Search Results (5,793)

A simplified kinetic model for the quantitative analysis of a potentiometric, pH-based urea biosensor is presented. The device was an electrolyte–insulator–semiconductor capacitor (EISCAP) with a pH-sensitive Ta₂O₅ gate functionalized by a polyallylamine hydrochloride (PAH)/urease bilayer. Within the steady-state approximation, the kinetic equations yielded an implicit algebraic relation linking the bulk urea concentration to the local pH at the sensor surface. Numerical solution of this equation, combined with a fitting routine, provides the apparent Michaelis–Menten constant ($K_M$) and the normalized maximum reaction rate (${\overline{k}}_V$). Validation against the literature data confirmed the reliability of the approach. Experimental results were then analyzed in both phosphate buffer (PBS) and artificial urine (AU), covering urea concentrations of 0.1–50 mM. The fitted parameters showed comparable $K_M$ values of 10.9 mM (PBS) and 32.4 mM (AU), but strongly different ${\overline{k}}_V$ values: $2.2\times {10}^{-4}$ (PBS) versus $8.6\times {10}^{-7}$ (AU). The three-order reduction in AU was attributed to the inhibitory effects inherent to complex biological fluids. These findings highlight the importance of the model-based quantitative analysis of EISCAP biosensors, enabling the accurate characterization of immobilized enzyme layers and guiding optimization for applications in realistic sample matrices. Full article

Background: Human papillomavirus (HPV)-associated oral and oropharyngeal squamous cell carcinomas have risen dramatically in incidence over recent decades. Yet, unlike cervical neoplasia, there is no established screening paradigm for HPV-driven oropharyngeal dysplasia, as precursor lesions are often occult and are not easily accessible for examination. This drives an urgent need for non-invasive biomarkers to enable early detection, risk stratification, and timely intervention. Objective of this review is to highlight advances in liquid biopsy modalities, specifically saliva- and blood-based biomarkers—in the context of HPV-driven oral carcinogenesis—and to evaluate their utility in early cancer detection, prognostic, post-treatment surveillance, and recurrence monitoring. Methods: We performed a narrative review of PubMed-indexed studies (2015–2025) focusing on HPV-positive oral and oropharyngeal squamous cell carcinomas. and liquid biopsy analytes. Key sources were high-impact original studies and meta-analyses from 2020–2025 examining circulating tumor DNA (ctDNA), viral nucleic acids, circulating tumor cells (CTCs), extracellular vesicles (EVs), and related biomarkers in saliva and blood. Reported data on assay performance, biases, and validation were reviewed to highlight how oral cancer findings align with trends seen in other solid tumors. Results: In reviewing recent studies (2015–2025), we found consistent evidence that saliva best captures locoregional tumor signals while plasma circulating tumor HPV DNA (ctHPV DNA) reflects systemic disease, and that using both matrices improves detection over either alone. Dual-fluid testing will potentially enable earlier identification of molecular residual disease with clinically meaningful lead time before radiographic recurrence, supporting risk-adapted surveillance. Overall, literature favors standardized pre-analytics and combined saliva plus plasma workflows to enhance early detection and follow-up in HPV-positive oral and oropharyngeal squamous cell carcinomas. Conclusions: Liquid biopsy approaches offer promising tools for the early, non-invasive detection and real-time monitoring of HPV-associated oral cancers. Realizing their full clinical potential will require robust prospective validation and standardization of pre-analytical protocols. Integrating salivary and blood biomarkers into tailored surveillance programs may further support earlier intervention and improved patient outcomes, while potentially reducing reliance on unnecessary invasive procedures. Full article

