed a combination of MOLS and VMD software to generate structural models of a cyclic peptide, both solvated and non-solvated, and then utilized the CHARMM force field to conduct energy calculations throughout the sampling process. In the presence of a solvent, this method predicted a structure close to the experimental crystal structure. A significant reduction was observed in gamma turn motifs in the presence of water. The solvent molecules also favored different hydrogen bonding patterns in the peptide by orchestrating an intermolecular interaction with the peptide atoms. This intermolecular interaction involves an ARG side chain and further stabilizes the backbone. It is evident that solvent interactions are key in designing antimicrobial peptides. This study will help in designing and understanding peptides for use as therapeutic agents like antibacterial or antimicrobial peptides. Each conformer obtained from the MOLS method would be one of the best starting points for molecular dynamic simulation to further explore the landscape. Full article