Search Results (5,209)

(1) Background: The concentration of lamotrigine, an antiepileptic drug very often used in bipolar disorder, is most often determined in the blood, with many inconveniences. An alternative may be to use saliva as a diagnostic material for this purpose. The development of a method to determine lamotrigine in saliva as a biological material significantly improves patient comfort during sampling. The developed method uses solid-phase extraction for the isolation of the drug from saliva for the first time. (2) Methods: This study aimed to develop a method to determine lamotrigine in saliva using solid-phase extraction (SPE) for isolation and liquid chromatography with a diode array detector (LC-DAD) for quantitative analysis. (3) Results: The method was validated by determining its linearity in the concentration range 10–2000 ng/mL (R² > 0.99), and the intra- and inter-day precision expressed as coefficient of variation (CV%) did not exceed 15%. (4) Conclusions: The developed method was used to determine the salivary concentration of lamotrigine in patients treated with the studied compound, confirming its usefulness in bipolar disorder (BD). Full article

Background and Objectives: Diabetes is a global public health challenge, with increasing prevalence worldwide. The implementation of artificial intelligence (AI) in the management of this condition offers potential benefits in improving healthcare outcomes. This study primarily investigates the barriers and facilitators perceived by healthcare professionals in the adoption of AI. Secondarily, by analyzing both quantitative and qualitative data collected, it aims to support the potential development of AI-based programs for diabetes management, with particular focus on a possible bottom-up approach. Materials and Methods: A scoping review was conducted following PRISMA-ScR guidelines for reporting and registered in the Open Science Framework (OSF) database. The study selection process was conducted in two phases—title/abstract screening and full-text review—independently by three researchers, with a fourth resolving conflicts. Data were extracted and assessed using Joanna Briggs Institute (JBI) tools. The included studies were synthesized narratively, combining both quantitative and qualitative analyses to ensure methodological rigor and contextual depth. Results: The adoption of AI tools in diabetes management is influenced by several barriers, including perceived unsatisfactory clinical performance, high costs, issues related to data security and decision-making transparency, as well as limited training among healthcare workers. Key facilitators include improved clinical efficiency, ease of use, time-saving, and organizational support, which contribute to broader acceptance of the technology. Conclusions: The active and continuous involvement of healthcare workers represents a valuable opportunity to develop more effective, reliable, and well-integrated AI solutions in clinical practice. Our findings emphasize the importance of a bottom-up approach and highlight how adequate training and organizational support can help overcome existing barriers, promoting sustainable and equitable innovation aligned with public health priorities. Full article

The aircraft nose-wheel steering system serves as a critical component for ensuring ground taxiing safety and maneuvering efficiency. However, its dynamic control stability faces significant challenges under complex operational conditions. Existing research predominantly focuses on single-discipline modeling, with insufficient in-depth analysis of the coupling effects between hydraulic system dynamics and mechanical dynamics. Traditional PID controllers exhibit limitations in scenarios involving nonlinear time-varying conditions caused by normal load fluctuations of the landing gear buffer strut during high-speed landing phases, including increased control overshoot and inadequate adaptability to abrupt load variations. These issues severely compromise the stability of high-speed deviation correction and overall aircraft safety. To address these challenges, this study constructs a digital twin model based on real aircraft data and innovatively implements multidisciplinary co-simulation via Simcenter 3D, AMESim 2021.1, and MATLAB R2020a. A fuzzy adaptive PID controller is specifically designed to achieve adaptive adjustment of control parameters. Comparative analysis through co-simulation demonstrates that the proposed mechanical–electrical–hydraulic collaborative control strategy significantly reduces response delay, effectively minimizes control overshoot, and decreases hydraulic pressure-fluctuation amplitude by over 85.2%. This work provides a novel methodology for optimizing steering stability under nonlinear interference scenarios, offering substantial engineering applicability and promotion value. Full article