Edible coatings are widely used to modulate oil uptake and moisture in fried foods. In this study, we evaluated a microfluid-assisted flow-blurring spray against conventional application by dipping/spraying, focusing on the coating efficiency and preliminary implications for sustainable process. This study combines benchtop experiments with a near-nozzle numerical analysis where the gas–liquid interface and primary breakup are modeled using the Volume of Fluid (VOF) approach implemented in OpenFOAM, configured for a flow-blurring geometry to generate whey protein isolate (WPI) coatings. Viscosity, density, solid content, and contact angle were validated experimentally and used in the simulation setup. An image-based droplet pipeline quantified spray characteristics, yielding a volumetric median diameter D₅₀ = 83.69 µm and confirming process uniformity. Contact angles showed marked substrate dependence: hydrophilic surfaces, 68°–85°; hydrophobic surfaces, 95°–110°. For turkey sausages, sessile-drop contact angles were not determinable (N.D.) due to wicking/roughness; wettability was therefore assessed on smooth surrogates and via performance metrics. Fit-for-purpose simulation procedures are outlined. Microfluidic application (WPI-McF) lowered oil uptake versus uncoated controls. Together, robust modeling, targeted image analytics, and high-precision microfluidics enable rational tuning of coating microstructure and barrier performance, offering a scalable pathway to reduce lipid content and enhance fried food quality. Full article

Distributed temperature sensing (DTS) has long been employed in the oil and gas industry to characterize reservoirs, optimize production, and extend well life. More recently, its application has expanded to geothermal energy development, where DTS provides critical insights into transient wellbore temperature profiles and flow behavior. A comprehensive understanding of such field measurements can be achieved by systematically comparing and interpreting DTS data in conjunction with robust numerical models. However, many existing wellbore models rely on steady-state heat transfer assumptions that fail to capture transient dynamics, while fully coupled wellbore–reservoir simulations are often computationally demanding and mathematically complex. This study aims to address this gap by developing a transient wellbore heat transfer model validated with DTS data. The model was formulated using a thermal-analogy approach based on the theoretical framework of Eickmeier et al. and implemented with a finite-difference scheme. Validation was performed by comparing thermal slug velocities predicted by the model with those extracted from DTS measurements. The results demonstrated strong agreement between modeled and measured slug velocities, confirming the model’s reliability. In addition, the modeled thermal slug velocity was lower than the corresponding fluid velocity, indicating that thermal front propagates more slowly than the fluid front. Consequently, this computationally efficient approach enhances the interpretation of DTS data and offers a practical tool for improved monitoring and management of geothermal operations. Full article

An ambit of enhancing heat transfer throughout thermal convection in a cavity is explored numerically in this study, contemplating the heat dispersal from a segmental heat source circumscribed in a square-vented porous cavity with a moving lid. The cavity can be used as a heat sink for electronic cooling, material processing, and convective drying. Aluminum $10$ PPI metal foam saturated by aluminum oxide–water nanofluid is occupied in this lid-driven vented cavity system. The bottom cavity wall is fully and partially heated by a heat source of specific length $L_H$, and the left wall and inlet fluid are kept at the same cold temperature, while the right wall and top-driven wall are thermally insulated. Thermal dispersion and local thermal non-equilibrium effects are included in an energy equation, and continuity and Darcy–Brinkmann–Forchheimer momentum equations are implemented and resolved by utilizing the finite volume method with the aid of a vorticity–stream function approach operation. The inspirations behind pertinent parameters, including the Reynolds number ($Re=10-50$), Grashof number ($Gr={10}^3-{10}^6$), inlet and outlet ports’ aspect ratio ($D/H=0.1-0.4$), outlet port location ratio ($S/H=0.25-0.75$), and discrete partial heating ratio ($L_H/L=0.25-1$) are scrutinized. The baseline circumstance corresponds to full-length heating $L_H/L=1$ and the outlet port location ratio $S/H=0.25$. The results reveal that the fluid and heat flow domains are addressed mostly via these specification alterations. For $Gr={10}^3$, increasing $Re$ from $10$ to $40$ does not alter streamlines or the isotherm field, but when $Re=50$ it is detected that streamlines increase monotonically. Streamlines are not altered when $L_H/L$ and $S/H$ are amplified but strengthened more when the opening vent aspect ratio is increased. A greater temperature difference occurs as $L_H/L$ is raised from $0.25-0.75$ and isotherms are intensified, and the thermal boundary layer becomes more distinct when $S/H$ is augmented. The average Nusselt number rises as $Re$, $Gr$, $L_H/L$, and $D/H$ are increased by about $30\%$, $3.5\%$, $23\%$, and $19.4\%$, respectively, and it decreases with $S/H$ amplifying is increased by around $5.5\%$. Full article