Aronia melanocarpa (black chokeberry) is a medicinally valuable small fruit species, yet its commercial propagation remains limited by low rooting and genotype-specific responses. This study developed an efficient, callus-free micropropagation and rooting protocol using a Shrub Plant Medium (SPM) supplemented with 5 mg/L BAP in large 660 mL jars, which yielded up to 27 shoots per explant. Optimal rooting (100%) was achieved with 0.5 mg/L NAA + 0.25 mg/L IBA in half-strength SPM. In the second phase, supervised machine learning models, including Random Forest (RF), XGBoost, Gaussian Process (GP), and Multilayer Perceptron (MLP), were employed to predict morphogenic traits based on culture conditions. XGBoost and RF outperformed other models, achieving R² values exceeding 0.95 for key variables such as shoot number and root length. These results demonstrate that data-driven modeling can enhance protocol precision and reduce experimental workload in plant tissue culture. The study also highlights the potential for combining physiological understanding with artificial intelligence to streamline future in vitro applications in woody species. Full article

Monitoring pH and acidity during yoghurt fermentation is essential for product quality and process efficiency. Conventional measurement methods, however, are invasive and labour-intensive. This study developed artificial neural network (ANN) models to predict pH and titratable acidity during yoghurt fermentation using CIELAB colour parameters (L, a*, b*). Reconstituted milk powder with 12% total solids was prepared with varying protein levels (4.2–4.8%), inoculum concentrations (1–3%), and fermentation temperatures (36–44 °C). Data were collected every 10 min until pH 4.6 was reached. Forty models were trained for each output variable, using 90% of the data for training and 10% for validation. The first two phases of the fermentation process were clearly distinguishable, lasting between 4.5 and 7 h and exceeding 0.6% lactic acid in all treatments evaluated. The best pH model used two hidden layers with 28 neurons (R² = 0.969; RMSE = 0.007), while the optimal acidity model had four hidden layers with 32 neurons (R² = 0.868; RMSE = 0.002). The strong correlation between colour and physicochemical changes confirms the feasibility of this non-destructive approach. Integrating ANN models and colourimetry offers a practical solution for real-time monitoring, helping improve process control in industrial yoghurt production. Full article

Background: This study was performed to validate the addition of capacitive-based pressure sensors to an existing smart sock developed by the research team. This study focused on evaluating the accuracy of soft robotic sensor (SRS) pressure data and its relationship with laboratory-grade Kistler force plates in collecting ground force reaction data. Methods: Nineteen participants performed walking trials while wearing the smart sock with and without shoes. Data was collected simultaneously with the sock and the force plates for each gait phase including foot-flat, heel-off, and midstance. The correlation between the smart sock and force plates was analyzed using Pearson’s correlation coefficient and R-squared values. Results: Overall, the strength of the relationship between the smart sock’s SRS data and the vertical ground reaction force (GRF) data from the force plates showed a strong correlation, with a Pearson’s correlation coefficient of 0.85 ± 0.1; 86% of the trials had a value higher than 0.75. The linear regression models also showed a strong correlation, with an R-squared value of 0.88 ± 0.12, which improved to 0.90 ± 0.07 when including a stretch-SRS for measuring ankle flexion. Conclusions: With these strong correlation results, there is potential for capacitive pressure sensors to be integrated into the proposed device and utilized in telehealth and sports performance applications. Full article

Fecal water syndrome (FWS) in horses is characterized by two-phase defecation, including both solid and liquid phases. While satisfactory explanations for FWS are unavailable, bacterial dysbiosis has been suggested as a contributing or causative factor. The objectives of this study were to determine whether fecal bacterial dysbiosis is associated with FWS in horses in the midwestern USA. Fecal samples were collected from horses with FWS and from unaffected horses at the same location. In total, 16S rRNA amplicon libraries produced from fecal bacterial DNA were sequenced using the Illumina sequencing platform. Significant differences in beta diversity were detected between affected and control horses (p = 7 × 10⁻⁴, F = 1.51), and differential abundance testing identified several features enriched in affected and control horses. These results agree with prior work regarding specific features in the bacterial microbiome associated with FWS, including Alloprevotella spp., and suggest fecal dysbiosis is associated with FWS. Full article

High moisture content (MC) harms wheat storage quality and readily leads to mold growth. Accurate localization of abnormal/high-moisture regions enables early warning, ensuring proper storage and reducing economic losses. The present study introduces the 2D microwave scanning method and investigates a novel localization method for addressing such a challenge. Both static and scanning experiments were performed on a developed mobile and non-destructive microwave detection system to quantify the MC of wheat and then locate abnormal moisture regions. For quantifying the wheat’s MC, a dual-parameter wheat MC prediction model with the random forest (RF) algorithm was constructed, achieving a high accuracy (R² = 0.9846, MSE = 0.2768, MAE = 0.3986). MC scanning experiments were conducted by synchronized moving waveguides; the maximum absolute error of MC prediction was 0.565%, with a maximum relative error of 3.166%. Furthermore, both one- and two-dimensional localizing methods were proposed for localizing abnormal moisture regions. The one-dimensional method evaluated two approaches—attenuation value and absolute attenuation gradient—using computer simulation technology (CST) modeling and scanning experiments. The experimental results confirmed the superior performance of the absolute gradient method, with a center detection error of less than 12 mm in the anomalous wheat moisture region and a minimum width detection error of 1.4 mm. The study performed two-dimensional antenna scanning and effectively imaged the high-MC regions using phase delay analysis. The imaging results coincide with the actual locations of moisture anomaly regions. This study demonstrated a promising solution for accurately localizing the wheat’s abnormal/high-moisture regions with the use of an emerging microwave transmission method. Full article

Background: Colorectal cancer (CRC) is strongly influenced by miRNAs as well as the circadian system. Methods: High-throughput sequencing of miRNAs expressed in the rat colon during 24 h light (L)/dark (D) cycle was performed to identify rhythmically expressed miRNAs. The role of miR-150-5p in CRC progression was analyzed in DLD1 cell line and human CRC tissues. Results: Nearly 10% of mature miRNAs showed a daily rhythm in expression. A peak of miRNAs’ levels was in most cases observed during the first half of the D phase of the LD cycle. The highest amplitude was detected in expression of miR-150-5p and miR-142-3p. In the L phase of the LD cycle, the maximum in miR-30d-5p expression was detected. Gene ontology enrichment analysis revealed that genes interfering with miRNAs with peak expression during the D phase influence apoptosis, angiogenesis, the immune system, and EGF and TGF-beta signaling. Rhythm in miR-150-5p, miR-142-3p, and miR-30d-5p expression was confirmed by real-time PCR. Oncogenes bcl2 and myb and clock gene cry1 were identified as miR-150-5p targets. miR-150-5p administration promoted camptothecin-induced apoptosis. Expression of myb showed a rhythmic profile in DLD1 cells with inverted acrophase with respect to miR-150-5p. miR-150-5p was decreased in cancer compared to adjacent tissue in CRC patients. Decrease in miR-150-5p was age dependent. Older patients with lower expression of miR-150-5p and higher expression of cry1 showed worse survival in comparison with younger patients. Conclusions: miRNA signaling differs between the L and D phases of the LD cycle. miR-150-5p, targeting myb, bcl2, and cry1, can influence CRC progression in a phase-dependent manner. Full article

Synthetic dyes are highly recalcitrant and are discharged in large volumes in industrial wastewater, which represents a serious environmental pollution problem. Biological methods for dye degradation are a potentially effective option for these synthetic products. In this study, a strain of Pleurotus ostreatus was used to evaluate the decolorization of the Remazol Brilliant Blue R (RBBR) dye added to the culture medium in the exponential growth phase of the fungus. The dye removal capacity of live and inactivated pellets by biosorption, as well as the enzymatic degradation of the dye using a cell-free culture broth considered an extracellular extract (EE), were also evaluated. The activity of laccase and dye-decolorizing peroxidase was determined in both the EE and the intrapellet extract (IPE); their values increased in the presence of dye in the culture medium. A decolorization of 98.5% and 98.0% was obtained in the culture broth and by the EE, respectively; biosorption of the dye by the inactivated pellets was 17 mg/g. The results suggest that the decolorization of the dye is primarily enzymatic, although there are also bioadsorption and bioaccumulation of the dye, which is then enzymatically degraded, and could be used as a carbon source. Full article