Background: The intracranial space has limited capacity; thus, volume changes in any component can raise intracranial pressure and cause mass effect. This mechanism underlies many neurological disorders. Artificial Intelligence, increasingly applied in medicine and diagnostic imaging, may support the evaluation of such conditions. This systematic review investigates AI-based models for cerebrospinal fluid segmentation and analysis on computed tomography. Methods: In December 2024, a systematic review was conducted across MEDLINE (PubMed), Scopus, Web of Science, Embase, and Cochrane Library. From 559 identified studies, 14 were included after independent review by two evaluators. Extracted data covered study characteristics, AI model design, dataset composition, and performance metrics for CSF segmentation. Quality assessment followed PRISMA 2020 and used JBI, AMSTAR 2, and CASP checklists. Results: The 14 studies demonstrated applications of AI in CSF segmentation and volumetric assessment, primarily for hydrocephalus diagnosis, mass effect evaluation, and stroke outcome prediction. Convolutional Neural Networks and Random Forests were the most frequent approaches. Reported segmentation accuracy was high, with Dice Similarity Coefficient values ranging from 0.75 to 0.95 and strong volumetric correlations (r up to 0.99) between AI-based and manual measurements. Conclusions: AI-assisted CSF segmentation from CT images shows promising accuracy and efficiency, with potential to enhance neurological diagnostics. Remaining challenges include dataset variability, inconsistent algorithm performance, and limited clinical validation. Future research should prioritize standardization of methods, larger and more diverse training datasets, and integration of AI tools into clinical workflows. Full article

Ferroptosis is a novel kind of regulated cell death that occurs when redox equilibrium is disrupted, leading to iron-dependent lipid peroxidation. Ferroptosis is defined by the buildup of deleterious lipid hydroperoxides, the inactivation of glutathione peroxidase 4 (GPX4), and mitochondrial shrinkage, setting it apart from apoptosis and necrosis. The relevance of this route to human reproduction remains unknown, despite its thorough investigation in neurodegeneration and cancer. Recent studies demonstrate that the ovarian follicular milieu is especially susceptible to ferroptosis owing to its high content of polyunsaturated fatty acids, iron-dependent metabolism, and the generation of reactive oxygen species. Dysregulation of ferroptosis may result in infertility by affecting granulosa cell survival, oocyte maturation, and embryonic competence. Ferroptotic activity correlates with oxidative stress indicators identified in clinical diseases including polycystic ovary syndrome, reduced ovarian reserve, and insufficient responsiveness to ovarian stimulation. Potential indicators include GPX4 expression, decreased glutathione levels, and the accumulation of lipid reactive oxygen species in granulosa cells and follicular fluid. Melatonin, which boosts antioxidant defences, and ferrostatin-1, a prototype inhibitor of ferroptosis that lowers lipid peroxidation, are two early candidates for treatment. For future evaluations, these agents should be used with standardised FF biomarker panels. Significantly, vitamin E, coenzyme Q10, and small-molecule ferroptosis inhibitors have shown efficacy in halting ferroptosis in experimental settings. These approaches have shown protective benefits in alternative systems and may signify viable treatment options for assisted reproduction. This narrative review encapsulates ferroptosis inside the ovarian follicle, its influence on oocyte quality, and the implications for in vitro fertilization results. Full article

The lack of detailed design information in legacy hydropower plants creates challenges for modernising their ageing turbine components. This research advances a digitalisation approach which combines inverse design methodology (IDM) with multi-objective genetic algorithms (MOGA) and computational fluid dynamics (CFD) to digitally reconstruct and optimise the Bérchules Francis turbine runner and guide vane geometries using limited available legacy data, avoiding invasive techniques. A two-stage optimisation process was conducted. The first stage of runner blade optimisation achieved a 22.7% reduction in profile loss and a 16.8% decrease in secondary flow factor while raising minimum pressure from −877,325.5 Pa to −132,703.4 Pa. Guide vane optimisation during Stage 2 produced additional performance gains through a 9.3% reduction in profile loss and a 20% decrease in secondary flow factor and a minimum pressure increase to +247,452.1 Pa which represented an 183% improvement. The CFD validation results showed that the final turbine efficiency reached 93.7% while producing more power than the plant’s rated 942 kW. The sensitivity analysis revealed that leading edge loading at mid-span and normal chord proved to be the most significant design parameters affecting pressure loss and flow behaviour metrics. The research proves that legacy turbines can be digitally restored through hybrid optimisation and CFD workflows, which enables data-driven refurbishment design without needing complete component replacement. Full article

As global Marine resource development continues to expand into deep-sea and ultra-deep-sea domains, the intelligent and green transformation of deep-sea aquaculture equipment has become a key direction for high-quality development of the Marine economy. Large deep-sea cages are considered essential equipment for deep-sea aquaculture. However, there are significant challenges associated with ensuring their structural integrity and long-term monitoring capabilities in the complex Marine environments characteristic of deep-sea aquaculture. The present study focuses on large deep-sea cages, addressing their dynamic response challenges and long-term monitoring power supply needs in complex Marine environments. The present study investigates the nonlinear vibration characteristics of flexible net structures under complex fluid loads. To this end, a multi-field coupled dynamic model is constructed to reveal vibration response patterns and instability mechanisms. A self-powered sensing system based on triboelectric nanogenerator (TENG) technology has been developed, featuring a curved surface adaptive TENG array for the real-time monitoring of net vibration states. This review aims to focus on the research of optimizing the design of curved surface adaptive TENG arrays and deep-sea cage monitoring. The present study will investigate the mechanisms of energy transfer and cooperative capture within multi-body coupled cage systems. In addition, the biomechanics of fish–cage flow field interactions and micro-energy capture technologies will be examined. By integrating different disciplinary perspectives and adopting innovative approaches, this work aims to break through key technical bottlenecks, thereby laying the necessary theoretical and technical foundations for optimizing the design and safe operation of large deep-sea cages. Full article

Ovarian follicular fluid (FF) is a metabolically active and biomarker-rich medium that mirrors the oocyte microenvironment. Its analysis is increasingly recognized in infertility diagnostics and assisted reproductive technologies (ART) for assessing oocyte competence, understanding reproductive disorders, and guiding personalized treatment. However, FF’s high viscosity, complex composition, and biochemical variability challenge reproducibility in sample preparation and molecular profiling. Sonication-based extraction has emerged as an effective approach to address these issues. By exploiting acoustic cavitation, sonication improves protein solubilization, metabolite release, and lipid recovery, while reducing solvent use and processing time. This review synthesizes recent advances in sonication-assisted FF analysis across proteomics, metabolomics, and lipidomics, emphasizing parameter optimization, integration with advanced mass spectrometry workflows, and emerging applications in microfluidics, automation, and point-of-care devices. Clinical implications are discussed in the context of enhanced biomarker discovery pipelines, real-time oocyte selection, and ART outcome prediction. Key challenges, such as preventing biomolecule degradation, standardizing protocols, and achieving inter-laboratory reproducibility, are addressed alongside regulatory considerations. Future directions highlight the potential of combining sonication with multi-omics strategies and AI-driven analytics, paving the way for high-throughput, standardized, and clinically actionable FF analysis to advance precision reproductive medicine. Full article