Bone metastasis remains a significant cause of morbidity and diminished quality of life in patients with advanced breast, prostate, and lung cancers. Emerging research highlights the pivotal role of reversible epigenetic alterations, including DNA methylation, histone modifications, chromatin remodeling complex dysregulation, and non-coding RNA networks, in orchestrating each phase of skeletal colonization. Site-specific promoter hypermethylation of tumor suppressor genes such as HIN-1 and RASSF1A, alongside global DNA hypomethylation that activates metastasis-associated genes, contributes to cancer cell plasticity and facilitates epithelial-to-mesenchymal transition (EMT). Key histone modifiers, including KLF5, EZH2, and the demethylases KDM4/6, regulate osteoclastogenic signaling pathways and the transition between metastatic dormancy and reactivation. Simultaneously, SWI/SNF chromatin remodelers such as BRG1 and BRM reconfigure enhancer–promoter interactions that promote bone tropism. Non-coding RNAs, including miRNAs, lncRNAs, and circRNAs (e.g., miR-34a, NORAD, circIKBKB), circulate via exosomes to modulate the RANKL/OPG axis, thereby conditioning the bone microenvironment and fostering the formation of a pre-metastatic niche. These mechanistic insights have accelerated the development of epigenetic therapies. DNA methyltransferase inhibitors (e.g., decitabine, guadecitabine) have shown promise in attenuating osteoclast differentiation, while histone deacetylase inhibitors display context-dependent effects on tumor progression and bone remodeling. Inhibitors targeting EZH2, BET proteins, and KDM1A are now advancing through early-phase clinical trials, often in combination with bisphosphonates or immune checkpoint inhibitors. Moreover, novel approaches such as CRISPR/dCas9-based epigenome editing and RNA-targeted therapies offer locus-specific reprogramming potential. Together, these advances position epigenetic modulation as a promising axis in precision oncology aimed at interrupting the pathological crosstalk between tumor cells and the bone microenvironment. This review synthesizes current mechanistic understanding, evaluates the therapeutic landscape, and outlines the translational challenges ahead in leveraging epigenetic science to prevent and treat bone metastases. Full article

Background/Objectives: Pain assessment scales provide a clear clinical benefit in patients who are unable to self-report. The Nociception Coma Scale-Revised—adapted for Intubated patients (NCS-R-I) was developed to assess pain in patients with acquired brain injury who are unable to self-report. However, this instrument has not yet been translated and validated for use in Spain. The objective was to translate the Nociception Coma Scale-Revised—adapted for Intubated patients (NCS-R-I) into Spanish and to assess the reliability and validity of the Spanish version in patients with brain injury. Methods: This study was carried out in two phases. First, the scale was translated into Spanish. Next, a psychometric analysis was performed to determine the reliability and validity of the Spanish version of the NCS-R-I in 207 critically ill patients with acquired brain injury and disorders of consciousness. Two blinded observers administered the scale at three time points: 5 min before, during, and 15 min after a series of nociceptive and non-nociceptive procedures. Results: The internal consistency of the NCS-R-I was acceptable (ordinal alpha = 0.60–0.90). Interobserver agreement was good (kappa = 0.80; intraclass correlation coefficient = 0.90). In terms of discriminant validity, the AUC was 0.952 (95% CI: 0.931–0.973). NCS-R-I scores increased significantly during performance of nociceptive procedures compared to scores obtained before and after these procedures, confirming the scale’s sensitivity to change. Similarly, during the performance of nociceptive procedures, scores on the NCS-R-I were significantly higher (p < 0.001) than those observed during non-nociceptive procedures. Conclusions: The results of this study demonstrate that the NCS-R-I is a valid, reliable tool for the assessment of pain in patients with acquired brain injury who are unable to self-report. Full article