Background/Objectives: Therapeutic drug monitoring (TDM) of antipsychotic medications plays an important role in optimizing treatment efficacy, reducing adverse effects, and supporting adherence. While Ultra-High Performance Liquid Chromatography–Tandem Mass Spectrometry (UHPLC–MS/MS) has long been the gold standard for antipsychotic quantification, recent advances in automated platforms and microsampling raise questions about its current clinical practicality. This systematic review evaluated the clinical applicability and analytical performance of UHPLC-based methods for monitoring antipsychotic drugs, focusing on precision, recovery, matrix effects, and suitability across various biological matrices. Methods: A systematic search of PubMed, Scopus, and Web of Science was conducted for studies published between 2013 and 2024 involving UHPLC-based quantification of antipsychotics in clinical samples from adult patients. Data on analytical parameters, sample matrices, and study characteristics were extracted. A custom quality checklist was used to assess methodological rigor. In addition to qualitative synthesis, non-traditional quantitative approaches were applied, including descriptive aggregation of recovery, matrix effects, and precision across studies, as well as correlation analyses to explore relationships among performance parameters. Results: Twelve studies were included, spanning a range of typical and atypical antipsychotics and metabolites. Plasma and serum demonstrated the highest analytical reliability (recovery >90%, minimal matrix effects), while dried blood spots (DBSs), whole blood, and oral fluid showed greater variability. Clinically, UHPLC–MS/MS enabled more accurate dose adjustments and identification of non-adherence, outperforming immunoassays in sensitivity, specificity, and metabolite detection. Microsampling methods showed promise for outpatient and decentralized care but require further clinical validation. Conclusions: UHPLC–MS/MS remains the most robust and reliable method for TDM of antipsychotics, especially when quantification of active metabolites is required. While logistical barriers remain, technological advances may enhance feasibility and support broader integration into routine psychiatric care. Full article

To investigate the three-dimensional spatial distribution characteristics of fluids during the combined production of coalbed methane from multi-coal reservoirs (MCR), a physical simulation test platform was established, and a quantitative characterization parameter calculation principle for fluid migration was developed. The influence of fluid pressure difference and in situ stress difference on the three-dimensional spatial distribution of fluids and their quantitative characterization parameters was analyzed. The results indicate that the dynamic pressure equilibrium between the coal reservoir and the wellbore forces fluids from high-pressure reservoirs to intrude into low-pressure reservoirs, altering the flow state of fluids in the latter. Consequently, the relative flow velocity in the low-pressure reservoir becomes negative, with the relative deflection angle approaching 180°, while the relative flow velocity in the high-pressure reservoir remains positive. An increase in the relative flow rate of 0.08 and 0.007 corresponds to a 1 MPa increase in fluid pressure difference and geostress difference, respectively. During the co-production of coalbed methane from MCR, the existing pressure difference and in situ stress difference between reservoirs modify the fluid migration patterns, leading to fluid interaction and interference effects. This results in centrifugal flow patterns in low-pressure reservoirs and centripetal flow patterns in high-pressure reservoirs. Compared to in situ stress difference, the fluid pressure difference exerts a more significant influence on the fluid migration patterns. Full article

Background/Objectives: Anterior cervical meningocele (ACM) is a rare congenital condition characterized by the herniation of the meninges through a defect in the anterior vertebral column. ACM clinical management is not standardized because this condition is rare, and guidelines are missing. Hereby, a systematic literature review is performed to determine management options and outcomes. Methods: The case of a 62-year-old patient with incidental diagnosis of C3-C5 ACM is presented. A systematic review was conducted using standard PRISMA (preferred reporting items for systematic reviews and meta-analyses) guidelines for all cases of anterior cervical meningocele from 1837 to 2025. Results: The review provided nine clinical cases and our illustrative case. The median age was 47 years, with a predominance of female patients (70%). The most common presenting symptom was neck pain (60%), followed by paresthesia and hypoesthesia in the upper limbs. Four patients underwent conservative management with clinical and radiological follow-up, while four patients underwent neurosurgical intervention. Surgical treatment was complicated by cerebrospinal fluid (CSF) leak in two patients, and one of them developed meningitis. Conclusions: ACM is typically associated with mesodermal dysplasia and dural ectasia. ACM usually has a benign clinical course, requiring neurological follow-up and conservative management alone. However, a surgical approach should be considered in cases of vertebral instability or symptoms related to upper airway compression or upper gastrointestinal tract compression despite the high risk of CSF leak when surgical repair is attempted. Full article

Background and Clinical Significance: Adverse reactions to metal debris (ARMD) are a rare but increasingly recognized complication following total hip arthroplasty (THA), with some studies suggesting upwards of 5% of metal-on-metal (MoM) and 3% of metal-on-polyethylene (MoP) prostheses being attributed to this. Historically, metallosis due to MoM implant design was the primary cause of ARMD. However, ARMD can also arise in metal-on-polyethylene (MoP) prostheses due to trunnionosis, which involves wear and corrosion at the modular femoral head–neck interface. Clinically, ARMD can resemble periprosthetic joint infection (PJI), complicating both diagnosis and management. Case Presentation: We present the case of a 40-year-old female with a history of systemic degenerative joint disease with bilateral MoP THAs who developed progressive pain and swelling in the upper left thigh, in which the prosthesis was first put in 22 years prior. The patient presented initially in a vascular surgery department for an infected iliopsoas cyst communicating with the hip where she had received surgery 2 years prior. The symptomatology reoccurred, and imaging revealed a large mass near the prosthesis and elevated inflammatory markers. Intraoperatively, a large volume of sero-purulent fluid was encountered, prompting a diagnostic workup for PJI. All cultures returned negative, and histopathology revealed macrophage-dominant infiltration with metallic debris, consistent with ARMD. After infection was definitively excluded, a revision THA was performed with an exchange of all modular components. The patient recovered without complications, and at six months follow-up, she demonstrated stable implant positioning, restored function, and no recurrence of symptoms. Conclusions: This case highlights the diagnostic complexity of PJI in joint arthroplasty and reveals the importance of a protocol-driven approach to exclude it prior to surgical revision. As the incidence of trunnion-related failure becomes more recognized in the literature, clinicians must consider ARMD in the differential diagnosis of late THA complications. Appropriate diagnosis is essential for guiding treatment and avoiding unnecessary complications, morbidity, and treatment related side-effects. Full article

Leveraging catalytic microreactors as compact yet powerful thermal sources represents a promising approach to enable rapid and reliable startup of small-scale solid oxide fuel cell (SOFC) systems. In the present study, the homogeneous–heterogeneous (HH) combustion behavior of a propane/air mixture in a Pt-catalyzed microreactor is investigated using two-dimensional computational fluid dynamic (CFD) simulations. The catalytic reaction kinetics model is integrated into the general module of ANSYSY Fluent via a user-defined function (UDF) interface. By varying the surface area factor, the ignition characteristics of the propane/air mixture under different catalyst activities are systematically explored. Numerical results reveal that the relative catalyst activity range of 0–2 represents a sensitive region for propane/air ignition characteristics, characterized by a 541 K decrease in ignition temperature and a 50% reduction in ignition delay time. Nevertheless, further increases in relative catalyst activity from 2 to 10, yield a much smaller reduction—64 K in ignition temperature and 6.7 s in ignition delay time—indicating a weakly responsive regime. The relative contribution of the heterogeneous reaction (HTR) to the total heat release decreases with higher feed temperatures but increases with enhanced catalyst activity. Regarding the temporal evolution of HTR contribution, the initiation of homogeneous ignition undermines the dominance of HTR contribution. Irrespective of catalytic activity levels, the relative contributions of the two reaction pathways subsequently undergo dynamic redistribution and ultimately stabilize, reaching an equilibrium state within approximately 10 s. These findings provide critical insights into the role of catalyst activity in propane/air mixture ignition and the interplay between homogeneous and heterogeneous reactions in microscale combustion systems. Full article