The sustainable management of Municipal Solid Waste (MSW) relies heavily on community participation in separating it at the source and delivering it to collection systems. These practices are crucial for reducing pollution, protecting ecosystems, and maximizing resource recovery. However, in the Global South context, with conditions of socioeconomic vulnerability, community participation in the sustainable management of MSW remains limited, highlighting the need to generate context-specific interventions. MSW includes items such as household appliances, batteries, and electronic devices, which require specialized handling due to their size, hazardous components, or material complexity. This study implemented a Community-Based Social Marketing approach during the research and design phases of an intervention focused on promoting source separation and management of hard-to-manage MSW in five municipalities within the administrative region of Norte de Santander (Colombia), which borders Venezuela. Using a mixed-methods approach, we collected data from 1775 individuals (63.83% women; M _age = 33.48 years; SD = 17.25), employing social mapping, focus groups, semi-structured interviews, participant observation, and a survey questionnaire. The results show that the source separation and delivery of hard-to-manage MSW to collection systems are limited by a set of psychosocial, structural, and institutional barriers that interact with each other, affecting communities’ willingness and capacity for action. Furthermore, a prediction model of willingness to engage in separation and delivery behaviors showed a good fit (R2 = 0.83). The strongest predictors were awareness of the negative consequences of non-participation and perceived environmental benefits, with subjective norms contributing to a lesser extent. Based on these results, we designed a context-specific intervention focused on reducing these barriers and promoting community engagement in the sustainable management of hard-to-manage MSW. Full article

To address the wear life prediction challenge of Guide Cones in passive compliant connectors under dynamic loads within specialized equipment, this study proposes a dynamic wear modeling and life assessment method based on the improved Archard model. Through integrated theoretical modeling, finite element simulation, and experimental validation, we establish a bidirectional coupling framework analyzing dynamic contact mechanics and wear evolution. By developing phased contact state identification criteria and geometric constraints, a transient load calculation model is established, revealing dynamic load characteristics with peak contact forces reaching 206.34 N. A dynamic contact stress integration algorithm is proposed by combining Archard’s theory with ABAQUS finite element simulation and ALE adaptive meshing technology, enabling real-time iterative updates of wear morphology and contact stress. This approach constructs an exponential model correlating cumulative wear depth with docking cycles (R² = 0.997). Prototype experiments demonstrate a mean absolute percentage error (MAPE) of 14.6% between simulated and measured wear depths, confirming model validity. With a critical wear threshold of 0.8 mm, the predicted service life reaches 45,270 cycles, meeting 50-year operational requirements (safety margin: 50.9%). This research provides theoretical frameworks and engineering guidelines for wear-resistant design, material selection, and life evaluation in high-reliability automatic docking systems. Full article

The catalytic decomposition of CH₄ is a promising method for producing high-purity CO_x-free hydrogen. A Ni-Al-LDH catalyst synthesized via coprecipitation was modified with alkali metals (Mg, La, Ca, or Li) through reconstruction to enhance catalytic activity and resistance to deactivation during catalytic methane decomposition (CMD). The catalysts were evaluated by two activation methods: H₂ reduction and direct heating with CH₄. The MgNA-R catalyst achieved the highest CH₄ conversion (65%) at 600 °C when reduced with H₂, attributed to a stronger Ni-Al interaction. Under CH₄ activation, LaNA-C achieved a 55% conversion at the same temperature, associated with a smaller crystallite size and higher reducibility due to La incorporation. Although all catalysts deactivated due to carbon deposition and/or sintering, LaNA-C was the only sample that could resist deactivation for a longer period, as La appears to have a protective effect on the active phase. Post-reaction characterizations revealed the formation of graphitic and filamentous carbon. Raman spectroscopy exhibited a higher degree of graphitization and structural order in LaNA-C, whereas SEM showed a more uniform distribution of carbon filaments. TEM confirmed the presence of multi-walled carbon nanotubes with encapsulated Ni particles in La-promoted samples. These results demonstrate that La addition improves the catalytic performance under CH₄ activation and carbon structure. This finding offers a practical advantage for CMD processes, as it reduces or eliminates the need to use hydrogen during catalyst activation. Full article